<![CDATA[Corona Virus Disease (COVID-19) is becoming a global pandemic. Indonesia, especially South Kalimantan had recorded increasing cases with a high fatality rate of 3.7%. Information about factors related to outcomes based on clinical and laboratory features in Indonesia is still limited. Identification of the risk is crucial to determine optimal management and reducing mortality. This retrospective study enrolled 455 adults COVID-19 patients, and data were extracted from medical records of Ulin General Hospital Banjarmasin. The latter is COVID-19 referral hospital in South Kalimantan between March-November 2020. Demographic data, comorbidities, and laboratory were all collected. Data were compared between survivors and non-survivors. Fisher’s exact test and chi-square were used to compare categorical variables. The Mann_Whitney U test was used to compare continuous variables. Analysis was continued by multivariate logistic regression then receiver operating characteristic (ROC) curve to determine cut-off value. The multivariate analysis showed that number of comorbidities [odds ratio (OR) 1,339 (95% confidence interval (CI): 1,064-1,685, P = 0,013) was a significant risk factor to the outcome. In laboratory, lactate dehydrogenase (LDH) [OR: 1.001, 95% CI: 1,000-1.002, P = 0.001], Ferritin (OR 1.000, CI: 1,000-1.001, P = 0.013), APTT (OR: 1.045, CI: 1.010-1.082, P = 0.012), and D-dimer (OR: 1.188, CI: 1.064 - 1.327, P = 0.002) were significant predictor factors but only LDH, ferritin, and D- dimer were obtained good AUC 0.731, 0.715, and 0.705, respectively. The cut of the value of LDH was 656.5 U/L, ferritin was 672.18 ng/ml, and D-dimer was 2.28 mg/L. Sensitivity and specificity were 66.7% and 68,0% for LDH, 83,2% and 56,3% for ferritin, and 62,8 and 70,8% for D-dimer. From this research, we revealed that the number of comorbidities was a risk factor for death. Elevated LDH, ferritin, and D-dimer could be good predictive factors for poor outcomes, thereby considering the accelerating management of COVID-19 patients.]]>
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