Prognostic nutritional index and diabetic peripheral neuropathy in type 2 diabetes: a machine learning approach.
Background: The prognostic nutritional index (PNI), an indicator of nutritional status, has been linked to various diabetic complications. However, its relationship with diabetic peripheral neuropathy (DPN) remains unclear. This study aimed to explore the association between PNI and DPN using machin...
| Publicado en: | Nutrition & Metabolism Vol. 22; no. 1; pp. 1 - 11 |
|---|---|
| Autores principales: | , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
BioMed Central
3/25/2025
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=184008207&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 184008207 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 17437075 1CYX jtl: Nutrition & Metabolism issn: 17437075 maglogo: N pubinfo: dt: 3/25/2025 vid: 22 iid: 1 pid: 24147 pub: BioMed Central artinfo: ui: 184008207 184008207 184008207 10.1186/s12986-025-00917-0 184008207 ppf: 1 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Prognostic nutritional index and diabetic peripheral neuropathy in type 2 diabetes: a machine learning approach. aug: au: Wu, Ya Dong, Danmeng Liu, Yang Xie, Xiaoyun affil: https://ror.org/03rc6as71 Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, Tongji University School of Medicine, 200072, Shanghai, China sug: subj: Diabetes Mellitus, Type 2 Complications Diabetic Neuropathies Prognosis Diabetic Neuropathies Prevention and Control Diabetic Neuropathies Risk Factors Nutritional Status Nutritional Assessment Machine Learning Risk Assessment Human Male Female Middle Age Aged Albumins Blood Lymphocyte Count Random Forest Models, Theoretical Multivariate Analysis Multiple Logistic Regression Odds Ratio Confidence Intervals Neural Conduction T-Tests Chi Square Test Spearman's Rank Correlation Coefficient Kruskal-Wallis Test Statistical Significance Data Analysis Software Descriptive Statistics Funding Source Middle Aged: 45-64 years Aged: 65+ years Male Female ab: Background: The prognostic nutritional index (PNI), an indicator of nutritional status, has been linked to various diabetic complications. However, its relationship with diabetic peripheral neuropathy (DPN) remains unclear. This study aimed to explore the association between PNI and DPN using machine learning (ML) approaches. Methods: A total of 625 patients with type 2 diabetes (T2D) were enrolled, with 282 diagnosed with DPN. PNI was calculated based on serum albumin and lymphocyte count. Random forest (RF) and eXtreme Gradient Boosting (XGBoost) models were developed to predict DPN using clinical and biochemical data. SHapley Additive exPlanations (SHAP) were applied to determine feature importance. Multivariate logistic regression was used to evaluate the relationship between PNI quartile and DPN risks. Results: Both RF and XGBoost models exhibited strong performance. The RF model achieved a recall of 78.4%, specificity of 87.8%, and accuracy of 84.0%, while the XGBoost model showed a recall of 77.4%, specificity of 92.1%, and accuracy of 84.8%. SHAP analysis identified lower PNI as a key factor for DPN. Multivariate logistic regression revealed that patients in the lowest PNI quartile had a significantly higher DPN risk compared to those in the highest quartile (OR: 3.271, 95% CI: 1.782–6.006, P < 0.001). Additionally, lower PNI levels were associated with impaired peripheral nerve function, including reduced motor and sensory nerve conduction velocity and action potential amplitudes. Conclusions: Lower PNI levels were associated with increased DPN risk and poorer nerve function, highlighting the importance of nutritional status in DPN management. Further longitudinal studies are needed to confirm these findings. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|