多中心数据库中 CABG 术后 30 天再住院的预测因素:一项横断面研究。

Arquivos brasileiros de cardiologia Pub Date : 2024-09-06 eCollection Date: 2024-01-01 DOI:10.36660/abc.20230768
Rene Augusto Gonçalves E Silva, Gabrielle Barbosa Borgomoni, Fabiane Letícia de Freitas, Adnaldo da Silveira Maia, Cleóstones Farias do Vale Junior, Eva da Silva Pereira, Leonardy Guilherme Ibrahim Silvestre, Luís Roberto Palma Dallan, Luiz Augusto Lisboa, Luís Alberto Oliveira Dallan, Fabio Biscegli Jatene, Omar Asdrúbal Vilca Mejia
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引用次数: 0

摘要

背景:分析再入院率等指标对于提高服务质量和医院流程管理至关重要:确定与冠状动脉旁路移植术(CABG)术后 30 天内再入院相关的变量:2017年6月至2019年6月,通过REPLICCAR II数据库(N=3392)进行横断面队列研究。采用单变量和多变量逻辑回归对150名患者进行回顾性分析,以确定与CABG术后30天内再入院相关的因素。分析使用 R 软件进行,显著性水平为 0.05,置信区间为 95%:在 3,392 例患者中,有 150 例(4,42%0)在 CABG 术后 30 天内再次入院,主要原因是感染(纵隔炎、手术伤口和败血症),占 52 例(34.66%)。其他原因包括手术并发症(14/150,9.33%)和肺炎(13/150,8.66%)。多变量回归模型发现了一个截距(OR:1.098,p 结论:4.42%的患者被误读为脓毒症:4.42%的患者在心血管造影术后再次入院,主要是由于感染。睡眠呼吸暂停(OR:1.117,p=0.0165)、心律失常(OR:1.040,p=0.0712)和主动脉内球囊泵的使用(OR:1.068,p=0.0021)等因素是再入院的预测因素,风险辨别度适中(AUC:0.70)。
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Predictors of 30-Day Hospital Readmission Following CABG in a Multicenter Database: A Cross-Sectional Study.

Background: The analysis of indicators such as hospital readmission rates is crucial for improving the quality of services and management of hospital processes.

Objectives: To identify the variables correlated with hospital readmission up to 30 days following coronary artery bypass grafting (CABG).

Methods: Cross-sectional cohort study by REPLICCAR II database (N=3,392) from June 2017 to June 2019. Retrospectively, 150 patients were analyzed to identify factors associated with hospital readmission within 30 days post-CABG using univariate and multivariate logistic regression. Analysis was conducted using software R, with a significance level of 0.05 and 95% confidence intervals.

Results: Out of 3,392 patients, 150 (4,42%0 were readmitted within 30 days post-discharge from CABG primarily due to infections (mediastinitis, surgical wounds, and sepsis) accounting for 52 cases (34.66%). Other causes included surgical complications (14/150, 9.33%) and pneumonia (13/150, 8.66%). The multivariate regression model identified an intercept (OR: 1.098, p<0.00001), sleep apnea (OR: 1.117, p=0.0165), cardiac arrhythmia (OR: 1.040, p=0.0712), and intra-aortic balloon pump use (OR: 1.068, p=0.0021) as predictors of the outcome, with an AUC of 0.70.

Conclusion: 4.42% of patients were readmitted post-CABG, mainly due to infections. Factors such as sleep apnea (OR: 1.117, p=0.0165), cardiac arrhythmia (OR: 1.040, p=0.0712), and intra-aortic balloon pump use (OR: 1.068, p=0.0021) were predictors of readmission, with moderate risk discrimination (AUC: 0.70).

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