Impact of Biochemical Parameters on Mortality in Critically Ill ICU Patients: The Role of Mechanical Ventilation,...

The mortality risk for critically ill patients in the intensive care unit (ICU) can be predicted through clinical assessments and laboratory test results. The accurate utilization of these parameters is essential for timely intervention and the initiation of appropriate therapeutic strategies. This study aims to retrospectively examine the relationship between patients' clinical status at ICU admission, prognostic risk scoring systems, biochemical and hematological parameters, and mortality outcomes.

This descriptive, cross-sectional, retrospective cohort study was conducted in the Internal Medicine Intensive Care Unit of Kütahya Health Sciences University Evliya Çelebi Training and Research Hospital, Turkey, between July 1, 2018, and July 30, 2020, and included a total of 490 patients. The initial admission data, encompassing variables such as gender, age, chronic conditions, reasons for ICU admission, ICU length of stay, total hospital stay, requirement for mechanical ventilation (MV), Nutrition Risk Screening 2002 (NRS-2002) score, hemogram, and biochemical parameters, were recorded. The clinical and demographic characteristics, along with the initial laboratory values of patients who either died or were discharged from the ICU, were subjected to statistical analysis.

Of the 490 patients, 258 were male, and 232 were female, with a median age of 72 (63-80). Of the 490 patients, 211 (43.1%) died, while 279 (46.6%) were discharged from the ICU. Logistic regression analysis showed that MV requirement, NRS-2002 score, lactate, and red cell distribution width (RDW-CV) were independent predictors of mortality (p < 0.05). MV requirement had the highest odds ratio.

In both multivariate analysis and clinical practice, the independent predictors of mortality in ICU patients were identified as the need for MV, elevated NRS-2002 scores, increased lactate levels, and higher RDW-CV values. Among these, the strongest predictor of mortality was the requirement for MV. We anticipate that the results of our study will aid in the enhancement of mortality prediction models and provide important parameters to inform clinical practice.