Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis

Xixi Liu; Dong Chen; Hongmin Fu; Xinbang Liu; Qiumei Zhang; Jingyun Zhang; Min Ding; Juanjuan Wen; Bai Chang

doi:10.3389/fpubh.2023.1128069

Development and validation of a risk prediction model for early diabetic peripheral neuropathy based on a systematic review and meta-analysis

Front Public Health. 2023 Feb 22:11:1128069. doi: 10.3389/fpubh.2023.1128069. eCollection 2023.

Authors

Xixi Liu¹, Dong Chen², Hongmin Fu¹, Xinbang Liu¹, Qiumei Zhang¹, Jingyun Zhang¹, Min Ding¹, Juanjuan Wen¹, Bai Chang²

Affiliations

¹ NHC Key Laboratory of Hormones and Development, Tianjin Key Laboratory of Metabolic Diseases, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China.
² Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.

Abstract

Background: Early identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.

Objective: To establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).

Methods: The derivation cohort was from a meta-analysis. Risk factors and the corresponding risk ratio (RR) were extracted. Only risk factors with statistical significance were included in the model and were scored by their weightings. An external cohort were used to validate this model. The outcome was the occurrence of DPN.

Results: A total of 95,604 patients with T2DM from 18 cohorts were included. Age, smoking, body mass index, duration of diabetes, hemoglobin A1c, low HDL-c, high triglyceride, hypertension, diabetic retinopathy, diabetic kidney disease, and cardiovascular disease were enrolled in the final model. The highest score was 52.0. The median follow-up of validation cohort was 4.29 years. The optimal cut-off point was 17.0, with a sensitivity of 0.846 and a specificity of 0.668, respectively. According to the total scores, patients from the validation cohort were divided into low-, moderate-, high- and very high-risk groups. The risk of developing DPN was significantly increased in moderate- (RR 3.3, 95% CI 1.5-7.2, P = 0.020), high- (RR 15.5, 95% CI 7.6-31.6, P < 0.001), and very high-risk groups (RR 45.0, 95% CI 20.5-98.8, P < 0.001) compared with the low-risk group.

Conclusion: A risk prediction model for DPN including 11 common clinical indicators were established. It is a simple and reliable tool for early prevention and intervention of DPN in patients with T2DM.

Keywords: cohort study; diabetic peripheral neuropathy; meta-analysis; prediction model; risk factors; type 2 diabetes mellitus.

Publication types

Meta-Analysis
Systematic Review
Research Support, Non-U.S. Gov't

MeSH terms

Diabetes Mellitus, Type 2* / complications
Diabetic Neuropathies* / etiology
Diabetic Retinopathy*
Glycated Hemoglobin
Humans
Risk Factors

Substances

Glycated Hemoglobin

Grants and funding

This work was funded by the National Natural Science Foundation of China (81973614), Tianjin Key Medical Discipline (Specialty) Construction Project (grant number: TJYXZDXK-032A), the Science and Technology Development Fund of Tianjin Education Commission for Higher Education (2018KJ047), and the Scientific Research Funding of Tianjin Medical University Chu Hsien-I Memorial Hospital (grant number: 2019ZDKF03).