Predicting Extended Intensive Care Unit Stay Following Coronary Artery Bypass Grafting and Its Impact on Hospitalization and Mortality.

IF 2 Q2 MEDICINE, GENERAL & INTERNAL Journal of clinical medicine research Pub Date : 2025-01-01 Epub Date: 2024-12-31 DOI:10.14740/jocmr6024
Nizar R Alwaqfi, Majd M AlBarakat, Walid K Hawashin, Hala R Qariouti, Ayah J Alkrarha, Rana B Altawalbeh
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Abstract

Background: Coronary artery bypass grafting (CABG) is a prevalent surgical procedure aimed at alleviating symptoms and improving survival in patients with coronary artery disease (CAD). Postoperative care typically necessitates an intensive care unit (ICU) stay, which is ideally less than 24 h. However, various preoperative, intraoperative, and postoperative factors can prolong ICU stays, adversely affecting hospital resources, patient outcomes, and overall healthcare costs. This study investigates the factors contributing to prolonged ICU stay (> 48 h) following CABG and CABG combined with valve surgery, and examines the associated impacts on complications and mortality.

Methods: This retrospective cohort study analyzed 1,395 patients who underwent isolated CABG or CABG combined with heart valve surgery at King Abdullah University Hospital (KAUH) between January 2004 and December 2022. Patients were categorized into two groups: those with ICU stays ≤ 48 h (group 1, n = 1,082) and those with ICU stays > 48 h (group 2, n = 313). Clinical, laboratory, and demographic data were collected and evaluated to identify risk factors for prolonged ICU stays.

Results: Patients in group 2 were older, with a mean age of 61.5 years compared to 58.7 years in group 1 (P < 0.001). Significant predictors of prolonged ICU stay included preoperative conditions such as recent myocardial infarction (odds ratio (OR) = 1.69, P = 0.015), chronic obstructive pulmonary disease or asthma (OR = 1.49, P = 0.003), and preoperative renal impairment (OR = 1.89, P = 0.002). Intraoperative factors such as emergency or urgent procedures (OR = 2.19, P < 0.001) and prolonged ventilator support (OR = 5.92, P < 0.001) were also significant. Postoperative complications, including renal impairment (OR = 6.78, P < 0.001) and pneumonia or sepsis (OR = 8.92, P < 0.001), were strongly associated with extended ICU stays.

Conclusions: Prolonged ICU stays are indicative of patients with more severe baseline conditions, greater surgical complexity, and higher rates of postoperative complications, which collectively contribute to increased risks of severe adverse outcomes and mortality. Prolonged ICU stays after CABG are strongly associated with preoperative comorbidities, intraoperative challenges, and postoperative complications, leading to increased mortality and significant healthcare resource utilization. Identifying these risk factors and implementing targeted strategies to address them can help minimize ICU stay durations, improve patient outcomes, and enhance the efficiency of cardiac surgery care. Future research should focus on refining predictive models and optimizing perioperative management to further reduce the burden of prolonged ICU stays on healthcare systems.

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预测冠状动脉搭桥术后延长重症监护病房时间及其对住院率和死亡率的影响。
背景:冠状动脉旁路移植术(CABG)是一种流行的外科手术,旨在减轻冠状动脉疾病(CAD)患者的症状和提高生存率。术后护理通常需要重症监护室(ICU)住院,理想情况下不超过24小时。然而,术前、术中和术后的各种因素可能延长ICU住院时间,对医院资源、患者预后和总体医疗成本产生不利影响。本研究探讨了冠状动脉搭桥及冠状动脉搭桥合并瓣膜手术后延长ICU住院时间(bbb48 h)的因素,并探讨了相关并发症和死亡率的影响。方法:这项回顾性队列研究分析了2004年1月至2022年12月在阿卜杜拉国王大学医院(KAUH)接受孤立CABG或CABG联合心脏瓣膜手术的1395例患者。将患者分为两组:ICU住院≤48 h组(1组,n = 1082)和ICU住院≤48 h组(2组,n = 313)。收集并评估临床、实验室和人口统计数据,以确定延长ICU住院时间的危险因素。结果:2组患者年龄较大,平均年龄为61.5岁,而1组为58.7岁(P < 0.001)。延长ICU住院时间的重要预测因素包括术前条件,如近期心肌梗死(优势比(OR) = 1.69, P = 0.015)、慢性阻塞性肺疾病或哮喘(OR = 1.49, P = 0.003)和术前肾功能损害(OR = 1.89, P = 0.002)。术中因素如急诊或紧急手术(or = 2.19, P < 0.001)和延长呼吸机支持(or = 5.92, P < 0.001)也具有显著性。术后并发症,包括肾功能损害(OR = 6.78, P < 0.001)和肺炎或脓毒症(OR = 8.92, P < 0.001),与延长ICU住院时间密切相关。结论:ICU住院时间延长表明患者基线情况更严重,手术复杂性更高,术后并发症发生率更高,这些因素共同导致严重不良结局和死亡率的风险增加。CABG术后ICU住院时间延长与术前合并症、术中挑战和术后并发症密切相关,导致死亡率增加和显著的医疗资源利用率。识别这些危险因素并实施有针对性的策略来解决这些问题可以帮助缩短ICU住院时间,改善患者预后,提高心脏手术护理的效率。未来的研究应侧重于完善预测模型和优化围手术期管理,以进一步减轻医疗系统延长ICU住院的负担。
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