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.
Beijing Hospital of Traditional Chinese Medicine, Capital Medical University, Beijing, China.
Front Public Health. 2023 Feb 22;11:1128069. doi: 10.3389/fpubh.2023.1128069. eCollection 2023.
Early identification and intervention of diabetic peripheral neuropathy is beneficial to improve clinical outcome.
To establish a risk prediction model for diabetic peripheral neuropathy (DPN) in patients with type 2 diabetes mellitus (T2DM).
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.
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, = 0.020), high- (RR 15.5, 95% CI 7.6-31.6, < 0.001), and very high-risk groups (RR 45.0, 95% CI 20.5-98.8, < 0.001) compared with the low-risk group.
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.
早期识别和干预糖尿病周围神经病变有利于改善临床结局。
建立 2 型糖尿病（T2DM）患者糖尿病周围神经病变（DPN）的风险预测模型。
来自荟萃分析的推导队列。提取危险因素及其相应的风险比（RR）。仅纳入有统计学意义的危险因素，并根据其权重进行评分。外部队列用于验证该模型。结局为 DPN 的发生。
纳入了来自 18 个队列的 95604 例 T2DM 患者。年龄、吸烟、体重指数、糖尿病病程、糖化血红蛋白、低高密度脂蛋白胆固醇、高甘油三酯、高血压、糖尿病视网膜病变、糖尿病肾病和心血管疾病被纳入最终模型。最高得分为 52.0。验证队列的中位随访时间为 4.29 年。最佳截断点为 17.0，敏感性为 0.846，特异性为 0.668。根据总分，验证队列的患者分为低危、中危、高危和极高危组。中危组（RR 3.3，95%CI 1.5-7.2， = 0.020）、高危组（RR 15.5，95%CI 7.6-31.6， < 0.001）和极高危组（RR 45.0，95%CI 20.5-98.8， < 0.001）发生 DPN 的风险显著增加，与低危组相比。
建立了一个包含 11 个常见临床指标的 DPN 风险预测模型。这是一种简单可靠的工具，可用于 T2DM 患者 DPN 的早期预防和干预。
