DOI 10.1016/j.wneu.2025.124293
Development of a Predictive Model for Kummell's Disease.
Аннотация
BACKGROUND
Kümmell's disease (KD) is a recognized complication of osteoporotic thoracolumbar vertebral compression fractures (OVCFs), but the risk factors for progression from OVCFs to KD remain unclear.
METHODS
This retrospective study included 104 patients with OVCFs from a tertiary hospital between January 2020 and December 2023. Patients were divided into a case group (56 patients with KD) and a control group (48 patients without KD). Data on 24 variables, including demographics, fracture characteristics, and biochemical markers, were collected and analyzed using SPSS 25.0 software. Statistical methods included independent samples t-test, Mann-Whitney U test, chi-square test, Fisher's exact test, and binary logistic regression.
RESULTS
Univariate analysis identified 5 significant factors related to KD onset: age, vertebral length, intervertebral foramen width, alkaline phosphatase, and albumin. Binary logistic regression analysis revealed 3 independent risk factors for KD: vertebral length, alkaline phosphatase, and albumin.
CONCLUSIONS
When treating OVCF patients, clinicians should consider comprehensive factors. Patients with high alkaline phosphatase levels, longer fractured vertebrae, and low albumin levels should be closely monitored. Targeted interventions, such as early surgery, enhanced nutrition, and optimized antiosteoporosis plans, may reduce KD risk and improve patient outcomes.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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