Predictive Model for Frailty in the Elderly Based on Fat Infiltration of the Para vertebral Muscles of the Thoracic Spine

Objectives This study aimed to examine the predictive value of thoracic para vertebral muscle fat infiltration for frailty in older adults. Methods A total of 390 patients elderly patients in the Geriatric Medicine and Orthopedic Departments of the Second Affiliated Hospital of Dalian Medical University between January 2020 and June 2024 were enrolled. Basic patient information, laboratory data, imaging findings, and Morse scale during hospitalization; general health status, activities of daily living, and other relevant scales through Telephone follow-up were collected. 1.Using 3D Slicer software, measured and calculated T5 and T10 Skeletal muscle cross-sectional area, corrected T5-T10 para vertebral muscle volume, fat volume of T5-T10 thoracic para vertebral muscles, then calculated T5 and T10 Skeletal muscle mass index (SMI) and Thoracic para vertebral muscle fat infiltration (MFI). 2. Based on telephone follow-up outcomes, all patients were categorized into three groups, Including the effective follow-up group (n=301), loss to follow-up group(n=143), and deceased group(n=35). Characteristics between effective follow-up group and deceased group were analyzed. 3. The effective follow-up group patients were divided into quadrilles by thoracic para vertebral MFI , then analyzing baseline and follow-up data. 4. Predictors of frailty was determined using binary logistic regression, and constructed nomogram based on these predictors. Bootstrap with 1000 resamples was used for internal validation of nomogram, Model discrimination, calibration, and clinical value were assessed using ROC curves, calibration curves, and decision curve analysis (DCA), respectively. Results 1.Comparing with the effective follow-up group, the deceased group exhibited higher thoracic para vertebral MFI. 2. Comparing with the first quartile group, the patients with para vertebral MFI exceeding 20.75% exhibited higher FRAIL score. 3. Multivariate binary logistic regression analysis for frailty revealed positive correlations between thoracic para vertebral MFI and frailty. 4. Nomogram was constructed based on binary logistic predictors. The AUC of validation set ROC curve was 0.785, sensitivity was 0.744, and specificity was 0.723. Calibration curve indicated that probabilities predicted by the nomogram agreed well with the actual observation. Decision curve analysis (DCA) revealed that the net benefit curves exceeded the All and None curves, indicating superior clinical net benefit. Conclusions 1. There is positive correlations between thoracic para vertebral MFI and frailty. 2. Patients with thoracic para vertebral MFI exceeding 20.75% are more prone to developing frailty.