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术前量表预测冠状动脉旁路手术后全因再入院。

Preoperative Scale to Determine All-Cause Readmission After Coronary Artery Bypass Operations.

机构信息

Department of Surgery, Morristown Medical Center, Morristown, New Jersey.

Department of Surgery, Robert Wood Johnson Barnabas Health, Newark Beth Israel, Saint Barnabas Medical Center, Newark and Livingston, New Jersey.

出版信息

Ann Thorac Surg. 2018 Apr;105(4):1086-1093. doi: 10.1016/j.athoracsur.2017.11.062. Epub 2017 Dec 27.

Abstract

BACKGROUND

Coronary artery bypass graft (CABG) operations are associated with all-cause readmission rates of approximately 15%. In attempts to reduce readmission rates, the Hospital Readmission Reduction Program expanded to include CABG operations in 2015. The aim of this study was therefore to develop a predictive readmission scale that would identify patients at higher risk of readmission after CABG using commonly available administrative data.

METHODS

Data of 126,519 patients from California and New York (derivation cohort) and 94,318 patients from Florida and Washington (validation cohort) were abstracted from the State Inpatient Database (2006 to 2011). The readmission after CABG scale was developed to predict 30-day readmission risk and was validated against a separate cohort.

RESULTS

Thirty-day CABG readmission rates were 23% in the derivation cohort and 21% in the validation cohort. Predictive factors included older age, female gender (odds ratio [OR], 1.34), African American ethnicity (OR, 1.13), Medicare or Medicaid insurance, and comorbidities, including renal failure (OR, 1.56) and congestive heart failure (OR, 2.82). These were independently predictive of increased readmission rates (p < 0.01). The readmission scale was then created with these preoperative factors. When applied to the validation cohort, it explained 98% of the readmission variability.

CONCLUSIONS

The readmission after CABG scale reliably predicts a patient's 30-day CABG readmission risk. By identifying patients at high-risk for readmission before their procedure, risk reduction strategies can be implemented to reduce readmissions and healthcare expenditures.

摘要

背景

冠状动脉旁路移植术(CABG)的全因再入院率约为 15%。为了降低再入院率,医院再入院率降低计划于 2015 年扩大到包括 CABG 手术。因此,本研究旨在开发一种预测再入院的量表,该量表使用常用的行政数据识别 CABG 后再入院风险较高的患者。

方法

从加利福尼亚州和纽约州(推导队列)的 126519 名患者和佛罗里达州和华盛顿州(验证队列)的 94318 名患者的数据中提取了来自州内住院患者数据库(2006 年至 2011 年)。建立了 CABG 后再入院量表,以预测 30 天再入院风险,并与另一队列进行了验证。

结果

推导队列中 30 天 CABG 再入院率为 23%,验证队列中为 21%。预测因素包括年龄较大、女性(优势比[OR],1.34)、非裔美国人(OR,1.13)、医疗保险或医疗补助保险以及合并症,包括肾衰竭(OR,1.56)和充血性心力衰竭(OR,2.82)。这些因素独立预测再入院率增加(p < 0.01)。然后使用这些术前因素创建再入院量表。当应用于验证队列时,它解释了 98%的再入院变异性。

结论

CABG 后再入院量表可靠地预测患者 30 天 CABG 再入院风险。通过在手术前识别出高再入院风险的患者,可以实施降低风险的策略,以降低再入院率和医疗保健支出。

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