Preoperative Mobile Health Data Improve Predictions of Recovery From Lumbar Spine Surgery

作者：Jacob K. Greenberg, Madelyn Frumkin, Ziqi Xu, Jingwen Zhang, Saad Javeed, Justin K. Zhang, Braeden Benedict, Kathleen Botterbush, Salim Yakdan, Camilo A. Molina, Brenton Pennicooke, Daniel Hafez, John Ogunlade, Nicholas A. Pallotta, Munish C. Gupta, Jacob M. Buchowski, Brian J. Neuman, Michael P. Steinmetz, Zoher Ghogawala, Michael P. Kelly, Burel R. Goodin, Jay F. Piccirillo, Thomas L. Rodebaugh, Chenyang Lu, Wilson Z. Ray · 发表于：Neurosurgery · 年份：2024 · DOI：10.1227/neu.0000000000002911 · 被引用次数：29 · 研究领域：Enhanced Recovery After Surgery、Total Knee Arthroplasty Outcomes、Music Therapy and Health

BACKGROUND AND OBJECTIVES: Neurosurgeons and hospitals devote tremendous resources to improving recovery from lumbar spine surgery. Current efforts to predict surgical recovery rely on one-time patient report and health record information. However, longitudinal mobile health (mHealth) assessments integrating symptom dynamics from ecological momentary assessment (EMA) and wearable biometric data may capture important influences on recovery. Our objective was to evaluate whether a preoperative mHealth assessment integrating EMA with Fitbit monitoring improved predictions of spine surgery recovery. METHODS: Patients age 21-85 years undergoing lumbar surgery for degenerative disease between 2021 and 2023 were recruited. For up to 3 weeks preoperatively, participants completed EMAs up to 5 times daily asking about momentary pain, disability, depression, and catastrophizing. At the same time, they were passively monitored using Fitbit trackers. Study outcomes were good/excellent recovery on the Quality of Recovery-15 (QOR-15) and a clinically important change in Patient-Reported Outcomes Measurement Information System Pain Interference 1 month postoperatively. After feature engineering, several machine learning prediction models were tested. Prediction performance was measured using the c-statistic. RESULTS: A total of 133 participants were included, with a median (IQR) age of 62 (53, 68) years, and 56% were female. The median (IQR) number of preoperative EMAs completed was 78 (61,...