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肥胖相关神经病变的诊断准确性提高:神经科医生面临的新挑战。

Better diagnostic accuracy of neuropathy in obesity: A new challenge for neurologists.

机构信息

Department of Neurology, University of Michigan, Ann Arbor, MI, USA.

School of Public Health, University of Michigan, Ann Arbor, MI, USA.

出版信息

Clin Neurophysiol. 2018 Mar;129(3):654-662. doi: 10.1016/j.clinph.2018.01.003. Epub 2018 Jan 16.

Abstract

OBJECTIVE

To determine the comparative diagnostic characteristics of neuropathy measures in an obese population.

METHODS

We recruited obese participants from the University of Michigan's Weight Management Program. Receiver operative characteristic analysis determined the area under the curve (AUC) of neuropathy measures for distal symmetric polyneuropathy (DSP), small fiber neuropathy (SFN), and cardiovascular autonomic neuropathy (CAN). The best test combinations were determined using stepwise and Score subset selection models.

RESULTS

We enrolled 120 obese participants. For DSP, seven of 42 neuropathy measures (Utah Early Neuropathy Score (UENS, N = 62), Michigan Neuropathy Screening Instrument (MNSI) reduced combined index, MNSI examination, nerve fiber density (NFD) leg, tibial F response, MNSI questionnaire, peroneal distal motor latency) had AUCs ≥ 0.75. Three of 19 small fiber nerve measures for SFN (UENS, NFD leg, Sudoscan feet (N = 70)) and zero of 16 CAN measures had AUCs ≥ 0.75. Combinations of tests performed better than individual tests with AUCs of 0.82 for DSP (two parameters) and 0.84 for SFN (three parameters).

CONCLUSIONS

Many neuropathy measures demonstrate good test performance for DSP in obese participants. Select few small fiber nerve measures performed well for SFN, and none for CAN.

SIGNIFICANCE

Specific combinations of tests should be used for research studies to maximize diagnostic performance in obese cohorts.

摘要

目的

确定肥胖人群中神经病变测量的比较诊断特征。

方法

我们从密歇根大学体重管理计划中招募了肥胖参与者。接收器工作特性分析确定了用于远端对称性多发性神经病(DSP)、小纤维神经病(SFN)和心血管自主神经病(CAN)的神经病测量的曲线下面积(AUC)。使用逐步和评分子集选择模型确定最佳测试组合。

结果

我们共纳入 120 名肥胖参与者。对于 DSP,42 种神经病变测量中的 7 种(犹他州早期神经病评分(UENS,N=62)、密歇根神经病筛查工具(MNSI)综合指数降低、MNSI 检查、神经纤维密度(NFD)腿部、胫骨 F 反应、MNSI 问卷、腓肠神经远端运动潜伏期)的 AUC 值≥0.75。SFN 的 19 种小纤维神经测量中的 3 种(UENS、NFD 腿部、Sudoscan 足部(N=70))和 CAN 测量中的 16 种均无 AUC 值≥0.75。与单个测试相比,测试组合的 AUC 值为 0.82,用于 DSP(两个参数)和 0.84,用于 SFN(三个参数),表现更好。

结论

许多神经病变测量在肥胖参与者中对 DSP 具有良好的测试性能。少数小纤维神经测量对 SFN 表现良好,对 CAN 则没有。

意义

应在研究研究中使用特定的测试组合,以最大限度地提高肥胖队列的诊断性能。

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