Developing a Prediction Model for Identification of Distinct Perioperative Clinical Stages in Spine Surgery With Smartphone-Based Mobility Data

BACKGROUND: Spine surgery outcomes assessment currently relies on patient-reported outcome measures, which satisfy established reliability and validity criteria, but are limited by the inherently subjective and discrete nature of data collection. Physical activity measured from smartphones offers a new data source to assess postoperative functional outcomes in a more objective and continuous manner. OBJECTIVE: To present a methodology to characterize preoperative mobility and gauge the impact of surgical intervention using objective activity data garnered from smartphone-based accelerometers. METHODS: Smartphone mobility data from 14 patients who underwent elective lumbar decompressive surgery were obtained. A time series analysis was conducted on the number of steps per day across a 2-year perioperative period. Five distinct clinical stages were identified using a data-driven approach and were validated with clinical documentation. RESULTS: Preoperative presentation was correctly classified as either a chronic or acute mobility decline in 92% of patients, with a mean onset of acute decline of 11.8 +/- 2.9 weeks before surgery. Postoperative recovery duration demonstrated wide variability, ranging from 5.6 to 29.4 weeks (mean: 20.6 +/- 4.9 weeks). Seventy-nine percentage of patients ultimately achieved a full recovery, associated with an 80% +/- 33% improvement in daily steps compared with each patient's preoperative baseline (P = .002). Two patients subsequently experienced a secondary decline in mobility, which was consistent with clinical history. CONCLUSION: The perioperative clinical course of patients undergoing spine surgery was systematically classified using smartphone-based mobility data. Our findings highlight the potential utility of such data in a novel quantitative and longitudinal surgical outcome measure.

Automated summary

This study utilized smartphone-based activity data to classify and assess the perioperative clinical course of patients undergoing spine surgery. The results demonstrated the potential clinical utility of this method for objectively and continuously evaluating postoperative functional outcomes.