How to Critically Appraise and Interpret Systematic Reviews and Meta-Analyses of Diagnostic Accuracy: A User Guide.

Systematic reviews of diagnostic accuracy studies can provide the best available evidence to inform decisions regarding the use of a diagnostic test. In this guide, the authors provide a practical approach for clinicians to appraise diagnostic accuracy systematic reviews and apply their results to patient care. The first step is to identify an appropriate systematic review with a research question matching the clinical scenario. The user should evaluate the rigor of the review methods to evaluate its credibility (Did the review use clearly defined eligibility criteria, a comprehensive search strategy, structured data collection, risk of bias and applicability appraisal, and appropriate meta-analysis methods?). If the review is credible, the next step is to decide whether the diagnostic performance is adequate for clinical use (Do sensitivity and specificity estimates exceed the threshold that makes them useful in clinical practice? Are these estimates sufficiently precise? Is variability in the estimates of diagnostic accuracy across studies explained?). Diagnostic accuracy systematic reviews that are judged to be credible and provide diagnostic accuracy estimates with sufficient certainty and relevance are the most useful to inform patient care. This review discusses comparative, noncomparative, and emerging approaches to systematic reviews of diagnostic accuracy using a clinical scenario and examples based on recent publications.

Rapid antigen-based and rapid molecular tests for the detection of SARS-CoV-2: a rapid review with network meta-analysis of diagnostic test accuracy studies.

BACKGROUND: The global spread of COVID-19 created an explosion in rapid tests with results in < 1 hour, but their relative performance characteristics are not fully understood yet. Our aim was to determine the most sensitive and specific rapid test for the diagnosis of SARS-CoV-2. METHODS: Design: Rapid review and diagnostic test accuracy network meta-analysis (DTA-NMA). ELIGIBILITY CRITERIA: Randomized controlled trials (RCTs) and observational studies assessing rapid antigen and/or rapid molecular test(s) to detect SARS-CoV-2 in participants of any age, suspected or not with SARS-CoV-2 infection. INFORMATION SOURCES: Embase, MEDLINE, and Cochrane Central Register of Controlled Trials, up to September 12, 2021. OUTCOME MEASURES: Sensitivity and specificity of rapid antigen and molecular tests suitable for detecting SARS-CoV-2. Data extraction and risk of bias assessment: Screening of literature search results was conducted by one reviewer; data abstraction was completed by one reviewer and independently verified by a second reviewer. Risk of bias was not assessed in the included studies. DATA SYNTHESIS: Random-effects meta-analysis and DTA-NMA. RESULTS: We included 93 studies (reported in 88 articles) relating to 36 rapid antigen tests in 104,961 participants and 23 rapid molecular tests in 10,449 participants. Overall, rapid antigen tests had a sensitivity of 0.75 (95% confidence interval 0.70-0.79) and specificity of 0.99 (0.98-0.99). Rapid antigen test sensitivity was higher when nasal or combined samples (e.g., combinations of nose, throat, mouth, or saliva samples) were used, but lower when nasopharyngeal samples were used, and in those classified as asymptomatic at the time of testing. Rapid molecular tests may result in fewer false negatives than rapid antigen tests (sensitivity: 0.93, 0.88-0.96; specificity: 0.98, 0.97-0.99). The tests with the highest sensitivity and specificity estimates were the Xpert Xpress rapid molecular test by Cepheid (sensitivity: 0.99, 0.83-1.00; specificity: 0.97, 0.69-1.00) among the 23 commercial rapid molecular tests and the COVID-VIRO test by AAZ-LMB (sensitivity: 0.93, 0.48-0.99; specificity: 0.98, 0.44-1.00) among the 36 rapid antigen tests we examined. CONCLUSIONS: Rapid molecular tests were associated with both high sensitivity and specificity, while rapid antigen tests were mainly associated with high specificity, according to the minimum performance requirements by WHO and Health Canada. Our rapid review was limited to English, peer-reviewed published results of commercial tests, and study risk of bias was not assessed. A full systematic review is required. REVIEW REGISTRATION: PROSPERO CRD42021289712.

Prognostic factors for the development and progression of proliferative diabetic retinopathy in people with diabetic retinopathy.

BACKGROUND: Diabetic retinopathy (DR) is characterised by neurovascular degeneration as a result of chronic hyperglycaemia. Proliferative diabetic retinopathy (PDR) is the most serious complication of DR and can lead to total (central and peripheral) visual loss. PDR is characterised by the presence of abnormal new blood vessels, so-called "new vessels," at the optic disc (NVD) or elsewhere in the retina (NVE). PDR can progress to high-risk characteristics (HRC) PDR (HRC-PDR), which is defined by the presence of NVD more than one-fourth to one-third disc area in size plus vitreous haemorrhage or pre-retinal haemorrhage, or vitreous haemorrhage or pre-retinal haemorrhage obscuring more than one disc area. In severe cases, fibrovascular membranes grow over the retinal surface and tractional retinal detachment with sight loss can occur, despite treatment. Although most, if not all, individuals with diabetes will develop DR if they live long enough, only some progress to the sight-threatening PDR stage.  OBJECTIVES: To determine risk factors for the development of PDR and HRC-PDR in people with diabetes and DR. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials (CENTRAL; which contains the Cochrane Eyes and Vision Trials Register; 2022, Issue 5), Ovid MEDLINE, and Ovid Embase. The date of the search was 27 May 2022. Additionally, the search was supplemented by screening reference lists of eligible articles. There were no restrictions to language or year of publication.  SELECTION CRITERIA: We included prospective or retrospective cohort studies and case-control longitudinal studies evaluating prognostic factors for the development and progression of PDR, in people who have not had previous treatment for DR. The target population consisted of adults (≥18 years of age) of any gender, sexual orientation, ethnicity, socioeconomic status, and geographical location, with non-proliferative diabetic retinopathy (NPDR) or PDR with less than HRC-PDR, diagnosed as per standard clinical practice. Two review authors independently screened titles and abstracts, and full-text articles, to determine eligibility; discrepancies were resolved through discussion. We considered prognostic factors measured at baseline and any other time points during the study and in any clinical setting. Outcomes were evaluated at three and eight years (± two years) or lifelong.  DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data from included studies using a data extraction form that we developed and piloted prior to the data collection stage. We resolved any discrepancies through discussion. We used the Quality in Prognosis Studies (QUIPS) tool to assess risk of bias. We conducted meta-analyses in clinically relevant groups using a random-effects approach. We reported hazard ratios (HR), odds ratios (OR), and risk ratios (RR) separately for each available prognostic factor and outcome, stratified by different time points. Where possible, we meta-analysed adjusted prognostic factors. We evaluated the certainty of the evidence with an adapted version of the GRADE framework.   MAIN RESULTS: We screened 6391 records. From these, we identified 59 studies (87 articles) as eligible for inclusion. Thirty-five were prospective cohort studies, 22 were retrospective studies, 18 of which were cohort and six were based on data from electronic registers, and two were retrospective case-control studies. Twenty-three studies evaluated participants with type 1 diabetes (T1D), 19 with type 2 diabetes (T2D), and 17 included mixed populations (T1D and T2D). Studies on T1D included between 39 and 3250 participants at baseline, followed up for one to 45 years. Studies on T2D included between 100 and 71,817 participants at baseline, followed up for one to 20 years. The studies on mixed populations of T1D and T2D ranged from 76 to 32,553 participants at baseline, followed up for four to 25 years.  We found evidence indicating that higher glycated haemoglobin (haemoglobin A1c (HbA1c)) levels (adjusted OR ranged from 1.11 (95% confidence interval (CI) 0.93 to 1.32) to 2.10 (95% CI 1.64 to 2.69) and more advanced stages of retinopathy (adjusted OR ranged from 1.38 (95% CI 1.29 to 1.48) to 12.40 (95% CI 5.31 to 28.98) are independent risk factors for the development of PDR in people with T1D and T2D. We rated the evidence for these factors as of moderate certainty because of moderate to high risk of bias in the studies.  There was also some evidence suggesting several markers for renal disease (for example, nephropathy (adjusted OR ranged from 1.58 (95% CI not reported) to 2.68 (2.09 to 3.42), and creatinine (adjusted meta-analysis HR 1.61 (95% CI 0.77 to 3.36)), and, in people with T1D, age at diagnosis of diabetes (< 12 years of age) (standardised regression estimate 1.62, 95% CI 1.06 to 2.48), increased triglyceride levels (adjusted RR 1.55, 95% CI 1.06 to 1.95), and larger retinal venular diameters (RR 4.28, 95% CI 1.50 to 12.19) may increase the risk of progression to PDR. The certainty of evidence for these factors, however, was low to very low, due to risk of bias in the included studies, inconsistency (lack of studies preventing the grading of consistency or variable outcomes), and imprecision (wide CIs). There was no substantial and consistent evidence to support duration of diabetes, systolic or diastolic blood pressure, total cholesterol, low- (LDL) and high- (HDL) density lipoproteins, gender, ethnicity, body mass index (BMI), socioeconomic status, or tobacco and alcohol consumption as being associated with incidence of PDR. There was insufficient evidence to evaluate prognostic factors associated with progression of PDR to HRC-PDR.  AUTHORS' CONCLUSIONS: Increased HbA1c is likely to be associated with progression to PDR; therefore, maintaining adequate glucose control throughout life, irrespective of stage of DR severity, may help to prevent progression to PDR and risk of its sight-threatening complications. Renal impairment in people with T1D or T2D, as well as younger age at diagnosis of diabetes mellitus (DM), increased triglyceride levels, and increased retinal venular diameters in people with T1D may also be associated with increased risk of progression to PDR. Given that more advanced DR severity is associated with higher risk of progression to PDR, the earlier the disease is identified, and the above systemic risk factors are controlled, the greater the chance of reducing the risk of PDR and saving sight.

ANTECEDENTES: La retinopatía diabética (RD) se caracteriza por la degeneración neurovascular como consecuencia de la hiperglucemia crónica. La retinopatía diabética proliferativa (RDP) es la complicación más grave de la RD y puede provocar una pérdida total (central y periférica) de la visión. La RDP se caracteriza por la presencia de vasos sanguíneos de neoformación anormales, neovascularización, en la papila óptica (NVP) o en cualquier otra parte de la retina (NVE). La RDP puede evolucionar a una RDP con características de alto riesgo (RDP­CAR), que se define por la presencia de NVP de más de un cuarto a un tercio del área discal más hemorragia vítrea o prerretiniana, o hemorragia vítrea o prerretiniana que oscurece más de un área papilar. En los casos graves, crecen membranas fibrovasculares sobre la superficie retiniana y se puede producir un desprendimiento de retina por tracción con pérdida de la visión, a pesar del tratamiento. Aunque la mayoría de las personas con diabetes, si no todas, desarrollarán RD si viven lo suficiente, solo algunas llegan a la fase de RDP, que pone en peligro la vista. OBJETIVOS: Determinar los factores de riesgo de aparición de la RDP y RDP­CAR en personas con diabetes y RD. MÉTODOS DE BÚSQUEDA: Se hicieron búsquedas en el Registro Cochrane central de ensayos controlados (Cochrane Central Register of Controlled Trials, CENTRAL; que contiene el Registro de ensayos del Grupo Cochrane de Salud ocular y de la visión [Cochrane Eyes and Vision]; 2022, número 5), Ovid MEDLINE y Ovid Embase. La fecha de búsqueda fue el 27 de mayo de 2022. Además, la búsqueda se complementó con el cribado de las listas de referencias de los artículos elegibles. No hubo restricciones en cuanto al idioma ni al año de publicación. CRITERIOS DE SELECCIÓN: Se incluyeron estudios de cohortes prospectivos o retrospectivos y estudios longitudinales de casos y controles que evaluaran los factores pronósticos para la aparición y la progresión de la RDP, en personas que no habían recibido tratamiento previo para la RD. La población de interés estaba formada por adultos (≥18 años de edad) de cualquier sexo, orientación sexual, etnia, nivel socioeconómico y ubicación geográfica, con retinopatía diabética no proliferativa (RDNP) o RDP sin llegar a RDP­CAR, diagnosticada según la práctica clínica habitual. Dos autores de la revisión examinaron de forma independiente los títulos y resúmenes, así como los artículos completos, para determinar la elegibilidad; las discrepancias se resolvieron mediante debate. Se tuvieron en cuenta los factores pronósticos medidos al inicio del estudio y en cualquier otro punto temporal durante el estudio y en cualquier contexto clínico. Los desenlaces se evaluaron a los tres y ocho años (± dos años) o de por vida. OBTENCIÓN Y ANÁLISIS DE LOS DATOS: Dos autores de la revisión extrajeron de forma independiente los datos de los estudios incluidos mediante un formulario de extracción de datos que se desarrolló y evaluó antes de la etapa de obtención de datos. Las discrepancias se resolvieron mediante debate. Para evaluar el riesgo de sesgo se utilizó la herramienta Quality in Prognosis Studies (QUIPS). Se realizaron metanálisis en grupos clínicamente relevantes utilizando un enfoque de efectos aleatorios. Se proporcionaron los cociente de riesgos instantáneos (CRI), los odds ratios (OR) y las razones de riesgos (RR) por separado para cada factor pronóstico y desenlace disponibles, estratificados por diferentes puntos temporales. Cuando fue posible, se realizó un metanálisis de los factores pronósticos ajustados. La certeza de la evidencia se evaluó con una versión adaptada del método GRADE. RESULTADOS PRINCIPALES: Se han examinado 6391 registros. A partir de estos se identificaron 59 estudios (87 artículos) elegibles para inclusión. Treinta y cinco fueron estudios de cohortes prospectivos, 22 fueron estudios retrospectivos, 18 de los cuales fueron de cohortes y 6 se basaron en datos de registros electrónicos, y 2 fueron estudios retrospectivos de casos y controles. Veintitrés estudios evaluaron a participantes con diabetes tipo 1 (DT1), 19 con diabetes tipo 2 (DT2) y 17 incluyeron poblaciones mixtas (DT1 y DT2). Los estudios sobre la DT1 incluyeron entre 39 y 3250 participantes al inicio del estudio, con un seguimiento de 1 a 45 años. Los estudios sobre la DT2 incluyeron entre 100 y 71 817 participantes al inicio del estudio, con un seguimiento de 1 a 20 años. Los estudios sobre poblaciones mixtas de DT1 y DT2 variaron entre 76 y 32 553 participantes al inicio del estudio, con un seguimiento de 4 a 25 años. Se encontró evidencia que indicó que los niveles más altos de hemoglobina glucosilada (hemoglobina A1c [HbA1c]) (OR ajustado que varió de 1,11 [intervalo de confianza (IC) del 95%: 0,93 a 1,32] a 2,10 [IC del 95%: 1,64 a 2,69]) y los estadios más avanzados de retinopatía (OR ajustado que varió entre 1,38 [IC del 95%: 1,29 a 1,48] y 12,40 [IC del 95%: 5,31 a 28,98]) son factores de riesgo independientes para el desarrollo de RDP en personas con DT1 y DT2. La evidencia para estos factores se consideró de certeza moderada debido al riesgo moderado a alto de sesgo en los estudios. También hubo alguna evidencia que indicó varios marcadores de enfermedad renal (por ejemplo, nefropatía [OR ajustado que varió entre 1,58 (IC del 95% no proporcionado) y 2,68 (2,09 a 3,42)] y creatinina [metanálisis ajustado CRI 1,61 (IC del 95%: 0,77 a 3.36)]), y, en las personas con DT1, la edad en el momento del diagnóstico de la diabetes (< 12 años) (estimación de la regresión estandarizada 1,62; IC del 95%: 1,06 a 2,48), el aumento de los niveles de triglicéridos (RR ajustado 1,55; IC del 95%: 1,06 a 1,95) y los diámetros venulares retinianos mayores (RR 4,28; IC del 95%: 1,50 a 12,19) podrían aumentar el riesgo de progresión a RDP. Sin embargo, la certeza de la evidencia para estos factores fue de baja a muy baja, debido al riesgo de sesgo en los estudios incluidos, la inconsistencia (falta de estudios que impide la calificación de consistencia o desenlaces variables) y la imprecisión (IC amplios). No hubo evidencia importante ni consistente que apoyara que la duración de la diabetes, la presión arterial sistólica o diastólica, el colesterol total, las lipoproteínas de baja (LDL) y alta (HDL) densidad, el sexo, el origen étnico, el índice de masa corporal (IMC), el nivel socioeconómico o el consumo de tabaco y alcohol estuvieran asociados con la incidencia de RDP. No hubo evidencia suficiente para evaluar los factores pronósticos asociados con la progresión de la RDP a RDP­CAR. CONCLUSIONES DE LOS AUTORES: Es probable que el aumento de la HbA1c se asocie con la progresión a la RDP; por lo tanto, mantener un control adecuado de la glucosa durante toda la vida, independientemente del estadio de gravedad de la RD, podría ayudar a prevenir la progresión a la RDP y el riesgo de sus complicaciones que ponen en peligro la vista. La insuficiencia renal en personas con DT1 o DT2, así como una menor edad en el momento del diagnóstico de la diabetes mellitus (DM), el aumento de los niveles de triglicéridos y el aumento de los diámetros venulares retinianos en personas con DT1 también se podrían asociar con un mayor riesgo de progresión a RDP. Dado que la gravedad más avanzada de la RD se asocia con un mayor riesgo de progresión a RDP, cuanto antes se identifique la enfermedad y se controlen los factores de riesgo sistémicos mencionados, mayores serán las posibilidades de reducir el riesgo de RDP y conservar la vista.

Health technology assessment of diagnostic tests: a state of the art review of methods guidance from international organizations.

OBJECTIVES: To identify which international health technology assessment (HTA) agencies are undertaking evaluations of medical tests, summarize commonalities and differences in methodological approach, and highlight examples of good practice. METHODS: A methodological review incorporating: systematic identification of HTA guidance documents mentioning evaluation of tests; identification of key contributing organizations and abstraction of approaches to all essential HTA steps; summary of similarities and differences between organizations; and identification of important emergent themes which define the current state of the art and frontiers where further development is needed. RESULTS: Seven key organizations were identified from 216 screened. The main themes were: elucidation of claims of test benefits; attitude to direct and indirect evidence of clinical effectiveness (including evidence linkage); searching; quality assessment; and health economic evaluation. With the exception of dealing with test accuracy data, approaches were largely based on general approaches to HTA with few test-specific modifications. Elucidation of test claims and attitude to direct and indirect evidence are where we identified the biggest dissimilarities in approach. CONCLUSIONS: There is consensus on some aspects of HTA of tests, such as dealing with test accuracy, and examples of good practice which HTA organizations new to test evaluation can emulate. The focus on test accuracy contrasts with universal acknowledgment that it is not a sufficient evidence base for test evaluation. There are frontiers where methodological development is urgently required, notably integrating direct and indirect evidence and standardizing approaches to evidence linkage.

Defining the Role of Cellular Immune Signatures in Diagnostic Evaluation of Suspected Tuberculosis.

BACKGROUND: Diagnosis of paucibacillary tuberculosis (TB) including extrapulmonary TB is a significant challenge, particularly in high-income, low-incidence settings. Measurement of Mycobacterium tuberculosis (Mtb)-specific cellular immune signatures by flow cytometry discriminates active TB from latent TB infection (LTBI) in case-control studies; however, their diagnostic accuracy and clinical utility in routine clinical practice is unknown. METHODS: Using a nested case-control study design within a prospective multicenter cohort of patients presenting with suspected TB in England, we assessed diagnostic accuracy of signatures in 134 patients who tested interferon-gamma release assay (IGRA)-positive and had final diagnoses of TB or non-TB diseases with coincident LTBI. Cellular signatures were measured using flow cytometry. RESULTS: All signatures performed less well than previously reported. Only signatures incorporating measurement of phenotypic markers on functional Mtb-specific CD4 T cells discriminated active TB from non-TB diseases with LTBI. The signatures measuring HLA-DR+IFNγ + CD4 T cells and CD45RA-CCR7-CD127- IFNγ -IL-2-TNFα + CD4 T cells performed best with 95% positive predictive value (95% confidence interval, 90-97) in the clinically challenging subpopulation of IGRA-positive but acid-fast bacillus (AFB) smear-negative TB suspects. CONCLUSIONS: Two cellular immune signatures could improve and accelerate diagnosis in the challenging group of patients who are IGRA-positive, AFB smear-negative, and have paucibacillary TB.

Limited Evidence for Use of a Black Race Modifier in eGFR Calculations: A Systematic Review.

BACKGROUND: Commonly used estimated glomerular filtration rate (eGFR) equations include a Black race modifier (BRM) that was incorporated during equation derivation. Race is a social construct, and a poorly characterized variable that is applied inconsistently in clinical settings. The BRM results in higher eGFR for any creatinine concentration, implying fundamental differences in creatinine production or excretion in Black individuals compared to other populations. Equations without inclusion of the BRM have the potential to detect kidney disease earlier in patients at the greatest risk of chronic kidney disease (CKD), but also has the potential to over-diagnose CKD or impact downstream clinical interventions. The purpose of this study was to use an evidence-based approach to systematically evaluate the literature relevant to the performance of the eGFR equations with and without the BRM and to examine the clinical impact of the use or removal. CONTENT: PubMed and Embase databases were searched for studies comparing measured GFR to eGFR in racially diverse adult populations using the Modification of Diet in Renal Disease or the 2009-Chronic Kidney Disease Epidemiology Collaboration-creatinine equations based on standardized creatinine measurements. Additionally, we searched for studies comparing clinical use of eGFR calculated with and without the BRM. Here, 8632 unique publications were identified; an additional 3 studies were added post hoc. In total, 96 studies were subjected to further analysis and 44 studies were used to make a final assessment. SUMMARY: There is limited published evidence to support the use of a BRM in eGFR equations.

Xpert MTB/RIF Ultra assay for tuberculosis disease and rifampicin resistance in children.

BACKGROUND: Every year, an estimated one million children and young adolescents become ill with tuberculosis, and around 226,000 of those children die. Xpert MTB/RIF Ultra (Xpert Ultra) is a molecular World Health Organization (WHO)-recommended rapid diagnostic test that simultaneously detects Mycobacterium tuberculosis complex and rifampicin resistance. We previously published a Cochrane Review 'Xpert MTB/RIF and Xpert MTB/RIF Ultra assays for tuberculosis disease and rifampicin resistance in children'. The current review updates evidence on the diagnostic accuracy of Xpert Ultra in children presumed to have tuberculosis disease. Parts of this review update informed the 2022 WHO updated guidance on management of tuberculosis in children and adolescents. OBJECTIVES: To assess the diagnostic accuracy of Xpert Ultra for detecting: pulmonary tuberculosis, tuberculous meningitis, lymph node tuberculosis, and rifampicin resistance, in children with presumed tuberculosis. Secondary objectives To investigate potential sources of heterogeneity in accuracy estimates. For detection of tuberculosis, we considered age, comorbidity (HIV, severe pneumonia, and severe malnutrition), and specimen type as potential sources. To summarize the frequency of Xpert Ultra trace results. SEARCH METHODS: We searched the Cochrane Infectious Diseases Group Specialized Register, MEDLINE, Embase, three other databases, and three trial registers without language restrictions to 9 March 2021. SELECTION CRITERIA: Cross-sectional and cohort studies and randomized trials that evaluated Xpert Ultra in HIV-positive and HIV-negative children under 15 years of age. We included ongoing studies that helped us address the review objectives. We included studies evaluating sputum, gastric, stool, or nasopharyngeal specimens (pulmonary tuberculosis), cerebrospinal fluid (tuberculous meningitis), and fine needle aspirate or surgical biopsy tissue (lymph node tuberculosis). For detecting tuberculosis, reference standards were microbiological (culture) or composite reference standard; for stool, we also included Xpert Ultra performed on a routine respiratory specimen. For detecting rifampicin resistance, reference standards were drug susceptibility testing or MTBDRplus. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and, using QUADAS-2, assessed methodological quality judging risk of bias separately for each target condition and reference standard. For each target condition, we used the bivariate model to estimate summary sensitivity and specificity with 95% confidence intervals (CIs). We stratified all analyses by type of reference standard. We summarized the frequency of Xpert Ultra trace results; trace represents detection of a very low quantity of Mycobacterium tuberculosis DNA. We assessed certainty of evidence using GRADE. MAIN RESULTS: We identified 14 studies (11 new studies since the previous review). For detection of pulmonary tuberculosis, 335 data sets (25,937 participants) were available for analysis. We did not identify any studies that evaluated Xpert Ultra accuracy for tuberculous meningitis or lymph node tuberculosis. Three studies evaluated Xpert Ultra for detection of rifampicin resistance. Ten studies (71%) took place in countries with a high tuberculosis burden based on WHO classification. Overall, risk of bias was low. Detection of pulmonary tuberculosis Sputum, 5 studies Xpert Ultra summary sensitivity verified by culture was 75.3% (95% CI 64.3 to 83.8; 127 participants; high-certainty evidence), and specificity was 97.1% (95% CI 94.7 to 98.5; 1054 participants; high-certainty evidence). Gastric aspirate, 7 studies Xpert Ultra summary sensitivity verified by culture was 70.4% (95% CI 53.9 to 82.9; 120 participants; moderate-certainty evidence), and specificity was 94.1% (95% CI 84.8 to 97.8; 870 participants; moderate-certainty evidence). Stool, 6 studies Xpert Ultra summary sensitivity verified by culture was 56.1% (95% CI 39.1 to 71.7; 200 participants; moderate-certainty evidence), and specificity was 98.0% (95% CI 93.3 to 99.4; 1232 participants; high certainty-evidence). Nasopharyngeal aspirate, 4 studies Xpert Ultra summary sensitivity verified by culture was 43.7% (95% CI 26.7 to 62.2; 46 participants; very low-certainty evidence), and specificity was 97.5% (95% CI 93.6 to 99.0; 489 participants; high-certainty evidence). Xpert Ultra sensitivity was lower against a composite than a culture reference standard for all specimen types other than nasopharyngeal aspirate, while specificity was similar against both reference standards. Interpretation of results In theory, for a population of 1000 children: • where 100 have pulmonary tuberculosis in sputum (by culture): - 101 would be Xpert Ultra-positive, and of these, 26 (26%) would not have pulmonary tuberculosis (false positive); and - 899 would be Xpert Ultra-negative, and of these, 25 (3%) would have tuberculosis (false negative). • where 100 have pulmonary tuberculosis in gastric aspirate (by culture): - 123 would be Xpert Ultra-positive, and of these, 53 (43%) would not have pulmonary tuberculosis (false positive); and - 877 would be Xpert Ultra-negative, and of these, 30 (3%) would have tuberculosis (false negative). • where 100 have pulmonary tuberculosis in stool (by culture): - 74 would be Xpert Ultra-positive, and of these, 18 (24%) would not have pulmonary tuberculosis (false positive); and - 926 would be Xpert Ultra-negative, and of these, 44 (5%) would have tuberculosis (false negative). • where 100 have pulmonary tuberculosis in nasopharyngeal aspirate (by culture): - 66 would be Xpert Ultra-positive, and of these, 22 (33%) would not have pulmonary tuberculosis (false positive); and - 934 would be Xpert Ultra-negative, and of these, 56 (6%) would have tuberculosis (false negative). Detection of rifampicin resistance Xpert Ultra sensitivity was 100% (3 studies, 3 participants; very low-certainty evidence), and specificity range was 97% to 100% (3 studies, 128 participants; low-certainty evidence). Trace results Xpert Ultra trace results, regarded as positive in children by WHO standards, were common. Xpert Ultra specificity remained high in children, despite the frequency of trace results. AUTHORS' CONCLUSIONS: We found Xpert Ultra sensitivity to vary by specimen type, with sputum having the highest sensitivity, followed by gastric aspirate and stool. Nasopharyngeal aspirate had the lowest sensitivity. Xpert Ultra specificity was high against both microbiological and composite reference standards. However, the evidence base is still limited, and findings may be imprecise and vary by study setting. Although we found Xpert Ultra accurate for detection of rifampicin resistance, results were based on a very small number of studies that included only three children with rifampicin resistance. Therefore, findings should be interpreted with caution. Our findings provide support for the use of Xpert Ultra as an initial rapid molecular diagnostic in children being evaluated for tuberculosis.

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.

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.

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.

MRI-Targeted or Standard Biopsy for Prostate-Cancer Diagnosis.

BACKGROUND: Multiparametric magnetic resonance imaging (MRI), with or without targeted biopsy, is an alternative to standard transrectal ultrasonography-guided biopsy for prostate-cancer detection in men with a raised prostate-specific antigen level who have not undergone biopsy. However, comparative evidence is limited. METHODS: In a multicenter, randomized, noninferiority trial, we assigned men with a clinical suspicion of prostate cancer who had not undergone biopsy previously to undergo MRI, with or without targeted biopsy, or standard transrectal ultrasonography-guided biopsy. Men in the MRI-targeted biopsy group underwent a targeted biopsy (without standard biopsy cores) if the MRI was suggestive of prostate cancer; men whose MRI results were not suggestive of prostate cancer were not offered biopsy. Standard biopsy was a 10-to-12-core, transrectal ultrasonography-guided biopsy. The primary outcome was the proportion of men who received a diagnosis of clinically significant cancer. Secondary outcomes included the proportion of men who received a diagnosis of clinically insignificant cancer. RESULTS: A total of 500 men underwent randomization. In the MRI-targeted biopsy group, 71 of 252 men (28%) had MRI results that were not suggestive of prostate cancer, so they did not undergo biopsy. Clinically significant cancer was detected in 95 men (38%) in the MRI-targeted biopsy group, as compared with 64 of 248 (26%) in the standard-biopsy group (adjusted difference, 12 percentage points; 95% confidence interval [CI], 4 to 20; P=0.005). MRI, with or without targeted biopsy, was noninferior to standard biopsy, and the 95% confidence interval indicated the superiority of this strategy over standard biopsy. Fewer men in the MRI-targeted biopsy group than in the standard-biopsy group received a diagnosis of clinically insignificant cancer (adjusted difference, -13 percentage points; 95% CI, -19 to -7; P<0.001). CONCLUSIONS: The use of risk assessment with MRI before biopsy and MRI-targeted biopsy was superior to standard transrectal ultrasonography-guided biopsy in men at clinical risk for prostate cancer who had not undergone biopsy previously. (Funded by the National Institute for Health Research and the European Association of Urology Research Foundation; PRECISION ClinicalTrials.gov number, NCT02380027 .).

The IDENTIFY study: the investigation and detection of urological neoplasia in patients referred with suspected urinary tract cancer - a multicentre observational study.

OBJECTIVE: To evaluate the contemporary prevalence of urinary tract cancer (bladder cancer, upper tract urothelial cancer [UTUC] and renal cancer) in patients referred to secondary care with haematuria, adjusted for established patient risk markers and geographical variation. PATIENTS AND METHODS: This was an international multicentre prospective observational study. We included patients aged ≥16 years, referred to secondary care with suspected urinary tract cancer. Patients with a known or previous urological malignancy were excluded. We estimated the prevalence of bladder cancer, UTUC, renal cancer and prostate cancer; stratified by age, type of haematuria, sex, and smoking. We used a multivariable mixed-effects logistic regression to adjust cancer prevalence for age, type of haematuria, sex, smoking, hospitals, and countries. RESULTS: Of the 11 059 patients assessed for eligibility, 10 896 were included from 110 hospitals across 26 countries. The overall adjusted cancer prevalence (n = 2257) was 28.2% (95% confidence interval [CI] 22.3-34.1), bladder cancer (n = 1951) 24.7% (95% CI 19.1-30.2), UTUC (n = 128) 1.14% (95% CI 0.77-1.52), renal cancer (n = 107) 1.05% (95% CI 0.80-1.29), and prostate cancer (n = 124) 1.75% (95% CI 1.32-2.18). The odds ratios for patient risk markers in the model for all cancers were: age 1.04 (95% CI 1.03-1.05; P < 0.001), visible haematuria 3.47 (95% CI 2.90-4.15; P < 0.001), male sex 1.30 (95% CI 1.14-1.50; P < 0.001), and smoking 2.70 (95% CI 2.30-3.18; P < 0.001). CONCLUSIONS: A better understanding of cancer prevalence across an international population is required to inform clinical guidelines. We are the first to report urinary tract cancer prevalence across an international population in patients referred to secondary care, adjusted for patient risk markers and geographical variation. Bladder cancer was the most prevalent disease. Visible haematuria was the strongest predictor for urinary tract cancer.

Screening tests for active pulmonary tuberculosis in children.

BACKGROUND: Globally, children under 15 years represent approximately 12% of new tuberculosis cases, but 16% of the estimated 1.4 million deaths. This higher share of mortality highlights the urgent need to develop strategies to improve case detection in this age group and identify children without tuberculosis disease who should be considered for tuberculosis preventive treatment. One such strategy is systematic screening for tuberculosis in high-risk groups. OBJECTIVES: To estimate the sensitivity and specificity of the presence of one or more tuberculosis symptoms, or symptom combinations; chest radiography (CXR); Xpert MTB/RIF; Xpert Ultra; and combinations of these as screening tests for detecting active pulmonary childhood tuberculosis in the following groups. - Tuberculosis contacts, including household contacts, school contacts, and other close contacts of a person with infectious tuberculosis. - Children living with HIV. - Children with pneumonia. - Other risk groups (e.g. children with a history of previous tuberculosis, malnourished children). - Children in the general population in high tuberculosis burden settings. SEARCH METHODS: We searched six databases, including the Cochrane Central Register of Controlled Trials, MEDLINE, and Embase, on 14 February 2020 without language restrictions and contacted researchers in the field. SELECTION CRITERIA: Cross-sectional and cohort studies where at least 75% of children were aged under 15 years. Studies were eligible if conducted for screening rather than diagnosing tuberculosis. Reference standards were microbiological (MRS) and composite reference standard (CRS), which may incorporate symptoms and CXR. DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed study quality using QUADAS-2. We consolidated symptom screens across included studies into groups that used similar combinations of symptoms as follows: one or more of cough, fever, or poor weight gain and one or more of cough, fever, or decreased playfulness. For combination of symptoms, a positive screen was the presence of one or more than one symptom. We used a bivariate model to estimate pooled sensitivity and specificity with 95% confidence intervals (CIs) and performed analyses separately by reference standard. We assessed certainty of evidence using GRADE. MAIN RESULTS: Nineteen studies assessed the following screens: one symptom (15 studies, 10,097 participants); combinations of symptoms (12 studies, 29,889 participants); CXR (10 studies, 7146 participants); and Xpert MTB/RIF (2 studies, 787 participants). Several studies assessed more than one screening test. No studies assessed Xpert Ultra. For 16 studies (84%), risk of bias for the reference standard domain was unclear owing to concern about incorporation bias. Across other quality domains, risk of bias was generally low. Symptom screen (verified by CRS) One or more of cough, fever, or poor weight gain in tuberculosis contacts (4 studies, tuberculosis prevalence 2% to 13%): pooled sensitivity was 89% (95% CI 52% to 98%; 113 participants; low-certainty evidence) and pooled specificity was 69% (95% CI 51% to 83%; 2582 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 339 would be screen-positive, of whom 294 (87%) would not have pulmonary tuberculosis (false positives); 661 would be screen-negative, of whom five (1%) would have pulmonary tuberculosis (false negatives). One or more of cough, fever, or decreased playfulness in children aged under five years, inpatient or outpatient (3 studies, tuberculosis prevalence 3% to 13%): sensitivity ranged from 64% to 76% (106 participants; moderate-certainty evidence) and specificity from 37% to 77% (2339 participants; low-certainty evidence). Of 1000 children where 50 have pulmonary tuberculosis, 251 to 636 would be screen-positive, of whom 219 to 598 (87% to 94%) would not have pulmonary tuberculosis; 364 to 749 would be screen-negative, of whom 12 to 18 (2% to 3%) would have pulmonary tuberculosis. One or more of cough, fever, poor weight gain, or tuberculosis close contact (World Health Organization four-symptom screen) in children living with HIV, outpatient (2 studies, tuberculosis prevalence 3% and 8%): pooled sensitivity was 61% (95% CI 58% to 64%; 1219 screens; moderate-certainty evidence) and pooled specificity was 94% (95% CI 86% to 98%; 201,916 screens; low-certainty evidence). Of 1000 symptom screens where 50 of the screens are on children with pulmonary tuberculosis, 88 would be screen-positive, of which 57 (65%) would be on children who do not have pulmonary tuberculosis; 912 would be screen-negative, of which 19 (2%) would be on children who have pulmonary tuberculosis. CXR (verified by CRS) CXR with any abnormality in tuberculosis contacts (8 studies, tuberculosis prevalence 2% to 25%): pooled sensitivity was 87% (95% CI 75% to 93%; 232 participants; low-certainty evidence) and pooled specificity was 99% (95% CI 68% to 100%; 3281 participants; low-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 63 would be screen-positive, of whom 19 (30%) would not have pulmonary tuberculosis; 937 would be screen-negative, of whom 6 (1%) would have pulmonary tuberculosis. Xpert MTB/RIF (verified by MRS) Xpert MTB/RIF, inpatient or outpatient (2 studies, tuberculosis prevalence 1% and 4%): sensitivity was 43% and 100% (16 participants; very low-certainty evidence) and specificity was 99% and 100% (771 participants; moderate-certainty evidence). Of 1000 children, where 50 have pulmonary tuberculosis, 31 to 69 would be Xpert MTB/RIF-positive, of whom 9 to 19 (28% to 29%) would not have pulmonary tuberculosis; 969 to 931 would be Xpert MTB/RIF-negative, of whom 0 to 28 (0% to 3%) would have tuberculosis. Studies often assessed more symptoms than those included in the index test and symptom definitions varied. These differences complicated data aggregation and may have influenced accuracy estimates. Both symptoms and CXR formed part of the CRS (incorporation bias), which may have led to overestimation of sensitivity and specificity. AUTHORS' CONCLUSIONS: We found that in children who are tuberculosis contacts or living with HIV, screening tests using symptoms or CXR may be useful, but our review is limited by design issues with the index test and incorporation bias in the reference standard. For Xpert MTB/RIF, we found insufficient evidence regarding screening accuracy. Prospective evaluations of screening tests for tuberculosis in children will help clarify their use. In the meantime, screening strategies need to be pragmatic to address the persistent gaps in prevention and case detection that exist in resource-limited settings.

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.

Predicting recurrent atrial fibrillation after catheter ablation: a systematic review of prognostic models.

AIMS: We assessed the performance of modelsf (risk scores) for predicting recurrence of atrial fibrillation (AF) in patients who have undergone catheter ablation. METHODS AND RESULTS: Systematic searches of bibliographic databases were conducted (November 2018). Studies were eligible for inclusion if they reported the development, validation, or impact assessment of a model for predicting AF recurrence after ablation. Model performance (discrimination and calibration) measures were extracted. The Prediction Study Risk of Bias Assessment Tool (PROBAST) was used to assess risk of bias. Meta-analysis was not feasible due to clinical and methodological differences between studies, but c-statistics were presented in forest plots. Thirty-three studies developing or validating 13 models were included; eight studies compared two or more models. Common model variables were left atrial parameters, type of AF, and age. Model discriminatory ability was highly variable and no model had consistently poor or good performance. Most studies did not assess model calibration. The main risk of bias concern was the lack of internal validation which may have resulted in overly optimistic and/or biased model performance estimates. No model impact studies were identified. CONCLUSION: Our systematic review suggests that clinical risk prediction of AF after ablation has potential, but there remains a need for robust evaluation of risk factors and development of risk scores.

Rapid diagnostic tests for Plasmodium vivax malaria in endemic countries.

BACKGROUND: Plasmodium vivax (P vivax) is a focus of malaria elimination. It is important because P vivax and Plasmodium falciparum infection are co-endemic in some areas. There are asymptomatic carriers of P vivax, and the treatment for P vivax and Plasmodium ovale malaria differs from that used in other types of malaria. Rapid diagnostic tests (RDTs) will help distinguish P vivax from other malaria species to help treatment and elimination. There are RDTs available that detect P vivax parasitaemia through the detection of P vivax-specific lactate dehydrogenase (LDH) antigens. OBJECTIVES: To assess the diagnostic accuracy of RDTs for detecting P vivax malaria infection in people living in malaria-endemic areas who present to ambulatory healthcare facilities with symptoms suggestive of malaria; and to identify which types and brands of commercial tests best detect P vivax malaria. SEARCH METHODS: We undertook a comprehensive search of the following databases up to 30 July 2019: Cochrane Infectious Diseases Group Specialized Register; Central Register of Controlled Trials (CENTRAL), published in the Cochrane Library; MEDLINE (PubMed); Embase (OVID); Science Citation Index Expanded (SCI-EXPANDED) and Conference Proceedings Citation Index-Science (CPCI-S), both in the Web of Science. SELECTION CRITERIA: Studies comparing RDTs with a reference standard (microscopy or polymerase chain reaction (PCR)) in blood samples from patients attending ambulatory health facilities with symptoms suggestive of malaria in P vivax-endemic areas. DATA COLLECTION AND ANALYSIS: For each included study, two review authors independently extracted data using a pre-piloted data extraction form. The methodological quality of the studies were assessed using a tailored Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool. We grouped studies according to commercial brand of the RDT and performed meta-analysis when appropriate. The results given by the index tests were based on the antibody affinity (referred to as the strength of the bond between an antibody and an antigen) and avidity (referred to as the strength of the overall bond between a multivalent antibody and multiple antigens). All analyses were stratified by the type of reference standard. The bivariate model was used to estimate the pooled sensitivity and specificity with 95% confidence intervals (CIs), this model was simplified when studies were few. We assessed the certainty of the evidence using the GRADE approach. MAIN RESULTS: We included 10 studies that assessed the accuracy of six different RDT brands (CareStart Malaria Pf/Pv Combo test, Falcivax Device Rapid test, Immuno-Rapid Malaria Pf/Pv test, SD Bioline Malaria Ag Pf/Pv test, OnSite Pf/Pv test and Test Malaria Pf/Pv rapid test) for detecting P vivax malaria. One study directly compared the accuracy of two RDT brands. Of the 10 studies, six used microscopy, one used PCR, two used both microscopy and PCR separately and one used microscopy corrected by PCR as the reference standard. Four of the studies were conducted in Ethiopia, two in India, and one each in Bangladesh, Brazil, Colombia and Sudan. The studies often did not report how patients were selected. In the patient selection domain, we judged the risk of bias as unclear for nine studies. We judged all studies to be of unclear applicability concern. In the index test domain, we judged most studies to be at low risk of bias, but we judged nine studies to be of unclear applicability concern. There was poor reporting on lot testing, how the RDTs were stored, and background parasitaemia density (a key variable determining diagnostic accuracy of RDTs). Only half of the included studies were judged to be at low risk of bias in the reference standard domain, Studies often did not report whether the results of the reference standard could classify the target condition or whether investigators knew the results of the RDT when interpreting the results of the reference standard. All 10 studies were judged to be at low risk of bias in the flow and timing domain. Only two brands were evaluated by more than one study. Four studies evaluated the CareStart Malaria Pf/Pv Combo test against microscopy and two studies evaluated the Falcivax Device Rapid test against microscopy. The pooled sensitivity and specificity were 99% (95% CI 94% to 100%; 251 patients, moderate-certainty evidence) and 99% (95% CI 99% to 100%; 2147 patients, moderate-certainty evidence) for CareStart Malaria Pf/Pv Combo test. For a prevalence of 20%, about 206 people will have a positive CareStart Malaria Pf/Pv Combo test result and the remaining 794 people will have a negative result. Of the 206 people with positive results, eight will be incorrect (false positives), and of the 794 people with a negative result, two would be incorrect (false negative). For the Falcivax Device Rapid test, the pooled sensitivity was 77% (95% CI: 53% to 91%, 89 patients, low-certainty evidence) and the pooled specificity was 99% (95% CI: 98% to 100%, 621 patients, moderate-certainty evidence), respectively. For a prevalence of 20%, about 162 people will have a positive Falcivax Device Rapid test result and the remaining 838 people will have a negative result. Of the 162 people with positive results, eight will be incorrect (false positives), and of the 838 people with a negative result, 46 would be incorrect (false negative). AUTHORS' CONCLUSIONS: The CareStart Malaria Pf/Pv Combo test was found to be highly sensitive and specific in comparison to microscopy for detecting P vivax in ambulatory healthcare in endemic settings, with moderate-certainty evidence. The number of studies included in this review was limited to 10 studies and we were able to estimate the accuracy of 2 out of 6 RDT brands included, the CareStart Malaria Pf/Pv Combo test and the Falcivax Device Rapid test. Thus, the differences in sensitivity and specificity between all the RDT brands could not be assessed. More high-quality studies in endemic field settings are needed to assess and compare the accuracy of RDTs designed to detect P vivax.