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Su1016 Risk Factors for Post-Operative Respiratory Failure in Liver Transplant Recipients

医学 射血分数 肺活量 DLCO公司 重症监护室 优势比 心脏病学 单变量分析 肝移植 内科学 外科 移植 心力衰竭 多元分析 扩散能力 肺功能
作者
Bryan A. Morse,Mark R. Pedersen,Laya Nasrollah,Mona Choi,Anil B. Seetharam
出处
期刊:Gastroenterology [Elsevier]
卷期号:148 (4): S-1039
标识
DOI:10.1016/s0016-5085(15)33546-0
摘要

Rationale: Post-operative respiratory failure (PRF) is a common complication after liver transplant (LT).PRF leads to increased length of intensive care unit (ICU) and hospital stay and predisposes to increased morbidity in the post-operative period.Further investigation is needed to identify risk factors for PRF in LT recipients.Aim: To evaluate pre-operative cardiopulmonary testing, recipient, donor, and surgical variables and their utility in prediction of PRF after LT.Methods: Retrospective case-control study performed on LT recipients from 2010-2012.Post-operative course was reviewed to evaluate for cases of PRF, defined as failure to extubate before or unplanned re-intubation within 48 hours from completion of LT surgery.Pre transplant recipient demographic characteristics were recorded.Donor and surgical characteristics including: simultaneous kidney transplant, cytomegalovirus (CMV) status, gender, donor source (deceased or living), age, warm and cold ischemic times were assessed.Pre-transplant cardiopulmonary testing examined included: the presence or absence of heart failure, diastolic dysfunction, left ventricular ejection fraction, right ventricular systolic pressure, forced expiratory volume in one second to forced vital capacity ratio (FEV1/ FVC), forced vital capacity (FVC), total lung capacity (TLC), forced expiratory volume in one second ( FEV1), and diffusion limit of carbon monoxide (DLCO).Variables of interest were analyzed using univariate logistic regression with an end point of PRF.Factors deemed most significant (p < 0.25) in predicting PRF were included in a multivariate regression analysis to estimate adjusted odds ratios (OR) for each variable.Variables with p < 0.05 were considered significant predictors of PRF in the final model.Results: A total of 170 patients were identified.Of those, 23.7% experienced PRF.Significant predictors including pre-transplant MELD, pre-operative respiratory failure, FVC <80%, FEV1 <80%, TLC <80%, and deceased donor source from univariate logistic regression [Table 1] were entered into multivariate logistic regression.In the final model, pre-operative respiratory failure (OR= 161.48, p = 0.002) was found to be predictive of PRF, in a model that explained 26.3 to 41.7% of variance [Table 2].Conclusions: Pre-operative respiratory failure from any etiology was identified as a significant predictor of PRF after LT.Pre-LT echocardiogram and pulmonary function testing had no predictive value for PRF.These findings support the development of protocols to aggressively wean ventilatory support immediately prior to LT. Univariate Analysis:
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