The impact of vaccination to clinical severity and mortality of COVID-19 patients

Abstract

Background: SARS-CoV-2 was discovered in December 2019 and later become global pandemic. Preliminary studies stated that broad vaccine coverage will suppress mortality and incidence of COVID-19. Therefore, we conduct a cross-sectional study to assess the efficacy of COVID-19 vaccination. Materials and Methods: We collected secondary data from electronic medical records of 343 COVID-19 positive patients confirmed via reverse transcription polymerase chain reaction from July 2021 to December 2021. We analyzed epidemiologic data, vaccination history, baseline symptoms, comorbidity, baseline vital signs, and outcome using hypothesis testing χ2 and logistic regression. Results: Sex had an χ2 of 9.34 (P < 0.001) while type of vaccine had an χ2 of 1.49 (P = 0.22) to clinical severity. Age, pulse rate, respiration rate, body temperature, and Glasgow coma scale were found to be significant risk factors to clinical severity. Number of vaccines previously received was found to be a protective factor to clinical severity (odds ratio (OR) = 0.49, 95% CI = 0.32–0.74, P < 0.001). We also found that sex (χ2 = 10.42, P < 0.001) was a predictor to discharge condition. Moreover, age was also found to be a significant predictor (OR = 1.03, 95% CI = 1.03–1.05, P < 0.001), as well as number of symptoms (OR = 0.66, P < 0.001), comorbidities (OR = 1.64, P < 0.001), pulse rate (OR = 1.04, P < 0.001), respiration rate (OR = 1.17, P < 0.001), and Glasgow coma scale (OR = 0.72, P = 0.03). Conclusion: Age, sex, number of vaccines received, number of symptoms, number of comorbidities, pulse rate, and respiration rate were significant predictors of clinical severity and outcome in COVID-19 patients. In addition, body temperature was also a predictor for clinical severity, while Glasgow coma scale was a predictor for outcome.

Keywords

• clinical severity
• covid-19
• mortality
• prediction model
• vaccination