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.
journal_name
Muscle Nervejournal_title
Muscle & nerveauthors
Bowman A,Rudolfer S,Weller P,Bland JDPdoi
10.1002/mus.26297subject
Has Abstractpub_date
2018-12-01 00:00:00pages
784-789issue
6eissn
0148-639Xissn
1097-4598journal_volume
58pub_type
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