Factors Related to Length of Stay of Critical Patients in Intensive Care Unit: A Single-center Cross-sectional Study
DOI:
https://doi.org/10.47895/Keywords:
Abstract
Background. Intensive care units (ICUs) provide specialized care for critically ill patients, but prolonged length of stay (LOS) can strain limited ICU capacity, increase healthcare costs, and negatively affect patient outcomes. Predicting LOS at the time of ICU admission remains challenging because of the complex interplay of patients’ clinical conditions and therapeutic needs.
Objective. This study aimed to identify clinical and admission-related factors associated with ICU LOS and determine predictors of prolonged stay among ICU patients.
Methods. This study employed a cross-sectional design, with data collected from patient medical records in 2024. The Charlson Comorbidity Index (CCI), Glasgow Coma Scale (GCS), Blood pressure (BP), and LOS were used as the dependent outcome variables. Data processing was conducted with the Pearson correlation coefficient, t-test, and Hierarchical multiple regression.
Results. A total of 146 ICU patients participated as respondents, with an average age of 63.36 ± 14.56 years, CCI (4.27 ± 2.33), GCS 12 ± 4, and the average LOS was 5.25 ± 4.99 days. The results showed that variables presenting a relationship with LOS were age (r = 0.17, p = 0.05), CCI (r = -0.46, p = 0.01), GCS (r = -0.54, p = 0.01), and use of a mechanical ventilator (MV) (t = 5.44, p = 0.01). Five variables identified as LOS predictors included age (B = 0.03), CCI (B = -0.37), GCS (B = -0.12), systolic blood pressure (SBP) (B = 0.01), and not using MV (B = -0.91), which were expected to cover 74% of the variance in LOS (adjusted RÇ = 0.725, F = 48.67).
Conclusion. Endeavors to minimize LOS can serve as a crucial strategy in reducing nosocomial infections, the financial burden of treatment, morbidity and mortality, and enhancing the quality of life of patients in the ICU. In addition, age, CCI, GCS, SBP, and MV were significant predictors of ICU patients' LOS, with CCI being the strongest predictor.