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Quantifying the Homeostatic Model Assessment of Insulin Resistance to Predict Mortality in Multi-organ Dysfunction
Sonu Sama1, Gaurav Jain1, Ravi Kant2
1Department of Anaesthesia and Critical Care, All India Institute of Medical Sciences, Rishikesh, Uttarakhand, India.
Background:
Insulin resistance is an integral component of a multi-organ dysfunction syndrome (MODS) associated with increased mortality. We determined a cutoff value for the homeostatic model assessment of insulin resistance (HOMA-IR) during an ICU admission that could predict 28-day mortality of nondiabetic MODS patients.
Materials And Methods:
In this prospective, outcome assessor blinded cohort design, we evaluated 82 such patients for fasting blood glucose (FBG)/insulin levels (FIL) during an ICU admission and followed their outcome for 28 days. The primary outcome variable was the HOMA-IR score calculated from the above variables. The statistical tool included receiver operating characteristic curve, Youden index, and correlation and regression analysis.
Results:
Overall, 38 patients succumbed to their illness. The optimal cutoff value for HOMA-IR was ≥1.61 (area under curve: 0.684, sensitivity: 36.8%, specificity: 95.5%). The 28-day survival was significantly lower (p = 0.001) at HOMA-IR threshold ≥1.61 (odds ratio: 12.25, hazard ratio: 2.98). The mean HOMA-IR among survivors vs nonsurvivors was 0.76 ± 0.61 and 1.38 ± 1.14, respectively (p = 0.004). Except for FIL and FBG, HOMA-IR values did not correlate with any other baseline or outcome parameters (demographics, APACHE II/sequential organ failure assessment score, vasopressor needs, or ICU/hospital stay). On comparing these parameters across the HOMA-IR threshold, only FIL and the hospital stay varied significantly. Most of the outcome parameters, however, varied significantly among nonsurvivors vs survivors.
Conclusion:
The HOMA-IR is a significant predictor of mortality in MODS. Its cutoff value may assist in determining a reference range for critically ill patients. Its routine use in the light of other disease severity scores may serve in their better prognostication.
How To Cite This Article:
Sama S, Jain G, Kant R, Bhadoria AS, Naithani M, Kumar A. Quantifying the Homeostatic Model Assessment of Insulin Resistance to Predict Mortality in Multi-organ Dysfunction Syndrome. Indian J Crit Care Med 2021;25(12):1364-1369.
Insights
The homeostatic model assessment of insulin resistance (HOMA-IR) can predict mortality in non-diabetic patients with multi-organ dysfunction syndrome (MODS). A HOMA-IR cutoff of ≥1.61 indicates a higher risk of 28-day mortality.
Area of Science:
- Critical Care Medicine
- Endocrinology
- Metabolic Syndrome
Background:
- Insulin resistance is a key factor in multi-organ dysfunction syndrome (MODS), contributing to increased mortality.
- Predicting mortality in non-diabetic MODS patients is crucial for effective clinical management.
Purpose of the Study:
- To determine a specific cutoff value for the homeostatic model assessment of insulin resistance (HOMA-IR) during ICU admission.
- To evaluate HOMA-IR's predictive capability for 28-day mortality in non-diabetic MODS patients.
Main Methods:
- A prospective, blinded cohort study involving 82 non-diabetic MODS patients.
- Fasting blood glucose (FBG) and insulin levels (FIL) were measured to calculate HOMA-IR.
- Statistical analysis included ROC curves, Youden index, correlation, and regression to identify mortality predictors.
Main Results:
- An optimal HOMA-IR cutoff value of ≥1.61 predicted 28-day mortality with 95.5% specificity and 36.8% sensitivity (AUC: 0.684).
- Patients with HOMA-IR ≥1.61 had significantly lower 28-day survival (p=0.001), with an odds ratio of 12.25.
- Mean HOMA-IR was significantly higher in non-survivors (1.38 ± 1.14) compared to survivors (0.76 ± 0.61) (p=0.004).
Conclusions:
- HOMA-IR is a significant predictor of mortality in patients with MODS.
- The identified HOMA-IR cutoff value (≥1.61) can aid in risk stratification for critically ill patients.
- Integrating HOMA-IR with existing disease severity scores may enhance prognostication in MODS.
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