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糖尿病周围神经病变的早期检测:聚焦于小神经纤维

Early Detection of Diabetic Peripheral Neuropathy: A Focus on Small Nerve Fibres.

作者信息

Burgess Jamie, Frank Bernhard, Marshall Andrew, Khalil Rashaad S, Ponirakis Georgios, Petropoulos Ioannis N, Cuthbertson Daniel J, Malik Rayaz A, Alam Uazman

机构信息

Diabetes & Endocrinology Research, Institute of Cardiovascular and Metabolic Medicine and The Pain Research Institute, University of Liverpool and Liverpool University NHS Hospital Trust, Liverpool L69 7ZX, UK.

The Walton Centre, Department of Pain Medicine, Liverpool L9 7LJ, UK.

出版信息

Diagnostics (Basel). 2021 Jan 24;11(2):165. doi: 10.3390/diagnostics11020165.

Abstract

Diabetic peripheral neuropathy (DPN) is the most common complication of both type 1 and 2 diabetes. As a result, neuropathic pain, diabetic foot ulcers and lower-limb amputations impact drastically on quality of life, contributing to the individual, societal, financial and healthcare burden of diabetes. DPN is diagnosed at a late, often pre-ulcerative stage due to a lack of early systematic screening and the endorsement of monofilament testing which identifies advanced neuropathy only. Compared to the success of the diabetic eye and kidney screening programmes there is clearly an unmet need for an objective reliable biomarker for the detection of early DPN. This article critically appraises research and clinical methods for the diagnosis or screening of early DPN. In brief, functional measures are subjective and are difficult to implement due to technical complexity. Moreover, skin biopsy is invasive, expensive and lacks diagnostic laboratory capacity. Indeed, point-of-care nerve conduction tests are convenient and easy to implement however questions are raised regarding their suitability for use in screening due to the lack of small nerve fibre evaluation. Corneal confocal microscopy (CCM) is a rapid, non-invasive, and reproducible technique to quantify small nerve fibre damage and repair which can be conducted alongside retinopathy screening. CCM identifies early sub-clinical DPN, predicts the development and allows staging of DPN severity. Automated quantification of CCM with AI has enabled enhanced unbiased quantification of small nerve fibres and potentially early diagnosis of DPN. Improved screening tools will prevent and reduce the burden of foot ulceration and amputations with the primary aim of reducing the prevalence of this common microvascular complication.

摘要

糖尿病周围神经病变(DPN)是1型和2型糖尿病最常见的并发症。因此,神经病理性疼痛、糖尿病足溃疡和下肢截肢对生活质量产生了巨大影响,增加了糖尿病患者个人、社会、经济和医疗保健负担。由于缺乏早期系统筛查以及仅能识别晚期神经病变的单丝试验的认可,DPN往往在晚期、通常是溃疡前期才被诊断出来。与糖尿病眼部和肾脏筛查项目的成功相比,显然迫切需要一种客观可靠的生物标志物来检测早期DPN。本文对早期DPN诊断或筛查的研究和临床方法进行了批判性评估。简而言之:功能测量是主观的,且由于技术复杂性难以实施。此外,皮肤活检具有侵入性、成本高且缺乏诊断实验室能力。的确,即时神经传导测试方便且易于实施,但由于缺乏对小神经纤维的评估,其在筛查中的适用性存在疑问。角膜共焦显微镜检查(CCM)是一种快速、无创且可重复的技术,可量化小神经纤维损伤和修复情况,可与视网膜病变筛查同时进行。CCM可识别早期亚临床DPN,预测其发展并对DPN严重程度进行分期。利用人工智能对CCM进行自动定量分析,能够对小神经纤维进行更客观的量化分析,并有可能实现DPN的早期诊断。改进的筛查工具将预防和减轻足部溃疡和截肢的负担,其主要目的是降低这种常见微血管并发症的患病率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eac9/7911433/edf857bb4972/diagnostics-11-00165-g001.jpg

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