Usefulness of Charlson comorbidity index-adjusted mortality prediction tools and factors influencing mortality in intensive care unit patients: a retrospective medical record review-based study.

PURPOSE: This study aimed to estimate the mortality rate in adult intensive care units (ICUs) using the Charlson comorbidity index (CCI)-adjusted Acute Physiology and Chronic Health Evaluation (APACHE) II and Simplified Acute Physiology Score (SAPS) III models, and to identify factors influencing mortality.

METHODS: This retrospective cohort study included adult patients admitted to the ICU at a tertiary hospital between June 1 and August 31, 2022. Among the 1,098 screened patients, those younger than 18 years, those discharged within 48 hours, and those with missing medical records were excluded. In total, 482 patients were analyzed using the chi-square test, independent t-test, and multivariate logistic regression. Model performance was evaluated using the c-statistic and the Hosmer-Lemeshow goodness-of-fit test.

RESULTS: The predictive accuracy of the mortality models was shown by c-statistic values of 0.817 for APACHE II, 0.857 for SAPS III, 0.697 for CCI, and 0.834 for CCI-adjusted APACHE II (0.834). Mechanical ventilation, cardiopulmonary cerebral resuscitation, continuous renal replacement therapy, and the presence of leukemia or lymphoma were significant predictors of mortality in adult ICU patients. Among the evaluated models, SAPS III and CCI-adjusted APACHE II demonstrated the highest predictive power.

CONCLUSION: The findings indicate that incorporating comorbidity indices such as the CCI with acute physiological parameters improves the accuracy of mortality prediction in ICU patients. Understanding mortality prediction models is essential for nurses to provide individualized, evidence-based, and high-quality care in adult ICUs.