Retrospective analysis of patients ≥ 60 years, treated conservatively for a CT-scan verified, low-energy pelvic ring fracture between August 2006 and December 2018. Survival data was available from patients\' charts and cantonal or national registries. The prognostic value of fracture characteristic describing the anterior and posterior involvement of the pelvic ring was investigated. This analysis was repeated after patients were stratified into a high-risk vs a low-risk group according to patient characteristic (age, gender, comorbidities, mobility, living situation). This allowed to assess the impact of the different fracture morphologies on mortality in fit vs. frail senior patients separately.
Overall, 428 patients (83.4% female) with a mean age of 83.7 years were included. Two thirds of patients were still living in their home and mobile without walking aid at baseline. In-hospital mortality was 0.7%, overall, one-year mortality 16.9%. An independent and significant association of age, gender and comorbidities to overall survival was found. Further, the occurrence of a horizontal sacral fracture as well as a ventral comminution or dislocation was associated with an increased mortality. The effect of a horizontal sacral fracture was more accentuated in low-risk patients while the ventral fracture components showed a larger effect on survival in high-risk patients.
Specific fracture characteristics may indicate a higher risk of mortality in conservatively treated patients with a low-energy pelvic ring fracture. Hence, they should be taken into account in future treatment algorithms and decisions on patient management.
≥60岁患者的回顾性分析,经过CT扫描的保守治疗,2006年8月至2018年12月期间的低能量骨盆环骨折.生存数据可从患者图表和州或国家登记处获得。研究了描述骨盆环前后受累的骨折特征的预后价值。根据患者特征(年龄,性别,合并症,移动性,生活情况)。这允许评估不同骨折形态对死亡率的影响脆弱的老年患者分开。
总的来说,包括428名患者(83.4%为女性),平均年龄为83.7岁。在基线时,三分之二的患者仍然生活在家中和移动中,没有助行器。住院死亡率为0.7%,总的来说,一年死亡率16.9%。独立和重要的年龄关联,发现性别和合并症对总生存率的影响.Further,骶骨水平骨折以及腹侧粉碎或脱位的发生与死亡率增加相关.在低风险患者中,水平骶骨骨折的影响更为突出,而在高风险患者中,腹侧骨折成分对生存的影响更大。
特定的骨折特征可能表明保守治疗的低能量骨盆环骨折患者的死亡风险更高。因此,在未来的治疗算法和患者管理决策中应考虑这些因素.