ArticleFrontiers in nutrition2026
A nomogram incorporating nutritional risk for predicting 31-day unplanned readmission in adults with type 2 diabetes mellitus using LASSO regression.
Article in Frontiers in nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Objective: To develop and validate a nomogram incorporating nutritional risk for predicting 31-day unplanned readmission in patients with type 2 diabetes mellitus (T2DM). Methods: This retrospective study included 1,627 T2DM patients. A nomogram was constructed using least absolute shrinkage and selection operator (LASSO) regression on a training set ( Results: The 31-day unplanned readmission rate was 18.50%. Six predictors were identified: smoking history, peripheral vascular disease in patients with type 2 diabetes mellitus (PVD in T2DM), diabetes duration, glycated hemoglobin (HbA1c), nutritional risk and neutrophil-to-lymphocyte ratio (NLR). The nomogram showed good discrimination in both training (AUC = 0.846; 95% CI: 0.814-0.878) and internal hold-out set (AUC = 0.817; 95% CI: 0.761-0.873), with acceptable calibration. Conclusion: In this single-center retrospective cohort, the nomogram demonstrated potential for predicting 31-day unplanned readmission in T2DM patients by integrating clinical, metabolic, inflammatory, and nutritional dimensions. Routine nutritional assessment at admission may help identify high-risk individuals; however, external validation in geographically and temporally diverse populations is necessary before clinical application.
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