Prognostic Value and Reproducibility of AI-assisted Analysis of Lung Involvement in COVID-19 on Low-Dose Submillisievert Chest CT: Sample Size Implications for Clinical Trials.

PURPOSE: To compare the prognostic value and reproducibility of visual versus AI-assisted analysis of lung involvement on submillisievert low-dose chest CT in COVID-19 patients. MATERIALS AND METHODS: This was a HIPAA-compliant, institutional review board-approved retrospective study. From March 15 to June 1, 2020, 250 RT-PCR confirmed COVID-19 patients were studied with low-dose chest CT at admission. Visual and AI-assisted analysis of lung involvement was performed by using a semi-quantitative CT score and a quantitative percentage of lung involvement. Adverse outcome was defined as intensive care unit (ICU) admission or death. Cox regression analysis, Kaplan-Meier curves, and cross-validated receiver operating characteristic curve with area under the curve (AUROC) analysis was performed to compare model performance. Intraclass correlation coefficients (ICCs) and Bland- Altman analysis was used to assess intra- and interreader reproducibility. RESULTS: Adverse outcome occurred in 39 patients (11 deaths, 28 ICU admissions). AUC values from AI-assisted analysis were significantly higher than those from visual analysis for both semi-quantitative CT scores and percentages of lung involvement (all P<0.001). Intrareader and interreader agreement rates were significantly higher for AI-assisted analysis than visual analysis (all ICC ≥0.960 versus ≥0.885). AI-assisted variability for quantitative percentage of lung involvement was 17.2% (coefficient of variation) versus 34.7% for visual analysis. The sample size to detect a 5% change in lung involvement with 90% power and an α error of 0.05 was 250 patients with AI-assisted analysis and 1014 patients with visual analysis. CONCLUSION: AI-assisted analysis of lung involvement on submillisievert low-dose chest CT outperformed conventional visual analysis in predicting outcome in COVID-19 patients while reducing CT variability. Lung involvement on chest CT could be used as a reliable metric in future clinical trials.

Accuracy and Reproducibility of Low-Dose Submillisievert Chest CT for the Diagnosis of COVID-19.

PURPOSE: To demonstrate the accuracy and reproducibility of low-dose submillisievert chest CT for the diagnosis of coronavirus disease 2019 (COVID-19) infection in patients in the emergency department. MATERIALS AND METHODS: This was a Health Insurance Portability and Accountability Act-compliant, institutional review board-approved retrospective study. From March 14 to 24, 2020, 192 patients in the emergency department with symptoms suggestive of COVID-19 infection were studied by using low-dose chest CT and real-time reverse transcription polymerase chain reaction (RT-PCR). Image analysis included the likelihood of COVID-19 infection and the semiquantitative extent of lung involvement. CT images were analyzed by two radiologists blinded to the RT-PCR results. Reproducibility was assessed using the McNemar test and intraclass correlation coefficient. Time between CT acquisition and report was measured. RESULTS: When compared with RT-PCR, low-dose submillisievert chest CT demonstrated excellent sensitivity, specificity, positive predictive value, negative predictive value, and accuracy for diagnosis of COVID-19 (86.7%, 93.6%, 91.1%, 90.3%, and 90.2%, respectively), in particular in patients with clinical symptoms for more than 48 hours (95.6%, 93.2%, 91.5%, 96.5%, and 94.4%, respectively). In patients with a positive CT result, the likelihood of disease increased from 43.2% (pretest probability) to 91.1% or 91.4% (posttest probability), while in patients with a negative CT result, the likelihood of disease decreased to 9.6% or 3.7% for all patients or those with clinical symptoms for >48 hours. The prevalence of alternative diagnoses based on chest CT in patients without COVID-19 infection was 17.6%. The mean effective radiation dose was 0.56 mSv ± 0.25 (standard deviation). Median time between CT acquisition and report was 25 minutes (interquartile range: 13-49 minutes). Intra- and interreader reproducibility of CT was excellent (all intraclass correlation coefficients ≥ 0.95) without significant bias in the Bland-Altman analysis. CONCLUSION: Low-dose submillisievert chest CT allows for rapid, accurate, and reproducible assessment of COVID-19 infection in patients in the emergency department, in particular in patients with symptoms lasting longer than 48 hours. Chest CT has the additional advantage of offering alternative diagnoses in a significant subset of patients.© RSNA, 2020.

Feasibility of using point-of-care lung ultrasound for early triage of COVID-19 patients in the emergency room.

PURPOSE: Diagnostic value of point-of-care lung ultrasound (POCUS) in detection of coronavirus disease (COVID-19) in an emergency setting is currently unclear. In this study, we aimed to compare diagnostic performance, in terms of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and accuracy, of POCUS lung, chest CT, and RT-PCR for clinically suspected COVID-19 infections in patients submitting to the emergency room (ER). MATERIAL AND METHODS: This retrospective study enrolled 93 patients with a suspected COVID-19 infection, admitted to the ER between March 28th and April 20th, 2020. Test subjects showed one or more symptoms of an acute respiratory infection, for which consequent COVID-19 testing was achieved using POCUS lung, chest CT, and RT-PCR. CT images were analyzed by 2 radiologists blinded to RT-PCR results. POCUS lung was performed by three emergency medical doctors, and reports were analyzed by the researcher, blinded to clinical information, US imaging, CT, and RT-PCR test results. RESULTS: Compared with RT-PCR, POCUS lung demonstrated outstanding sensitivity and NPV (93.3% and 94.1% respectively) while showing poor values for specificity, PPV, and accuracy (21.3%, 19.2%, and 33.3% respectively). In contrast, similar inquiries using chest CT as index test, excellent sensitivity, specificity, NPV, and accuracy (80.0%, 86.7%, 95.6%, and 85.6%, respectively) were reported, beside a moderate value for PPV (54.5%). CONCLUSION: POCUS may provide early ER triage with a useful, rapid, low-threshold, and safe screening tool in evaluating possible COVID-19 infections. Due to limited specificity, suggestive POCUS lung findings should be confirmed with RT-PCR or chest CT.

Frailty and Mortality in Hospitalized Older Adults With COVID-19: Retrospective Observational Study.

OBJECTIVES: To determine the association between frailty and short-term mortality in older adults hospitalized for coronavirus disease 2019 (COVID-19). DESIGN: Retrospective single-center observational study. SETTING AND PARTICIPANTS: Eighty-one patients with COVID-19 confirmed by reverse-transcriptase polymerase chain reaction (RT-PCR), at the Geriatrics department of a general hospital in Belgium. MEASUREMENTS: Frailty was graded according to the Rockwood Clinical Frailty Scale (CFS). Demographic, biochemical, and radiologic variables, comorbidities, symptoms, and treatment were extracted from electronic medical records. RESULTS: Participants (N = 48 women, 59%) had a median age of 85 years (range 65-97 years) and a median CFS score of 7 (range 2-9); 42 (52%) were long-term care residents. Within 6 weeks, 18 patients died. Mortality was significantly but weakly associated with age (Spearman r = 0.241, P = .03) and CFS score (r = 0.282, P = .011), baseline lactate dehydrogenase (LDH; r = 0.301, P = .009), lymphocyte count (r = -0.262, P = .02), and RT-PCR cycle threshold (Ct, r = -0.285, P = .015). Mortality was not associated with long-term care residence, dementia, delirium, or polypharmacy. In multivariable logistic regression analyses, CFS, LDH, and RT-PCR Ct (but not age) remained independently associated with mortality. Both age and frailty had poor specificity to predict survival. A multivariable model combining age, CFS, LDH, and viral load significantly predicted survival. CONCLUSIONS AND IMPLICATIONS: Although their prognosis is worse, even the oldest and most severely frail patients may benefit from hospitalization for COVID-19, if sufficient resources are available.