Abstract 14177: Gender Disparities in Failure to Rescue After Cardiac Surgeries

Circulation(2021)

引用 0|浏览0
暂无评分
摘要
Introduction: Women have a higher risk of mortality than men after cardiac surgery, independent of other risk factors. Death after postoperative complications, known as “failure to rescue (FTR)”, is a nationally endorsed quality care metric. This study was designed to evaluate differences in FTR after cardiac surgery in women and men. Methods: In this retrospective analysis, post-operative outcomes of 30,973 men (70.4%) and 13,033 women (29.6%) aged over 18 years undergoing coronary bypass or valve surgery identified from statewide administrative data from New York (2016-2019) and California (2016-2018) who experienced at least one serious postoperative complication, were compared according to gender. The primary outcome was FTR. Multivariable logistic regression was used to identify independent predictors of death after complication. Propensity matching was used to adjust for baseline differences between genders and yielded 12,608 pairs. Results: Women were older (mean age 67.8 vs 66.6, P<0.001), more frail (median frailty score 0.1 vs 0.07, P<0.001) and had more comorbidities (median Charlson score 2.5 vs 2.3, p<0.001) than men. The overall FTR rate was 5.7% (2,524 of 44,006). Men were less likely to die after a complication than women (4.8% vs 8%, P<0.001). Independent predictors of FTR included female gender, age≥75 years, higher Charlson comorbidity score, and higher number of postoperative complications (Figure). In the propensity matched cohort, FTR was significantly lower among men than women (5.7% vs 7.9%, P<0.001). This difference in FTR was mainly driven by the difference in FTR after respiratory failure, bleeding, myocardial infarction, shock, and acute kidney failure. Conclusion: Women are more likely to die following complications after cardiac surgery, independent of clinical and socioeconomic characteristics, than men. Clinical practices contributing to this disparity may be an appropriate target for quality improvement.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要