Abstract
Objective: The lung is a target organ of diabetes mellitus (DM) via glycation of pulmonary elastin and collagen. In addition, hyperglycemia facilitates hypercapnic respiratory failure, which is instead mitigated by low‐carbohydrate high‐lipid (LC‐HL) nutrition. We sought to determine the association between diabetes and severe respiratory failure (SRF, i.e., need of reintubation\tracheostomy) after open aortic arch replacement (AAR).Methods: Machine learning algorithms were evaluated for precision and recall (F2 score) and for clinical applicability to predict SRF. Conditional regression evaluated independent predictors of SRF after 1:2 propensity‐score matching.Results: Information on diabetic status was available in 1275 patients undergoing AAR (1997–2023). Although support vector machine presented the highest F2 score (F2 = 0.337), conditional inference trees provided the most clinically applicable algorithm: diabetes was the best predictor of SRF, which occurred in 20/150 diabetics (13.3%) vs. 40/1125 nondiabetics (3.6%) (p < 0.01). In diabetics, left ventricular ejection fraction (LVEF) was the next best predictor of SRF, which occurred in 8/20 diabetics with LVEF ≤ 30% (40%) vs. 12/130 diabetics with LVEF >30% (9.2%) (p = 0.02). In nondiabetics, chronic obstructive pulmonary disease (COPD) was the next best predictor of respiratory failure, which occurred in 14/177 nondiabetics with COPD (7.9%) vs. 26/948 nondiabetics without COPD (2.7%) (p = 0.01). In the matched sample, diabetes was independently able to predict SRF (OR 2.20, 95% CI 1.10 | 4.42).Conclusions: DM was the best predictor of SRF after AAR. Strict glycemic control and LC‐HL nutrition should be evaluated as measures to reduce postoperative SRF in diabetic patients.
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