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手术人群中测量衰弱的风险分析指数的开发与初步验证

Development and Initial Validation of the Risk Analysis Index for Measuring Frailty in Surgical Populations.

作者信息

Hall Daniel E, Arya Shipra, Schmid Kendra K, Blaser Casey, Carlson Mark A, Bailey Travis L, Purviance Georgia, Bockman Tammy, Lynch Thomas G, Johanning Jason

机构信息

Veterans Affairs Pittsburgh Healthcare System, Pittsburgh, Pennsylvania2University of Pittsburgh, Pittsburgh, Pennsylvania.

Atlanta Veterans Affairs Medical Center, Atlanta, Georgia4Emory University, Atlanta, Georgia.

出版信息

JAMA Surg. 2017 Feb 1;152(2):175-182. doi: 10.1001/jamasurg.2016.4202.

DOI:10.1001/jamasurg.2016.4202
PMID:27893030
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7140150/
Abstract

IMPORTANCE

Growing consensus suggests that frailty-associated risks should inform shared surgical decision making. However, it is not clear how best to screen for frailty in preoperative surgical populations.

OBJECTIVE

To develop and validate the Risk Analysis Index (RAI), a 14-item instrument used to measure surgical frailty. It can be calculated prospectively (RAI-C), using a clinical questionnaire, or retrospectively (RAI-A), using variables from the surgical quality improvement databases (Veterans Affairs or American College of Surgeons National Surgical Quality Improvement Projects).

DESIGN, SETTING, AND PARTICIPANTS: Single-site, prospective cohort from July 2011 to September 2015 at the Veterans Affairs Nebraska-Western Iowa Heath Care System, a Level 1b Veterans Affairs Medical Center. The study included all patients presenting to the medical center for elective surgery.

EXPOSURES

We assessed the RAI-C for all patients scheduled for surgery, linking these scores to administrative and quality improvement data to calculate the RAI-A and the modified Frailty Index.

MAIN OUTCOMES AND MEASURES

Receiver operator characteristics and C statistics for each measure predicting postoperative mortality and morbidity.

RESULTS

Of the participants, the mean (SD) age was 60.7 (13.9) years and 249 participants (3.6%) were women. We assessed the RAI-C 10 698 times, from which we linked 6856 unique patients to mortality data. The C statistic predicting 180-day mortality for the RAI-C was 0.772. Of these 6856 unique patients, we linked 2785 to local Veterans Affairs Surgeons National Surgical Quality Improvement Projects data and calculated the C statistic for both the RAI-A (0.823) and RAI-C (0.824), along with the correlation between the 2 scores (r = 0.478; P < .001). Of these 2785 patients, there were sufficient data to calculate the modified Frailty Index for 1021, in which the C statistics were 0.865 (RAI-A), 0.797 (RAI-C), and 0.811 (modified Frailty Index). The correlation between the RAI-A and RAI-C was 0.547, and the correlations of the modified Frailty Index to the RAI-A and RAI-C were 0.301 and 0.269, respectively (all P < .001). A cutoff of RAI-C of at least 21 classified 18.3% patients as "frail" with a sensitivity of 0.50 and specificity of 0.82, whereas the RAI-A was less sensitive (0.25) and more specific (0.97), classifying only 3.7% as "frail."

CONCLUSIONS AND RELEVANCE

The RAI-C and RAI-A represent effective tools for measuring frailty in surgical populations with predictive ability on par with other frailty tools. Moderate correlation between the measures suggests convergent validity. The RAI-C offers the advantage of prospective, preoperative assessment that is proved feasible for large-scale screening in clinical practice. However, further efforts should be directed at determining the optimal components of preoperative frailty assessment.

摘要

重要性

越来越多的共识表明,与衰弱相关的风险应指导手术共同决策。然而,目前尚不清楚如何在术前手术人群中最好地筛查衰弱。

目的

开发并验证风险分析指数(RAI),这是一种用于测量手术衰弱的14项工具。它可以通过临床问卷进行前瞻性计算(RAI-C),也可以使用手术质量改进数据库(退伍军人事务部或美国外科医师学会国家手术质量改进项目)中的变量进行回顾性计算(RAI-A)。

设计、地点和参与者:2011年7月至2015年9月在退伍军人事务部内布拉斯加州-爱荷华州西部医疗保健系统(一家1b级退伍军人事务部医疗中心)进行的单中心前瞻性队列研究。该研究纳入了所有到该医疗中心进行择期手术的患者。

暴露因素

我们对所有计划手术的患者评估了RAI-C,并将这些分数与行政和质量改进数据相关联,以计算RAI-A和改良衰弱指数。

主要结局和测量指标

每种测量指标预测术后死亡率和发病率的受试者工作特征曲线及C统计量。

结果

参与者的平均(标准差)年龄为60.7(13.9)岁,249名参与者(3.6%)为女性。我们对RAI-C进行了10698次评估,从中将6856名独特患者与死亡率数据相关联。RAI-C预测180天死亡率的C统计量为0.772。在这6856名独特患者中,我们将2785名患者与当地退伍军人事务部外科医生国家手术质量改进项目数据相关联,并计算了RAI-A(0.823)和RAI-C(0.824)的C统计量,以及两个分数之间的相关性(r = 0.478;P < 0.001)。在这2785名患者中,有足够的数据为1021名患者计算改良衰弱指数,其中C统计量分别为0.865(RAI-A)、0.797(RAI-C)和0.811(改良衰弱指数)。RAI-A与RAI-C之间的相关性为0.547,改良衰弱指数与RAI-A和RAI-C的相关性分别为0.301和0.269(均P < 0.001)。RAI-C至少为21的临界值将18.3%的患者分类为“衰弱”,敏感性为0.50,特异性为0.82,而RAI-A的敏感性较低(0.25),特异性较高(0.97),仅将3.7%的患者分类为“衰弱”。

结论及相关性

RAI-C和RAI-A是测量手术人群衰弱的有效工具,其预测能力与其他衰弱工具相当。测量指标之间的中度相关性表明具有收敛效度。RAI-C具有前瞻性术前评估的优势,已证明在临床实践中进行大规模筛查是可行的。然而,应进一步努力确定术前衰弱评估的最佳组成部分。

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