Development and validation of a risk nomogram model for predicting peripheral neuropathy in patients with type 2 diabetes mellitus

Front Endocrinol (Lausanne). 2024 Apr 29:15:1338167. doi: 10.3389/fendo.2024.1338167. eCollection 2024.

Abstract

Objective: Diabetic peripheral neuropathy frequently occurs and presents severely in individuals suffering from type 2 diabetes mellitus, representing a significant complication. The objective of this research was to develop a risk nomogram for DPN, ensuring its internal validity and evaluating its capacity to predict the condition.

Methods: In this retrospective analysis, Suqian First Hospital's cohort from January 2021 to June 2022 encompassed 397 individuals diagnosed with T2DM. A random number table method was utilized to allocate these patients into two groups for training and validation, following a 7:3 ratio. By applying univariate and multivariable logistic regression, predictive factors were refined to construct the nomogram. The model's prediction accuracy was assessed through metrics like the ROC area, HL test, and an analysis of the calibration curve. DCA further appraised the clinical applicability of the model. Emphasis was also placed on internal validation to confirm the model's dependability and consistency.

Results: Out of 36 evaluated clinicopathological characteristics, a set of four, duration, TBIL, TG, and DPVD, were identified as key variables for constructing the predictive nomogram. The model exhibited robust discriminatory power, evidenced by an AUC of 0.771 (95% CI: 0.714-0.828) in the training cohort and an AUC of 0.754 (95% CI: 0.663-0.845) in the validation group. The congruence of the model's predictions with actual findings was corroborated by the calibration curve. Furthermore, DCA affirmed the clinical value of the model in predicting DPN.

Conclusion: This research introduces an innovative risk nomogram designed for the prediction of diabetic peripheral neuropathy in individuals suffering from type 2 diabetes mellitus. It offers a valuable resource for healthcare professionals to pinpoint those at elevated risk of developing this complication. As a functional instrument, it stands as a viable option for the prognostication of DPN in clinical settings.

Keywords: diabetic peripheral neuropathy; model; nomogram; prediction; risk factor.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Diabetes Mellitus, Type 2* / complications
  • Diabetic Neuropathies* / diagnosis
  • Diabetic Neuropathies* / epidemiology
  • Diabetic Neuropathies* / etiology
  • Female
  • Humans
  • Male
  • Middle Aged
  • Nomograms*
  • Peripheral Nervous System Diseases / diagnosis
  • Peripheral Nervous System Diseases / epidemiology
  • Peripheral Nervous System Diseases / etiology
  • Prognosis
  • Retrospective Studies
  • Risk Assessment / methods
  • Risk Factors

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. Funding for this research was supported by the Suqian Sci&Tech Program, under Grant Number KY202213.