Predicting Mortality in COVID-19 Patients with Hypertension using ECLA Score (ECG, Chest X-Ray and Laboratory Analysis)

Background: COVID-19 patients with hypertension are at higher risk for complications and have higher mortality rate. Rapid scoring can be important to determine the prognosis of COVID-19. Objective: We developed a scoring system to predict mortality to facilitate coordinated care planning. Methods: This study included 406 data confirmed COVID-19 with hypertension in East Java. Electrocardiography (ECG), laboratory analysis and chest x-ray (CXR) findings are examined to develop scoring system to predict mortality. Results: After multivariable adjustment and stepwise elimination, seven of 13 variables: cardiomegaly ( p = 0.036), sinus tachycardia ( p = 0.001), ST-segment abnormalities ( p = 0.036), right bundle branch block ( p = 0.008), left bundle branch block ( p = 0.046), left ventricle hypertrophy ( p = 0,023), and creatinine ( p = 0.000) were retained and compared. Each variable has a different risk score and is used to classify the patients into risk groups: low risk (0–2 points), moderate risk (3–6 points), and high risk ($ 7 points), determined by calculating the sum of the risk in the scoring system. ROC curve analysis of the ability of the scoring system to predict mortality showed an area under the curve (AUC) of 75,8% (confidence interval: 95%), a cutoff point of # 1,5 with a sensitivity of 76,3% and specificity of 62,1%. Conclusion: We concluded that the final model has the potential to predict mortality in hypertensive COVID-19 patients during hospital admission. The mortality rate is therefore expected to regress following risk group determination using our scoring model, which would yield a more comprehensive treatment plan.