MORTALITY PREDICTORS AND PROGNOSTICATION MODELS IN DIABETIC KETOACIDOSIS: A PROSPECTIVE COHORT STUDY

Abstract

Background: Diabetic ketoacidosis (DKA) remains a significant cause of morbidity and mortality worldwide, especially in developing countries. Understanding predictors of mortality and applying reliable prognostication models is essential for improving patient outcomes.

Objectives: To evaluate and compare the efficacy of the DKA Mortality Prediction Model (DKA-MPM) and APACHE II scoring systems in predicting mortality among DKA patients, and identify clinical and laboratory parameters significantly associated with mortality.

Methods: A prospective cohort study involving 100 DKA patients admitted from the Medical Triage Ward to the ICU. Parameters including age, sex, serum glucose, acid-base balance, mental status, fever, and insulin requirements were recorded. Mortality predictors were statistically analyzed using chi-square and Student T-tests.

Results: Mortality was 34%. Significant factors associated with mortality included advanced age, male sex, fever, depressed mental status, serum glucose >300 mg/dL, heart rate, respiratory rate, serum creatinine, pH, and GCS score (all p < 0.05). The APACHE II and DKA-MPM scores also significantly predicted mortality (p < 0.05). Comorbidities were not significantly correlated with mortality (p = 0.377).

Conclusion: Clinical parameters along with scoring systems like APACHE II and DKA-MPM can effectively predict DKA mortality. Early identification of high-risk patients may improve management strategies and outcomes