
A A Novel Risk Score to Predict New Onset Atrial Fibrillation in Patients Undergoing Isolated Coronary Artery Bypass Grafting
Author(s) -
Sophie Lin,
Todd C. Crawford,
Alejandro SuarezPierre,
J. Trent Magruder,
Michael V. Carter,
Duke E. Cameron,
Glenn J.R. Whitman,
Jennifer S. Lawton,
William A. Baumgartner,
Kaushik Mandal
Publication year - 2018
Publication title -
the heart surgery forum/the heart surgery forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.255
H-Index - 38
eISSN - 1522-6662
pISSN - 1098-3511
DOI - 10.1532/hsf.2151
Subject(s) - medicine , atrial fibrillation , cardiology , derivation , logistic regression , cohort , incidence (geometry) , odds ratio , framingham risk score , risk factor , coronary artery bypass surgery , artery , physics , disease , optics
Background: Atrial fibrillation (AF) is common after cardiac surgery and contributes to increased morbidity and mortality. Our objective was to derive and validate a predictive model for AF after CABG in patients, incorporating novel echocardiographic and laboratory values.
Methods: We retrospectively reviewed patients at our institution without preexisting dysrhythmia who underwent on-pump, isolated CABG from 2011-2015. The primary outcome was new onset AF lasting >1 hour on continuous telemetry or requiring medical treatment. Patients with a preoperative echocardiographic measurement of left atrial diameter were included in a risk model, and were randomly divided into derivation (80%) and validation (20%) cohorts. The predictors of AF after CABG (PAFAC) score was derived from a multivariable logistic regression model by multiplying the adjusted odds ratios of significant risk factors (P < .05) by a factor of 4 to derive an integer point system.
Results: 1307 patients underwent isolated CABG, including 762/1307 patients with a preoperative left atrial diameter measurement. 209/762 patients (27%) developed new onset AF including 165/611 (27%) in the derivation cohort. We identified four risk factors independently associated with postoperative AF which comprised the PAFAC score: age > 60 years (5 points), White race (5 points), baseline GFR 4.5 cm (4 points). Scores ranged from 0-18. The PAFAC score was then applied to the validation cohort and predicted incidence of AF strongly correlated with observed incidence (r = 0.92).
Conclusion: The PAFAC score is easy to calculate and can be used upon ICU admission to reliably identify patients at high risk of developing AF after isolated CABG.