A Multicenter Validation of a Novel Prediction Model for Elbow Flexion Recovery after Nerve Transfer Surgery in Brachial Plexus Injuries

Abstract

Background:. Nerve transfer surgery for brachial plexus injuries exhibits variable success rates, potentially resulting in prolonged limb dysfunction for more than 2 years. A proposed prediction model has been developed to predict the unsuccessful recovery of elbow flexion after the surgery. The model consisted of six variables, namely body mass index 23 kg/m2 or more, smoking, total arm type, donor nerve, ipsilateral upper extremity fracture, and ipsilateral vascular injury. This study aimed to assess the external validity of the model for wider applicability. Methods:. This retrospective analysis examined the medical records of 213 eligible patients with traumatic brachial plexus injuries who underwent surgery at two referral centers between July 2008 and June 2022. The prediction model was applied to estimate recovery failure probability, which was compared with the observed outcomes for each patient. Both the original and simplified models were validated for discrimination and calibration using metrics including c-statistic, Hosmer–Lemeshow goodness-of-fit test, calibration plot, calibration slope, and intercept. Results:. Thirty-two percent of patients experienced unsuccessful elbow flexion recovery. Both the original and simplified models demonstrated good discrimination (c-statistics: 0.748 and 0.759, respectively). The Hosmer–Lemeshow test revealed strong agreement between predicted and observed probabilities for both models (P = 0.66 and P = 0.92, respectively). The calibration plot exhibited good agreement, with a calibration slope of 0.928 and an intercept of 0.377. Conclusions:. The prediction model showed strong external validation, confirming its clinical value. High-risk patients should be educated on the risks and benefits of nerve transfer surgery and consider alternative treatments such as primary free functioning muscle transfer.