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. 2015 Feb;99(2):482-9.
doi: 10.1016/j.athoracsur.2014.09.038. Epub 2014 Dec 18.

Preoperative performance status impacts perioperative morbidity and mortality after lung transplantation

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Preoperative performance status impacts perioperative morbidity and mortality after lung transplantation

Joshua C Grimm et al. Ann Thorac Surg. 2015 Feb.

Abstract

Background: The aim of this study was to determine which factors predict poor postoperative performance and to evaluate the impact of these variables on 1-year mortality.

Methods: The United Network for Organ Sharing database was queried for adult patients undergoing lung transplantation (LTx) from 2007 to 2011. Patients were divided based on their preoperative Karnofsky Performance Status score (KPS) into 3 groups. Regression analysis was conducted to determine which factors predicted poor postoperative performance. Cox modeling was utilized to identify which of these factors was associated with an increased risk of mortality after LTx.

Results: Of the 7,832 patients included in this study, 30.1% required complete assistance, 57.7% required partial assistance, and 12.3% needed no assistance preoperatively. Postoperative KPS was assessed at a mean of 2.6 ± 1.5 years after transplant. A number of factors, including primary graft failure, redo and single LTx, and intensive care unit status prior to LTx independently predicted poor performance; whereas a body mass index 18.5 kg/m(2) or greater and some degree of preoperative functional independence were protective. Age greater than 60 years, donor tobacco use, and intensive care unit status, extracorporeal membrane oxygenation support, and mechanical ventilation prior to LTx were associated with an increased risk 1-year mortality, while preoperative functional independence and a body mass index 18.5 to 30 kg/m(2) were protective.

Conclusions: This is the largest known study to examine the issue of disability in LTx and its relationship to mortality. Preoperative performance status significantly impacts post-LTx mortality. Patient optimization may improve outcomes and should alter decisions regarding graft selection and allocation.

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