评估85岁以上心脏手术患者生存预后因素的Cox比例模型

Corona Alberto, Catena Emanuele, Savi Claudio Federico
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引用次数: 0

摘要

引言:“越来越多的80多岁老人(0岁以上)和80多岁老人(> 0岁)易接受心脏手术,这引发了对这些患者使用有限的重症监护资源的有用性和机会的伦理和经济反思。方法:本研究的主要终点是通过建立Cox比例风险模型来强调(O)和(>O)患者术后和ICU死亡率的差异。结果:6.9%的研究人群年龄在85岁及以上;85岁以上亚组(≥85岁)889例,85岁以下亚组11966例。在85岁以上的人群中,住院死亡率明显更高(+4.3%)。与术后85年以上住院生存率显著相关的因素。发现:(i)男性、动脉疾病、慢性阻塞性肺病、主动脉和二尖瓣病变;(ii)不稳定型心绞痛与常见主干梗阻的相互作用,CCS量表值;(iii) RBC和FFP输注,以及总失血量;(iv)术后感染性休克、急性肾功能衰竭、脑中风、机械通气、呼吸机相关性肺炎和气管切开术。结论:我们的数据表明了年龄变量的重要性,以及这两个人群截然不同的事实。进一步和未来的多变量分析将使用倾向评分匹配进行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Cox’s Proportional Model to Assess Survival Prognostic Factors in Patients Over 85 Years of Age Undergoing Heart Surgery
Introduction: “The progressive and growing prevalence of octuagenarians (O) and over-octuagenarians (>O), susceptible to cardiac surgery has generated an ethical and economic reflection on the usefulness and opportunity to use the limited resources of intensive care for these patients. Methods: The primary end point of the study has been highlight any difference in post-operative and ICU mortality between patients (O) and (>O) by setting a Cox’s proportional hazard model. Results: The 6.9% of the population studied were 85 years of age or older; therefore the over 85 yrs sub-group (≥ 85 yrs.) was 889 patients and the under 85 yrs sub-group 11966. Hospital mortality was found to be significantly higher (+4.3%) in the over 85 yrs. Factors significantly associated with postoperative hospital survival of over 85 yrs. were found to be: (i) male gender, arterial disease, COPD, pathology of the aortic and mitral valve; (ii) interaction unstable angina and common trunk obstruction, the value of the CCS scale; (iii) RBC and FFP transfusions, together with total blood loss; (iv) post-operative septic shock, acute renal failure, cerebral stroke, mechanical ventilation, ventilator associated pneumonia, and tracheostomy. Conclusions: Our data suggest the importance of the age variable as well as the fact that the two populations are distinct and different. A further and future multivariate analysis will be conducted with the use of propensity score matching.
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