The prediction of postoperative stroke or death in patients with preoperative atrial fibrillation undergoing non-cardiac surgery: a VISION sub-study.
BACKGROUND
The optimal means of pre-operative risk stratification in patients with atrial fibrillation (AF) is uncertain.


OBJECTIVE
To examine the accuracy of AF thromboembolic risk models (the CHADS2, CHA2DS2-VASc, and R2CHADS2 scores) for predicting 30-day stroke and/or all-cause mortality after non-cardiac surgery in patients with preoperative AF, and to compare these risk scores with the Revised Cardiac Risk Index (RCRI).


METHODS
A multicentre (8 countries, 2007-2011) prospective cohort study of patients ≥ 45 years of age undergoing inpatient non-cardiac surgery, who were followed until 30 days after surgery. We calculated c-statistics for each risk prediction model and net reclassification improvements (NRIs) compared with the RCRI.


RESULTS
The 961 patients with preoperative AF were at higher risk of any cardiovascular event in the 30 days postoperatively compared with the 13 001 patients without AF: 26.6% vs. 9.0%; adjusted odds ratio, 1.58; 95% confidence interval [CI], 1.33-1.88. All thromboembolic risk scores predicted postoperative death just as well as the RCRI (with c-indices between 0.67 and 0.72). Compared with the RCRI (which had a c-index of 0.64 for 30-day stroke/death), the CHADS2 (c-index, 0.67; NRI, 0.31; 95% CI, 0.02-0.61) significantly improved postoperative stroke/mortality risk prediction, largely due to improved discrimination of patients who did not subsequently have an event.


CONCLUSIONS
In AF patients, the three thromboembolic risk scores performed similarly to the RCRI in predicting death within 30 days and the CHADS2 score was the best predictor of postoperative stroke/death regardless of type of surgery.
Patient Health Outcomes Research and Clinical Effectiveness Unit, Edmonton, AB, Canada.|Division of General Internal Medicine, Department of Medicine, Edmonton, AB, Canada.
F A
FA
McAlister
Division of Critical Care Medicine, Department of Medicine, Edmonton, AB, Canada.
M
M
Jacka
Division of Cardiology, Department of Medicine, Edmonton, AB, Canada.
M
M
Graham
Patient Health Outcomes Research and Clinical Effectiveness Unit, Edmonton, AB, Canada.
E
E
Youngson
Division of Medical Biochemistry, Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, AB, Canada.
G
G
Cembrowski
Division of Critical Care Medicine, Department of Medicine, Edmonton, AB, Canada.
S M
SM
Bagshaw
Division of Critical Care Medicine, Department of Medicine, Edmonton, AB, Canada.
N
N
Pannu
Division of Critical Care Medicine, Department of Medicine, Edmonton, AB, Canada.
D R
DR
Townsend
Department of Surgery, University of Manitoba, Winnipeg, MB, Canada.
S
S
Srinathan
Iberoamerican Cochrane Center, Biomedical Research Institute Sant Pau (IIB-Sant Pau), CIBER de Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
P
P
Alonso-Coello
Departments of Clinical Epidemiology and Biostatistics and Medicine, The Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.
P J
PJ
Devereaux
D000368:Aged; D000369:Aged, 80 and over; D001281:Atrial Fibrillation / Q000150:complications* / Q000175:diagnosis / Q000401:mortality; D003661:Decision Support Techniques; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D018579:Patient Selection; D011237:Predictive Value of Tests; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D020521:Stroke / Q000175:diagnosis / Q000209:etiology* / Q000401:mortality; D013514:Surgical Procedures, Operative / Q000009:adverse effects* / Q000401:mortality; D013997:Time Factors; D016896:Treatment Outcome
atrial fibrillation; data interpretation, statistical; decision support techniques; preoperative care; risk assessment