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MICRO-CONTROLLED THERMAL STIMULATOR FOR DETECTING FINE FIBER CHANGES IN PATIENTS WITH DIABETES MELLITUS: A DIAGNOSTIC ACCURACY STUDY
Authors:João Corrêa Paixão  Fábio Ricardo de Oliveira  Nathalia Sernizon Guimarães  José Augusto Nogueira Machado  Maria Regina Calsolari Pereira de Souza
Institution:1. Santa Casa de Belo Horizonte, Brazil;2. Universidade Federal de Ouro Preto, Brazil
Abstract:AimTo evaluate sensitivity and specificity of the micro-controlled thermal stimulator (MTS) for detecting pathological changes in fine fiber of neuropathy patients with DM.MethodsA diagnostic accuracy study including 84 patients, aged 15–75 years was conducted. A patient’s foot was subjected to dermatological, musculoskeletal, vascular, and neurological evaluations. The latter was performed through the perception of a sharp touch with a toothpick (pinprick), thermal sensitivity (cold and hot temperature sensations measured using Diapason Handle and MTS, respectively), vibratory sensitivity (128 Hz Diapason Handle), 10 g Semmes-Weinstein monofilament, and a reflex test. Statistical analyses were performed using Stata® software version 13.0. The sensitivity, specificity, positive and negative predictive values, likelihood ratios, AUC, Kappa index, and accuracy of the diagnostic instruments were evaluated.ResultsOf the 84 volunteers, 66.7% were female, with an average age of 54 years. We observed that 17% of the total patients were positive for pain sensations in the foot, 13% for cold-temperature sensations, and 21% for hot-temperature sensations. The MTS (hot temperature) obtained 97.6% sensitivity and 90% specificity, agreeing on 87.5% (Kappa index) with the Diapason Handle (cold temperature) (AUC > 0.937; p < 0.05).ConclusionMTS is an accurate, sensitive, and specific instrument for the evaluation of diabetic neuropathy as compared with the tuning fork as the standard method and, consequently, it could be of help for the early diagnosis of diabetic neuropathy.
Keywords:diabetic neuropathy  diabetes mellitus  early diagnosis  data reliability
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