ABSTRACT
Background: The outbreak of coronavirus disease 2019 (COVID-19) dates back to December 2019 in China. Iran has been among the most prone countries to the virus. The aim of this study was to report demographics, clinical data, and their association with death and CFR. Methods: This observational cohort study was performed from 20th March 2020 to 18th March 2021 in three tertiary educational hospitals in Tehran, Iran. All patients were admitted based on the WHO, CDC, and Iran's National Guidelines. Their information was recorded in their medical files. Multivariable analysis was performed to assess demographics, clinical profile, outcomes of disease, and finding the predictors of death due to COVID-19. Results: Of all 5318 participants, the median age was 60.0 years, and 57.2% of patients were male. The most significant comorbidities were hypertension and diabetes mellitus. Cough, dyspnea, and fever were the most dominant symptoms. Results showed that ICU admission, elderly age, decreased consciousness, low BMI, HTN, IHD, CVA, dialysis, intubation, Alzheimer disease, blood injection, injection of platelets or FFP, and high number of comorbidities were associated with a higher risk of death related to COVID-19. The trend of CFR was increasing (WPC: 1.86) during weeks 25 to 51. Conclusions: Accurate detection of predictors of poor outcomes helps healthcare providers in stratifying patients, based on their risk factors and healthcare requirements to improve their survival chance.
Subject(s)
COVID-19 , Hypertension , Aged , COVID-19/epidemiology , Cohort Studies , Comorbidity , Female , Humans , Hypertension/epidemiology , Iran/epidemiology , Male , Middle Aged , Retrospective Studies , Risk Factors , SARS-CoV-2ABSTRACT
INTRODUCTION: Predicting the outcomes of COVID-19 cases using different clinical, laboratory, and imaging parameters is one of the most interesting fields of research in this regard. This study aimed to evaluate the correlation between chest computed tomography (CT) scan findings and outcomes of COVID-19 cases. METHODS: This cross sectional study was carried out on confirmed COVID-19 cases with clinical manifestations and chest CT scan findings based on Iran's National Guidelines for defining COVID-19. Baseline and chest CT scan characteristics of patients were investigated and their correlation with mortality was analyzed and reported using SPSS 21.0. RESULTS: 380 patients with the mean age of 53.62 ± 16.66 years were evaluated (66.1% male). The most frequent chest CT scan abnormalities were in peripheral (86.6%) and peribronchovascular interstitium (34.6%), with ground glass pattern (54.1%), and round (53.6%) or linear (46.7%) shape. There was a significant correlation between shape of abnormalities (p = 0.003), CT scan Severity Score (CTSS) (p <0.0001), and pulmonary artery CT diameter (p = 0. 01) with mortality. The mean CTSS of non-survived cases was significantly higher (13.68 ± 4.59 versus 8.72 ± 4.42; <0.0001). The area under the receiver operating characteristic (ROC) curve of CTSS in predicting the patients' mortality was 0.800 (95% CI: 0.716-0.884). The best cut off point of chest CTSS in this regard was 12 with 75.82% (95% CI: 56.07%-88.98%) sensitivity and 75.78% (95% CI: 70.88%-80.10%) specificity. The mean main pulmonary artery diameter in patients with CTSS ≥ 12 was higher than cases with CTSS < 12 (27.89 ± 3.73 vs 26.24 ± 3.14 mm; p < 0.0001). CONCLUSION: Based on the results of the present study it seems that there is a significant correlation between chest CT scan characteristics and mortality of COVID-19 cases. Patients with lower CTSS, lower pulmonary artery CT diameter, and round shape opacity had lower mortality.