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角膜共焦显微镜预测糖尿病神经病变的发展:一项纵向诊断多国联盟研究。

Corneal Confocal Microscopy Predicts the Development of Diabetic Neuropathy: A Longitudinal Diagnostic Multinational Consortium Study.

机构信息

Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada

Division of Endocrinology and Metabolism, Department of Medicine, University of Toronto, Toronto, Ontario, Canada.

出版信息

Diabetes Care. 2021 Sep;44(9):2107-2114. doi: 10.2337/dc21-0476. Epub 2021 Jul 1.

Abstract

OBJECTIVE

Corneal nerve fiber length (CNFL) has been shown in research studies to identify diabetic peripheral neuropathy (DPN). In this longitudinal diagnostic study, we assessed the ability of CNFL to predict the development of DPN.

RESEARCH DESIGN AND METHODS

From a multinational cohort of 998 participants with type 1 and type 2 diabetes, we studied the subset of 261 participants who were free of DPN at baseline and completed at least 4 years of follow-up for incident DPN. The predictive validity of CNFL for the development of DPN was determined using time-dependent receiver operating characteristic (ROC) curves.

RESULTS

A total of 203 participants had type 1 and 58 had type 2 diabetes. Mean follow-up time was 5.8 years (interquartile range 4.2-7.0). New-onset DPN occurred in 60 participants (23%; 4.29 events per 100 person-years). Participants who developed DPN were older and had a higher prevalence of type 2 diabetes, higher BMI, and longer duration of diabetes. The baseline electrophysiology and corneal confocal microscopy parameters were in the normal range but were all significantly lower in participants who developed DPN. The time-dependent area under the ROC curve for CNFL ranged between 0.61 and 0.69 for years 1-5 and was 0.80 at year 6. The optimal diagnostic threshold for a baseline CNFL of 14.1 mm/mm was associated with 67% sensitivity, 71% specificity, and a hazard ratio of 2.95 (95% CI 1.70-5.11; < 0.001) for new-onset DPN.

CONCLUSIONS

CNFL showed good predictive validity for identifying patients at higher risk of developing DPN ∼6 years in the future.

摘要

目的

研究表明,角膜神经纤维长度(CNFL)可用于识别糖尿病周围神经病变(DPN)。在这项纵向诊断研究中,我们评估了 CNFL 预测 DPN 发展的能力。

研究设计和方法

我们对来自 998 名 1 型和 2 型糖尿病患者的多国队列进行了研究,其中 261 名参与者在基线时无 DPN 且至少完成了 4 年的随访以发生 DPN。使用时间依赖性接受者操作特征(ROC)曲线确定 CNFL 对 DPN 发展的预测有效性。

结果

共有 203 名参与者患有 1 型糖尿病,58 名参与者患有 2 型糖尿病。平均随访时间为 5.8 年(四分位间距 4.2-7.0)。60 名参与者(23%)发生新诊断的 DPN(4.29 例/100 人年)。发生 DPN 的参与者年龄较大,2 型糖尿病患病率较高,BMI 较高,糖尿病病程较长。基线电生理学和角膜共聚焦显微镜参数均在正常范围内,但在发生 DPN 的参与者中均显著降低。CNFL 的时间依赖性 ROC 曲线下面积在第 1 至 5 年之间在 0.61 至 0.69 之间,在第 6 年时为 0.80。基线 CNFL 为 14.1mm/mm 时的最佳诊断阈值与 67%的敏感性、71%的特异性和 2.95 的风险比(95%CI 1.70-5.11;<0.001)相关,提示发生新诊断的 DPN 的风险较高。

结论

CNFL 对未来约 6 年内发生 DPN 的高危患者具有良好的预测有效性。

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