{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T05:53:13Z","timestamp":1789537993924,"version":"build-2803163510"},"reference-count":26,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T00:00:00Z","timestamp":1730246400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"abstract":"<jats:p>Objective: The development of adjacent segment disease or the progression of spondylosis following the surgical treatment of spinal stenosis and spondylolisthesis is well documented and can lead to subsequent functional decline after a successful index surgery. The early detection of negative inflection points during patients\u2019 functional recovery can improve timely intervention. In this study, we developed machine learning (ML) models to predict the occurrence of post-operative decline in patient mobility. Methods: Patients receiving spine surgery for degenerative spinal stenosis or spondylolisthesis were retroactively consented and enrolled. Activity data (steps-per-day) previously recorded across a 4-year peri-operative were collected alongside relevant clinical and demographic variables. Logistic regression (LR), random forest (RF), and extreme gradient boosting (XGBoost) ML models were constructed and trained on 80% of the dataset and validated using the remaining 20%. The study\u2019s primary endpoint was the models\u2019 ability to predict post-operative decline in patient mobility. Results: A total of 75 patients were included. Following training, RF and XGBoost models achieved accuracy values of 86.7% (sensitivity 80%, specificity 90%) and 80% (sensitivity 60%, specificity 90%), respectively, in predicting post-operative functional decline. The LR model was the least effective with an accuracy of 73.3% (sensitivity 50%, specificity 88.8%). Receiver operating characteristic curves showed an area under the curve of 0.80 for RF, 0.70 for XGBoost, and 0.69 for LR. Conclusions: ML models trained on activity data collected from smartphones successfully forecast functional decline in post-operative activity following spine surgery. These results lay the groundwork for the future integration of ML into the surgeon\u2019s toolbox for prognostication and surgical planning.<\/jats:p>","DOI":"10.3390\/jcm13216515","type":"journal-article","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T09:10:44Z","timestamp":1730279444000},"page":"6515","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Machine Learning Models Leveraging Smartphone-Based Patient Mobility Data Can Accurately Predict Functional Outcomes After Spine Surgery"],"prefix":"10.3390","volume":"13","author":[{"given":"Hasan S.","family":"Ahmad","sequence":"first","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daksh","family":"Chauhan","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5201-6720","authenticated-orcid":false,"given":"Mert Marcel","family":"Dagli","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-9258-2123","authenticated-orcid":false,"given":"Ryan W.","family":"Turlip","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0398-3367","authenticated-orcid":false,"given":"Malek","family":"Bashti","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Miller School of Medicine, University of Miami, Miami, FL 33136, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Hamade","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Patrick T.","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yohannes","family":"Ghenbot","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrew I.","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Barrow Neurological Institute, Phoenix, AZ 85013, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gregory W.","family":"Basil","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Miller School of Medicine, University of Miami, Miami, FL 33136, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"William C.","family":"Welch","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jang Won","family":"Yoon","sequence":"additional","affiliation":[{"name":"Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1056\/NEJMoa1508788","article-title":"Laminectomy plus fusion versus laminectomy alone for lumbar spondylolisthesis","volume":"374","author":"Ghogawala","year":"2016","journal-title":"N. 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