A vein bypass first versus a best endovascular treatment first revascularisation strategy for patients with chronic limb threatening ischaemia who required an infra-popliteal, with or without an additional more proximal infra-inguinal revascularisation procedure to restore limb perfusion (BASIL-2): an open-label, randomised, multicentre, phase 3 trial.

BACKGROUND: Chronic limb-threatening ischaemia is the severest manifestation of peripheral arterial disease and presents with ischaemic pain at rest or tissue loss (ulceration, gangrene, or both), or both. We compared the effectiveness of a vein bypass first with a best endovascular treatment first revascularisation strategy in terms of preventing major amputation and death in patients with chronic limb threatening ischaemia who required an infra-popliteal, with or without an additional more proximal infra-inguinal, revascularisation procedure to restore limb perfusion. METHODS: Bypass versus Angioplasty for Severe Ischaemia of the Leg (BASIL)-2 was an open-label, pragmatic, multicentre, phase 3, randomised trial done at 41 vascular surgery units in the UK (n=39), Sweden (n=1), and Denmark (n=1). Eligible patients were those who presented to hospital-based vascular surgery units with chronic limb-threatening ischaemia due to atherosclerotic disease and who required an infra-popliteal, with or without an additional more proximal infra-inguinal, revascularisation procedure to restore limb perfusion. Participants were randomly assigned (1:1) to receive either vein bypass (vein bypass group) or best endovascular treatment (best endovascular treatment group) as their first revascularisation procedure through a secure online randomisation system. Participants were excluded if they had ischaemic pain or tissue loss considered not to be primarily due to atherosclerotic peripheral artery disease. Most vein bypasses used the great saphenous vein and originated from the common or superficial femoral arteries. Most endovascular interventions comprised plain balloon angioplasty with selective use of plain or drug eluting stents. Participants were followed up for a minimum of 2 years. Data were collected locally at participating centres. In England, Wales, and Sweden, centralised databases were used to collect information on amputations and deaths. Data were analysed centrally at the Birmingham Clinical Trials Unit. The primary outcome was amputation-free survival defined as time to first major (above the ankle) amputation or death from any cause measured in the intention-to-treat population. Safety was assessed by monitoring serious adverse events up to 30-days after first revascularisation. The trial is registered with the ISRCTN registry, ISRCTN27728689. FINDINGS: Between July 22, 2014, and Nov 30, 2020, 345 participants (65 [19%] women and 280 [81%] men; median age 72·5 years [62·7-79·3]) with chronic limb-threatening ischaemia were enrolled in the trial and randomly assigned: 172 (50%) to the vein bypass group and 173 (50%) to the best endovascular treatment group. Major amputation or death occurred in 108 (63%) of 172 patients in the vein bypass group and 92 (53%) of 173 patients in the best endovascular treatment group (adjusted hazard ratio [HR] 1·35 [95% CI 1·02-1·80]; p=0·037). 91 (53%) of 172 patients in the vein bypass group and 77 (45%) of 173 patients in the best endovascular treatment group died (adjusted HR 1·37 [95% CI 1·00-1·87]). In both groups the most common causes of morbidity and death, including that occurring within 30 days of their first revascularisation, were cardiovascular (61 deaths in the vein bypass group and 49 in the best endovascular treatment group) and respiratory events (25 deaths in the vein bypass group and 23 in the best endovascular treatment group; number of cardiovascular and respiratory deaths were not mutually exclusive). INTERPRETATION: In the BASIL-2 trial, a best endovascular treatment first revascularisation strategy was associated with a better amputation-free survival, which was largely driven by fewer deaths in the best endovascular treatment group. These data suggest that more patients with chronic limb-threatening ischaemia who required an infra-popliteal, with or without an additional more proximal infra-inguinal, revascularisation procedure to restore limb perfusion should be considered for a best endovascular treatment first revascularisation strategy. FUNDING: UK National Institute of Health Research Health Technology Programme.

Pressure-garment therapy for preventing hypertrophic scarring after burn injury.

BACKGROUND: Burn damage to skin often results in scarring; however in some individuals the failure of normal wound-healing processes results in excessive scar tissue formation, termed 'hypertrophic scarring'. The most commonly used method for the prevention and treatment of hypertrophic scarring is pressure-garment therapy (PGT). PGT is considered standard care globally; however, there is continued uncertainty around its effectiveness. OBJECTIVES: To evaluate the benefits and harms of pressure-garment therapy for the prevention of hypertrophic scarring after burn injury. SEARCH METHODS: We used standard, extensive Cochrane search methods. We searched CENTRAL, MEDLINE, Embase, two other databases, and two trials registers on 8 June 2023 with reference checking, citation searching, and contact with study authors to identify additional studies. SELECTION CRITERIA: We included randomised controlled trials (RCTs) comparing PGT (alone or in combination with other scar-management therapies) with scar management therapies not including PGT, or comparing different PGT pressures or different types of PGT. DATA COLLECTION AND ANALYSIS: At least two review authors independently selected trials for inclusion using predetermined inclusion criteria, extracted data, and assessed risk of bias using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. MAIN RESULTS: We included 15 studies in this review (1179 participants), 14 of which (1057 participants) presented useable data. The sample size of included studies ranged from 17 to 159 participants. Most studies included both adults and children. Eight studies compared a pressure garment (with or without another scar management therapy) with scar management therapy alone, five studies compared the same pressure garment at a higher pressure versus a lower pressure, and two studies compared two different types of pressure garments. Studies used a variety of pressure garments (e.g. in-house manufactured or a commercial brand). Types of scar management therapies included were lanolin massage, topical silicone gel, silicone sheet/dressing, and heparin sodium ointment. Meta-analysis was not possible as there was significant clinical and methodological heterogeneity between studies. Main outcome measures were scar improvement assessed using the Vancouver Scar Scale (VSS) or the Patient and Observer Scar Assessment Scale (POSAS) (or both), pain, pruritus, quality of life, adverse events, and adherence to therapy. Studies additionally reported a further 14 outcomes, mostly individual scar parameters, some of which contributed to global scores on the VSS or POSAS. The amount of evidence for each individual outcome was limited. Most studies had a short follow-up, which may have affected results as the full effect of any therapy on scar healing may not be seen until around 18 months. PGT versus no treatment/lanolin We included five studies (378 participants). The evidence is very uncertain on whether PGT improves scars as assessed by the VSS compared with no treatment/lanolin. The evidence is also very uncertain for pain, pruritus, adverse events, and adherence. No study used the POSAS or assessed quality of life. One additional study (122 participants) did not report useable data. PGT versus silicone We included three studies (359 participants). The evidence is very uncertain on the effect of PGT compared with silicone, as assessed by the VSS and POSAS. The evidence is also very uncertain for pain, pruritus, quality of life, adverse events, adherence, and other scar parameters. It is possible that silicone may result in fewer adverse events or better adherence compared with PGT but this was also based on very low-certainty evidence. PGT plus silicone versus no treatment/lanolin We included two studies (200 participants). The evidence is very uncertain on whether PGT plus silicone improves scars as assessed by the VSS compared with no treatment/lanolin. The evidence is also very uncertain for pain, pruritus, and adverse events. No study used the POSAS or assessed quality of life or adherence. PGT plus silicone versus silicone We included three studies (359 participants). The evidence is very uncertain on the effect of PGT plus silicone compared with silicone, as assessed by the VSS and POSAS. The evidence is also very uncertain for pain, pruritus, quality of life, adverse events, and adherence. PGT plus scar management therapy including silicone versus scar management therapy including silicone We included one study (88 participants). The evidence is very uncertain on the effect of PGT plus scar management therapy including silicone versus scar management therapy including silicone, as assessed by the VSS and POSAS. The evidence is also very uncertain for pain, pruritus, quality of life, adverse events, and adherence. High-pressure versus low-pressure garments We included five studies (262 participants). The evidence is very uncertain on the effect of high pressure versus low pressure PGT on adverse events and adherence. No study used the VSS or the POSAS or assessed pain, pruritus, or quality of life. Different types of PGT (Caroskin Tricot + an adhesive silicone gel sheet versus Gecko Nanoplast (silicone gel bandage)) We included one study (60 participants). The evidence is very uncertain on the effect of Caroskin Tricot versus Gecko Nanoplast on the POSAS, pain, pruritus, and adverse events. The study did not use the VSS or assess quality of life or adherence. Different types of pressure garments (Jobst versus Tubigrip) We included one study (110 participants). The evidence is very uncertain on the adherence to either Jobst or Tubigrip. This study did not report any other outcomes. AUTHORS' CONCLUSIONS: There is insufficient evidence to recommend using either PGT or an alternative for preventing hypertrophic scarring after burn injury. PGT is already commonly used in practice and it is possible that continuing to do so may provide some benefit to some people. However, until more evidence becomes available, it may be appropriate to allow patient preference to guide therapy.

Laboratory-based molecular test alternatives to RT-PCR for the diagnosis of SARS-CoV-2 infection.

BACKGROUND: Diagnosing people with a SARS-CoV-2 infection played a critical role in managing the COVID-19 pandemic and remains a priority for the transition to long-term management of COVID-19. Initial shortages of extraction and reverse transcription polymerase chain reaction (RT-PCR) reagents impaired the desired upscaling of testing in many countries, which led to the search for alternatives to RNA extraction/purification and RT-PCR testing. Reference standard methods for diagnosing the presence of SARS-CoV-2 infection rely primarily on real-time reverse transcription-polymerase chain reaction (RT-PCR). Alternatives to RT-PCR could, if sufficiently accurate, have a positive impact by expanding the range of diagnostic tools available for the timely identification of people infected by SARS-CoV-2, access to testing and the use of resources. OBJECTIVES: To assess the diagnostic accuracy of alternative (to RT-PCR assays) laboratory-based molecular tests for diagnosing SARS-CoV-2 infection. SEARCH METHODS: We searched the COVID-19 Open Access Project living evidence database from the University of Bern until 30 September 2020 and the WHO COVID-19 Research Database until 31 October 2022. We did not apply language restrictions. SELECTION CRITERIA: We included studies of people with suspected or known SARS-CoV-2 infection, or where tests were used to screen for infection, and studies evaluating commercially developed laboratory-based molecular tests for the diagnosis of SARS-CoV-2 infection considered as alternatives to RT-PCR testing. We also included all reference standards to define the presence or absence of SARS-CoV-2, including RT-PCR tests and established clinical diagnostic criteria. DATA COLLECTION AND ANALYSIS: Two authors independently screened studies and resolved disagreements by discussing them with a third author. Two authors independently extracted data and assessed the risk of bias and applicability of the studies using the QUADAS-2 tool. We presented sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots and summarised results using average sensitivity and specificity using a bivariate random-effects meta-analysis. We illustrated the findings per index test category and assay brand compared to the WHO's acceptable sensitivity and specificity threshold for diagnosing SARS-CoV-2 infection using nucleic acid tests. MAIN RESULTS: We included data from 64 studies reporting 94 cohorts of participants and 105 index test evaluations, with 74,753 samples and 7517 confirmed SARS-CoV-2 cases. We did not identify any published or preprint reports of accuracy for a considerable number of commercially produced NAAT assays. Most cohorts were judged at unclear or high risk of bias in more than three QUADAS-2 domains. Around half of the cohorts were considered at high risk of selection bias because of recruitment based on COVID status. Three quarters of 94 cohorts were at high risk of bias in the reference standard domain because of reliance on a single RT-PCR result to determine the absence of SARS-CoV-2 infection or were at unclear risk of bias due to a lack of clarity about the time interval between the index test assessment and the reference standard, the number of missing results, or the absence of a participant flow diagram. For index tests categories with four or more evaluations and when summary estimations were possible, we found that: a) For RT-PCR assays designed to omit/adapt RNA extraction/purification, the average sensitivity was 95.1% (95% CI 91.1% to 97.3%), and the average specificity was 99.7% (95% CI 98.5% to 99.9%; based on 27 evaluations, 2834 samples and 1178 SARS-CoV-2 cases); b) For RT-LAMP assays, the average sensitivity was 88.4% (95% CI 83.1% to 92.2%), and the average specificity was 99.7% (95% CI 98.7% to 99.9%; 24 evaluations, 29,496 samples and 2255 SARS-CoV-2 cases); c) for TMA assays, the average sensitivity was 97.6% (95% CI 95.2% to 98.8%), and the average specificity was 99.4% (95% CI 94.9% to 99.9%; 14 evaluations, 2196 samples and 942 SARS-CoV-2 cases); d) for digital PCR assays, the average sensitivity was 98.5% (95% CI 95.2% to 99.5%), and the average specificity was 91.4% (95% CI 60.4% to 98.7%; five evaluations, 703 samples and 354 SARS-CoV-2 cases); e) for RT-LAMP assays omitting/adapting RNA extraction, the average sensitivity was 73.1% (95% CI 58.4% to 84%), and the average specificity was 100% (95% CI 98% to 100%; 24 evaluations, 14,342 samples and 1502 SARS-CoV-2 cases). Only two index test categories fulfil the WHO-acceptable sensitivity and specificity requirements for SARS-CoV-2 nucleic acid tests: RT-PCR assays designed to omit/adapt RNA extraction/purification and TMA assays. In addition, WHO-acceptable performance criteria were met for two assays out of 35 when tests were used according to manufacturer instructions. At 5% prevalence using a cohort of 1000 people suspected of SARS-CoV-2 infection, the positive predictive value of RT-PCR assays omitting/adapting RNA extraction/purification will be 94%, with three in 51 positive results being false positives, and around two missed cases. For TMA assays, the positive predictive value of RT-PCR assays will be 89%, with 6 in 55 positive results being false positives, and around one missed case. AUTHORS' CONCLUSIONS: Alternative laboratory-based molecular tests aim to enhance testing capacity in different ways, such as reducing the time, steps and resources needed to obtain valid results. Several index test technologies with these potential advantages have not been evaluated or have been assessed by only a few studies of limited methodological quality, so the performance of these kits was undetermined. Only two index test categories with enough evaluations for meta-analysis fulfil the WHO set of acceptable accuracy standards for SARS-CoV-2 nucleic acid tests: RT-PCR assays designed to omit/adapt RNA extraction/purification and TMA assays. These assays might prove to be suitable alternatives to RT-PCR for identifying people infected by SARS-CoV-2, especially when the alternative would be not having access to testing. However, these findings need to be interpreted and used with caution because of several limitations in the evidence, including reliance on retrospective samples without information about the symptom status of participants and the timing of assessment. No extrapolation of found accuracy data for these two alternatives to any test brands using the same techniques can be made as, for both groups, one test brand with high accuracy was overrepresented with 21/26 and 12/14 included studies, respectively. Although we used a comprehensive search and had broad eligibility criteria to include a wide range of tests that could be alternatives to RT-PCR methods, further research is needed to assess the performance of alternative COVID-19 tests and their role in pandemic management.

Accuracy of routine laboratory tests to predict mortality and deterioration to severe or critical COVID-19 in people with SARS-CoV-2.

BACKGROUND: Identifying patients with COVID-19 disease who will deteriorate can be useful to assess whether they should receive intensive care, or whether they can be treated in a less intensive way or through outpatient care. In clinical care, routine laboratory markers, such as C-reactive protein, are used to assess a person's health status. OBJECTIVES: To assess the accuracy of routine blood-based laboratory tests to predict mortality and deterioration to severe or critical (from mild or moderate) COVID-19 in people with SARS-CoV-2. SEARCH METHODS: On 25 August 2022, we searched the Cochrane COVID-19 Study Register, encompassing searches of various databases such as MEDLINE via PubMed, CENTRAL, Embase, medRxiv, and ClinicalTrials.gov. We did not apply any language restrictions. SELECTION CRITERIA: We included studies of all designs that produced estimates of prognostic accuracy in participants who presented to outpatient services, or were admitted to general hospital wards with confirmed SARS-CoV-2 infection, and studies that were based on serum banks of samples from people. All routine blood-based laboratory tests performed during the first encounter were included. We included any reference standard used to define deterioration to severe or critical disease that was provided by the authors. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from each included study, and independently assessed the methodological quality using the Quality Assessment of Prognostic Accuracy Studies tool. As studies reported different thresholds for the same test, we used the Hierarchical Summary Receiver Operator Curve model for meta-analyses to estimate summary curves in SAS 9.4. We estimated the sensitivity at points on the SROC curves that corresponded to the median and interquartile range boundaries of specificities in the included studies. Direct and indirect comparisons were exclusively conducted for biomarkers with an estimated sensitivity and 95% CI of ≥ 50% at a specificity of ≥ 50%. The relative diagnostic odds ratio was calculated as a summary of the relative accuracy of these biomarkers. MAIN RESULTS: We identified a total of 64 studies, including 71,170 participants, of which 8169 participants died, and 4031 participants deteriorated to severe/critical condition. The studies assessed 53 different laboratory tests. For some tests, both increases and decreases relative to the normal range were included. There was important heterogeneity between tests and their cut-off values. None of the included studies had a low risk of bias or low concern for applicability for all domains. None of the tests included in this review demonstrated high sensitivity or specificity, or both. The five tests with summary sensitivity and specificity above 50% were: C-reactive protein increase, neutrophil-to-lymphocyte ratio increase, lymphocyte count decrease, d-dimer increase, and lactate dehydrogenase increase. Inflammation For mortality, summary sensitivity of a C-reactive protein increase was 76% (95% CI 73% to 79%) at median specificity, 59% (low-certainty evidence). For deterioration, summary sensitivity was 78% (95% CI 67% to 86%) at median specificity, 72% (very low-certainty evidence). For the combined outcome of mortality or deterioration, or both, summary sensitivity was 70% (95% CI 49% to 85%) at median specificity, 60% (very low-certainty evidence). For mortality, summary sensitivity of an increase in neutrophil-to-lymphocyte ratio was 69% (95% CI 66% to 72%) at median specificity, 63% (very low-certainty evidence). For deterioration, summary sensitivity was 75% (95% CI 59% to 87%) at median specificity, 71% (very low-certainty evidence). For mortality, summary sensitivity of a decrease in lymphocyte count was 67% (95% CI 56% to 77%) at median specificity, 61% (very low-certainty evidence). For deterioration, summary sensitivity of a decrease in lymphocyte count was 69% (95% CI 60% to 76%) at median specificity, 67% (very low-certainty evidence). For the combined outcome, summary sensitivity was 83% (95% CI 67% to 92%) at median specificity, 29% (very low-certainty evidence). For mortality, summary sensitivity of a lactate dehydrogenase increase was 82% (95% CI 66% to 91%) at median specificity, 60% (very low-certainty evidence). For deterioration, summary sensitivity of a lactate dehydrogenase increase was 79% (95% CI 76% to 82%) at median specificity, 66% (low-certainty evidence). For the combined outcome, summary sensitivity was 69% (95% CI 51% to 82%) at median specificity, 62% (very low-certainty evidence). Hypercoagulability For mortality, summary sensitivity of a d-dimer increase was 70% (95% CI 64% to 76%) at median specificity of 56% (very low-certainty evidence). For deterioration, summary sensitivity was 65% (95% CI 56% to 74%) at median specificity of 63% (very low-certainty evidence). For the combined outcome, summary sensitivity was 65% (95% CI 52% to 76%) at median specificity of 54% (very low-certainty evidence). To predict mortality, neutrophil-to-lymphocyte ratio increase had higher accuracy compared to d-dimer increase (RDOR (diagnostic Odds Ratio) 2.05, 95% CI 1.30 to 3.24), C-reactive protein increase (RDOR 2.64, 95% CI 2.09 to 3.33), and lymphocyte count decrease (RDOR 2.63, 95% CI 1.55 to 4.46). D-dimer increase had higher accuracy compared to lymphocyte count decrease (RDOR 1.49, 95% CI 1.23 to 1.80), C-reactive protein increase (RDOR 1.31, 95% CI 1.03 to 1.65), and lactate dehydrogenase increase (RDOR 1.42, 95% CI 1.05 to 1.90). Additionally, lactate dehydrogenase increase had higher accuracy compared to lymphocyte count decrease (RDOR 1.30, 95% CI 1.13 to 1.49). To predict deterioration to severe disease, C-reactive protein increase had higher accuracy compared to d-dimer increase (RDOR 1.76, 95% CI 1.25 to 2.50). The neutrophil-to-lymphocyte ratio increase had higher accuracy compared to d-dimer increase (RDOR 2.77, 95% CI 1.58 to 4.84). Lastly, lymphocyte count decrease had higher accuracy compared to d-dimer increase (RDOR 2.10, 95% CI 1.44 to 3.07) and lactate dehydrogenase increase (RDOR 2.22, 95% CI 1.52 to 3.26). AUTHORS' CONCLUSIONS: Laboratory tests, associated with hypercoagulability and hyperinflammatory response, were better at predicting severe disease and mortality in patients with SARS-CoV-2 compared to other laboratory tests. However, to safely rule out severe disease, tests should have high sensitivity (> 90%), and none of the identified laboratory tests met this criterion. In clinical practice, a more comprehensive assessment of a patient's health status is usually required by, for example, incorporating these laboratory tests into clinical prediction rules together with clinical symptoms, radiological findings, and patient's characteristics.

Rapid intrapartum test for maternal group B streptococcal colonisation and its effect on antibiotic use in labouring women with risk factors for early-onset neonatal infection (GBS2): cluster randomised trial with nested test accuracy study.

BACKGROUND: Mother-to-baby transmission of group B Streptococcus (GBS) is the main cause of early-onset infection. We evaluated whether, in women with clinical risk factors for early neonatal infection, the use of point-of-care rapid intrapartum test to detect maternal GBS colonisation reduces maternal antibiotic exposure compared with usual care, where antibiotics are administered due to those risk factors. We assessed the accuracy of the rapid test in diagnosing maternal GBS colonisation, against the reference standard of selective enrichment culture. METHODS: We undertook a parallel-group cluster randomised trial, with nested test accuracy study and microbiological sub-study. UK maternity units were randomised to a strategy of rapid test (GeneXpert GBS system, Cepheid) or usual care. Within units assigned to rapid testing, vaginal-rectal swabs were taken from women with risk factors for vertical GBS transmission in established term labour. The trial primary outcome was the proportion of women receiving intrapartum antibiotics to prevent neonatal early-onset GBS infection. The accuracy of the rapid test was compared against the standard of selective enrichment culture in diagnosing maternal GBS colonisation. Antibiotic resistance profiles were determined in paired maternal and infant samples. RESULTS: Twenty-two maternity units were randomised and 20 were recruited. A total of 722 mothers (749 babies) participated in rapid test units; 906 mothers (951 babies) were in usual care units. There was no evidence of a difference in the rates of intrapartum antibiotic prophylaxis (relative risk 1.16, 95% CI 0.83 to 1.64) between the rapid test (41%, 297/716) and usual care (36%, 328/906) units. No serious adverse events were reported. The sensitivity and specificity measures of the rapid test were 86% (95% CI 81 to 91%) and 89% (95% CI 85 to 92%), respectively. Babies born to mothers who carried antibiotic-resistant Escherichia coli were more likely to be colonised with antibiotic-resistant strains than those born to mothers with antibiotic-susceptible E. coli. CONCLUSION: The use of intrapartum rapid test to diagnose maternal GBS colonisation did not reduce the rates of antibiotics administered for preventing neonatal early-onset GBS infection than usual care, although with considerable uncertainty. The accuracy of the rapid test is within acceptable limits. TRIAL REGISTRATION: ISRCTN74746075 . Prospectively registered on 16 April 2015.

Broadening symptom criteria improves early case identification in SARS-CoV-2 contacts.

BACKGROUND: The success of case isolation and contact tracing for the control of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission depends on the accuracy and speed of case identification. We assessed whether inclusion of additional symptoms alongside three canonical symptoms (CS), i.e. fever, cough and loss or change in smell or taste, could improve case definitions and accelerate case identification in SARS-CoV-2 contacts. METHODS: Two prospective longitudinal London (UK)-based cohorts of community SARS-CoV-2 contacts, recruited within 5 days of exposure, provided independent training and test datasets. Infected and uninfected contacts completed daily symptom diaries from the earliest possible time-points. Diagnostic information gained by adding symptoms to the CS was quantified using likelihood ratios and area under the receiver operating characteristic curve. Improvements in sensitivity and time to detection were compared with penalties in terms of specificity and number needed to test. RESULTS: Of 529 contacts within two cohorts, 164 (31%) developed PCR-confirmed infection and 365 (69%) remained uninfected. In the training dataset (n=168), 29% of infected contacts did not report the CS. Four symptoms (sore throat, muscle aches, headache and appetite loss) were identified as early-predictors (EP) which added diagnostic value to the CS. The broadened symptom criterion "≥1 of the CS, or ≥2 of the EP" identified PCR-positive contacts in the test dataset on average 2 days earlier after exposure (p=0.07) than "≥1 of the CS", with only modest reduction in specificity (5.7%). CONCLUSIONS: Broadening symptom criteria to include individuals with at least two of muscle aches, headache, appetite loss and sore throat identifies more infections and reduces time to detection, providing greater opportunities to prevent SARS-CoV-2 transmission.

Point-of-care viral load tests to detect high HIV viral load in people living with HIV/AIDS attending health facilities.

BACKGROUND: Viral load (VL) testing in people living with HIV (PLHIV) helps to monitor antiretroviral therapy (ART). VL is still largely tested using central laboratory-based platforms, which have long test turnaround times and involve sophisticated equipment. VL tests with point-of-care (POC) platforms capable of being used near the patient are potentially easy to use, give quick results, are cost-effective, and could replace central or reference VL testing platforms. OBJECTIVES: To estimate the diagnostic accuracy of POC tests to detect high viral load levels in PLHIV attending healthcare facilities. SEARCH METHODS: We searched eight electronic databases using standard, extensive Cochrane search methods, and did not use any language, document type, or publication status limitations. We also searched the reference lists of included studies and relevant systematic reviews, and consulted an expert in the field from the World Health Organization (WHO) HIV Department for potentially relevant studies. The latest search was 23 November 2020. SELECTION CRITERIA: We included any primary study that compared the results of a VL test with a POC platform to that of a central laboratory-based reference test to detect high viral load in PLHIV on HIV/AIDS care or follow-up. We included all forms of POC tests for VL as defined by study authors, regardless of the healthcare facility in which the test was conducted. We excluded diagnostic case-control studies with healthy controls and studies that did not provide sufficient data to create the 2 × 2 tables to calculate sensitivity and specificity. We did not limit our study inclusion to age, gender, or geographical setting. DATA COLLECTION AND ANALYSIS: Two review authors independently screened the titles, abstracts, and full texts of the search results to identify eligible articles. They also independently extracted data using a standardized data extraction form and conducted risk of bias assessment using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2) tool. Using participants as the unit of analysis, we fitted simplified univariable models for sensitivity and specificity separately, employing a random-effects model to estimate the summary sensitivity and specificity at the current and commonly reported World Health Organization (WHO) threshold (≥ 1000 copies/mL). The bivariate models did not converge to give a model estimate. MAIN RESULTS: We identified 18 studies (24 evaluations, 10,034 participants) defining high viral loads at main thresholds ≥ 1000 copies/mL (n = 20), ≥ 5000 copies/mL (n = 1), and ≥ 40 copies/mL (n = 3). All evaluations were done on samples from PLHIV retrieved from routine HIV/AIDS care centres or health facilities. For clinical applicability, we included 14 studies (20 evaluations, 8659 participants) assessing high viral load at the clinical threshold of ≥ 1000 copies/mL in the meta-analyses. Of these, sub-Saharan Africa, Europe, and Asia contributed 16, three, and one evaluation respectively. All included participants were on ART in only nine evaluations; in the other 11 evaluations the proportion of participants on ART was either partial or not clearly stated. Thirteen evaluations included adults only (n = 13), five mixed populations of adults and children, whilst in the remaining two the age of included populations was not clearly stated. The majority of evaluations included commercially available tests (n = 18). Ten evaluations were POC VL tests conducted near the patient in a peripheral or onsite laboratory, whilst the other 10 were evaluations of POC VL tests in a central or reference laboratory setting. The test types evaluated as POC VL tests included Xpert HIV-1 Viral Load test (n = 8), SAMBA HIV-1 Semi-Q Test (n = 9), Alere Q NAT prototype assay for HIV-1 (n = 2) and m-PIMA HIV-1/2 Viral Load test (n = 1). The majority of evaluations (n = 17) used plasma samples, whilst the rest (n = 3) utilized whole blood samples. Pooled sensitivity (95% confidence interval (CI)) of POC VL at a threshold of ≥ 1000 copies/mL was 96.6% (94.8 to 97.8) (20 evaluations, 2522 participants), and pooled specificity (95% CI) was 95.7% (90.8 to 98.0) (20 evaluations, 6137 participants). Median prevalence for high viral load (≥ 1000 copies/mL) (n = 20) was 33.4% (range 6.9% to 88.5%). Limitations The risk of bias was mostly assessed as unclear across the four domains due to incomplete reporting. AUTHORS' CONCLUSIONS: We found POC VL to have high sensitivity and high specificity for the diagnosis of high HIV viral load in PLHIV attending healthcare facilities at a clinical threshold of ≥ 1000 copies/mL.

Menopausal status, ultrasound and biomarker tests in combination for the diagnosis of ovarian cancer in symptomatic women.

BACKGROUND: Ovarian cancer (OC) has the highest case fatality rate of all gynaecological cancers. Diagnostic delays are caused by non-specific symptoms. Existing systematic reviews have not comprehensively covered tests in current practice, not estimated accuracy separately in pre- and postmenopausal women, or used inappropriate meta-analytic methods. OBJECTIVES: To establish the accuracy of combinations of menopausal status, ultrasound scan (USS) and biomarkers for the diagnosis of ovarian cancer in pre- and postmenopausal women and compare the accuracy of different test combinations. SEARCH METHODS: We searched CENTRAL, MEDLINE (Ovid), Embase (Ovid), five other databases and three trial registries from 1991 to 2015 and MEDLINE (Ovid) and Embase (Ovid) form June 2015 to June 2019. We also searched conference proceedings from the European Society of Gynaecological Oncology, International Gynecologic Cancer Society, American Society of Clinical Oncology and Society of Gynecologic Oncology, ZETOC and Conference Proceedings Citation Index (Web of Knowledge). We searched reference lists of included studies and published systematic reviews. SELECTION CRITERIA: We included cross-sectional diagnostic test accuracy studies evaluating single tests or comparing two or more tests, randomised trials comparing two or more tests, and studies validating multivariable models for the diagnosis of OC investigating test combinations, compared with a reference standard of histological confirmation or clinical follow-up in women with a pelvic mass (detected clinically or through USS) suspicious for OC. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed quality using QUADAS-2. We used the bivariate hierarchical model to indirectly compare tests at commonly reported thresholds in pre- and postmenopausal women separately. We indirectly compared tests across all thresholds and estimated sensitivity at fixed specificities of 80% and 90% by fitting hierarchical summary receiver operating characteristic (HSROC) models in pre- and postmenopausal women separately. MAIN RESULTS: We included 59 studies (32,059 women, 9545 cases of OC). Two tests evaluated the accuracy of a combination of menopausal status and USS findings (IOTA Logistic Regression Model 2 (LR2) and the Assessment of Different NEoplasias in the adneXa model (ADNEX)); one test evaluated the accuracy of a combination of menopausal status, USS findings and serum biomarker CA125 (Risk of Malignancy Index (RMI)); and one test evaluated the accuracy of a combination of menopausal status and two serum biomarkers (CA125 and HE4) (Risk of Ovarian Malignancy Algorithm (ROMA)). Most studies were at high or unclear risk of bias in participant, reference standard, and flow and timing domains. All studies were in hospital settings. Prevalence was 16% (RMI, ROMA), 22% (LR2) and 27% (ADNEX) in premenopausal women and 38% (RMI), 45% (ROMA), 52% (LR2) and 55% (ADNEX) in postmenopausal women. The prevalence of OC in the studies was considerably higher than would be expected in symptomatic women presenting in community-based settings, or in women referred from the community to hospital with a suspicion of OC. Studies were at high or unclear applicability because presenting features were not reported, or USS was performed by experienced ultrasonographers for RMI, LR2 and ADNEX. The higher sensitivity and lower specificity observed in postmenopausal compared to premenopausal women across all index tests and at all thresholds may reflect highly selected patient cohorts in the included studies. In premenopausal women, ROMA at a threshold of 13.1 (± 2), LR2 at a threshold to achieve a post-test probability of OC of 10% and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 77.4%, 95% CI 72.7% to 81.5%; LR2: 83.3%, 95% CI 74.7% to 89.5%; ADNEX: 95.5%, 95% CI 91.0% to 97.8%) compared to RMI (57.2%, 95% CI 50.3% to 63.8%). The specificity of ROMA and ADNEX were lower in premenopausal women (ROMA: 84.3%, 95% CI 81.2% to 87.0%; ADNEX: 77.8%, 95% CI 67.4% to 85.5%) compared to RMI 92.5% (95% CI 90.3% to 94.2%). The specificity of LR2 was comparable to RMI (90.4%, 95% CI 84.6% to 94.1%). In postmenopausal women, ROMA at a threshold of 27.7 (± 2), LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) demonstrated a higher sensitivity (ROMA: 90.3%, 95% CI 87.5% to 92.6%; LR2: 94.8%, 95% CI 92.3% to 96.6%; ADNEX: 97.6%, 95% CI 95.6% to 98.7%) compared to RMI (78.4%, 95% CI 74.6% to 81.7%). Specificity of ROMA at a threshold of 27.7 (± 2) (81.5, 95% CI 76.5% to 85.5%) was comparable to RMI (85.4%, 95% CI 82.0% to 88.2%), whereas for LR2 (post-test probability 10%) and ADNEX (post-test probability 10%) specificity was lower (LR2: 60.6%, 95% CI 50.5% to 69.9%; ADNEX: 55.0%, 95% CI 42.8% to 66.6%). AUTHORS' CONCLUSIONS: In specialist healthcare settings in both premenopausal and postmenopausal women, RMI has poor sensitivity. In premenopausal women, ROMA, LR2 and ADNEX offer better sensitivity (fewer missed cancers), but for ROMA and ADNEX this is off-set by a decrease in specificity and increase in false positives. In postmenopausal women, ROMA demonstrates a higher sensitivity and comparable specificity to RMI. ADNEX has the highest sensitivity in postmenopausal women, but reduced specificity. The prevalence of OC in included studies is representative of a highly selected referred population, rather than a population in whom referral is being considered. The comparative accuracy of tests observed here may not be transferable to non-specialist settings. Ultimately health systems need to balance accuracy and resource implications to identify the most suitable test.

Guaiac-based faecal occult blood tests versus faecal immunochemical tests for colorectal cancer screening in average-risk individuals.

BACKGROUND: Worldwide, many countries have adopted colorectal cancer (CRC) screening programmes, often based on faecal occult blood tests (FOBTs). CRC screening aims to detect advanced neoplasia (AN), which is defined as CRC or advanced adenomas. FOBTs fall into two categories based on detection technique and the detected blood component: qualitative guaiac-based FOBTs (gFOBTs) and faecal immunochemical tests (FITs), which can be qualitative and quantitative. Screening with gFOBTs reduces CRC-related mortality. OBJECTIVES: To compare the diagnostic test accuracy of gFOBT and FIT screening for detecting advanced colorectal neoplasia in average-risk individuals. SEARCH METHODS: We searched CENTRAL, MEDLINE, Embase, BIOSIS Citation Index, Science Citation Index Expanded, and Google Scholar. We searched the reference lists and PubMed-related articles of included studies to identify additional studies. SELECTION CRITERIA: We included prospective and retrospective studies that provided the number of true positives, false positives, false negatives, and true negatives for gFOBTs, FITs, or both, with colonoscopy as reference standard. We excluded case-control studies. We included studies in which all participants underwent both index test and reference standard ("reference standard: all"), and studies in which only participants with a positive index test underwent the reference standard while participants with a negative test were followed for at least one year for development of interval carcinomas ("reference standard: positive"). The target population consisted of asymptomatic, average-risk individuals undergoing CRC screening. The target conditions were CRC and advanced neoplasia (advanced adenomas and CRC combined). DATA COLLECTION AND ANALYSIS: Two review authors independently screened and selected studies for inclusion. In case of disagreement, a third review author made the final decision. We used the Rutter and Gatsonis hierarchical summary receiver operating characteristic model to explore differences between tests and identify potential sources of heterogeneity, and the bivariate hierarchical model to estimate sensitivity and specificity at common thresholds: 10 µg haemoglobin (Hb)/g faeces and 20 µg Hb/g faeces. We performed indirect comparisons of the accuracy of the two tests and direct comparisons when both index tests were evaluated in the same population. MAIN RESULTS: We ran the initial search on 25 June 2019, which yielded 63 studies for inclusion. We ran a top-up search on 14 September 2021, which yielded one potentially eligible study, currently awaiting classification. We included a total of 33 "reference standard: all" published articles involving 104,640 participants. Six studies evaluated only gFOBTs, 23 studies evaluated only FITs, and four studies included both gFOBTs and FITs. The cut-off for positivity of FITs varied between 2.4 µg and 50 µg Hb/g faeces. For each Quality Assessment of Diagnostic Accuracy Studies (QUADAS)-2 domain, we assessed risk of bias as high in less than 20% of studies. The summary curve showed that FITs had a higher discriminative ability than gFOBTs for AN (P < 0.001) and CRC (P = 0.004). For the detection of AN, the summary sensitivity of gFOBTs was 15% (95% confidence interval (CI) 12% to 20%), which was significantly lower than FITs at both 10 µg and 20 µg Hb/g cut-offs with summary sensitivities of 33% (95% CI 27% to 40%; P < 0.001) and 26% (95% CI 21% to 31%, P = 0.002), respectively. Results were simulated in a hypothetical cohort of 10,000 screening participants with 1% CRC prevalence and 10% AN prevalence. Out of 1000 participants with AN, gFOBTs missed 850, while FITs missed 670 (10 µg Hb/g cut-off) and 740 (20 µg Hb/g cut-off). No significant differences in summary specificity for AN detection were found between gFOBTs (94%; 95% CI 92% to 96%), and FITs at 10 µg Hb/g cut-off (93%; 95% CI 90% to 95%) and at 20 µg Hb/g cut-off (97%; 95% CI 95% to 98%). So, among 9000 participants without AN, 540 were offered (unnecessary) colonoscopy with gFOBTs compared to 630 (10 µg Hb/g) and 270 (20 µg Hb/g) with FITs. Similarly, for the detection of CRC, the summary sensitivity of gFOBTs, 39% (95% CI 25% to 55%), was significantly lower than FITs at 10 µg and 20 µg Hb/g cut-offs: 76% (95% CI 57% to 88%: P = 0.001) and 65% (95% CI 46% to 80%; P = 0.035), respectively. So, out of 100 participants with CRC, gFOBTs missed 61, and FITs missed 24 (10 µg Hb/g) and 35 (20 µg Hb/g). No significant differences in summary specificity for CRC were found between gFOBTs (94%; 95% CI 91% to 96%), and FITs at the 10 µg Hb/g cut-off (94%; 95% CI 87% to 97%) and 20 µg Hb/g cut-off (96%; 95% CI 91% to 98%). So, out of 9900 participants without CRC, 594 were offered (unnecessary) colonoscopy with gFOBTs versus 594 (10 µg Hb/g) and 396 (20 µg Hb/g) with FITs. In five studies that compared FITs and gFOBTs in the same population, FITs showed a higher discriminative ability for AN than gFOBTs (P = 0.003). We included a total of 30 "reference standard: positive" studies involving 3,664,934 participants. Of these, eight were gFOBT-only studies, 18 were FIT-only studies, and four studies combined both gFOBTs and FITs. The cut-off for positivity of FITs varied between 5 µg to 250 µg Hb/g faeces. For each QUADAS-2 domain, we assessed risk of bias as high in less than 20% of studies. The summary curve showed that FITs had a higher discriminative ability for detecting CRC than gFOBTs (P < 0.001). The summary sensitivity for CRC of gFOBTs, 59% (95% CI 55% to 64%), was significantly lower than FITs at the 10 µg Hb/g cut-off, 89% (95% CI 80% to 95%; P < 0.001) and the 20 µg Hb/g cut-off, 89% (95% CI 85% to 92%; P < 0.001). So, in the hypothetical cohort with 100 participants with CRC, gFOBTs missed 41, while FITs missed 11 (10 µg Hb/g) and 11 (20 µg Hb/g). The summary specificity of gFOBTs was 98% (95% CI 98% to 99%), which was higher than FITs at both 10 µg and 20 µg Hb/g cut-offs: 94% (95% CI 92% to 95%; P < 0.001) and 95% (95% CI 94% to 96%; P < 0.001), respectively. So, out of 9900 participants without CRC, 198 were offered (unnecessary) colonoscopy with gFOBTs compared to 594 (10 µg Hb/g) and 495 (20 µg Hb/g) with FITs. At a specificity of 90% and 95%, FITs had a higher sensitivity than gFOBTs. AUTHORS' CONCLUSIONS: FITs are superior to gFOBTs in detecting AN and CRC in average-risk individuals. Specificity of both tests was similar in "reference standard: all" studies, whereas specificity was significantly higher for gFOBTs than FITs in "reference standard: positive" studies. However, at pre-specified specificities, the sensitivity of FITs was significantly higher than gFOBTs.

Rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection.

BACKGROUND: Accurate rapid diagnostic tests for SARS-CoV-2 infection would be a useful tool to help manage the COVID-19 pandemic. Testing strategies that use rapid antigen tests to detect current infection have the potential to increase access to testing, speed detection of infection, and inform clinical and public health management decisions to reduce transmission. This is the second update of this review, which was first published in 2020. OBJECTIVES: To assess the diagnostic accuracy of rapid, point-of-care antigen tests for diagnosis of SARS-CoV-2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. Sources of heterogeneity investigated included setting and indication for testing, assay format, sample site, viral load, age, timing of test, and study design. SEARCH METHODS: We searched the COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) on 08 March 2021. We included independent evaluations from national reference laboratories, FIND and the Diagnostics Global Health website. We did not apply language restrictions. SELECTION CRITERIA: We included studies of people with either suspected SARS-CoV-2 infection, known SARS-CoV-2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen tests. We included evaluations of single applications of a test (one test result reported per person) and evaluations of serial testing (repeated antigen testing over time). Reference standards for presence or absence of infection were any laboratory-based molecular test (primarily reverse transcription polymerase chain reaction (RT-PCR)) or pre-pandemic respiratory sample. DATA COLLECTION AND ANALYSIS: We used standard screening procedures with three people. Two people independently carried out quality assessment (using the QUADAS-2 tool) and extracted study results. Other study characteristics were extracted by one review author and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test, and pooled data using the bivariate model. We investigated heterogeneity by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. MAIN RESULTS: We included 155 study cohorts (described in 166 study reports, with 24 as preprints). The main results relate to 152 evaluations of single test applications including 100,462 unique samples (16,822 with confirmed SARS-CoV-2). Studies were mainly conducted in Europe (101/152, 66%), and evaluated 49 different commercial antigen assays. Only 23 studies compared two or more brands of test. Risk of bias was high because of participant selection (40, 26%); interpretation of the index test (6, 4%); weaknesses in the reference standard for absence of infection (119, 78%); and participant flow and timing 41 (27%). Characteristics of participants (45, 30%) and index test delivery (47, 31%) differed from the way in which and in whom the test was intended to be used. Nearly all studies (91%) used a single RT-PCR result to define presence or absence of infection. The 152 studies of single test applications reported 228 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies, with consistently high specificities. Average sensitivity was higher in symptomatic (73.0%, 95% CI 69.3% to 76.4%; 109 evaluations; 50,574 samples, 11,662 cases) compared to asymptomatic participants (54.7%, 95% CI 47.7% to 61.6%; 50 evaluations; 40,956 samples, 2641 cases). Average sensitivity was higher in the first week after symptom onset (80.9%, 95% CI 76.9% to 84.4%; 30 evaluations, 2408 cases) than in the second week of symptoms (53.8%, 95% CI 48.0% to 59.6%; 40 evaluations, 1119 cases). For those who were asymptomatic at the time of testing, sensitivity was higher when an epidemiological exposure to SARS-CoV-2 was suspected (64.3%, 95% CI 54.6% to 73.0%; 16 evaluations; 7677 samples, 703 cases) compared to where COVID-19 testing was reported to be widely available to anyone on presentation for testing (49.6%, 95% CI 42.1% to 57.1%; 26 evaluations; 31,904 samples, 1758 cases). Average specificity was similarly high for symptomatic (99.1%) or asymptomatic (99.7%) participants. We observed a steady decline in summary sensitivities as measures of sample viral load decreased. Sensitivity varied between brands. When tests were used according to manufacturer instructions, average sensitivities by brand ranged from 34.3% to 91.3% in symptomatic participants (20 assays with eligible data) and from 28.6% to 77.8% for asymptomatic participants (12 assays). For symptomatic participants, summary sensitivities for seven assays were 80% or more (meeting acceptable criteria set by the World Health Organization (WHO)). The WHO acceptable performance criterion of 97% specificity was met by 17 of 20 assays when tests were used according to manufacturer instructions, 12 of which demonstrated specificities above 99%. For asymptomatic participants the sensitivities of only two assays approached but did not meet WHO acceptable performance standards in one study each; specificities for asymptomatic participants were in a similar range to those observed for symptomatic people. At 5% prevalence using summary data in symptomatic people during the first week after symptom onset, the positive predictive value (PPV) of 89% means that 1 in 10 positive results will be a false positive, and around 1 in 5 cases will be missed. At 0.5% prevalence using summary data for asymptomatic people, where testing was widely available and where epidemiological exposure to COVID-19 was suspected, resulting PPVs would be 38% to 52%, meaning that between 2 in 5 and 1 in 2 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. AUTHORS' CONCLUSIONS: Antigen tests vary in sensitivity. In people with signs and symptoms of COVID-19, sensitivities are highest in the first week of illness when viral loads are higher. Assays that meet appropriate performance standards, such as those set by WHO, could replace laboratory-based RT-PCR when immediate decisions about patient care must be made, or where RT-PCR cannot be delivered in a timely manner. However, they are more suitable for use as triage to RT-PCR testing. The variable sensitivity of antigen tests means that people who test negative may still be infected. Many commercially available rapid antigen tests have not been evaluated in independent validation studies. Evidence for testing in asymptomatic cohorts has increased, however sensitivity is lower and there is a paucity of evidence for testing in different settings. Questions remain about the use of antigen test-based repeat testing strategies. Further research is needed to evaluate the effectiveness of screening programmes at reducing transmission of infection, whether mass screening or targeted approaches including schools, healthcare setting and traveller screening.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.

BACKGROUND: COVID-19 illness is highly variable, ranging from infection with no symptoms through to pneumonia and life-threatening consequences. Symptoms such as fever, cough, or loss of sense of smell (anosmia) or taste (ageusia), can help flag early on if the disease is present. Such information could be used either to rule out COVID-19 disease, or to identify people who need to go for COVID-19 diagnostic tests. This is the second update of this review, which was first published in 2020. OBJECTIVES: To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19. SEARCH METHODS: We undertook electronic searches up to 10 June 2021 in the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We used artificial intelligence text analysis to conduct an initial classification of documents. We did not apply any language restrictions. SELECTION CRITERIA: Studies were eligible if they included people with clinically suspected COVID-19, or recruited known cases with COVID-19 and also controls without COVID-19 from a single-gate cohort. Studies were eligible when they recruited people presenting to primary care or hospital outpatient settings. Studies that included people who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently selected all studies, at both title and abstract, and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and assessed risk of bias using the QUADAS-2 checklist, and resolved disagreements by discussion with a third review author. Analyses were restricted to prospective studies only. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic (ROC) space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary prospective studies were available, and whenever heterogeneity across studies was deemed acceptable. MAIN RESULTS: We identified 90 studies; for this update we focused on the results of 42 prospective studies with 52,608 participants. Prevalence of COVID-19 disease varied from 3.7% to 60.6% with a median of 27.4%. Thirty-five studies were set in emergency departments or outpatient test centres (46,878 participants), three in primary care settings (1230 participants), two in a mixed population of in- and outpatients in a paediatric hospital setting (493 participants), and two overlapping studies in nursing homes (4007 participants). The studies did not clearly distinguish mild COVID-19 disease from COVID-19 pneumonia, so we present the results for both conditions together. Twelve studies had a high risk of bias for selection of participants because they used a high level of preselection to decide whether reverse transcription polymerase chain reaction (RT-PCR) testing was needed, or because they enrolled a non-consecutive sample, or because they excluded individuals while they were part of the study base. We rated 36 of the 42 studies as high risk of bias for the index tests because there was little or no detail on how, by whom and when, the symptoms were measured. For most studies, eligibility for testing was dependent on the local case definition and testing criteria that were in effect at the time of the study, meaning most people who were included in studies had already been referred to health services based on the symptoms that we are evaluating in this review. The applicability of the results of this review iteration improved in comparison with the previous reviews. This version has more studies of people presenting to ambulatory settings, which is where the majority of assessments for COVID-19 take place. Only three studies presented any data on children separately, and only one focused specifically on older adults. We found data on 96 symptoms or combinations of signs and symptoms. Evidence on individual signs as diagnostic tests was rarely reported, so this review reports mainly on the diagnostic value of symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. RT-PCR was the most often used reference standard (40/42 studies). Only cough (11 studies) had a summary sensitivity above 50% (62.4%, 95% CI 50.6% to 72.9%)); its specificity was low (45.4%, 95% CI 33.5% to 57.9%)). Presence of fever had a sensitivity of 37.6% (95% CI 23.4% to 54.3%) and a specificity of 75.2% (95% CI 56.3% to 87.8%). The summary positive likelihood ratio of cough was 1.14 (95% CI 1.04 to 1.25) and that of fever 1.52 (95% CI 1.10 to 2.10). Sore throat had a summary positive likelihood ratio of 0.814 (95% CI 0.714 to 0.929), which means that its presence increases the probability of having an infectious disease other than COVID-19. Dyspnoea (12 studies) and fatigue (8 studies) had a sensitivity of 23.3% (95% CI 16.4% to 31.9%) and 40.2% (95% CI 19.4% to 65.1%) respectively. Their specificity was 75.7% (95% CI 65.2% to 83.9%) and 73.6% (95% CI 48.4% to 89.3%). The summary positive likelihood ratio of dyspnoea was 0.96 (95% CI 0.83 to 1.11) and that of fatigue 1.52 (95% CI 1.21 to 1.91), which means that the presence of fatigue slightly increases the probability of having COVID-19. Anosmia alone (7 studies), ageusia alone (5 studies), and anosmia or ageusia (6 studies) had summary sensitivities below 50% but summary specificities over 90%. Anosmia had a summary sensitivity of 26.4% (95% CI 13.8% to 44.6%) and a specificity of 94.2% (95% CI 90.6% to 96.5%). Ageusia had a summary sensitivity of 23.2% (95% CI 10.6% to 43.3%) and a specificity of 92.6% (95% CI 83.1% to 97.0%). Anosmia or ageusia had a summary sensitivity of 39.2% (95% CI 26.5% to 53.6%) and a specificity of 92.1% (95% CI 84.5% to 96.2%). The summary positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.55 (95% CI 3.46 to 5.97) and 4.99 (95% CI 3.22 to 7.75) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The summary positive likelihood ratio of ageusia alone was 3.14 (95% CI 1.79 to 5.51). Twenty-four studies assessed combinations of different signs and symptoms, mostly combining olfactory symptoms. By combining symptoms with other information such as contact or travel history, age, gender, and a local recent case detection rate, some multivariable prediction scores reached a sensitivity as high as 90%. AUTHORS' CONCLUSIONS: Most individual symptoms included in this review have poor diagnostic accuracy. Neither absence nor presence of symptoms are accurate enough to rule in or rule out the disease. The presence of anosmia or ageusia may be useful as a red flag for the presence of COVID-19. The presence of cough also supports further testing. There is currently no evidence to support further testing with PCR in any individuals presenting only with upper respiratory symptoms such as sore throat, coryza or rhinorrhoea. Combinations of symptoms with other readily available information such as contact or travel history, or the local recent case detection rate may prove more useful and should be further investigated in an unselected population presenting to primary care or hospital outpatient settings. The diagnostic accuracy of symptoms for COVID-19 is moderate to low and any testing strategy using symptoms as selection mechanism will result in both large numbers of missed cases and large numbers of people requiring testing. Which one of these is minimised, is determined by the goal of COVID-19 testing strategies, that is, controlling the epidemic by isolating every possible case versus identifying those with clinically important disease so that they can be monitored or treated to optimise their prognosis. The former will require a testing strategy that uses very few symptoms as entry criterion for testing, the latter could focus on more specific symptoms such as fever and anosmia.

Antibody tests for identification of current and past infection with SARS-CoV-2.

BACKGROUND: The diagnostic challenges associated with the COVID-19 pandemic resulted in rapid development of diagnostic test methods for detecting SARS-CoV-2 infection. Serology tests to detect the presence of antibodies to SARS-CoV-2 enable detection of past infection and may detect cases of SARS-CoV-2 infection that were missed by earlier diagnostic tests. Understanding the diagnostic accuracy of serology tests for SARS-CoV-2 infection may enable development of effective diagnostic and management pathways, inform public health management decisions and understanding of SARS-CoV-2 epidemiology. OBJECTIVES: To assess the accuracy of antibody tests, firstly, to determine if a person presenting in the community, or in primary or secondary care has current SARS-CoV-2 infection according to time after onset of infection and, secondly, to determine if a person has previously been infected with SARS-CoV-2. Sources of heterogeneity investigated included: timing of test, test method, SARS-CoV-2 antigen used, test brand, and reference standard for non-SARS-CoV-2 cases. SEARCH METHODS: The COVID-19 Open Access Project living evidence database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) was searched on 30 September 2020. We included additional publications from the Evidence for Policy and Practice Information and Co-ordinating Centre (EPPI-Centre) 'COVID-19: Living map of the evidence' and the Norwegian Institute of Public Health 'NIPH systematic and living map on COVID-19 evidence'. We did not apply language restrictions. SELECTION CRITERIA: We included test accuracy studies of any design that evaluated commercially produced serology tests, targeting IgG, IgM, IgA alone, or in combination. Studies must have provided data for sensitivity, that could be allocated to a predefined time period after onset of symptoms, or after a positive RT-PCR test. Small studies with fewer than 25 SARS-CoV-2 infection cases were excluded. We included any reference standard to define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction tests (RT-PCR), clinical diagnostic criteria, and pre-pandemic samples). DATA COLLECTION AND ANALYSIS: We use standard screening procedures with three reviewers. Quality assessment (using the QUADAS-2 tool) and numeric study results were extracted independently by two people. Other study characteristics were extracted by one reviewer and checked by a second. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and, for meta-analysis, we fitted univariate random-effects logistic regression models for sensitivity by eligible time period and for specificity by reference standard group. Heterogeneity was investigated by including indicator variables in the random-effects logistic regression models. We tabulated results by test manufacturer and summarised results for tests that were evaluated in 200 or more samples and that met a modification of UK Medicines and Healthcare products Regulatory Agency (MHRA) target performance criteria. MAIN RESULTS: We included 178 separate studies (described in 177 study reports, with 45 as pre-prints) providing 527 test evaluations. The studies included 64,688 samples including 25,724 from people with confirmed SARS-CoV-2; most compared the accuracy of two or more assays (102/178, 57%). Participants with confirmed SARS-CoV-2 infection were most commonly hospital inpatients (78/178, 44%), and pre-pandemic samples were used by 45% (81/178) to estimate specificity. Over two-thirds of studies recruited participants based on known SARS-CoV-2 infection status (123/178, 69%). All studies were conducted prior to the introduction of SARS-CoV-2 vaccines and present data for naturally acquired antibody responses. Seventy-nine percent (141/178) of studies reported sensitivity by week after symptom onset and 66% (117/178) for convalescent phase infection. Studies evaluated enzyme-linked immunosorbent assays (ELISA) (165/527; 31%), chemiluminescent assays (CLIA) (167/527; 32%) or lateral flow assays (LFA) (188/527; 36%). Risk of bias was high because of participant selection (172, 97%); application and interpretation of the index test (35, 20%); weaknesses in the reference standard (38, 21%); and issues related to participant flow and timing (148, 82%). We judged that there were high concerns about the applicability of the evidence related to participants in 170 (96%) studies, and about the applicability of the reference standard in 162 (91%) studies. Average sensitivities for current SARS-CoV-2 infection increased by week after onset for all target antibodies. Average sensitivity for the combination of either IgG or IgM was 41.1% in week one (95% CI 38.1 to 44.2; 103 evaluations; 3881 samples, 1593 cases), 74.9% in week two (95% CI 72.4 to 77.3; 96 evaluations, 3948 samples, 2904 cases) and 88.0% by week three after onset of symptoms (95% CI 86.3 to 89.5; 103 evaluations, 2929 samples, 2571 cases). Average sensitivity during the convalescent phase of infection (up to a maximum of 100 days since onset of symptoms, where reported) was 89.8% for IgG (95% CI 88.5 to 90.9; 253 evaluations, 16,846 samples, 14,183 cases), 92.9% for IgG or IgM combined (95% CI 91.0 to 94.4; 108 evaluations, 3571 samples, 3206 cases) and 94.3% for total antibodies (95% CI 92.8 to 95.5; 58 evaluations, 7063 samples, 6652 cases). Average sensitivities for IgM alone followed a similar pattern but were of a lower test accuracy in every time slot. Average specificities were consistently high and precise, particularly for pre-pandemic samples which provide the least biased estimates of specificity (ranging from 98.6% for IgM to 99.8% for total antibodies). Subgroup analyses suggested small differences in sensitivity and specificity by test technology however heterogeneity in study results, timing of sample collection, and smaller sample numbers in some groups made comparisons difficult. For IgG, CLIAs were the most sensitive (convalescent-phase infection) and specific (pre-pandemic samples) compared to both ELISAs and LFAs (P < 0.001 for differences across test methods). The antigen(s) used (whether from the Spike-protein or nucleocapsid) appeared to have some effect on average sensitivity in the first weeks after onset but there was no clear evidence of an effect during convalescent-phase infection. Investigations of test performance by brand showed considerable variation in sensitivity between tests, and in results between studies evaluating the same test. For tests that were evaluated in 200 or more samples, the lower bound of the 95% CI for sensitivity was 90% or more for only a small number of tests (IgG, n = 5; IgG or IgM, n = 1; total antibodies, n = 4). More test brands met the MHRA minimum criteria for specificity of 98% or above (IgG, n = 16; IgG or IgM, n = 5; total antibodies, n = 7). Seven assays met the specified criteria for both sensitivity and specificity. In a low-prevalence (2%) setting, where antibody testing is used to diagnose COVID-19 in people with symptoms but who have had a negative PCR test, we would anticipate that 1 (1 to 2) case would be missed and 8 (5 to 15) would be falsely positive in 1000 people undergoing IgG or IgM testing in week three after onset of SARS-CoV-2 infection. In a seroprevalence survey, where prevalence of prior infection is 50%, we would anticipate that 51 (46 to 58) cases would be missed and 6 (5 to 7) would be falsely positive in 1000 people having IgG tests during the convalescent phase (21 to 100 days post-symptom onset or post-positive PCR) of SARS-CoV-2 infection. AUTHORS' CONCLUSIONS: Some antibody tests could be a useful diagnostic tool for those in whom molecular- or antigen-based tests have failed to detect the SARS-CoV-2 virus, including in those with ongoing symptoms of acute infection (from week three onwards) or those presenting with post-acute sequelae of COVID-19. However, antibody tests have an increasing likelihood of detecting an immune response to infection as time since onset of infection progresses and have demonstrated adequate performance for detection of prior infection for sero-epidemiological purposes. The applicability of results for detection of vaccination-induced antibodies is uncertain.

Thoracic imaging tests for the diagnosis of COVID-19.

BACKGROUND: Our March 2021 edition of this review showed thoracic imaging computed tomography (CT) to be sensitive and moderately specific in diagnosing COVID-19 pneumonia. This new edition is an update of the review. OBJECTIVES: Our objectives were to evaluate the diagnostic accuracy of thoracic imaging in people with suspected COVID-19; assess the rate of positive imaging in people who had an initial reverse transcriptase polymerase chain reaction (RT-PCR) negative result and a positive RT-PCR result on follow-up; and evaluate the accuracy of thoracic imaging for screening COVID-19 in asymptomatic individuals. The secondary objective was to assess threshold effects of index test positivity on accuracy. SEARCH METHODS: We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 17 February 2021. We did not apply any language restrictions. SELECTION CRITERIA: We included diagnostic accuracy studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19. Studies had to assess chest CT, chest X-ray, or ultrasound of the lungs for the diagnosis of COVID-19, use a reference standard that included RT-PCR, and report estimates of test accuracy or provide data from which we could compute estimates. We excluded studies that used imaging as part of the reference standard and studies that excluded participants with normal index test results. DATA COLLECTION AND ANALYSIS: The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using QUADAS-2. We presented sensitivity and specificity per study on paired forest plots, and summarized pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. MAIN RESULTS: We included 98 studies in this review. Of these, 94 were included for evaluating the diagnostic accuracy of thoracic imaging in the evaluation of people with suspected COVID-19. Eight studies were included for assessing the rate of positive imaging in individuals with initial RT-PCR negative results and positive RT-PCR results on follow-up, and 10 studies were included for evaluating the accuracy of thoracic imaging for imagining asymptomatic individuals. For all 98 included studies, risk of bias was high or unclear in 52 (53%) studies with respect to participant selection, in 64 (65%) studies with respect to reference standard, in 46 (47%) studies with respect to index test, and in 48 (49%) studies with respect to flow and timing. Concerns about the applicability of the evidence to: participants were high or unclear in eight (8%) studies; index test were high or unclear in seven (7%) studies; and reference standard were high or unclear in seven (7%) studies. Imaging in people with suspected COVID-19 We included 94 studies. Eighty-seven studies evaluated one imaging modality, and seven studies evaluated two imaging modalities. All studies used RT-PCR alone or in combination with other criteria (for example, clinical signs and symptoms, positive contacts) as the reference standard for the diagnosis of COVID-19. For chest CT (69 studies, 28285 participants, 14,342 (51%) cases), sensitivities ranged from 45% to 100%, and specificities from 10% to 99%. The pooled sensitivity of chest CT was 86.9% (95% confidence interval (CI) 83.6 to 89.6), and pooled specificity was 78.3% (95% CI 73.7 to 82.3). Definition for index test positivity was a source of heterogeneity for sensitivity, but not specificity. Reference standard was not a source of heterogeneity. For chest X-ray (17 studies, 8529 participants, 5303 (62%) cases), the sensitivity ranged from 44% to 94% and specificity from 24 to 93%. The pooled sensitivity of chest X-ray was 73.1% (95% CI 64. to -80.5), and pooled specificity was 73.3% (95% CI 61.9 to 82.2). Definition for index test positivity was not found to be a source of heterogeneity. Definition for index test positivity and reference standard were not found to be sources of heterogeneity. For ultrasound of the lungs (15 studies, 2410 participants, 1158 (48%) cases), the sensitivity ranged from 73% to 94% and the specificity ranged from 21% to 98%. The pooled sensitivity of ultrasound was 88.9% (95% CI 84.9 to 92.0), and the pooled specificity was 72.2% (95% CI 58.8 to 82.5). Definition for index test positivity and reference standard were not found to be sources of heterogeneity. Indirect comparisons of modalities evaluated across all 94 studies indicated that chest CT and ultrasound gave higher sensitivity estimates than X-ray (P = 0.0003 and P = 0.001, respectively). Chest CT and ultrasound gave similar sensitivities (P=0.42). All modalities had similar specificities (CT versus X-ray P = 0.36; CT versus ultrasound P = 0.32; X-ray versus ultrasound P = 0.89). Imaging in PCR-negative people who subsequently became positive For rate of positive imaging in individuals with initial RT-PCR negative results, we included 8 studies (7 CT, 1 ultrasound) with a total of 198 participants suspected of having COVID-19, all of whom had a final diagnosis of COVID-19. Most studies (7/8) evaluated CT. Of 177 participants with initially negative RT-PCR who had positive RT-PCR results on follow-up testing, 75.8% (95% CI 45.3 to 92.2) had positive CT findings. Imaging in asymptomatic PCR-positive people For imaging asymptomatic individuals, we included 10 studies (7 CT, 1 X-ray, 2 ultrasound) with a total of 3548 asymptomatic participants, of whom 364 (10%) had a final diagnosis of COVID-19. For chest CT (7 studies, 3134 participants, 315 (10%) cases), the pooled sensitivity was 55.7% (95% CI 35.4 to 74.3) and the pooled specificity was 91.1% (95% CI 82.6 to 95.7). AUTHORS' CONCLUSIONS: Chest CT and ultrasound of the lungs are sensitive and moderately specific in diagnosing COVID-19. Chest X-ray is moderately sensitive and moderately specific in diagnosing COVID-19. Thus, chest CT and ultrasound may have more utility for ruling out COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. The uncertainty resulting from high or unclear risk of bias and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results.

QUADAS-C: A Tool for Assessing Risk of Bias in Comparative Diagnostic Accuracy Studies.

Comparative diagnostic test accuracy studies assess and compare the accuracy of 2 or more tests in the same study. Although these studies have the potential to yield reliable evidence regarding comparative accuracy, shortcomings in the design, conduct, and analysis may bias their results. The currently recommended quality assessment tool for diagnostic test accuracy studies, QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies-2), is not designed for the assessment of test comparisons. The QUADAS-C (Quality Assessment of Diagnostic Accuracy Studies-Comparative) tool was developed as an extension of QUADAS-2 to assess the risk of bias in comparative diagnostic test accuracy studies. Through a 4-round Delphi study involving 24 international experts in test evaluation and a face-to-face consensus meeting, an initial version of the tool was developed that was revised and finalized following a pilot study among potential users. The QUADAS-C tool retains the same 4-domain structure of QUADAS-2 (Patient Selection, Index Test, Reference Standard, and Flow and Timing) and comprises additional questions to each QUADAS-2 domain. A risk-of-bias judgment for comparative accuracy requires a risk-of-bias judgment for the accuracy of each test (resulting from QUADAS-2) and additional criteria specific to test comparisons. Examples of such additional criteria include whether participants either received all index tests or were randomly assigned to index tests, and whether index tests were interpreted with blinding to the results of other index tests. The QUADAS-C tool will be useful for systematic reviews of diagnostic test accuracy addressing comparative questions. Furthermore, researchers may use this tool to identify and avoid risk of bias when designing a comparative diagnostic test accuracy study.

Comparative effect of physical exercise versus statins on improving arterial stiffness in patients with high cardiometabolic risk: A network meta-analysis.

BACKGROUND: The comparative analysis of the effect of several doses of statins against different intensities of physical exercise on arterial stiffness (a measure of cardiovascular risk) could shed light for clinicians on which method is most effective in preventing cardiovascular disease (CVD) and be used to inform shared decision-making between doctors and patients. This study was aimed at analyzing the effect, in high cardiometabolic risk patients, of different statins doses and exercise intensities on arterial stiffness (a measure of cardiovascular risk) by integrating all available direct and indirect evidence in network meta-analyses. METHODS AND FINDINGS: We systematically searched MEDLINE, Embase, SPORTDiscus, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Web of Science databases from their inception to February 28, 2020; for unpublished trials, we also searched ClinicalTrials.gov. We searched for studies concerning the effect of statins or physical exercise on arterial stiffness, measured by pulse wave velocity (PWV). For methodological quality assessment, Cochrane Collaboration's tool for assessing risk of bias (RoB2) was used. A network geometry graph was used to assess the strength of the evidence. Comparative evaluation of the interventions effect was performed by conducting a standard pairwise meta-analysis and a network meta-analysis (NMA) for direct and indirect comparisons between interventions and control/nonintervention. A total of 22 studies were included in the analyses (18 randomized controlled trials (RCTs) and 4 nonrandomized experimental studies), including 1,307 patients with high cardiometabolic risk from Asia (3 studies), Oceania (2 studies), Europe (10 studies), North America (5 studies), and South America (2 studies). The overall risk of bias assessed with RoB2 was high in all included studies. For standard pairwise meta-analysis and NMA, high-intensity exercise versus control (mean difference (MD) -0.56; 95% CI: -1.01, -0.11; p = 0.015 and -0.62; 95% CI: -1.20, -0.04; p = 0.038, respectively) and moderate statin dose versus control (MD -0.80, 95% CI: -1.59, -0.01; p = 0.048 and -0.73, 95% CI: -1.30, -0.15; p = 0.014, respectively) showed significant MDs. When nonrandomized experimental studies were excluded, the effect on high-intensity exercise versus control and moderate statin dose versus was slightly modified. The main limitation of this study was that the magnitude of the effect of the exercise interventions could be underestimated due to regression toward the mean bias because the baseline cardiometabolic risk profile of patients in the physical exercise intervention trials was healthier than those in the statins ones; consequently, more modest improvements in physical exercise interventions compared to statins interventions can be expected. Additionally, we might consider as limitations the small study sizes, the heterogeneous patient groups, the focus on a proxy endpoint (PWV), and the high risk of bias. CONCLUSIONS: In this NMA, we found that although many patients could benefit from statins for reducing CVD risk, our results support that, considering the beneficial effects of high-intensity exercise on arterial stiffness, it would be worthwhile to refocus our attention on this type of exercise as an effective tool for the prevention of CVD. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42019123120.

Point-of-care tests detecting HIV nucleic acids for diagnosis of HIV-1 or HIV-2 infection in infants and children aged 18 months or less.

BACKGROUND: The standard method of diagnosing HIV in infants and children less than 18 months is with a nucleic acid amplification test reverse transcriptase polymerase chain reaction test (NAT RT-PCR) detecting viral ribonucleic acid (RNA). Laboratory testing using the RT-PCR platform for HIV infection is limited by poor access, logistical support, and delays in relaying test results and initiating therapy in low-resource settings. The use of rapid diagnostic tests at or near the point-of-care (POC) can increase access to early diagnosis of HIV infection in infants and children less than 18 months of age and timely initiation of antiretroviral therapy (ART). OBJECTIVES: To summarize the diagnostic accuracy of point-of-care nucleic acid-based testing (POC NAT) to detect HIV-1/HIV-2 infection in infants and children aged 18 months or less exposed to HIV infection. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (until 2 February 2021), MEDLINE and Embase (until 1 February 2021), and LILACS and Web of Science (until 2 February 2021) with no language or publication status restriction. We also searched conference websites and clinical trial registries, tracked reference lists of included studies and relevant systematic reviews, and consulted experts for potentially eligible studies. SELECTION CRITERIA: We defined POC tests as rapid diagnostic tests conducted at or near the patient site. We included any primary study that compared the results of a POC NAT to a reference standard of laboratory NAT RT-PCR or total nucleic acid testing to detect the presence or absence of HIV infection denoted by HIV viral nucleic acids in infants and children aged 18 months or less who were exposed to HIV-1/HIV-2 infection. We included cross-sectional, prospective, and retrospective study designs and those that provided sufficient data to create the 2 × 2 table to calculate sensitivity and specificity. We excluded diagnostic case control studies with healthy controls. DATA COLLECTION AND ANALYSIS: We extracted information on study characteristics using a pretested standardized data extraction form. We used the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies) tool to assess the risk of bias and applicability concerns of the included studies. Two review authors independently selected and assessed the included studies, resolving any disagreements by consensus. The unit of analysis was the participant. We first conducted preliminary exploratory analyses by plotting estimates of sensitivity and specificity from each study on forest plots and in receiver operating characteristic (ROC) space. For the overall meta-analyses, we pooled estimates of sensitivity and specificity using the bivariate meta-analysis model at a common threshold (presence or absence of infection). MAIN RESULTS: We identified a total of 12 studies (15 evaluations, 15,120 participants). All studies were conducted in sub-Saharan Africa. The ages of included infants and children in the evaluations were as follows: at birth (n = 6), ≤ 12 months (n = 3), ≤ 18 months (n = 5), and ≤ 24 months (n = 1). Ten evaluations were field evaluations of the POC NAT test at the point of care, and five were laboratory evaluations of the POC NAT tests.The POC NAT tests evaluated included Alere q HIV-1/2 Detect qualitative test (recently renamed m-PIMA q HIV-1/2 Detect qualitative test) (n = 6), Xpert HIV-1 qualitative test (n = 6), and SAMBA HIV-1 qualitative test (n = 3). POC NAT pooled sensitivity and specificity (95% confidence interval (CI)) against laboratory reference standard tests were 98.6% (96.1 to 99.5) (15 evaluations, 1728 participants) and 99.9% (99.7 to 99.9) (15 evaluations, 13,392 participants) in infants and children ≤ 18 months. Risk of bias in the included studies was mostly low or unclear due to poor reporting. Five evaluations had some concerns for applicability for the index test, as they were POC tests evaluated in a laboratory setting, but there was no difference detected between settings in sensitivity (-1.3% (95% CI -4.1 to 1.5)); and specificity results were similar. AUTHORS' CONCLUSIONS: For the diagnosis of HIV-1/HIV-2 infection, we found the sensitivity and specificity of POC NAT tests to be high in infants and children aged 18 months or less who were exposed to HIV infection.

Signs and symptoms to determine if a patient presenting in primary care or hospital outpatient settings has COVID-19.

BACKGROUND: The clinical implications of SARS-CoV-2 infection are highly variable. Some people with SARS-CoV-2 infection remain asymptomatic, whilst the infection can cause mild to moderate COVID-19 and COVID-19 pneumonia in others. This can lead to some people requiring intensive care support and, in some cases, to death, especially in older adults. Symptoms such as fever, cough, or loss of smell or taste, and signs such as oxygen saturation are the first and most readily available diagnostic information. Such information could be used to either rule out COVID-19, or select patients for further testing. This is an update of this review, the first version of which published in July 2020. OBJECTIVES: To assess the diagnostic accuracy of signs and symptoms to determine if a person presenting in primary care or to hospital outpatient settings, such as the emergency department or dedicated COVID-19 clinics, has COVID-19. SEARCH METHODS: For this review iteration we undertook electronic searches up to 15 July 2020 in the Cochrane COVID-19 Study Register and the University of Bern living search database. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. SELECTION CRITERIA: Studies were eligible if they included patients with clinically suspected COVID-19, or if they recruited known cases with COVID-19 and controls without COVID-19. Studies were eligible when they recruited patients presenting to primary care or hospital outpatient settings. Studies in hospitalised patients were only included if symptoms and signs were recorded on admission or at presentation. Studies including patients who contracted SARS-CoV-2 infection while admitted to hospital were not eligible. The minimum eligible sample size of studies was 10 participants. All signs and symptoms were eligible for this review, including individual signs and symptoms or combinations. We accepted a range of reference standards. DATA COLLECTION AND ANALYSIS: Pairs of review authors independently selected all studies, at both title and abstract stage and full-text stage. They resolved any disagreements by discussion with a third review author. Two review authors independently extracted data and resolved disagreements by discussion with a third review author. Two review authors independently assessed risk of bias using the Quality Assessment tool for Diagnostic Accuracy Studies (QUADAS-2) checklist. We presented sensitivity and specificity in paired forest plots, in receiver operating characteristic space and in dumbbell plots. We estimated summary parameters using a bivariate random-effects meta-analysis whenever five or more primary studies were available, and whenever heterogeneity across studies was deemed acceptable. MAIN RESULTS: We identified 44 studies including 26,884 participants in total. Prevalence of COVID-19 varied from 3% to 71% with a median of 21%. There were three studies from primary care settings (1824 participants), nine studies from outpatient testing centres (10,717 participants), 12 studies performed in hospital outpatient wards (5061 participants), seven studies in hospitalised patients (1048 participants), 10 studies in the emergency department (3173 participants), and three studies in which the setting was not specified (5061 participants). The studies did not clearly distinguish mild from severe COVID-19, so we present the results for all disease severities together. Fifteen studies had a high risk of bias for selection of participants because inclusion in the studies depended on the applicable testing and referral protocols, which included many of the signs and symptoms under study in this review. This may have especially influenced the sensitivity of those features used in referral protocols, such as fever and cough. Five studies only included participants with pneumonia on imaging, suggesting that this is a highly selected population. In an additional 12 studies, we were unable to assess the risk for selection bias. This makes it very difficult to judge the validity of the diagnostic accuracy of the signs and symptoms from these included studies. The applicability of the results of this review update improved in comparison with the original review. A greater proportion of studies included participants who presented to outpatient settings, which is where the majority of clinical assessments for COVID-19 take place. However, still none of the studies presented any data on children separately, and only one focused specifically on older adults. We found data on 84 signs and symptoms. Results were highly variable across studies. Most had very low sensitivity and high specificity. Only cough (25 studies) and fever (7 studies) had a pooled sensitivity of at least 50% but specificities were moderate to low. Cough had a sensitivity of 67.4% (95% confidence interval (CI) 59.8% to 74.1%) and specificity of 35.0% (95% CI 28.7% to 41.9%). Fever had a sensitivity of 53.8% (95% CI 35.0% to 71.7%) and a specificity of 67.4% (95% CI 53.3% to 78.9%). The pooled positive likelihood ratio of cough was only 1.04 (95% CI 0.97 to 1.11) and that of fever 1.65 (95% CI 1.41 to 1.93). Anosmia alone (11 studies), ageusia alone (6 studies), and anosmia or ageusia (6 studies) had sensitivities below 50% but specificities over 90%. Anosmia had a pooled sensitivity of 28.0% (95% CI 17.7% to 41.3%) and a specificity of 93.4% (95% CI 88.3% to 96.4%). Ageusia had a pooled sensitivity of 24.8% (95% CI 12.4% to 43.5%) and a specificity of 91.4% (95% CI 81.3% to 96.3%). Anosmia or ageusia had a pooled sensitivity of 41.0% (95% CI 27.0% to 56.6%) and a specificity of 90.5% (95% CI 81.2% to 95.4%). The pooled positive likelihood ratios of anosmia alone and anosmia or ageusia were 4.25 (95% CI 3.17 to 5.71) and 4.31 (95% CI 3.00 to 6.18) respectively, which is just below our arbitrary definition of a 'red flag', that is, a positive likelihood ratio of at least 5. The pooled positive likelihood ratio of ageusia alone was only 2.88 (95% CI 2.02 to 4.09). Only two studies assessed combinations of different signs and symptoms, mostly combining fever and cough with other symptoms. These combinations had a specificity above 80%, but at the cost of very low sensitivity (< 30%). AUTHORS' CONCLUSIONS: The majority of individual signs and symptoms included in this review appear to have very poor diagnostic accuracy, although this should be interpreted in the context of selection bias and heterogeneity between studies. Based on currently available data, neither absence nor presence of signs or symptoms are accurate enough to rule in or rule out COVID-19. The presence of anosmia or ageusia may be useful as a red flag for COVID-19. The presence of fever or cough, given their high sensitivities, may also be useful to identify people for further testing. Prospective studies in an unselected population presenting to primary care or hospital outpatient settings, examining combinations of signs and symptoms to evaluate the syndromic presentation of COVID-19, are still urgently needed. Results from such studies could inform subsequent management decisions.

Rapid, point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection.

BACKGROUND: Accurate rapid diagnostic tests for SARS-CoV-2 infection could contribute to clinical and public health strategies to manage the COVID-19 pandemic. Point-of-care antigen and molecular tests to detect current infection could increase access to testing and early confirmation of cases, and expediate clinical and public health management decisions that may reduce transmission. OBJECTIVES: To assess the diagnostic accuracy of point-of-care antigen and molecular-based tests for diagnosis of SARS-CoV-2 infection. We consider accuracy separately in symptomatic and asymptomatic population groups. SEARCH METHODS: Electronic searches of the Cochrane COVID-19 Study Register and the COVID-19 Living Evidence Database from the University of Bern (which includes daily updates from PubMed and Embase and preprints from medRxiv and bioRxiv) were undertaken on 30 Sept 2020. We checked repositories of COVID-19 publications and included independent evaluations from national reference laboratories, the Foundation for Innovative New Diagnostics and the Diagnostics Global Health website to 16 Nov 2020. We did not apply language restrictions. SELECTION CRITERIA: We included studies of people with either suspected SARS-CoV-2 infection, known SARS-CoV-2 infection or known absence of infection, or those who were being screened for infection. We included test accuracy studies of any design that evaluated commercially produced, rapid antigen or molecular tests suitable for a point-of-care setting (minimal equipment, sample preparation, and biosafety requirements, with results within two hours of sample collection). We included all reference standards that define the presence or absence of SARS-CoV-2 (including reverse transcription polymerase chain reaction (RT-PCR) tests and established diagnostic criteria). DATA COLLECTION AND ANALYSIS: Studies were screened independently in duplicate with disagreements resolved by discussion with a third author. Study characteristics were extracted by one author and checked by a second; extraction of study results and assessments of risk of bias and applicability (made using the QUADAS-2 tool) were undertaken independently in duplicate. We present sensitivity and specificity with 95% confidence intervals (CIs) for each test and pooled data using the bivariate model separately for antigen and molecular-based tests. We tabulated results by test manufacturer and compliance with manufacturer instructions for use and according to symptom status. MAIN RESULTS: Seventy-eight study cohorts were included (described in 64 study reports, including 20 pre-prints), reporting results for 24,087 samples (7,415 with confirmed SARS-CoV-2). Studies were mainly from Europe (n = 39) or North America (n = 20), and evaluated 16 antigen and five molecular assays. We considered risk of bias to be high in 29 (50%) studies because of participant selection; in 66 (85%) because of weaknesses in the reference standard for absence of infection; and in 29 (45%) for participant flow and timing. Studies of antigen tests were of a higher methodological quality compared to studies of molecular tests, particularly regarding the risk of bias for participant selection and the index test. Characteristics of participants in 35 (45%) studies differed from those in whom the test was intended to be used and the delivery of the index test in 39 (50%) studies differed from the way in which the test was intended to be used. Nearly all studies (97%) defined the presence or absence of SARS-CoV-2 based on a single RT-PCR result, and none included participants meeting case definitions for probable COVID-19. Antigen tests Forty-eight studies reported 58 evaluations of antigen tests. Estimates of sensitivity varied considerably between studies. There were differences between symptomatic (72.0%, 95% CI 63.7% to 79.0%; 37 evaluations; 15530 samples, 4410 cases) and asymptomatic participants (58.1%, 95% CI 40.2% to 74.1%; 12 evaluations; 1581 samples, 295 cases). Average sensitivity was higher in the first week after symptom onset (78.3%, 95% CI 71.1% to 84.1%; 26 evaluations; 5769 samples, 2320 cases) than in the second week of symptoms (51.0%, 95% CI 40.8% to 61.0%; 22 evaluations; 935 samples, 692 cases). Sensitivity was high in those with cycle threshold (Ct) values on PCR ≤25 (94.5%, 95% CI 91.0% to 96.7%; 36 evaluations; 2613 cases) compared to those with Ct values >25 (40.7%, 95% CI 31.8% to 50.3%; 36 evaluations; 2632 cases). Sensitivity varied between brands. Using data from instructions for use (IFU) compliant evaluations in symptomatic participants, summary sensitivities ranged from 34.1% (95% CI 29.7% to 38.8%; Coris Bioconcept) to 88.1% (95% CI 84.2% to 91.1%; SD Biosensor STANDARD Q). Average specificities were high in symptomatic and asymptomatic participants, and for most brands (overall summary specificity 99.6%, 95% CI 99.0% to 99.8%). At 5% prevalence using data for the most sensitive assays in symptomatic people (SD Biosensor STANDARD Q and Abbott Panbio), positive predictive values (PPVs) of 84% to 90% mean that between 1 in 10 and 1 in 6 positive results will be a false positive, and between 1 in 4 and 1 in 8 cases will be missed. At 0.5% prevalence applying the same tests in asymptomatic people would result in PPVs of 11% to 28% meaning that between 7 in 10 and 9 in 10 positive results will be false positives, and between 1 in 2 and 1 in 3 cases will be missed. No studies assessed the accuracy of repeated lateral flow testing or self-testing. Rapid molecular assays Thirty studies reported 33 evaluations of five different rapid molecular tests. Sensitivities varied according to test brand. Most of the data relate to the ID NOW and Xpert Xpress assays. Using data from evaluations following the manufacturer's instructions for use, the average sensitivity of ID NOW was 73.0% (95% CI 66.8% to 78.4%) and average specificity 99.7% (95% CI 98.7% to 99.9%; 4 evaluations; 812 samples, 222 cases). For Xpert Xpress, the average sensitivity was 100% (95% CI 88.1% to 100%) and average specificity 97.2% (95% CI 89.4% to 99.3%; 2 evaluations; 100 samples, 29 cases). Insufficient data were available to investigate the effect of symptom status or time after symptom onset. AUTHORS' CONCLUSIONS: Antigen tests vary in sensitivity. In people with signs and symptoms of COVID-19, sensitivities are highest in the first week of illness when viral loads are higher. The assays shown to meet appropriate criteria, such as WHO's priority target product profiles for COVID-19 diagnostics ('acceptable' sensitivity ≥ 80% and specificity ≥ 97%), can be considered as a replacement for laboratory-based RT-PCR when immediate decisions about patient care must be made, or where RT-PCR cannot be delivered in a timely manner. Positive predictive values suggest that confirmatory testing of those with positive results may be considered in low prevalence settings. Due to the variable sensitivity of antigen tests, people who test negative may still be infected. Evidence for testing in asymptomatic cohorts was limited. Test accuracy studies cannot adequately assess the ability of antigen tests to differentiate those who are infectious and require isolation from those who pose no risk, as there is no reference standard for infectiousness. A small number of molecular tests showed high accuracy and may be suitable alternatives to RT-PCR. However, further evaluations of the tests in settings as they are intended to be used are required to fully establish performance in practice. Several important studies in asymptomatic individuals have been reported since the close of our search and will be incorporated at the next update of this review. Comparative studies of antigen tests in their intended use settings and according to test operator (including self-testing) are required.

Thoracic imaging tests for the diagnosis of COVID-19.

BACKGROUND: The respiratory illness caused by SARS-CoV-2 infection continues to present diagnostic challenges. Our 2020 edition of this review showed thoracic (chest) imaging to be sensitive and moderately specific in the diagnosis of coronavirus disease 2019 (COVID-19). In this update, we include new relevant studies, and have removed studies with case-control designs, and those not intended to be diagnostic test accuracy studies. OBJECTIVES: To evaluate the diagnostic accuracy of thoracic imaging (computed tomography (CT), X-ray and ultrasound) in people with suspected COVID-19. SEARCH METHODS: We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, The Stephen B. Thacker CDC Library, and repositories of COVID-19 publications through to 30 September 2020. We did not apply any language restrictions. SELECTION CRITERIA: We included studies of all designs, except for case-control, that recruited participants of any age group suspected to have COVID-19 and that reported estimates of test accuracy or provided data from which we could compute estimates. DATA COLLECTION AND ANALYSIS: The review authors independently and in duplicate screened articles, extracted data and assessed risk of bias and applicability concerns using the QUADAS-2 domain-list. We presented the results of estimated sensitivity and specificity using paired forest plots, and we summarised pooled estimates in tables. We used a bivariate meta-analysis model where appropriate. We presented the uncertainty of accuracy estimates using 95% confidence intervals (CIs). MAIN RESULTS: We included 51 studies with 19,775 participants suspected of having COVID-19, of whom 10,155 (51%) had a final diagnosis of COVID-19. Forty-seven studies evaluated one imaging modality each, and four studies evaluated two imaging modalities each. All studies used RT-PCR as the reference standard for the diagnosis of COVID-19, with 47 studies using only RT-PCR and four studies using a combination of RT-PCR and other criteria (such as clinical signs, imaging tests, positive contacts, and follow-up phone calls) as the reference standard. Studies were conducted in Europe (33), Asia (13), North America (3) and South America (2); including only adults (26), all ages (21), children only (1), adults over 70 years (1), and unclear (2); in inpatients (2), outpatients (32), and setting unclear (17). Risk of bias was high or unclear in thirty-two (63%) studies with respect to participant selection, 40 (78%) studies with respect to reference standard, 30 (59%) studies with respect to index test, and 24 (47%) studies with respect to participant flow. For chest CT (41 studies, 16,133 participants, 8110 (50%) cases), the sensitivity ranged from 56.3% to 100%, and specificity ranged from 25.4% to 97.4%. The pooled sensitivity of chest CT was 87.9% (95% CI 84.6 to 90.6) and the pooled specificity was 80.0% (95% CI 74.9 to 84.3). There was no statistical evidence indicating that reference standard conduct and definition for index test positivity were sources of heterogeneity for CT studies. Nine chest CT studies (2807 participants, 1139 (41%) cases) used the COVID-19 Reporting and Data System (CO-RADS) scoring system, which has five thresholds to define index test positivity. At a CO-RADS threshold of 5 (7 studies), the sensitivity ranged from 41.5% to 77.9% and the pooled sensitivity was 67.0% (95% CI 56.4 to 76.2); the specificity ranged from 83.5% to 96.2%; and the pooled specificity was 91.3% (95% CI 87.6 to 94.0). At a CO-RADS threshold of 4 (7 studies), the sensitivity ranged from 56.3% to 92.9% and the pooled sensitivity was 83.5% (95% CI 74.4 to 89.7); the specificity ranged from 77.2% to 90.4% and the pooled specificity was 83.6% (95% CI 80.5 to 86.4). For chest X-ray (9 studies, 3694 participants, 2111 (57%) cases) the sensitivity ranged from 51.9% to 94.4% and specificity ranged from 40.4% to 88.9%. The pooled sensitivity of chest X-ray was 80.6% (95% CI 69.1 to 88.6) and the pooled specificity was 71.5% (95% CI 59.8 to 80.8). For ultrasound of the lungs (5 studies, 446 participants, 211 (47%) cases) the sensitivity ranged from 68.2% to 96.8% and specificity ranged from 21.3% to 78.9%. The pooled sensitivity of ultrasound was 86.4% (95% CI 72.7 to 93.9) and the pooled specificity was 54.6% (95% CI 35.3 to 72.6). Based on an indirect comparison using all included studies, chest CT had a higher specificity than ultrasound. For indirect comparisons of chest CT and chest X-ray, or chest X-ray and ultrasound, the data did not show differences in specificity or sensitivity. AUTHORS' CONCLUSIONS: Our findings indicate that chest CT is sensitive and moderately specific for the diagnosis of COVID-19. Chest X-ray is moderately sensitive and moderately specific for the diagnosis of COVID-19. Ultrasound is sensitive but not specific for the diagnosis of COVID-19. Thus, chest CT and ultrasound may have more utility for excluding COVID-19 than for differentiating SARS-CoV-2 infection from other causes of respiratory illness. Future diagnostic accuracy studies should pre-define positive imaging findings, include direct comparisons of the various modalities of interest in the same participant population, and implement improved reporting practices.

Quantitative IFN-γ Release Assay and Tuberculin Skin Test Results to Predict Incident Tuberculosis. A Prospective Cohort Study.

Rationale: Development of diagnostic tools with improved predictive value for tuberculosis (TB) is a global research priority.Objectives: We evaluated whether implementing higher diagnostic thresholds than currently recommended for QuantiFERON Gold-in-Tube (QFT-GIT), T-SPOT.TB, and the tuberculin skin test (TST) might improve prediction of incident TB.Methods: Follow-up of a UK cohort of 9,610 adult TB contacts and recent migrants was extended by relinkage to national TB surveillance records (median follow-up 4.7 yr). Incidence rates and rate ratios, sensitivities, specificities, and predictive values for incident TB were calculated according to ordinal strata for quantitative results of QFT-GIT, T-SPOT.TB, and TST (with adjustment for prior bacillus Calmette-Guérin [BCG] vaccination).Measurements and Main Results: For all tests, incidence rates and rate ratios increased with the magnitude of the test result (P < 0.0001). Over 3 years' follow-up, there was a modest increase in positive predictive value with the higher thresholds (3.0% for QFT-GIT ≥0.35 IU/ml vs. 3.6% for ≥4.00 IU/ml; 3.4% for T-SPOT.TB ≥5 spots vs. 5.0% for ≥50 spots; and 3.1% for BCG-adjusted TST ≥5 mm vs. 4.3% for ≥15 mm). As thresholds increased, sensitivity to detect incident TB waned for all tests (61.0% for QFT-GIT ≥0.35 IU/ml vs. 23.2% for ≥4.00 IU/ml; 65.4% for T-SPOT.TB ≥5 spots vs. 27.2% for ≥50 spots; 69.7% for BCG-adjusted TST ≥5 mm vs. 28.1% for ≥15 mm).Conclusions: Implementation of higher thresholds for QFT-GIT, T-SPOT.TB, and TST modestly increases positive predictive value for incident TB, but markedly reduces sensitivity. Novel biomarkers or validated multivariable risk algorithms are required to improve prediction of incident TB.