Vesseur Maud A M, Quaedvlieg Lars, Schotanus Martijn G M, Most Jasper, Bouwman Lee H, van Vugt Raoul, Boonen Bert
Multidisciplinary Trauma Unit, Zuyderland Medical Center, Heerlen, The Netherlands.
Department of Orthopaedic Surgery, Zuyderland Medical Center, Sittard-Geleen, The Netherlands.
Hip Int. 2025 Mar;35(2):214-219. doi: 10.1177/11207000241312306. Epub 2025 Jan 8.
Proximal femoral fractures are common within the elderly population and are associated with a high risk of mortality and reduced quality of life. Hemiarthroplasty or osteosynthesis (extramedullary or intramedullary) is the primary treatment option for these fractures. However, within this fragile patient population many comorbidities, among others dementia, are seen. Therefore, predicting patients with a high mortality risk after surgery may lead to adopting alternative treatment options with less risks. This paper proposes a new model to distinguish patients with high postoperative mortality risk with adequate follow-up time in combination with a wide set of useful and available variables.
Patients treated with hemiarthroplasty or osteosynthesis for proximal femoral fractures were studied, with a follow-up period of 6 months. Patients who died within this follow-up period were compared to survivors, and predicting variables were assessed in logistic regression: The Zuyderland Hip Inference for Survival and Lifetime Expectancy (ZHISLE). The model was validated internally against a held-out dataset. Furthermore, the model performance was compared against the Almelo Hip Fracture Score (AHFS) on the same sample.
Out of 2463 patients undergoing surgical treatment for proximal femoral fractures, 415 (16.8%) died within 183 days. Predictors for early mortality included old age, male sex, high heartbeat, KATZ-ADL and GFI scores, C-reactive protein and urea concentrations and low albumin concentration. Our model showed satisfactory predictive and discriminatory power (ROC curve = 0.81). Internal validation was good (ROC in validation dataset = 0.81), and better than the AHFS (ROC = 0.57).
The ZHISLE model demonstrates good predictive power concerning mortality risk for old patients with a proximal femoral fracture. The model could benefit patients by indicating if a conservative, non-invasive policy might be a better option for those patients.
股骨近端骨折在老年人群中很常见，与高死亡率和生活质量下降相关。半髋关节置换术或骨固定术（髓外或髓内）是这些骨折的主要治疗选择。然而，在这个脆弱的患者群体中，存在许多合并症，其中包括痴呆症。因此，预测术后高死亡风险的患者可能会促使采用风险较低的替代治疗方案。本文提出了一种新模型，结合一系列有用且可得的变量，在有足够随访时间的情况下区分术后高死亡风险的患者。
对接受半髋关节置换术或骨固定术治疗股骨近端骨折的患者进行研究，随访期为6个月。将在此随访期内死亡的患者与幸存者进行比较，并在逻辑回归中评估预测变量：祖伊德兰德髋部生存与预期寿命推断（ZHISLE）。该模型在一个保留数据集上进行内部验证。此外，在同一样本上，将该模型的性能与阿尔梅洛髋部骨折评分（AHFS）进行比较。
在2463例接受股骨近端骨折手术治疗的患者中，415例（16.8%）在183天内死亡。早期死亡的预测因素包括高龄、男性、心跳过快、KATZ-ADL和GFI评分、C反应蛋白和尿素浓度以及低白蛋白浓度。我们的模型显示出令人满意的预测和区分能力（ROC曲线 = 0.81）。内部验证良好（验证数据集中的ROC = 0.81），且优于AHFS（ROC = 0.57）。
ZHISLE模型在预测老年股骨近端骨折患者的死亡风险方面显示出良好的预测能力。该模型可以通过表明对于某些患者，保守的、非侵入性的策略是否可能是更好的选择，从而使患者受益。
