A prognostic model for the patient‐reported outcome of surgical treatment of carpal tunnel syndrome. Issue 6 (15th October 2018)

• Record Type: Journal Article
• Authors: Bowman, Angela; Rudolfer, Stephan; Weller, Peter; Bland, Jeremy D. P.
• Is Part Of: Muscle & nerve. Volume 58:Issue 6(2018)
• Page Start: 784
• Page End: 789
• Publication Date: 2018-10-15
• Subjects: artificial neural networks -- carpal tunnel syndrome -- corticosteroid injection -- electrodiagnosis -- prognosis -- surgery; Neuromuscular diseases -- Periodicals; Muscles -- Periodicals; Nerves -- Periodicals; 616.74
• DOI: 10.1002/mus.26297
• Languages: English
• ISSNs: 0148-639X

Abstract

ABSTRACT: Introduction: Many prognostic factors have been studied in carpal tunnel decompression, but most studies consider only a subset of variables. Methods: Three thousand three hundred thirty‐two operations were used to develop prognostic models, and 885 operations were used for validation. Outcome recorded on a Likert scale was dichotomized into success or failure. Modeling was performed with both logistic regression and artificial neural networks using 87 candidate variables. Results: Both approaches produced predictive multivariate models for outcome with areas under a receiver operating characteristic curve of 0.7 in the validation data set. Patients with moderately severe nerve conduction abnormalities, night waking, a family history of carpal tunnel syndrome, a good response to corticosteroid injection, and women have better outcomes. Greater functional impairment, diabetes, hypertension, and surgery on the dominant hand are associated with poorer outcomes. Discussion: A multivariate model partially predicts the outcome of carpal tunnel surgery, aids decision making, and helps to manage patient expectations. Muscle Nerve 58 :784–789, 2018