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1.
Anaesthesia ; 75(1): 27-36, 2020 Jan.
Article in English | MEDLINE | ID: mdl-31282570

ABSTRACT

It is unclear how best to predict peri-operative cardiovascular risk in patients with atrial fibrillation undergoing non-cardiac surgery. This study examined the accuracy of the revised cardiac risk index and three atrial fibrillation thrombo-embolic risk models for predicting 30-day cardiovascular events after non-cardiac surgery in patients with a pre-operative history of atrial fibrillation. We conducted a prospective cohort study in 28 centres from 2007 to 2013 of 40,004 patients ≥ 45 years of age undergoing inpatient non-cardiac surgery who were followed until 30 days after surgery for cardiovascular events (defined as myocardial injury, heart failure, stroke, resuscitated cardiac arrest or cardiovascular death). The 2088 patients with a pre-operative history of atrial fibrillation were at higher risk of peri-operative cardiovascular events compared with the 34,830 patients without a history of atrial fibrillation (29% vs. 13%, respectively, adjusted odds ratio 1.30 (95%CI 1.17-1.45). Compared with the revised cardiac risk index (c-index 0.60), all atrial fibrillation thrombo-embolic risk scores were significantly better at predicting peri-operative cardiovascular events: CHADS2 (c-index 0.62); CHA2 DS2 -VASc (c-index 0.63); and R2 CHADS2 (c-index 0.65), respectively. Although the three thrombo-embolic risk prediction models were significantly better than the revised cardiac risk index for prediction of peri-operative cardiovascular events, none of the four models exhibited strong discrimination metrics. There remains a need to develop a better peri-operative risk prediction model.


Subject(s)
Cardiovascular Diseases/complications , Cardiovascular Diseases/diagnosis , Models, Statistical , Surgical Procedures, Operative , Aged , Atrial Fibrillation/complications , Cohort Studies , Female , Humans , Male , Reproducibility of Results , Risk Assessment , Severity of Illness Index
2.
J Thromb Haemost ; 13(10): 1768-75, 2015 Oct.
Article in English | MEDLINE | ID: mdl-26270168

ABSTRACT

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). PATIENTS/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.


Subject(s)
Atrial Fibrillation/complications , Decision Support Techniques , Stroke/etiology , Surgical Procedures, Operative/adverse effects , Aged , Aged, 80 and over , Atrial Fibrillation/diagnosis , Atrial Fibrillation/mortality , Female , Humans , Male , Middle Aged , Patient Selection , Predictive Value of Tests , Prospective Studies , Risk Assessment , Risk Factors , Stroke/diagnosis , Stroke/mortality , Surgical Procedures, Operative/mortality , Time Factors , Treatment Outcome
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