Department of Surgery, Emory University School of Medicine, Atlanta, Georgia; Division of Acute Care Surgery, Grady Memorial Hospital, Atlanta, Georgia.
Department of Surgery, Mercer University School of Medicine, Savannah, Georgia.
J Surg Res. 2020 Nov;255:456-462. doi: 10.1016/j.jss.2020.05.090. Epub 2020 Jun 30.
The 5-factor modified frailty index (mFI-5) and the 11-factor modified frailty index (mFI-11) are equally effective in predicting adverse outcomes in the American College of Surgeons National Surgical Quality Improvement Program database. The similarly structured American College of Surgeons Trauma Quality Improvement Program (TQIP) database has not been studied with these two frailty indices. We hypothesized that the mFI-5 and mFI-11 could similarly predict adverse outcomes with TQIP data.
The mFI-5 and mFI-11 were calculated for each patient comprising our institutional TQIP registry (2016-2018). Spearman ρ was calculated to assess correlations between the two indices across multiple predefined TQIP patient cohorts. Complications were stratified by frailty score for each index. Multivariable logistic regression models adjusting for age, Glasgow Coma Scale score, and Injury Severity Score were created to assess each mFI's association with any complication and discharge dispositions (home, facility, and expired).
There were 8467 patients. Spearman ρ was >0.9 (P < 0.0001) for all patient cohorts except elderly, elderly blunt multisystem, and isolated hip fractures. Increasing frailty scores for both mFIs were associated with greater rates of acute kidney injury (P < 0.0001), myocardial infarction (P < 0.001), severe sepsis (P < 0.05), unplanned return to the intensive care unit (P < 0.0001), and unplanned intubation (P < 0.0001). On separate multivariable logistic regressions, the mFI-5 and mFI-11 were each predictive of any complication (P < 0.0001) and a facility discharge (P < 0.001). Neither the mFI-5 nor the mFI-11 were associated with mortality (P > 0.05).
The mFI-5 and mFI-11 are highly correlated across several TQIP patient cohorts. They also are both predictive of complications and discharge dispositions; however, neither index can predict mortality. Given its ease of use, the mFI-5 may be a better option for identifying frail patients and predicting adverse outcomes at the point of care in trauma.
在美国外科医师学院国家手术质量改进计划（ACS-NSQIP）数据库中，五因素改良衰弱指数（mFI-5）和十一因素改良衰弱指数（mFI-11）在预测不良结局方面同样有效。结构相似的美国外科医师学院创伤质量改进计划（TQIP）数据库尚未使用这两个衰弱指数进行研究。我们假设 mFI-5 和 mFI-11 可以使用 TQIP 数据类似地预测不良结局。
为我们机构的 TQIP 登记处（2016-2018 年）中的每位患者计算 mFI-5 和 mFI-11。计算两个指数之间的 Spearman ρ，以评估它们在多个预先定义的 TQIP 患者队列中的相关性。根据每个指数的衰弱评分对并发症进行分层。创建多变量逻辑回归模型，以调整年龄、格拉斯哥昏迷评分和损伤严重程度评分，以评估每个 mFI 与任何并发症和出院处置（家庭、设施和死亡）的关联。
共有 8467 名患者。除了老年人、老年人钝性多系统和孤立性髋部骨折外，所有患者队列的 Spearman ρ 均>0.9（P<0.0001）。两个 mFI 的衰弱评分增加与急性肾损伤（AKI）（P<0.0001）、心肌梗死（P<0.001）、严重脓毒症（P<0.05）、计划外返回重症监护病房（P<0.0001）和计划外插管（P<0.0001）的发生率增加相关。在单独的多变量逻辑回归中，mFI-5 和 mFI-11 均与任何并发症（P<0.0001）和设施出院（P<0.001）相关。mFI-5 和 mFI-11 均与死亡率（P>0.05）无关。
mFI-5 和 mFI-11 在多个 TQIP 患者队列中高度相关。它们也都可以预测并发症和出院处置；然而，两个指数都不能预测死亡率。鉴于其易用性，mFI-5 可能是在创伤护理点识别脆弱患者和预测不良结局的更好选择。
