The Osteoporotic Vertebral Fracture Conservative Treatment Prognosis Score (OVF-CTPS): Development and Validation of a Prognostic Tool for Conservative Treatment of OVFs Based on a Prospective Cohort Study.

Abstract

A prospective cohort study (Level 3). To develop and validate a clinical scoring system (Osteoporotic Vertebral Fracture Conservative Treatment Prognosis Score, OVF-CTPS) for predicting the prognosis of conservative treatment in patients with osteoporotic vertebral fractures (OVFs), addressing clinical uncertainty in treatment selection. OVFs face uncertainty in choosing conservative vs. surgical management. 10-40% of patients have conservative treatment failure (e.g., non-union, collapse). Existing classification systems lack prognostic value, highlighting the need for a practical predictive tool. 201 patients with acute OVFs undergoing conservative treatment were prospectively followed for 6 months. Baseline assessments included demographics, pain, quality of life measures, and multimodal imaging (X-ray, CT, MRI). The primary outcome was conservative treatment failure. Independent predictors were identified using multivariate logistic regression and weighted to create the OVF-CTPS, which was validated using receiver operating characteristic (ROC) analysis. The conservative treatment failure rate was 29.9%. Six independent predictors were identified: Sugita "bow-shaped" or "concave" type, standing vertebral collapse degree <80%, middle column/posterior wall injury, T2WI "diffuse low" signal, STIR linear black signal, and basivertebral foramen involvement. The OVF-CTPS (range 0-13) demonstrated excellent predictive performance (AUC=0.918). At an optimal cutoff score of 6, the sensitivity was 91.3% and specificity was 84.0%. The low-risk group (score <6) had a 96.3% treatment success rate, while the high-risk group (score ≥6) had a success rate of 32.3. The OVF-CTPS is a validated prognostic tool that integrates fracture morphology, injury severity, and MRI-based perfusion markers. It accurately stratifies patients based on their risk of conservative treatment failure, enabling clinicians to identify low-risk patients suitable for conservative care and high-risk patients who may benefit from early surgical evaluation.