Diagnostic Accuracy of Perception Threshold Tracking in the Detection of Small Fiber Damage in Type 1 Diabetes.

IF 4.1 Q2 ENDOCRINOLOGY & METABOLISM

Journal of Diabetes Science and Technology Pub Date : 2024-09-01 Epub Date: 2023-02-24 DOI:10.1177/19322968231157431

Johan Røikjer, Suganthiya Santhiapillai Croosu, Benn Falch Sejergaard, Tine Maria Hansen, Jens Brøndum Frøkjær, Chris Bath Søndergaard, Ioannis N Petropoulos, Rayaz A Malik, Esben Nielsen, Carsten Dahl Mørch, Niels Ejskjaer

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Abstract

Aim: An objective assessment of small nerve fibers is key to the early detection of diabetic peripheral neuropathy (DPN). This study investigates the diagnostic accuracy of a novel perception threshold tracking technique in detecting small nerve fiber damage.

Methods: Participants with type 1 diabetes (T1DM) without DPN (n = 20), with DPN (n = 20), with painful DPN (n = 20) and 20 healthy controls (HCs) underwent perception threshold tracking on the foot and corneal confocal microscopy. Diagnostic accuracy of perception threshold tracking compared to corneal confocal microscopy was analyzed using logistic regression.

Results: The rheobase, corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fiber length (CNFL) (all P < .001) differed between groups. The diagnostic accuracy of perception threshold tracking (rheobase) was excellent for identifying small nerve fiber damage, especially for CNFL with a sensitivity of 94%, specificity 94%, positive predictive value 97%, and negative predictive value 89%. There was a significant correlation between rheobase with CNFD, CNBD, CNFL, and Michigan Neuropathy Screening Instrument (all P < .001).

Conclusion: Perception threshold tracking had a very high diagnostic agreement with corneal confocal microscopy for detecting small nerve fiber loss and may have clinical utility for assessing small nerve fiber damage and hence early DPN.

Clinical trials: NCT04078516.

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感知阈值跟踪在检测1型糖尿病小纤维损伤中的诊断准确性。

目的：对小神经纤维进行客观评估是早期发现糖尿病周围神经病变（DPN）的关键。本研究探讨了一种新的感知阈值跟踪技术在检测小神经纤维损伤中的诊断准确性。方法：1型糖尿病（T1DM）无DPN（n=20）、有DPN（n=20）、疼痛性DPN（n/20）和20名健康对照（HC）的参与者在足部和角膜共聚焦显微镜下接受感知阈值跟踪。使用逻辑回归分析感知阈值跟踪与角膜共焦显微镜相比的诊断准确性。结果：各组间的流变基底、角膜神经纤维密度（CNFD）、角膜神经分支密度（CNBD）和角膜神经纤维长度（CNFL）均有差异（均P＜0.001）。感知阈值跟踪（rheobase）的诊断准确性在识别小神经纤维损伤方面非常好，尤其是对CNFL的诊断，其敏感性为94%，特异性为94%，阳性预测值为97%，阴性预测值为89%。变阻性碱基与CNFD、CNBD、CNFL、，和Michigan Neuropathy Screening Instrument（均P＜0.001）。结论：感知阈值跟踪与角膜共聚焦显微镜在检测小神经纤维损失方面具有非常高的诊断一致性，可能对评估小神经纤维损伤和早期DPN具有临床实用性。临床试验：NCT04078516。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Diabetes Science and Technology Medicine-Internal Medicine

CiteScore

7.50

自引率

12.00%

发文量

148

期刊介绍： The Journal of Diabetes Science and Technology (JDST) is a bi-monthly, peer-reviewed scientific journal published by the Diabetes Technology Society. JDST covers scientific and clinical aspects of diabetes technology including glucose monitoring, insulin and metabolic peptide delivery, the artificial pancreas, digital health, precision medicine, social media, cybersecurity, software for modeling, physiologic monitoring, technology for managing obesity, and diagnostic tests of glycation. The journal also covers the development and use of mobile applications and wireless communication, as well as bioengineered tools such as MEMS, new biomaterials, and nanotechnology to develop new sensors. Articles in JDST cover both basic research and clinical applications of technologies being developed to help people with diabetes.