Abstract

Background: Traumatic injuries of the thoracolumbar junction (Th11–L2) are one of the most common sites of spinal trauma and frequently combine structural instability with neurological deficit, while treatment planning - conservative versus operative management, short versus long fixation, decompression, anterior column reconstruction - varies substantially between surgeons. Classification systems describe injury severity but provide little formalization of the tactical extent of intervention. The aim was to present an individualized treatment-planning algorithm and to evaluate how observed structural failures mapped to predefined decision levels in a retrospective cohort. Methods. The algorithm was assembled by integrating morphometric, prognostic, and biomechanical models and structured as if–then sequences separating the strategic, tactical, and technical decision levels. Its inputs are the AO Spine type, the morpho-functional variant, the neurological status by ISNCSCI (AIS grade), the spinal canal state, the posterior ligamentous complex (PLC) state, bone density (HU), mechanical exposure, and clinical context. The retrospective evaluation was performed on 326 patients (12-month follow-up in 297), matching endpoint events to the algorithm’s branch points. Results. The algorithm operates as a sequence of gates: a verification gate, a morphological branch (A1–A2, A3–A4, B, C), and neurological, ligamentous, densitometric, and contextual modifying gates, followed by the choice of strategy and tactical extent. Among the 297 patients with 12-month follow-up, 43 endpoint events occurred (41 structural failures and 2 clinico-deformational failures; an adverse outcome in 38 patients); 40 of the 41 structural failures mapped to the tactical level, and no isolated strategic-level failures were found. Corpectomy was associated with the numerically highest observed rate of structural failure (6/23; 26.1%; 95% CI 10.2–48.4%), all due to cage subsidence; this estimate was descriptive owing to the small subgroup size and probable confounding by indication, with no descriptive advantage in neurological recovery (47.8% versus 51.2%). The evaluation showed that the algorithm mainly refines the tactical rather than the strategic level of a decision. Conclusions. The proposed algorithm provides a transparent framework for treatment planning, and its underlying modules showed internal performance compatible with exploratory risk stratification. In retrospective decision-level evaluation, most structural failures mapped to tactical branch points. The algorithm should be considered a decision support tool and requires prospective external validation.

Keywords

thoracolumbar junction, spinal injury, treatment planning, clinical decision support, AO Spine, transpedicular fixation