Sarthak Mohanty, Fthimnir M Hassan, Lawrence G Lenke, Erik Lewerenz, Peter Passias, Eric O Klineberg, Virginie Lafage, Justin S Smith, D Kojo Hamilton, Jeffrey L Gum, Renaud Lafage, Jeffrey Mullin, Bassel Diebo, Thomas J Buell, Han Jo Kim, Khalid Kebaish, Robert Eastlack, Alan Daniels, Gregory Mundis, Richard Hostin, Themistocles S Protopsaltis, Robert A Hart, Munish Gupta, Frank J Schwab, Christopher I Shaffrey, Christopher P Ames, Douglas Burton, Shay Bess
BACKGROUND CONTEXT: Among adult spinal deformity (ASD) patients, heterogeneity in patient pathology, surgical expectations, baseline impairments, and frailty complicates comparisons in clinical outcomes and research. This study aims to qualitatively segment ASD patients using machine learning-based clustering on a large, multicenter, prospectively gathered ASD cohort. PURPOSE: To qualitatively segment adult spinal deformity patients using machine learning-based clustering on a large, multicenter, prospectively gathered cohort...
February 14, 2024: Spine Journal: Official Journal of the North American Spine Society