TY - JOUR
T1 - Risk factors for atrial fibrillation after lung cancer surgery
T2 - Analysis of the society of thoracic surgeons general thoracic surgery database
AU - Decamp, Malcolm M.
AU - Onaitis,
AU - Detterbeck, Frank C.
PY - 2010/8
Y1 - 2010/8
N2 - Background: Atrial fibrillation is responsible for significant morbidity after lung cancer surgery, and preoperative and perioperative risk factors are not well described. Methods: The Society of Thoracic Surgeons (STS) database was queried for all lobectomy and pneumonectomy patients with a diagnosis of lung cancer. A multivariable logistic regression model was developed to predict the risk of atrial arrhythmia as a function of preoperative and perioperative factors. Generalized estimating equations methodology was used to account for correlation among observations from the same institution. Missing data were handled using the method of chained equations with 10 randomly imputed data sets. Results: A total of 13,906 patients who underwent resection for lung cancer at participating institutions had complete information for postoperative atrial arrhythmia, of whom 1,755 (12.6%) experienced the outcome. Multivariable logistic analysis indentified increasing age, increasing extent of operation, male sex, nonblack race, and stage II or greater tumors as predictors of postoperative atrial fibrillation. Conclusions: Analysis of the STS database has identified five variables that predict postoperative atrial fibrillation. This predictive model may be useful to develop strategies for risk stratification, prophylaxis, and treatment.
AB - Background: Atrial fibrillation is responsible for significant morbidity after lung cancer surgery, and preoperative and perioperative risk factors are not well described. Methods: The Society of Thoracic Surgeons (STS) database was queried for all lobectomy and pneumonectomy patients with a diagnosis of lung cancer. A multivariable logistic regression model was developed to predict the risk of atrial arrhythmia as a function of preoperative and perioperative factors. Generalized estimating equations methodology was used to account for correlation among observations from the same institution. Missing data were handled using the method of chained equations with 10 randomly imputed data sets. Results: A total of 13,906 patients who underwent resection for lung cancer at participating institutions had complete information for postoperative atrial arrhythmia, of whom 1,755 (12.6%) experienced the outcome. Multivariable logistic analysis indentified increasing age, increasing extent of operation, male sex, nonblack race, and stage II or greater tumors as predictors of postoperative atrial fibrillation. Conclusions: Analysis of the STS database has identified five variables that predict postoperative atrial fibrillation. This predictive model may be useful to develop strategies for risk stratification, prophylaxis, and treatment.
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U2 - 10.1016/j.athoracsur.2010.03.100
DO - 10.1016/j.athoracsur.2010.03.100
M3 - Article
C2 - 20667313
AN - SCOPUS:77955687064
SN - 0003-4975
VL - 90
SP - 368
EP - 374
JO - Annals of Thoracic Surgery
JF - Annals of Thoracic Surgery
IS - 2
ER -