From the Department of Orthopaedic Surgery, Johns Hopkins University School of Medicine, Baltimore, MD.
J Am Acad Orthop Surg. 2021 Dec 1;29(23):e1264-e1273. doi: 10.5435/JAAOS-D-20-01309.
Current mortality predictive tools, in the setting of completed or impending pathologic fractures, are nonspecific. Clinical decision making and mortality prediction in research would benefit from creation of a high-fidelity scoring system for calculating the risk of 30-day postoperative mortality. The purpose of this study is to develop a validated research and clinical tool that is superior to existing methods in estimating postoperative mortality risk after fixation of pathologic fractures.
One thousand two hundred nineteen patients who underwent fixation for either completed or impending pathologic fractures in the National Surgical Quality Improvement Program (2012 to 2018) database were analyzed. Multivariable logistic regression with diagnostics was used to develop a predictive model in a derivation cohort and then validated in a validation cohort. Area under the curve (AUC) from receiver operator curve analysis was used to assess accuracy. A score was derived and compared with the American Society of Anesthesiologists classification and modified five-component frailty index (mF-I5). The score was validated in an exclusive cohort of patients who underwent fixation for pathologic fractures at a tertiary care center.
Of 1,219, a total of 177 (15%) patients did not survive beyond 30 days postoperatively. AUC for our predictive model was 0.76 in the derivation and 0.75 in the validation National Surgical Quality Improvement Program cohorts. The derived Pathologic Fracture Morbidity Index included seven data points: anemia, alkaline phosphatase > 150 U/L, albumin < 3.5 mg/dL, pulmonary disease, recent weight loss, functional dependence, and white blood cell count >12,000. The PFMI (AUC = 0.75) was more accurate than ASA (AUC = 0.60) or mF-5 (AUC = 0.58) (P < 0.01). The AUC for PFMI in predicting 30-day mortality in the exclusive cohort (N = 39) was 0.74.
The PFMI is a validated tool that may be used for predicting postoperative 30-day mortality after fixation of pathologic fractures, with higher level of accuracy compared with ASA or mF-I5.
在已发生或即将发生病理性骨折的情况下,目前的死亡率预测工具并不具有特异性。临床决策和死亡率预测研究将受益于创建一个高保真评分系统,以计算 30 天术后死亡率的风险。本研究的目的是开发一种经过验证的研究和临床工具,该工具在估计病理性骨折固定术后的术后死亡率风险方面优于现有方法。
分析了 2012 年至 2018 年国家手术质量改进计划(National Surgical Quality Improvement Program,NSQIP)数据库中 1219 例接受病理性骨折固定治疗的患者。多变量逻辑回归与诊断用于推导队列中的预测模型,然后在验证队列中进行验证。使用接收器工作特性曲线分析的曲线下面积(area under the curve,AUC)来评估准确性。得出一个评分,并与美国麻醉医师协会分类(American Society of Anesthesiologists classification,ASA)和改良五组分虚弱指数(modified five-component frailty index,mF-I5)进行比较。该评分在一家三级保健中心接受病理性骨折固定治疗的患者的专属队列中进行了验证。
在 1219 例患者中,共有 177 例(15%)患者在术后 30 天内未存活。我们的预测模型在推导和验证 NSQIP 队列中的 AUC 分别为 0.76 和 0.75。病理性骨折发病率指数(Pathologic Fracture Morbidity Index,PFMI)包括七个数据点:贫血、碱性磷酸酶>150 U/L、白蛋白<3.5mg/dL、肺部疾病、近期体重减轻、功能依赖和白细胞计数>12000。PFMI(AUC=0.75)比 ASA(AUC=0.60)或 mF-5(AUC=0.58)更准确(P<0.01)。PFMI 在预测 39 例专属队列(N=39)患者 30 天死亡率的 AUC 为 0.74。
PFMI 是一种经过验证的工具,可用于预测病理性骨折固定术后 30 天的死亡率,其准确性高于 ASA 或 mF-I5。