Simultaneous Venous-Arterial Doppler Ultrasound During Early Fluid Resuscitation to Characterize a Novel Doppler Starling Curve: A Prospective Observational Pilot Study.

Background: The likelihood of a patient being preload responsive-a state where the cardiac output or stroke volume (SV) increases significantly in response to preload-depends on both cardiac filling and function. This relationship is described by the canonical Frank-Starling curve. Research Question: We hypothesize that a novel method for phenotyping hypoperfused patients (ie, the "Doppler Starling curve") using synchronously measured jugular venous Doppler as a marker of central venous pressure (CVP) and corrected flow time of the carotid artery (ccFT) as a surrogate for SV will refine the pretest probability of preload responsiveness/unresponsiveness. Study Design and Methods: We retrospectively analyzed a prospectively collected convenience sample of hypoperfused adult emergency department (ED) patients. Doppler measurements were obtained before and during a preload challenge using a wireless, wearable Doppler ultrasound system. Based on internal jugular and carotid artery Doppler surrogates of CVP and SV, respectively, we placed hemodynamic assessments into quadrants (Qx) prior to preload augmentation: low CVP with normal SV (Q1), high CVP and normal SV (Q2), low CVP and low SV (Q3) and high CVP and low SV (Q4). The proportion of preload responsive and unresponsive assessments in each quadrant was calculated based on the maximal change in ccFT (ccFTΔ) during either a passive leg raise or rapid fluid challenge. Results: We analyzed 41 patients (68 hemodynamic assessments) between February and April 2021. The prevalence of each phenotype was: 15 (22%) in Q1, 8 (12%) in Q2, 39 (57%) in Q3, and 6 (9%) in Q4. Preload unresponsiveness rates were: Q1, 20%; Q2, 50%; Q3, 33%, and Q4, 67%. Interpretation: Even fluid naïve ED patients with sonographic estimates of low CVP have high rates of fluid unresponsiveness, making dynamic testing valuable to prevent ineffective IVF administration.

Venous congestion in septic shock quantified with point-of-care ultrasound: a pilot prospective multicentre cohort study.

PURPOSE: Venous congestion is a pathophysiologic state that can result in organ dysfunction, particularly acute kidney injury (AKI). We sought to evaluate the feasibility of performing a definitive observational study to determine the impact of venous congestion quantified using point-of-care ultrasound (POCUS) in patients with septic shock. METHODS: We conducted a prospective observational feasibility study at two intensive care units (ICUs). We recruited adult patients with septic shock within 12 hr of ICU admission. Using the validated Venous Excess Ultrasound Score (VEXUS), we quantified venous congestion on day 1 and day 3 of ICU admission. The primary feasibility outcome was successful completion rate of the two VEXUS scores. We performed a survival analysis to quantify the hazard of renal replacement therapy (RRT). RESULTS: We enrolled 75 patients from January 2022 to January 2023. The success rate of completion for VEXUS scans was 94.5% (95% confidence interval [CI], 89.5 to 97.6). Severe venous congestion was present in 19% (14/75) of patients on ICU admission day 1 and in 16% (10/61) of patients on day 3. Venous congestion on ICU admission may be associated with a higher risk of requiring RRT (unadjusted hazard ratio, 3.35; 95% CI, 0.94 to 11.88; P = 0.06). CONCLUSIONS: It is feasible to conduct a definitive observational study exploring the association between venous congestion quantified with POCUS and clinical outcomes in patients with septic shock. We hypothesize that venous congestion may be associated with an increased hazard of receiving RRT.

RéSUMé: OBJECTIF: La congestion veineuse est un état physiopathologique qui peut entraîner un dysfonctionnement des organes, en particulier une insuffisance rénale aiguë (IRA). Nous avons cherché à évaluer la faisabilité de la réalisation d'une étude observationnelle définitive pour déterminer l'impact de la congestion veineuse quantifiée à l'aide de l'échographie ciblée (POCUS) chez des patient·es en choc septique. MéTHODE: Nous avons réalisé une étude de faisabilité observationnelle prospective dans deux unités de soins intensifs (USI). Nous avons recruté des patient·es adultes souffrant d'un choc septique dans les 12 heures suivant leur admission aux soins intensifs. À l'aide du score VEXUS (score d'échographie de l'excès veineux) validé, nous avons quantifié la congestion veineuse au jour 1 et au jour 3 de leur admission aux soins intensifs. Le principal critère de faisabilité était le taux de réussite des deux scores VEXUS. Nous avons réalisé une analyse de survie pour quantifier le risque de thérapie de substitution rénale (TSR). RéSULTATS: Nous avons recruté 75 patient·es de janvier 2022 à janvier 2023. Le taux de réussite des scores VEXUS était de 94,5 % (intervalle de confiance [IC] à 95 %, 89,5 à 97,6). Une congestion veineuse sévère était présente chez 19 % (14/75) des patient·es au jour 1 d'admission aux soins intensifs et chez 16 % (10/61) des patient·es au jour 3. La congestion veineuse lors de l'admission aux soins intensifs peut être associée à un risque plus élevé de nécessiter une TSR (rapport de risque non ajusté, 3,35; IC 95 %, 0,94 à 11,88; P = 0,06). CONCLUSION: Il est possible de mener une étude observationnelle définitive explorant l'association entre la congestion veineuse quantifiée par POCUS et les devenirs cliniques chez les patient·es en choc septique. Nous émettons l'hypothèse que la congestion veineuse peut être associée à un risque accru de recevoir une thérapie de substitution rénale.

Indications, Clinical Impact, and Complications of Critical Care Transesophageal Echocardiography: A Scoping Review.

BACKGROUND: Critical care transesophageal echocardiography (ccTEE) is an increasingly popular tool used by intensivists to characterize and manage hemodynamics at the bedside. Its usage appears to be driven by expanded diagnostic scope as well as the limitations of transthoracic echocardiography (TTE) - lack of acoustic windows, patient positioning, and competing clinical interests (eg, the need to perform chest compressions). The objectives of this scoping review were to determine the indications, clinical impact, and complications of ccTEE. METHODS: MEDLINE, EMBASE, Cochrane, and six major conferences were searched without a time or language restriction on March 31st, 2021. Studies were included if they assessed TEE performed for adult critically ill patients by intensivists, emergency physicians, or anesthesiologists. Intraoperative or post-cardiac surgical TEE studies were excluded. Study demographics, indication for TEE, main results, and complications were extracted in duplicate. RESULTS: Of the 4403 abstracts screened, 289 studies underwent full-text review, with 108 studies (6739 patients) included. Most studies were retrospective (66%), performed in academic centers (84%), in the intensive care unit (73%), and were observational (55%). The most common indications for ccTEE were hemodynamic instability, trauma, cardiac arrest, respiratory failure, and procedural guidance. Across multiple indications, ccTEE was reported to change the diagnosis in 52% to 78% of patients and change management in 32% to79% patients. During cardiac arrest, ccTEE identified the cause of arrest in 25% to 35% of cases. Complications of ccTEE included two cases of significant gastrointestinal bleeding requiring intervention, but no other major complications (death or esophageal perforation) reported. CONCLUSIONS: The use of ccTEE has been described for the diagnosis and management of a broad range of clinical problems. Overall, ccTEE was commonly reported to offer additional diagnostic yield beyond TTE with a low observed complication rate. Additional high quality ccTEE studies will permit stronger conclusions and a more precise understanding of the trends observed in this scoping review.

Association of Accuracy, Conclusions, and Reporting Completeness With Acceptance by Radiology Conferences and Journals.

BACKGROUND: Preferential publication of studies with positive findings can lead to overestimation of diagnostic test accuracy (i.e. publication bias). Understanding the contribution of the editorial process to publication bias could inform interventions to optimize the evidence guiding clinical decisions. PURPOSE/HYPOTHESIS: To evaluate whether accuracy estimates, abstract conclusion positivity, and completeness of abstract reporting are associated with acceptance to radiology conferences and journals. STUDY TYPE: Meta-research. POPULATION: Abstracts submitted to radiology conferences (European Society of Gastrointestinal and Abdominal Radiology (ESGAR) and International Society for Magnetic Resonance in Medicine (ISMRM)) from 2008 to 2018 and manuscripts submitted to radiology journals (Radiology, Journal of Magnetic Resonance Imaging [JMRI]) from 2017 to 2018. Primary clinical studies evaluating sensitivity and specificity of a diagnostic imaging test in humans with available editorial decisions were included. ASSESSMENT: Primary variables (Youden's index [YI > 0.8 vs. <0.8], abstract conclusion positivity [positive vs. neutral/negative], number of reported items on the Standards for Reporting of Diagnostic Accuracy Studies [STARD] for Abstract guideline) and confounding variables (prospective vs. retrospective/unreported, sample size, study duration, interobserver agreement assessment, subspecialty, modality) were extracted. STATISTICAL TESTS: Multivariable logistic regression to obtain adjusted odds ratio (OR) as a measure of the association between the primary variables and acceptance by radiology conferences and journals; 95% confidence intervals (CIs) and P-values were obtained; the threshold for statistical significance was P < 0.05. RESULTS: A total of 1000 conference abstracts (500 ESGAR and 500 ISMRM) and 1000 journal manuscripts (505 Radiology and 495 JMRI) were included. Conference abstract acceptance was not significantly associated with YI (adjusted OR = 0.97 for YI > 0.8; CI = 0.70-1.35), conclusion positivity (OR = 1.21 for positive conclusions; CI = 0.75-1.90) or STARD for Abstracts adherence (OR = 0.96 per unit increase in reported items; CI = 0.82-1.18). Manuscripts with positive abstract conclusions were less likely to be accepted by radiology journals (OR = 0.45; CI = 0.24-0.86), while YI (OR = 0.85; CI = 0.56-1.29) and STARD for Abstracts adherence (OR = 1.06; CI = 0.87-1.30) showed no significant association. Positive conclusions were present in 86.7% of submitted conference abstracts and 90.2% of journal manuscripts. DATA CONCLUSION: Diagnostic test accuracy studies with positive findings were not preferentially accepted by the evaluated radiology conferences or journals. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

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.

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.

Overinterpretation of Research Findings: Evaluation of "Spin" in Systematic Reviews of Diagnostic Accuracy Studies in High-Impact Factor Journals.

BACKGROUND: To compare the frequency of "spin" in systematic reviews of diagnostic accuracy studies in high-impact journals with the frequency a previously assessed series of reviews. METHODS: Medline was searched from January 2010 to January 2019. Systematic reviews of diagnostic accuracy studies were included if they reported a meta-analysis and were published in a journal with an impact factor >5. Two investigators independently scored each included systematic review for positivity of conclusions and for actual and potential overinterpretation practices. RESULTS: Of 137 included systematic reviews, actual overinterpretation was present in ≥1 form in the abstract in 63 (46%) and in the full-text report in 52 (38%); 108 (79%) contained a form of potential overinterpretation. Compared with the previously assessed series (reviews published 2015-2016), reviews in this series were less likely to contain ≥1 form of actual overinterpretation in the abstract and full-text report or ≥1 form of potential overinterpretation (P < 0.001 for all comparisons). The significance of these comparisons did not persist for actual overinterpretation in sensitivity analysis in which Cochrane systematic reviews were removed. Reviews published in the Cochrane Database of Systematic Reviews were less likely to contain actual overinterpretation in the abstract or the full-text report than reviews in other high-impact journals (P < 0.001 for both comparisons). CONCLUSIONS: Reviews of diagnostic accuracy studies in high-impact journals are less likely to contain overinterpretation or spin. This difference is largely due to the reviews published in the Cochrane Database of Systematic Reviews, which contain spin less often than reviews published in other high-impact journals.

Thoracic imaging tests for the diagnosis of COVID-19.

BACKGROUND: The diagnosis of infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) presents major challenges. Reverse transcriptase polymerase chain reaction (RT-PCR) testing is used to diagnose a current infection, but its utility as a reference standard is constrained by sampling errors, limited sensitivity (71% to 98%), and dependence on the timing of specimen collection. Chest imaging tests are being used in the diagnosis of COVID-19 disease, or when RT-PCR testing is unavailable. OBJECTIVES: To determine the diagnostic accuracy of chest imaging (computed tomography (CT), X-ray and ultrasound) in people with suspected or confirmed COVID-19. SEARCH METHODS: We searched the COVID-19 Living Evidence Database from the University of Bern, the Cochrane COVID-19 Study Register, and The Stephen B. Thacker CDC Library. In addition, we checked repositories of COVID-19 publications. We did not apply any language restrictions. We conducted searches for this review iteration up to 5 May 2020. SELECTION CRITERIA: We included studies of all designs that produce estimates of test accuracy or provide data from which estimates can be computed. We included two types of cross-sectional designs: a) where all patients suspected of the target condition enter the study through the same route and b) where it is not clear up front who has and who does not have the target condition, or where the patients with the target condition are recruited in a different way or from a different population from the patients without the target condition. When studies used a variety of reference standards, we included all of them. DATA COLLECTION AND ANALYSIS: We screened studies and extracted data independently, in duplicate. We also assessed the risk of bias and applicability concerns independently, in duplicate, using the QUADAS-2 checklist and presented the results of estimated sensitivity and specificity, using paired forest plots, and summarised in tables. We used a hierarchical meta-analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs). MAIN RESULTS: We included 84 studies, falling into two categories: studies with participants with confirmed diagnoses of COVID-19 at the time of recruitment (71 studies with 6331 participants) and studies with participants suspected of COVID-19 (13 studies with 1948 participants, including three case-control studies with 549 cases and controls). Chest CT was evaluated in 78 studies (8105 participants), chest X-ray in nine studies (682 COVID-19 cases), and chest ultrasound in two studies (32 COVID-19 cases). All evaluations of chest X-ray and ultrasound were conducted in studies with confirmed diagnoses only. Twenty-five per cent (21/84) of all studies were available only as preprints, 15/71 studies in the confirmed cases group and 6/13 of the studies in the suspected group. Among 71 studies that included confirmed cases, 41 studies had included symptomatic cases only, 25 studies had included cases regardless of their symptoms, five studies had included asymptomatic cases only, three of which included a combination of confirmed and suspected cases. Seventy studies were conducted in Asia, 2 in Europe, 2 in North America and one in South America. Fifty-one studies included inpatients while the remaining 24 studies were conducted in mixed or unclear settings. Risk of bias was high in most studies, mainly due to concerns about selection of participants and applicability. Among the 13 studies that included suspected cases, nine studies were conducted in Asia, and one in Europe. Seven studies included inpatients while the remaining three studies were conducted in mixed or unclear settings. In studies that included confirmed cases the pooled sensitivity of chest CT was 93.1% (95%CI: 90.2 - 95.0 (65 studies, 5759 cases); and for X-ray 82.1% (95%CI: 62.5 to 92.7 (9 studies, 682 cases). Heterogeneity judged by visual assessment of the ROC plots was considerable. Two studies evaluated the diagnostic accuracy of point-of-care ultrasound and both reported zero false negatives (with 10 and 22 participants having undergone ultrasound, respectively). These studies only reported True Positive and False Negative data, therefore it was not possible to pool and derive estimates of specificity. In studies that included suspected cases, the pooled sensitivity of CT was 86.2% (95%CI: 71.9 to 93.8 (13 studies, 2346 participants) and specificity was 18.1% (95%CI: 3.71 to 55.8). Heterogeneity judged by visual assessment of the forest plots was high. Chest CT may give approximately the same proportion of positive results for patients with and without a SARS-CoV-2 infection: the chances of getting a positive CT result are 86% (95% CI: 72 to 94) in patient with a SARS-CoV-2 infection and 82% (95% CI: 44 to 96) in patients without. AUTHORS' CONCLUSIONS: The uncertainty resulting from the poor study quality and the heterogeneity of included studies limit our ability to confidently draw conclusions based on our results. Our findings indicate that chest CT is sensitive but not specific for the diagnosis of COVID-19 in suspected patients, meaning that CT may not be capable of differentiating SARS-CoV-2 infection from other causes of respiratory illness. This low specificity could also be the result of the poor sensitivity of the reference standard (RT-PCR), as CT could potentially be more sensitive than RT-PCR in some cases. Because of limited data, accuracy estimates of chest X-ray and ultrasound of the lungs for the diagnosis of COVID-19 should be carefully interpreted. Future diagnostic accuracy studies should avoid cases-only studies and pre-define positive imaging findings. Planned updates of this review will aim to: increase precision around the accuracy estimates for CT (ideally with low risk of bias studies); obtain further data to inform accuracy of chest X rays and ultrasound; and continue to search for studies that fulfil secondary objectives to inform the utility of imaging along different diagnostic pathways.

Thoracic imaging tests for the diagnosis of COVID-19.

BACKGROUND: The respiratory illness caused by SARS-CoV-2 infection continues to present diagnostic challenges. Early research showed thoracic (chest) imaging to be sensitive but not specific in the diagnosis of coronavirus disease 2019 (COVID-19). However, this is a rapidly developing field and these findings need to be re-evaluated in the light of new research. This is the first update of this 'living systematic review'. This update focuses on people suspected of having COVID-19 and excludes studies with only confirmed COVID-19 participants. 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 22 June 2020. We did not apply any language restrictions. SELECTION CRITERIA: We included studies of all designs that recruited participants of any age group suspected to have COVID-19, and which reported estimates of test accuracy, or provided data from which estimates could be computed. When studies used a variety of reference standards, we retained the classification of participants as COVID-19 positive or negative as used in the study. DATA COLLECTION AND ANALYSIS: We screened studies, extracted data, and assessed the risk of bias and applicability concerns using the QUADAS-2 domain-list independently, in duplicate. We categorised included studies into three groups based on classification of index test results: studies that reported specific criteria for index test positivity (group 1); studies that did not report specific criteria, but had the test reader(s) explicitly classify the imaging test result as either COVID-19 positive or negative (group 2); and studies that reported an overview of index test findings, without explicitly classifying the imaging test as either COVID-19 positive or negative (group 3). We presented the results of estimated sensitivity and specificity using paired forest plots, and summarised in tables. We used a bivariate meta-analysis model where appropriate. We presented uncertainty of the accuracy estimates using 95% confidence intervals (CIs). MAIN RESULTS: We included 34 studies: 30 were cross-sectional studies with 8491 participants suspected of COVID-19, of which 4575 (54%) had a final diagnosis of COVID-19; four were case-control studies with 848 cases and controls in total, of which 464 (55%) had a final diagnosis of COVID-19. Chest CT was evaluated in 31 studies (8014 participants, 4224 (53%) cases), chest X-ray in three studies (1243 participants, 784 (63%) cases), and ultrasound of the lungs in one study (100 participants, 31 (31%) cases). Twenty-six per cent (9/34) of all studies were available only as preprints. Nineteen studies were conducted in Asia, 10 in Europe, four in North America and one in Australia. Sixteen studies included only adults, 15 studies included both adults and children and one included only children. Two studies did not report the ages of participants. Twenty-four studies included inpatients, four studies included outpatients, while the remaining six studies were conducted in unclear settings. The majority of included studies had a high or unclear risk of bias with respect to participant selection, index test, reference standard, and participant flow. For chest CT in suspected COVID-19 participants (31 studies, 8014 participants, 4224 (53%) cases) the sensitivity ranged from 57.4% to 100%, and specificity ranged from 0% to 96.0%. The pooled sensitivity of chest CT in suspected COVID-19 participants was 89.9% (95% CI 85.7 to 92.9) and the pooled specificity was 61.1% (95% CI 42.3 to 77.1). Sensitivity analyses showed that when the studies from China were excluded, the studies from other countries demonstrated higher specificity compared to the overall included studies. When studies that did not classify index tests as positive or negative for COVID-19 (group 3) were excluded, the remaining studies (groups 1 and 2) demonstrated higher specificity compared to the overall included studies. Sensitivity analyses limited to cross-sectional studies, or studies where at least two reverse transcriptase polymerase chain reaction (RT-PCR) tests were conducted if the first was negative, did not substantively alter the accuracy estimates. We did not identify publication status as a source of heterogeneity. For chest X-ray in suspected COVID-19 participants (3 studies, 1243 participants, 784 (63%) cases) the sensitivity ranged from 56.9% to 89.0% and specificity from 11.1% to 88.9%. The sensitivity and specificity of ultrasound of the lungs in suspected COVID-19 participants (1 study, 100 participants, 31 (31%) cases) were 96.8% and 62.3%, respectively. We could not perform a meta-analysis for chest X-ray or ultrasound due to the limited number of included studies. AUTHORS' CONCLUSIONS: Our findings indicate that chest CT is sensitive and moderately specific for the diagnosis of COVID-19 in suspected patients, meaning that CT may have limited capability in differentiating SARS-CoV-2 infection from other causes of respiratory illness. However, we are limited in our confidence in these results due to the poor study quality and the heterogeneity of included studies. Because of limited data, accuracy estimates of chest X-ray and ultrasound of the lungs for the diagnosis of suspected COVID-19 cases should be carefully interpreted. Future diagnostic accuracy studies should pre-define positive imaging findings, include direct comparisons of the various modalities of interest on the same participant population, and implement improved reporting practices. Planned updates of this review will aim to: increase precision around the accuracy estimates for chest CT (ideally with low risk of bias studies); obtain further data to inform accuracy of chest X-rays and ultrasound; and obtain data to further fulfil secondary objectives (e.g. 'threshold' effects, comparing accuracy estimates across different imaging modalities) to inform the utility of imaging along different diagnostic pathways.

Medico-legal risks of point-of-care ultrasound: a closed-case analysis of Canadian Medical Protective Association medico-legal cases.

BACKGROUND: Point-of-care ultrasound (POCUS) has become a core diagnostic tool for many physicians due to its portability, excellent safety profile, and diagnostic utility. Despite its growing use, the potential risks of POCUS use should be considered by providers. We analyzed the Canadian Medical Protective Association (CMPA) repository to identify medico-legal cases arising from the use of POCUS. METHODS: We retrospectively searched the CMPA closed-case repository for cases involving diagnostic POCUS between January 1st, 2012 and December 31st, 2021. Cases included civil-legal actions, medical regulatory authority (College) cases, and hospital complaints. Patient and physician demographics, outcomes, reason for complaint, and expert-identified contributing factors were analyzed. RESULTS: From 2012 to 2021, there were 58,626 closed medico-legal cases in the CMPA repository with POCUS determined to be a contributing factor for medico-legal action in 15 cases; in all cases the medico-legal outcome was decided against the physicians. The most common reasons for patient complaints were diagnostic error, deficient assessment, and failure to perform a test or intervention. Expert analysis of these cases determined the most common contributing factors for medico-legal action was failure to perform POCUS when indicated (7 cases, 47%); however, medico-legal action also resulted from diagnostic error, incorrect sonographic approach, deficient assessment, inadequate skill, inadequate documentation, or inadequate reporting. CONCLUSIONS: Although the most common reason associated with the medico-legal action in these cases is failure to perform POCUS when indicated, inappropriate use of POCUS may lead to medico-legal action. Due to limitations in granularity of data, the exact number of civil-legal, College cases, and hospital complaints for each contributing factor is unavailable. To enhance patient care and mitigate risk for providers, POCUS should be carefully integrated with other clinical information, performed by providers with adequate skill, and carefully documented.

Resuscitative transesophageal echocardiography during the acute resuscitation of trauma: A retrospective observational study.

BACKGROUND: Resuscitative transesophageal echocardiography (TEE) is an emerging POCUS modality that can be used to guide trauma resuscitation. METHODS: Trauma patients who underwent TEE within 24 h of admission from 2013 to 2022 were prospectively identified. We retrospectively analyzed resuscitative TEE reports and patient charts in duplicate. RESULTS: 29 providers performed TEE for 54 acute trauma patients. 28 (52%) died in hospital; 33 (61%) required operative intervention (<24 h). Median injury severity score was 29 [IQR 22-43]. The most common indications for TEE were hemodynamic instability (34, 63%), inadequate windows for transthoracic echocardiography (14, 26%) and cardiac arrest (11, 20%). There were no identified complications. A new diagnosis was made in 31 (57%) cases: most commonly right ventricular dysfunction (10, 19%), pericardial effusion (9, 17%), and hypovolemia (6, 11%). TEE ruled out major cardiac injury in 83% of cases. TEE changed resuscitative strategy, in 17 (32%) patients, diagnostic imaging approach in 6 (11%) patients, procedural or operative approach in 5 (9%) patients and disposition from the trauma bay in 4 (7%) patients. CONCLUSION: Resuscitative TEE during acute trauma care has an additional diagnostic yield to existing diagnostic pathways and may impact definitive management for some patients in the trauma bay.

Automated Real-Time Detection of Lung Sliding Using Artificial Intelligence: A Prospective Diagnostic Accuracy Study.

BACKGROUND: Rapid evaluation for pneumothorax is a common clinical priority. Although lung ultrasound (LUS) often is used to assess for pneumothorax, its diagnostic accuracy varies based on patient and provider factors. To enhance the performance of LUS for pulmonary pathologic features, artificial intelligence (AI)-assisted imaging has been adopted; however, the diagnostic accuracy of AI-assisted LUS (AI-LUS) deployed in real time to diagnose pneumothorax remains unknown. RESEARCH QUESTION: In patients with suspected pneumothorax, what is the real-time diagnostic accuracy of AI-LUS to recognize the absence of lung sliding? STUDY DESIGN AND METHODS: We performed a prospective AI-assisted diagnostic accuracy study of AI-LUS to recognize the absence of lung sliding in a convenience sample of patients with suspected pneumothorax. After calibrating the model parameters and imaging settings for bedside deployment, we prospectively evaluated its diagnostic accuracy for lung sliding compared with a reference standard of expert consensus. RESULTS: Two hundred forty-one lung sliding evaluations were derived from 62 patients. AI-LUS showed a sensitivity of 0.921 (95% CI, 0.792-0.973), specificity of 0.802 (95% CI, 0.735-0.856), area under the receiver operating characteristic curve of 0.885 (95% CI, 0.828-0.956), and accuracy of 0.824 (95% CI, 0.766-0.870) for the diagnosis of absent lung sliding. INTERPRETATION: In this study, real-time AI-LUS showed high sensitivity and moderate specificity to identify the absence of lung sliding. Further research to improve model performance and optimize the integration of AI-LUS into existing diagnostic pathways is warranted.

Improving the Generalizability and Performance of an Ultrasound Deep Learning Model Using Limited Multicenter Data for Lung Sliding Artifact Identification.

Deep learning (DL) models for medical image classification frequently struggle to generalize to data from outside institutions. Additional clinical data are also rarely collected to comprehensively assess and understand model performance amongst subgroups. Following the development of a single-center model to identify the lung sliding artifact on lung ultrasound (LUS), we pursued a validation strategy using external LUS data. As annotated LUS data are relatively scarce-compared to other medical imaging data-we adopted a novel technique to optimize the use of limited external data to improve model generalizability. Externally acquired LUS data from three tertiary care centers, totaling 641 clips from 238 patients, were used to assess the baseline generalizability of our lung sliding model. We then employed our novel Threshold-Aware Accumulative Fine-Tuning (TAAFT) method to fine-tune the baseline model and determine the minimum amount of data required to achieve predefined performance goals. A subgroup analysis was also performed and Grad-CAM++ explanations were examined. The final model was fine-tuned on one-third of the external dataset to achieve 0.917 sensitivity, 0.817 specificity, and 0.920 area under the receiver operator characteristic curve (AUC) on the external validation dataset, exceeding our predefined performance goals. Subgroup analyses identified LUS characteristics that most greatly challenged the model's performance. Grad-CAM++ saliency maps highlighted clinically relevant regions on M-mode images. We report a multicenter study that exploits limited available external data to improve the generalizability and performance of our lung sliding model while identifying poorly performing subgroups to inform future iterative improvements. This approach may contribute to efficiencies for DL researchers working with smaller quantities of external validation data.

A Wireless, Wearable Carotid Doppler Ultrasound Aids Diagnosis and Monitoring of Pericardial Tamponade: A Case Report.

Pericardial tamponade can often be diagnosed through clinical findings and echocardiography; however, the diagnosis can be aided by demonstrating the hemodynamic consequences of the effusion. We describe the use of a wearable carotid Doppler device to help diagnose and monitor pericardial tamponade. CASE SUMMARY: A 54-year-old man developed hypotension after an endobronchial biopsy for a lung mass. Echocardiography showed a pericardial effusion with sonographic evidence of tamponade. A wearable carotid Doppler device demonstrated low corrected carotid flow time (CFT) (a surrogate for stroke volume) with significant respiratory variation, supporting the diagnosis of tamponade. The patient underwent pericardiocentesis which revealed purulent pericardial fluid from a mediastinal abscess. After drainage there was increased CFT and reduced respiratory variability in Doppler, surrogates of improved stroke volume. CONCLUSION: A wearable carotid Doppler device is a noninvasive tool that can help determine the hemodynamic impact of a pericardial effusion, and potentially aid in the diagnosis of pericardial tamponade.

Unifying Fluid Responsiveness and Tolerance With Physiology: A Dynamic Interpretation of the Diamond-Forrester Classification.

Point of care ultrasound (POCUS) is a first-line tool to assess hemodynamically unstable patients, however, there is confusion surrounding intertwined concepts such as: "flow," "congestion," "fluid responsiveness (FR)," and "fluid tolerance." We argue that the Frank-Starling relationship is clarifying because it describes the interplay between "congestion" and "flow" on the x-axis and y-axis, respectively. Nevertheless, a single, simultaneous assessment of congestion and flow via POCUS remains a static approach. To expand this, we propose a two-step process. The first step is to place the patient on an ultrasonographic Diamond-Forrester plot. The second step is a dynamic assessment for FR (e.g., passive leg raise), which individualizes therapy across the arc of critical illness.

The effect of gravity-induced preload change on the venous excess ultrasound (VExUS) score and internal jugular vein Doppler in healthy volunteers.

BACKGROUND: The venous excess ultrasound (VExUS) score is a multi-organ Doppler approach to assess venous congestion. Despite growing use of VExUS in research and clinical practice, other veins can be visualized to assess for venous hypertension, which may overcome acquisition barriers of the VExUS exam. In this pilot, observational study, we used a wearable Doppler ultrasound to assess the relationship between jugular venous Doppler and the VExUS score under different preload conditions. We hypothesized that jugular Doppler morphology would accurately distinguish preload conditions, that it would most closely relate to the hepatic venous Doppler morphology in the fully supine position and that the VExUS score would be influenced by preload condition. RESULTS: We recruited 15 healthy volunteers with no cardiovascular history. Preload change was achieved using a tilt-table with three positions: supine, fully upright, and 30-degree head-down tilt. In each position, a VExUS score was performed; furthermore, inferior vena collapsibility and sphericity index were calculated. At the same time, jugular venous Doppler was captured by a novel, wireless, wearable ultrasound system. A continuous jugular venous Doppler morphology was 96% accurate for detecting the low preload condition. The jugular venous Doppler morphology was highly correlated with the hepatic vein, but only in the supine position. Gravitational position did not significantly affect the sphericity index or the VExUS score. CONCLUSIONS: The jugular vein Doppler morphology was able to accurately distinguish low from high preload conditions in healthy volunteers. Comparisons between VExUS Doppler morphologies and other veins should occur in the supine position when gravitational pressure gradients are minimized; finally, different preload conditions in healthy subjects did not affect the VExUS score.

Point-of-care Ultrasound to Assess Hemodynamic Contributors to Acute Kidney Injury in Pediatric Patients With Cerebral Malaria: A Pilot Study.

BACKGROUND: Acute kidney injury is common in severe malaria and is independently associated with mortality. The pathogenesis of acute kidney injury (AKI) in severe malaria remains incompletely understood. Ultrasound-based tools such as point-of-care ultrasound (POCUS), ultrasound cardiac output monitors (USCOMs) and renal arterial resistive index (RRI) can be used to detect hemodynamic and renal blood flow abnormalities contributing to AKI in malaria. METHODS: We conducted a prospective study of Malawian children with cerebral malaria to determine the feasibility of using POCUS and USCOM to characterize hemodynamic contributors to severe AKI (Kidney Disease: Improving Global Outcomes stage 2 or 3). The primary outcome was feasibility (completion rate of study procedures). We also assessed for differences in POCUS and hemodynamic variables for patients with or without severe AKI. RESULTS: We enrolled 27 patients who had admission cardiac and renal ultrasounds and USCOM. Completion rates were high for cardiac (96%), renal (100%) and USCOM studies (96%). Severe AKI occurred in 13 of 27 patients (48%). No patients had ventricular dysfunction. Only 1 patient in the severe AKI group was determined to be hypovolemic ( P = 0.64). No significant differences in USCOM, RRI or venous congestion parameters were detected among patients with and without severe AKI. Mortality was 11% (3/27) with the 3 deaths occurring in the severe AKI group ( P = 0.056). CONCLUSIONS: Ultrasound-based cardiac, hemodynamic and renal blood flow measurements appear to be feasible in pediatric patients with cerebral malaria. We were unable to detect hemodynamic or renal blood flow abnormalities contributing to severe AKI in cerebral malaria. Larger studies are needed to corroborate these findings.

Inferior Vena Caval Measures Do Not Correlate with Carotid Artery Corrected Flow Time Change Measured Using a Wireless Doppler Patch in Healthy Volunteers.

(1) Background: The inspiratory collapse of the inferior vena cava (IVC), a non-invasive surrogate for right atrial pressure, is often used to predict whether a patient will augment stroke volume (SV) in response to a preload challenge. There is a correlation between changing stroke volume (SV∆) and corrected flow time of the common carotid artery (ccFT∆). (2) Objective: We studied the relationship between IVC collapsibility and ccFT∆ in healthy volunteers during preload challenges. (3) Methods: A prospective, observational, pilot study in euvolemic, healthy volunteers with no cardiovascular history was undertaken in a local physiology lab. Using a tilt-table, we studied two degrees of preload augmentation from (a) supine to 30-degrees head-down and (b) fully-upright to 30-degrees head down. In the supine position, % of IVC collapse with respiration, sphericity index and portal vein pulsatility was calculated. The common carotid artery Doppler pulse was continuously captured using a wireless, wearable ultrasound system. (4) Results: Fourteen subjects were included. IVC % collapse with respiration ranged between 10% and 84% across all subjects. Preload responsiveness was defined as an increase in ccFT∆ of at least 7 milliseconds. A total of 79% (supine baseline) and 100% (head-up baseline) of subjects were preload-responsive. No supine venous measures (including IVC % collapse) were significantly related to ccFT∆. (5) Conclusions: From head-up baseline, 100% of healthy subjects were 'preload-responsive' as per the ccFT∆. Based on the 42% and 25% IVC collapse thresholds in the supine position, only 50% and 71% would have been labeled 'preload-responsive'.