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Ann Thorac Surg 2010;90:368-374. doi:10.1016/j.athoracsur.2010.03.100
© 2010 The Society of Thoracic Surgeons
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Mark Onaitis
Thomas D'Amico
Sean O'Brien
David Harpole
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Right arrow Lung - cancer
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Original Articles: General Thoracic

Risk Factors for Atrial Fibrillation After Lung Cancer Surgery: Analysis of The Society of Thoracic Surgeons General Thoracic Surgery Database

Mark Onaitis, MDa,*, Thomas D'Amico, MDa, Yue Zhao, PhDb, Sean O'Brien, PhDb, David Harpole, MDa

a Department of Surgery, Duke University, Durham, North Carolina
b Duke Clinical Research Institute, Durham, North Carolina

Accepted for publication March 26, 2010.

* Address correspondence to Dr Onaitis, Department of Surgery, Duke University, DUMC Box 3305, Durham, NC 27710 (Email: mark.onaitis{at}duke.edu).

Presented at the Forty-sixth Annual Meeting of The Society of Thoracic Surgeons, Fort Lauderdale, FL, Jan 25–27, 2010.

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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