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.

/pdf/thoracic-imaging-tests-for-the-diagnosis-of-covid-19-4io5u4fgmc.pdf

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 64.1 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. 

/pdf/thoracic-imaging-tests-for-the-diagnosis-of-covid-19-c20mrhn8.pdf

Thoracic imaging tests for the diagnosis of COVID-19

Reverse transcription-polymerase chain reaction (RT-PCR) is currently the gold standard in COVID-19 diagnosis. It can, however, take days to provide the diagnosis, and false negative rate is relatively high. Imaging, in particular chest computed tomography (CT), can assist with diagnosis and assessment of this disease. Nevertheless, it is shown that standard dose CT scan gives significant radiation burden to patients, especially those in need of multiple scans. In this study, we consider low-dose and ultra-low-dose (LDCT and ULDCT) scan protocols that reduce the radiation exposure close to that of a single X-Ray, while maintaining an acceptable resolution for diagnosis purposes. Since thoracic radiology expertise may not be widely available during the pandemic, we develop an Artificial Intelligence (AI)-based framework using a collected dataset of LDCT/ULDCT scans, to study the hypothesis that the AI model can provide human-level performance. The AI model uses a two stage capsule network architecture and can rapidly classify COVID-19, community acquired pneumonia (CAP), and normal cases, using LDCT/ULDCT scans. The AI model achieves COVID-19 sensitivity of 89.5% +\- 0.11, CAP sensitivity of 95% +\- 0.11, normal cases sensitivity (specificity) of 85.7% +\- 0.16, and accuracy of 90% +\- 0.06. By incorporating clinical data (demographic and symptoms), the performance further improves to COVID-19 sensitivity of 94.3% +\- pm 0.05, CAP sensitivity of 96.7% +\- 0.07, normal cases sensitivity (specificity) of 91% +\- 0.09 , and accuracy of 94.1% +\- 0.03. The proposed AI model achieves human-level diagnosis based on the LDCT/ULDCT scans with reduced radiation exposure. We believe that the proposed AI model has the potential to assist the radiologists to accurately and promptly diagnose COVID-19 infection and help control the transmission chain during the pandemic.

Human-level COVID-19 Diagnosis from Low-dose CT Scans Using a Two-stage Time-distributed Capsule Network.

According to the current state of knowledge, several internal organs are usually involved in cases of SARS-CoV‑2 infections with a fatal course. Pathological changes are primarily found in lung tissues but there are also reports concerning direct or indirect (histo)pathological changes due to SARS-CoV‑2 infections in samples from the kidneys, liver and myocardium. Comparing three fatal cases associated with SARS-CoV‑2 infections in men using conventional histological staining, there were partly identical findings that enabled interpretations with respect to the chronology and pathophysiology of the disease. Of the men two were invasively ventilated in the intensive care unit and one man died after 8 days in domestic quarantine without treatment. A wide spectrum of findings potentially associated with SARS-CoV‑2 must be taken into account.

/pdf/histopathological-findings-following-sars-cov-2-infection-4557baj4o9.pdf

[Histopathological findings following SARS-CoV-2 infection with and without treatment-Report of three autopsies].

Aim To evaluate mortality and risk factors for death in patients with COVID-19 who required admission to intensive care units (ICU) for respiratory support in Russia Material and methods In a retrospective study, we collected medical records of the consecutive ICU patients submitted by the local COVID-19 hospitals across Russia to the Federal Center at the Sechenov University (Moscow) betweenMarch 16 to May 3, 2020 All patients have completed their hospital stay (death or recovery) Diagnosis of SARS-CoV-2 pneumonia was established both by polymerase chain reaction (PCR) and CT In patients with inconclusive or negative results of PCR, the SARS-CoV-2 pneumonia was defined as severe acute respiratory infection with typical CT findings and no other obvious aetiology We used Cox proportional hazards regression model adjusted for age, sex and other risk factors to estimate hazard ratios (HR) and 95% confidence intervals (CI) Results We studied 1522 ICU patients with SARS-CoV-2 induced acute respiratory distress syndrome (ARDS), including 864 males and 658 females at the median age of 62 years Nine hundred twenty two records (60 1%) were submitted from Moscow and Moscow province, and 600 records (39 4%) were received from the hospitals located in 70 regions of Russia SARS-CoV-2 was verified by PCR in 995 (65 4%) patients Among 1522 patients enrolled in the study,995 patients (65 4%) died, and 527 (34 6%) patients recovered The most common causes of death were ARDS (93 2%), cardiovascular events (3 7%) and pulmonary embolism (1 0%) The mortality rate was low in patients with less severe pneumonia requiring oxygen therapy (10 1%) However, it increased significantly in patients who were placed on noninvasive or invasive ventilation (36 8% and 76 5%, respectively) Risk of death increased with age, and in males older than 50 years it was significantly higher than in females of similar age In a unvariate analysis, arterial hypertension, coronary artery disease (CAD), history of stroke, atrial fibrillation, type 2 diabetes, obesity and malignancies were associated with an increased risk of death However, only CAD (HR1 257, 95% CI 1 064-1 485, p=0 007), type 2 diabetes (HR1 300, 95% CI 1 131-1 494, p<0 0001) and obesity (HR1 347,95% CI 1 166-1 556, p<0 0001) retained statistical signicance in multiple factor analysis Conclusion In ICU patients with COVID-19, severity ofARDS (i e requirement in mechanical ventilation), age, malegender, CAD, obesity and type 2 diabetes were associatedwith a higher risk of death Цель Изучение летальности и факторов рискасмерти больных с COVID-19, госпитализированных для респираторной поддержки в отделения реанимации и интенсивной терапии(ОРИТ) лечебных учреждений Российской Федерации Материал и методы Ретроспективноеисследование было выполнено в Федеральномдистанционном консультативном центре анестезиологии и реаниматологии для взрослыхпациентов с COVID-19 на базе Первого МГМУим И М Сеченова В исследование включаливсех пациентов с известными исходами (смертьот любых причин или выздоровление) SARS-CoV-2 пневмонии, осложнившейся острым респираторным дистресс синдромом (ОРДС),которые были проконсультированы с 16 мартапо 3 мая 2020 г Факторы риска смерти анализировали с помощью многофакторной регрессионной модели Кокса Результаты В исследование были включены 1522 пациента, 864 (56,8%) мужчины и 658(43,2%) женщин Медиана возраста - 62 года 922 (60,6%) больных находились в ОРИТ стационаров Москвы и Московской области, 600(39,4%) - лечебных учреждений в 70 регионахРоссийской Федерации У 995 (65,4%) больных диагноз SARS-CoV-2 инфекции был подтвержден с помощью ПЦР Умерли 995 (65,4%)пациентов, выжили 527 (34,6%) Основнымипричинами смерти были ОРДС (93,2%), сердечно-сосудистые осложнения (3,7%) и тромбоэмболия легочной артерии (1,0%) Летальность была низкой у пациентов, находившихся на оксигенотерапии (10,1%), изначительно повышалась у больных, которыхприходилось переводить на неинвазивную(36,8%) или инвазивную (76,5%) вентиляциюлегких Риск смерти увеличивался с возрастоми в возрастных группах старше 50 лет у мужчинбыл достоверно выше, чем у женщин В однофакторных моделях заболеваниями, ассоциировавшимися с развитием летального исхода,были артериальная гипертония, ИБС, инсульт,фибрилляция предсердий, сахарный диабет 2типа, ожирение и солидные опухоли, однако вмногофакторной модели, построенной по всемпризнакам с коррекцией по полу и возрасту,статистическое значение сохранили толькоИБС (отношение рисков [ОР] 1,257, 95% доверительный интервал [ДИ] 1,064-1,485,p=0,007), сахарный диабет 2 типа (ОР 1,300,95% ДИ 1,131-1,494, p<0,0001) и ожирение(ОР 1,347, 95% ДИ 1,166-1,556, p<0,0001) Заключение Основными факторами рискасмерти больных с COVID-19, переведенных вОРИТ для респираторной поддержки, былитяжесть ОРДС, прежде всего необходимость вИВЛ, пожилой возраст, мужской пол, а такжеИБС, ожирение и сахарный диабет 2 типа

/pdf/clinical-outcomes-of-patients-with-covid-19-admitted-for-4t0hl8sh6p.pdf

Clinical outcomes of patients with COVID-19 admitted for respiratory support to the intensive care units in Russia

BACKGROUND: Only limited evidence has been available to date on the accuracy of systematic low-dose chest computed tomography (LDCT) use in the diagnosis of COVID-19 in patients with non-specific clinical symptoms. METHODS: The COVID-19 Imaging Registry Study Aachen (COVID-19-Bildgebungs-Register Aachen, COBRA) collects data on imaging in patients with COVID-19. Two of the COBRA partner hospitals (RWTH Aachen University Hospital and Dueren Hospital) systematically perform reverse transcriptase polymerase chain reaction (RT-PCR) from nasopharyngeal swabs as well as LDCT in all patients presenting with manifestations that are compatible with COVID-19. In accordance with the COV-RADS protocol, the LDCT scans were prospectively evaluated before the RT-PCR findings were available in order to categorize the likelihood of COVID-19. RESULTS: From 18 March to 5 May 2020, 191 patients with COVID-19 manifestations (117 male, age 65 ± 16 years) underwent RT-PCR testing and LDCT. The mean time from the submission of the sample to the availability of the RT-PCR findings was 491 minutes (interquartile range [IQR: 276-1066]), while that from the performance of the CT to the availability of its findings was 9 minutes (IQR: 6-11). A diagnosis of COVID-19 was made in 75/191 patients (39%). The LDCT was positive in 71 of these 75 patients and negative in 106 of the 116 patients without COVID-19, corresponding to 94.7% sensitivity (95% confidence interval [86.9; 98.5]), 91.4% specificity [84.7; 95.8], positive and negative predictive values of 87.7% [78.5; 93.9] and 96.4% [91.1; 98.6], respectively, and an AUC (area under the curve) of 0.959 [0.930; 0.988]. The initial RT-PCR test results were falsely negative in six patients, yielding a sensitivity of 92.0% [83.4; 97.0]; these six patients had positive LDCT findings. 47.4% of the LDCTs that were negative for COVID-19 (55/116) exhibited pathological pulmonary changes, including infiltrates, that were correctly distinguished from SARS-CoV-2 related changes. CONCLUSION: In patients with symptoms compatible with COVID-19, LDCT can esablish the diagnosis of COVID-19 with comparable sensitivity to RT-PCR testing. In addition, it offers a high specificity for distinguishing COVID-19 from other diseases associated with the same or similar clinical symptoms. We propose the systematic use of LDCT in addition to RT-PCR testing because it helps correct false-negative RT-PCR results, because its results are available much faster than those of RT-PCRtesting, and because it provides additional diagnostic information useful for treatment planning regardless of the type of the infectious agent.

Low-Dose Chest CT for the Diagnosis of COVID-19­A Systematic, Prospective Comparison With PCR

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Low-Dose Chest CT for the Diagnosis of COVID-19A Systematic, Prospective Comparison With PCR

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Low-Dose Chest CT for the Diagnosis of COVID-19­A Systematic, Prospective Comparison With PCR

Low-Dose Chest CT for the Diagnosis of COVID-19A Systematic, Prospective Comparison With PCR