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PurposeTo evaluate diagnostic performance of greyscale and inverted greyscale Chest X-ray (CXR) using Computed Tomography (CT) scan as a gold standard. MethodsIn this retrospective study, electronic medical records of 120 patients who had valid CXR and High-resolution CT (HRCT) within less than 24 hours after having a positive COVID-19 RT-PCR test during the period from May 19 th to May 23 rd 2020 in a single tertiary care center were reviewed. PA chest radiographs were presented on 2 occasions to 5 radiologists to evaluate the role and appropriateness of greyscale and inverted greyscale chest radiographs (CXR). The images were viewed on high-specification viewing systems using a primary display monitors and compared it to computed tomography (CT) findings for screening and management of suspected or confirmed COVID-19 patients. ResultsNinety-six (80%) patients had positive CT findings, 81 (67.5%) had positive grey scale CXR lesions, and 25 (20.8%) had better detection in the inverted grey scale CXR. The CXR sensitivity for COVID-19 pneumonia was 93.8% (95% CI (86.2% - 98.0%) and the specificity was 48.7% (95% CI (32.4% - 65.2%). The CXR sensitivity of detection of lung lesions was slightly higher in male (95.1% (95% CI (86.3% - 99.0%)) than female (90.0% (95% CI (68.3% - 98.8%)), while the specificity was 48.0% (95% CI (27.8% - 68.7%) and 50.0% (95% CI (23.0% - 77.0%) in males and females, respectively. However, no significant difference was detected in ROC area between men and women. ConclusionsThe sensitivity of detection of lung lesions of CXR was relatively high, particularly in men. The results of the study support the idea of considering conventional radiographs as an important diagnostic tool in suspected COVID-19 patients especially in healthcare facilities where there is no access to HRCT scans. HighlightsO_LICXR shows high sensitivity for detecting lung lesions in HRCT confirmed COVID-19 patients. C_LIO_LIBetter detection of lesions was noted in the inverted grey scale CXR in (20.8%) of cases with positive findings in standard greyscale CXR. C_LIO_LIConventional radiographs can be used as diagnostic tools in suspected COVID-19 patients especially in healthcare facilities where there is no access to HRCT scans. C_LI
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BackgroundThe COVID-19 RT-PCR confirmed cases could be symptomatic or asymptomatic. In the United Arab Emirates (UAE), the identified COVID-19 RT-PCR confirmed cases are yet to be characterized. In this study, we characterized the first cohort of COVID-19 RT-PCR confirmed cases reported in the Abu Dhabi Emirate, UAE, according to symptomatic state, and identified factors associated with the symptomatic state. Also, the strength of association between the symptomatic state and testing positive in three subsequent RT-PCR testing rounds was examined and quantified. MethodWe analyzed data collected from the first cohort of the RT-PCR confirmed COVID-19 cases reported to the health authorities in the Abu Dhabi Emirate - UAE between February 28 and April 08, 2020. Self-reported sociodemographic, working status, travel history, and chronic comorbidities of 1,249 COVID-19 cases were analyzed according to symptomatic state (symptomatic and asymptomatic). After the first RT-PCR confirmatory test, the results of three subsequent testing rounds were also analyzed. ResultsA total of 791 confirmed cases with a mean age of 35.6 years{+/-}12.7 (range: 1-81 years) and information on symptomatic state were analyzed. Nearly, 56.0% were asymptomatic cases. The most frequent two symptoms were fever (58.0%) and cough (41.0%). The mean age of symptomatic (36.3 year {+/-}12.6SD) was significantly higher than that of asymptomatic cases (34.5 year {+/-}12.7SD). Compared to non-working populations, working in public places (aOR, 1.76, 95% CI: 1.11-2.80), healthcare settings (aOR, 2.09, 95% CI: 1.01-4.31), or in aviation and tourism sector (aOR, 2.24, 95% CI: 1.14-4.40), were independently associated with symptomatic state. Reporting at least one chronic comorbidity was also associated with symptomatic cases (aOR, 1.76, 5% CI: 1.03-3.01). Compared to asymptomatic, symptomatic COVID-19 cases had consistent odds of two or more of testing positive to COVID-19 in three subsequent testing rounds. ConclusionsA substantial proportion of the diagnosed COVID-19 cases in the Abu Dhabi Emirate was asymptomatic. Quarantine of asymptomatic cases along with prevention measures and raising awareness of populations working in high-risk settings is warranted. Further follow up research is needed to understand viral clearance and clinical outcomes according to the symptomatic state of the COVID-19 cases.
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BackgroundA plethora of studies on COVID-19 investigating mortality and recovery have used the Cox Proportional Hazards (Cox PH) model without taking into account the presence of competing risks. We investigate, through extensive simulations, the bias in estimating the hazard ratio (HR) and the absolute risk reduction (ARR) of death when competing risks are ignored, and suggest an alternative method. MethodsWe simulated a fictive clinical trial on COVID-19 mimicking studies investigating interventions such as Hydroxychloroquine, Remdesivir, or convalescent plasma. The outcome is time from randomization until death. Six scenarios for the effect of treatment on death and recovery were considered. The HR and the 28-day ARR of death were estimated using the Cox PH and the Fine and Gray (FG) models. Estimates were then compared with the true values, and the magnitude of misestimation was quantified. ResultsThe Cox PH model misestimated the true HR and the 28-day ARR of death in the majority of scenarios. The magnitude of misestimation increased when recovery was faster and/or chance of recovery was higher. In some scenarios, this model has shown harmful treatment effect when it was beneficial. Estimates obtained from FG model were all consistent and showed no misestimation or changes in direction. ConclusionThere is a substantial risk of misleading results in COVID-19 research if recovery and death due to COVID-19 are not considered as competing risk events. We strongly recommend the use of a competing risk approach to re-analyze relevant published data that have used the Cox PH model.