Department of Orthopaedic and Neuro-Musculoskeletal Surgery, Faculty of Medical and Pharmaceutical Sciences, Kumamoto University, 1-1-1 Honjo, Kumamoto 860-8556, Japan.
Clin Orthop Relat Res. 2009 Dec;467(12):3327-33. doi: 10.1007/s11999-009-0915-6. Epub 2009 Jun 4.
Predicting the postoperative course of patients with hip fractures would be helpful for surgical planning and risk management. We therefore established equations to predict the morbidity and mortality rates in candidates for hip fracture surgery using the Estimation of Physiologic Ability and Surgical Stress (E-PASS) risk-scoring system. First we evaluated the correlation between the E-PASS scores and postoperative morbidity and mortality rates in all 722 patients surgically treated for hip fractures during the study period (Group A). Next we established equations to predict morbidity and mortality rates. We then applied these equations to all 633 patients with hip fractures treated at seven other hospitals (Group B) and compared the predicted and actual morbidity and mortality rates to assess the predictive ability of the E-PASS and Physiological and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) systems. The ratio of actual to predicted morbidity and mortality rates was closer to 1.0 with the E-PASS than the POSSUM system. Our data suggest the E-PASS scoring system is useful for defining postoperative risk and its underlying algorithm accurately predicts morbidity and mortality rates in patients with hip fractures before surgery. This information then can be used to manage their condition and potentially improve treatment outcomes.
Level II, prognostic study. See the Guidelines for Authors for a complete description of levels of evidence.
预测髋部骨折患者的术后病程有助于手术规划和风险管理。因此,我们使用生理能力和手术应激评估(E-PASS)风险评分系统建立了预测髋部骨折手术候选者发病率和死亡率的方程。首先,我们评估了 722 例接受髋部骨折手术治疗的患者的 E-PASS 评分与术后发病率和死亡率之间的相关性(A 组)。接下来,我们建立了预测发病率和死亡率的方程。然后,我们将这些方程应用于在另外七家医院接受髋部骨折治疗的 633 例患者(B 组),并比较预测和实际发病率和死亡率,以评估 E-PASS 和生理及手术严重程度评分预测死亡率和发病率(POSSUM)系统的预测能力。实际发病率和死亡率与预测发病率和死亡率的比值更接近 1.0 的是 E-PASS 系统,而不是 POSSUM 系统。我们的数据表明,E-PASS 评分系统可用于定义术后风险,其潜在算法可准确预测髋部骨折患者术前的发病率和死亡率。这些信息可用于管理他们的病情并有可能改善治疗结果。
II 级,预后研究。有关证据水平的完整描述,请参见作者指南。