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.