瓣膜手术患者出血风险的预测因素。

Arquivos brasileiros de cardiologia Pub Date : 2024-10-18 eCollection Date: 2024-01-01 DOI:10.36660/abc.20230453
Alef de Carvalho Vieira, Renato Tambellini Arnoni, Ana Beatriz Silva Barbosa, Attila Santos Berriel, Rafael Guimarães Vianna, Mario Issa
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引用次数: 0

摘要

背景:心脏瓣膜手术术后因出血风险而具有挑战性,出血会导致并发症,增加发病率和死亡率:方法:对 2021 年至 2022 年期间接受手术的患者进行回顾性研究:方法:对 2021 年至 2022 年期间接受手术的患者进行回顾性研究。根据 BARC 和 Bojar 标准筛选出大出血患者。对与出血相关的因素进行了逻辑回归分析,并绘制了评分提名图。统计结果显示,PResults:分析了 525 名患者,平均年龄 56 岁,女性居多。最常见的瓣膜疾病是二尖瓣关闭不全,8.8%的患者出血量增加,4.3%的患者进行过外科再手术。具有统计学意义的变量是三尖瓣关闭不全(OR 3.31,P < 0.001)、慢性肾病/急性肾损伤(OR 2.97,P = 0.006)、术前血红蛋白(OR 0.73,p<0.001)、再次手术(OR 2,5,p=0.003)、心肺旁路(CPB)时间(OR 1.12,p<0.001)、2瓣膜方法OR 2.23(p=0.013)、使用包装红细胞OR 2.8(p=0.001)。在多重模型中,三尖瓣关闭不全、CPB 时间和术前血红蛋白具有统计学意义:结论:CPB 时间、术前血红蛋白和三尖瓣关闭不全与术后出血密切相关。建议的量表是可信的,有助于预测出血风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Predictive Factors for Bleeding Risk in Patients Undergoing Valvular Surgery.

Background: The postoperative period of heart valve surgery is challenging due to the risk of bleeding, leading to complications and increased morbidity and mortality.

Objective: To develop a risk score to predict bleeding in patients after valve surgery.

Methods: Retrospective study of patients operated on between 2021 and 2022. Patients with major bleeding were selected based on the BARC and Bojar criteria. A logistic regression analysis was performed for factors related to bleeding and a nomogram of scores was created. For statistical significance, p<0.05 and a 95% confidence interval were considered. The study was approved by the CEP.

Results: 525 patients were analyzed, with a mean age of 56 years and a predominance of females. The most common valve disease was mitral insufficiency, 8.8% had increased bleeding and 4.3% had surgical reoperations. The variables with statistical significance were tricuspid insufficiency (OR 3.31, p < 0.001), chronic kidney disease/acute kidney injury (OR 2.97, p = 0.006), preoperative hemoglobin (OR 0.73, p < 0.001), reoperations (OR 2, 5, p = 0.003), cardiopulmonary bypass (CPB) time (OR 1.12, p < 0.001), 2-valve approach OR of 2.23 (p = 0.013), use of packed red blood cells OR of 2.8 (p = 0.001). In the multiple model, tricuspid insufficiency, CPB time and preoperative hemoglobin reached statistical significance.

Conclusion: CPB time, preoperative hemoglobin and tricuspid insufficiency were independently associated with postoperative bleeding. The proposed scale is plausible and can help predict the risk of bleeding.

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