Dataset Information

Severity of Carpal Tunnel Syndrome and Diagnostic Accuracy of Hand and Body Anthropometric Measures.

ABSTRACT:

Objective

To study the diagnostic properties of hand/wrist and body measures according to validated clinical and electrophysiological carpal tunnel syndrome (CTS) severity scales.

Methods

We performed a prospective case-control study. For each case, two controls were enrolled. Two five-stage clinical and electrophysiological scales were used to evaluate CTS severity. Anthropometric measurements were collected and obesity indicators and hand/wrist ratios were calculated. Area under the receiver operating characteristic curves (AUC), sensitivity, specificity, and likelihood ratios were calculated separately by gender.

Results

We consecutively enrolled 370 cases and 747 controls. The wrist-palm ratio, waist-hip-height ratio and waist-stature ratio showed the highest proportion of cases with abnormal values in the severe stages of CTS for clinical and electrophysiological severity scales in both genders. Accuracy tended to increase with CTS severity for females and males. In severe stage, most of the indexes presented moderate accuracy in both genders. Among subjects with severe CTS, the wrist-palm ratio presented the highest AUC for hand measures in the clinical and electrophysiological severity scales both in females (AUC 0.83 and 0.76, respectively) and males (AUC 0.91 and 0.82, respectively). Among subjects with severe CTS, the waist-stature ratio showed the highest AUC for body measures in the clinical and electrophysiological severity scales both in females (AUC 0.78 and 0.77, respectively) and males (AUC 0.84 and 0.76, respectively). The results of waist-hip-height ratio AUC were similar.

Conclusions

Wrist-palm ratio, waist-hip-height ratio and waist-stature ratio could contribute to support the diagnostic hypothesis of severe CTS that however has to be confirmed by nerve conduction study.

SUBMITTER: Mondelli M

PROVIDER: S-EPMC5074522 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Severity of Carpal Tunnel Syndrome and Diagnostic Accuracy of Hand and Body Anthropometric Measures.

Mondelli Mauro M Farioli Andrea A Mattioli Stefano S Aretini Alessandro A Ginanneschi Federica F Greco Giuseppe G Curti Stefania S

PloS one 20161021 10

<h4>Objective</h4>To study the diagnostic properties of hand/wrist and body measures according to validated clinical and electrophysiological carpal tunnel syndrome (CTS) severity scales.<h4>Methods</h4>We performed a prospective case-control study. For each case, two controls were enrolled. Two five-stage clinical and electrophysiological scales were used to evaluate CTS severity. Anthropometric measurements were collected and obesity indicators and hand/wrist ratios were calculated. Area under ...[more]

PMID: 27768728

Similar Datasets

Project description:BackgroundCarpal tunnel syndrome (CTS), the most common neuropathy, is caused by a compression of the median nerve in the carpal tunnel and is related to aging. The initial symptom is numbness and pain of the median nerve distributed in the hand area, while thenar muscle atrophy occurs in advanced stages. This atrophy causes failure of thumb motion and results in clumsiness; even after surgery, thenar atrophy does not recover for an extended period. Medical examination and electrophysiological testing are useful to diagnose CTS; however, visits to the doctor tend to be delayed because patients neglect the symptom of numbness in the hand. To avoid thenar atrophy-related clumsiness, early detection of CTS is important.ObjectiveTo establish a CTS screening system without medical examination, we have developed a tablet-based CTS detection system, focusing on movement of the thumb in CTS patients; we examined the accuracy of this screening system.MethodsA total of 22 female CTS patients, involving 29 hands, and 11 female non-CTS participants were recruited. The diagnosis of CTS was made by hand surgeons based on electrophysiological testing. We developed an iPad-based app that recorded the speed and timing of thumb movements while playing a short game. A support vector machine (SVM) learning algorithm was then used by comparing the thumb movements in each direction among CTS and non-CTS groups with leave-one-out cross-validation; with this, we conducted screening for CTS in real time.ResultsThe maximum speed of thumb movements between CTS and non-CTS groups in each direction did not show any statistically significant difference. The CTS group showed significantly slower average thumb movement speed in the 3 and 6 o'clock directions (P=.03 and P=.005, respectively). The CTS group also took a significantly longer time to reach the points in the 2, 3, 4, 5, 6, 8, 9, and 11 o'clock directions (P<.05). Cross-validation revealed that 27 of 29 CTS hands (93%) were classified as having CTS, while 2 of 29 CTS hands (7%) did not have CTS. CTS and non-CTS were classified with 93% sensitivity and 73% specificity.ConclusionsOur newly developed app could classify disturbance of thumb opposition movement and could be useful as a screening test for CTS patients. Outside of the clinic, this app might be able to detect middle-to-severe-stage CTS and prompt these patients to visit a hand surgery specialist; this may also lead to medical cost-savings.

Dataset Information

Severity of Carpal Tunnel Syndrome and Diagnostic Accuracy of Hand and Body Anthropometric Measures.

Objective

Methods

Results

Conclusions

Publications

Severity of Carpal Tunnel Syndrome and Diagnostic Accuracy of Hand and Body Anthropometric Measures.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets