Study population This is a prospective multi-center study that included patients aged more than 21 years old with different clinical presentations other than pulmonary manifestation presenting to different healthcare facilities from June to December 2020. HRCT scan of the chest in order to detect COVID-19 patients was offered after signing an informed consent. Demographic data, clinical presentations, laboratory data, oxygen saturation, radiological findings in HRCT scan of the chest, severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) polymerase chain reaction (PCR) results and the need for mechanical ventilation were reported. Effects of different baseline characteristics, findings in HRCT scan of the chest on patient outcomes were analyzed.~Data collection:~Clinical presentations including history of potential source of infection, contact with COVID-19 patients, clinical examination findings were registered. HRCT scan of the chest for all patients and scoring system for severity of lung affection was performed. Patients with positive HRCT chest findings were investigated with PCR result for COVID-19. Complete blood picture with differential and serum ferritin level levels were examined. Baseline oxygen saturation on room air (RA), follow up of oxygen status, need for oxygen, non-invasive ventilation (NIV), mechanical ventilation (MV) and need for ICU admission were reported.~Outcomes:~The primary outcome was intensive care unit admission, use of non-invasive ventilation or mechanical ventilation. The secondary outcome was mortality.~Sample size:~Using Epi Info program for sample size calculation and assuming prevalence of asymptomatic COVID-19 patients was ranging from 10% (p=0.1) with margin of error 5% precision 5% (precision d=0.05), at 95% confidence level, Z statistic for a 95% level of confidence (Z=1.96) and used equation (n= {Z2×P× (1-P)}/d2), sample size of at least 139 patients were needed. All patients fulfilling the inclusion criteria were included in the study till completion of the sample size.~Statistical analysis:~Data were collected and analyzed using Statistical Package for Social Science (SPSS) program for statistical analysis, (version 23; Inc., Chicago. IL). Quantitative data were presented as mean, standard deviation (SD), and range. Qualitative data were presented as frequency and percent. Chi- square test was used to measure association between qualitative variables. Fisher exact test was used for 2x2 qualitative variables when more than 25% of the cells have expected count less than 5. Mann Whitney test was used to compare mean and SD of 2 sets of quantitative data when these data were not normally distributed. Logistic regression model was used to give adjusted odds ratio and 95% confidence interval of the effect of the different risk factors for subjects in the study. The Receiver Operating Characteristic (ROC) curve was done to detect the cutoff value with highest sensitivity and specificity. Sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy were calculated. P-value considered statistically significant when it was less than 0.05.~Ethical consideration:~The project ethical approval was obtained from Faculty of Medicine, Al-Menoufia University ethics committee. Confidentiality of data was ensured throughout the study. Informed consent was obtained from all participants following the provision of an explanation of the study rationale and procedures.
Coronavirus disease 2019 (COVID-19) can present with pulmonary and non-pulmonary manifestations or it may be asymptomatic. Asymptomatic patients have a major impact on transmission of the disease and prediction of their outcome and prognosis is challenging. We aim to identify the predictors of intensive care unit (ICU) admission and mortality in hospitalized COVID-19 patients with initially asymptomatic presentation.This was a prospective multi-center study using cohort data included all admitted patients aged 21 years and above, with different clinical presentations other (than pulmonary manifestation) and discovered to have COVID-19. Demographic data, clinical data and progression were reported. Univariate analysis and logistic regression analysis were performed to predict ICU admission and mortality during hospitalization.