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常用指标预测根治性膀胱切除术不良结局的判别能力:人口统计学数据、美国麻醉医师协会、改良 Charlson 合并症指数和改良衰弱指数的比较。

Discriminative Ability of Commonly Used Indexes to Predict Adverse Outcomes After Radical Cystectomy: Comparison of Demographic Data, American Society of Anesthesiologists, Modified Charlson Comorbidity Index, and Modified Frailty Index.

机构信息

Department of Urology, NYU Langone Health, New York, NY.

Department of Medicine, Rutgers New Jersey Medical School, Newark, NJ.

出版信息

Clin Genitourin Cancer. 2018 Aug;16(4):e843-e850. doi: 10.1016/j.clgc.2018.02.009. Epub 2018 Feb 26.

Abstract

BACKGROUND

The American Society of Anesthesiologists physical status classification system, modified Charlson Comorbidity Index (mCCI), and modified Frailty Index have been associated with complications after urologic surgery. No study has compared the predictive performance of these indexes for postoperative complications after radical cystectomy (RC) for bladder cancer.

MATERIALS AND METHODS

Data from 1516 patients undergoing elective RC for bladder cancer were extracted from the 2005 to 2011 American College of Surgeons National Surgical Quality Improvement Program for a retrospective review. The perioperative outcome variables assessed were occurrence of minor adverse events, severe adverse events, infectious adverse events, any adverse event, extended length of hospital stay, discharge to a higher level of care, and mortality. Patient comorbidity indexes and demographic data were assessed for their discriminative ability in predicting perioperative adverse outcomes using an area under the curve (AUC) analysis from the receiver operating characteristic curves.

RESULTS

The most predictive comorbidity index for any adverse event was the mCCI (AUC, 0.511). The demographic factors were the body mass index (BMI; AUC, 0.519) and sex (AUC, 0.519). However, the overall performance for all predictive indexes was poor for any adverse event (AUC < 0.52). Combining the most predictive demographic factor (BMI) and comorbidity index (mCCI) resulted in incremental improvements in discriminative ability compared with that for the individual outcome variables.

CONCLUSION

For RC, easily obtained patient mCCI, BMI, and sex have overall similar discriminative abilities for perioperative adverse outcomes compared with the tabulated indexes, which are more difficult to implement in clinical practice. However, both the demographic factors and the comorbidity indexes had poor discriminative ability for adverse events.

摘要

背景

美国麻醉医师协会身体状况分类系统、改良 Charlson 合并症指数(mCCI)和改良衰弱指数与泌尿外科手术后并发症相关。尚无研究比较这些指数在预测膀胱癌根治性膀胱切除术(RC)术后并发症方面的预测性能。

材料与方法

从 2005 年至 2011 年美国外科医师学会国家手术质量改进计划中提取了 1516 例接受择期 RC 治疗膀胱癌的患者数据进行回顾性研究。评估的围手术期结局变量包括轻微不良事件、严重不良事件、感染性不良事件、任何不良事件、延长住院时间、转至更高水平的护理以及死亡率。使用受试者工作特征曲线下面积(AUC)分析评估患者合并症指数和人口统计学数据对预测围手术期不良结局的区分能力。

结果

预测任何不良事件的最具预测性的合并症指数是 mCCI(AUC,0.511)。人口统计学因素是体重指数(BMI;AUC,0.519)和性别(AUC,0.519)。然而,对于所有预测指数,所有不良事件的整体性能均较差(AUC<0.52)。与单独的结局变量相比,将最具预测性的人口统计学因素(BMI)和合并症指数(mCCI)相结合可提高区分能力。

结论

对于 RC,易于获得的患者 mCCI、BMI 和性别在预测围手术期不良结局方面与列表中的指数具有相似的区分能力,而列表中的指数在临床实践中更难实施。然而,人口统计学因素和合并症指数对不良事件的区分能力均较差。

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