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Published on: November 29, 2024
Modified Nutrition Risk in Critically Ill Score, A Prognostic Marker of Morbidity and Mortality in Mechanically
Marius Dsouza1, Vidya S Nagar2, Rahul Radhakrishnan3
1Assistant Professor;Corresponding Author.
Background:
Critically ill (CI) patients, especially those requiring mechanical ventilation (MV) are at a higher risk of malnutrition, which in turn is associated with increased hospitalization and excess mortality. The modified Nutrition Risk in Critically Ill (mNUTRIC) score, a predictor of mortality, has not been validated adequately in CI Indian patients. Thus, this study evaluated the mNUTRIC score as a prognostic marker of morbidity and mortality in CI patients requiring MV.
Materials And Methods:
This prospective observational study was performed, between January 2018 and June 2019, in the intensive critical care unit (ICCU) of the medicine department of a tertiary care hospital. A total of 250 patients aged above 12 years, admitted in ICCU, and requiring MV for >48 hours were included. Based on the data collected, mNUTRIC score was calculated and patients were classified as at low (0-4) and high (5-9) nutritional risk. Mortality was the outcome variable.
Results:
More than a quarter of patients had a high mNUTRIC score (28.4%) and the overall mortality was 35.6%. A significantly greater proportion of non-survivors had a high mNUTRIC score (p-value<0.0001). Likewise, the mean Acute Physiology and Chronic Health Evaluation II (APACHE II) score, Sequential Organ Failure Assessment (SOFA) score, and mNUTRIC score (all p-values<0.0001) were significantly higher among the non-survivors than the survivors. On receiver operator characteristic (ROC) curve analysis, a cutoff value of >2 predicted mortality [area under the curve (AUC): 0.83; 95% confidence interval: 0.778-0.874] with a sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of 80.9, 76.4, 65.5, and 87.9%, respectively.
Conclusion:
At a cutoff of >2, mNUTRIC score had high sensitivity and specificity in the prediction of mortality.
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