Can we predict morbidity and mortality before an operation?
Estimation of perioperative morbidity and mortality has been the subject of numerous studies in patients undergoing major lung resection. Multivariate models have been developed with the goal of improving patient selection for surgery, especially with recent impetus for systems-based quality improvement and a need to provide high-quality data for evidence-based decision making for high-risk patients. This article explores relationships between the variables studied and predictors of outcome, and discusses if it is ever possible to accurately predict risk of morbidity and mortality after major lung resection.
Department of Surgery, The University of Chicago Medicine, The University of Chicago, 5841 South Maryland Avenue, MC 6040, Chicago, IL 60637, USA.
Sabha
S
Ganai
Mark K
MK
Ferguson
D000368:Aged; D006801:Humans; D008175:Lung Neoplasms / Q000601:surgery*; D008875:Middle Aged; D009017:Morbidity; D011013:Pneumonectomy / Q000009:adverse effects / Q000401:mortality / Q000706:statistics & numerical data*; D011183:Postoperative Complications / Q000453:epidemiology / Q000401:mortality; D018570:Risk Assessment
Complications; Lung resection; Morbidity; Mortality; Prediction; Thoracic