Prediction of mortality and the development of critical illness in the course of COVID-19 with tertiary hospital data: vaccines? Critical illness scores? Mortality scores?

OBJECTIVE

Even though COVID-19 affects some risk groups more severely than others, there are still unknowns concerning the intensive care procedure and death in non-risk categories, making it vital to identify critical sickness and fatality risk factors at this time. The purpose of this study was to look into the efficacy of critical illness and mortality scores, as well as other risk factors in COVID-19.

PATIENTS AND METHODS

Two hundred twenty-eight inpatients diagnosed with COVID-19 were included in the study. Sociodemographic, clinical, and laboratory data were recorded and risk calculations were made with the help of web-based patient data-based calculation programs called COVID-GRAM Critical Illness and 4C-Mortality score.

RESULTS

The median age of 228 patients included in the study was 56.5 years, 51.3% of them were males, and ninety-six (42.1%) were unvaccinated. According to the multivariate analysis, the factors affecting the development of critical illness were cough [odds ratio=0.303, 95% CI (0.123,0.749), p=0.010], creatinine [odds ratio=1.542, 95% CI (1.100, 2.161), p=0.012], respiratory rate [odds ratio=1.484, 95% CI (1.302, 1.692), p=0.000], COVID-GRAM Critical Illness Score [odds ratio=3.005, 95% CI (1.288, 7.011), p=0.011]. Factors affecting survival were vaccine status [odds ratio=0.320, 95% CI (0.127,0.802), p=0.015], blood urea nitrogen (BUN) [odds ratio=1.032, 95% CI (1.012, 1.053), p=0.002], respiratory rate [odds ratio=1.173, 95% CI (1.070, 1.285), p=0.001], COVID-GRAM-critical-illness score [odds ratio=2.714, 95% CI (1.123, 6.556), p=0.027].

CONCLUSIONS

The findings suggested that risk assessment might employ risk scoring, such as COVID-GRAM Critical Illness, and that immunization against COVID-19 will reduce the occurrence of mortality.