1997-P: Beyond HbA1c: Machine Learning–Derived Triglyceride–BMI–Duration Axis as a Superior Predictor of Multisystem Diabetes Complications

Introduction and Objective: Diabetes risk stratification relies predominantly on HbA1c despite evidences that metabolic dysregulation beyond glycemia drives complications. We developed and validated a comprehensive machine learning model integrating 47 clinical parameters to predict multi-system complications and identify novel risk axes. Methods: Analysis of 400 T2DM patients from community screening camps with comprehensive assessment across 47 parameters. Primary outcome: multi-system complications (≥2 of: bone disease, neuropathy, dyslipidemia, pulmonary risk, hepatic steatosis). Ensemble machine learning (Random Forest, XGBoost, Neural Networks) with SHAP analysis for feature importance and interaction detection. Results: Integrated ML model achieved AUROC 0.87 (95% CI 0.83-0.91) for multi-system complications, significantly outperforming HbA1c-only model (AUROC 0.58, p0.001). SHAP analysis revealed novel “TG-BMI-Duration Axis” as primary driver: triglycerides contributed 28% of model variance, BMI 24%, diabetes duration 18%, while HbA1c contributed only 9%. Feature interactions showed synergistic effects: TG200 mg/dL + BMI30 increased complication odds 8.4-fold (OR 8.42, CI 4.67-15.18) versus either alone (OR 2.1-2.8). Model-derived Diabetes Complexity Score (DCS) stratified patients into low (DCS30, 12% complications), moderate (DCS 30-60, 48% complications), and high-risk (DCS60, 82% complications) categories, enabling precision intervention. Early achievement of targets within 5 years reduced DCS by 45 points and complication probability from 68% to 18% (NNT=2). Conclusion: Comprehensive multi-parameter machine learning identifies TG-BMI-duration axis as primary driver. Model-derived Complexity Score enables precision risk stratification (82% high-risk complication rate versus 12% low-risk) and demonstrates that early intensive metabolic intervention targeting TG/BMI yields greater benefit than HbA1c reduction alone. Disclosure A. Maheshwari: None. S. Patil: None. S. Singla: None. A. Tewari: None. N. Verma: None.