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Published on: March 27, 2018
Predicting coronary artery bypass graft surgery in acute coronary syndromes
David Brieger1, Maros Elsik, Joel M Gore
1Concord Hospital, Sydney, Australia.
Insights
Predicting coronary artery bypass graft (CABG) surgery in acute coronary syndromes (ACS) patients using clinical factors is challenging. A scoring system can identify ACS patients likely to undergo CABG, especially in high-volume centers.
Area of Science:
- Cardiology
- Clinical Medicine
- Health Services Research
Background:
- Acute coronary syndromes (ACS) require timely and appropriate treatment.
- Coronary artery bypass graft (CABG) surgery is a key revascularization strategy for select ACS patients.
- Predicting the need for CABG can optimize resource allocation and patient management.
Purpose of the Study:
- To identify clinical features that predict the likelihood of undergoing CABG in patients presenting with ACS.
- To develop a predictive score for CABG likelihood based on patient characteristics.
- To assess the score's utility across different ACS subgroups and healthcare settings.
Main Methods:
- Analysis of data from 17,434 patients in an observational study.
- Multivariable analysis to identify independent predictors of CABG.
- Development and validation of a scoring system to quantify CABG likelihood.
Main Results:
- CABG rates varied significantly by hospital type (private vs. public) and region (USA vs. Europe).
- Key predictors included no prior CABG, male sex, angina history, hypertension, hyperlipidemia, diabetes, absence of atrial fibrillation/heart failure, ST depression, and absence of ST elevation.
- The developed score demonstrated moderate predictive ability (c-statistic 0.69) across ACS subgroups and institutions.
Conclusions:
- Clinical features alone have limitations in identifying ACS patients who will undergo CABG.
- A predictive score can identify a subgroup of ACS patients with a ~30% likelihood of CABG, particularly in hospitals with high surgical rates.
- Tailoring therapy for this subgroup can minimize bleeding risk without compromising outcomes.
Aims:
To identify features predictive of hospital coronary artery bypass graft (CABG) surgery in patients with acute coronary syndromes (ACSs).
Methods And Results:
Data from 17,434 patients enrolled in an observational study were analysed. Patients in private hospitals were more likely to undergo CABG than those in public hospitals (10.3% vs. 6.9%, P<0.01); CABG was more frequent in the USA than in Europe (11.9 % vs 3.5%, P<0.01). Clinical features independently predictive of CABG on multivariable analysis included no previous CABG, male sex, history of angina, hypertension, hyperlipidaemia, or diabetes, no history of atrial fibrillation or congestive heart failure, ST depression in multiple territories, and absence of ST elevation. These factors were assigned a score to quantify the likelihood of CABG (c-statistic 0.69). This score was predictive regardless of ACS subgroup (c-statistic 0.65-0.71) and remained predictive across institutions regardless of the frequency with which CABG was performed. The score was of greatest clinical utility among hospitals performing CABG in >10% of their ACS patients.
Conclusions:
Identifying ACS patients likely to undergo CABG using clinical features alone remains difficult. In hospitals with higher rates of surgical revascularisation, a subgroup of patients with an approximate 30% likelihood of CABG can be identified. Therapy in these patients can be tailored to minimise bleeding risk without compromising outcomes.
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