A prognostic model for the patient-reported outcome of surgical treatment of carpal tunnel syndrome.

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.