Incremental Value of Exercise ECG to Myocardial Perfusion Single-Photon Emission Computed Tomography for Prediction of Cardiac Events.
Morten KraenShahnaz AkilBo HedénJonathan BergEllen OstenfeldMarcus CarlssonHåkan ArhedenHenrik EngblomPublished in: Journal of the American Heart Association (2023)
Background Both myocardial perfusion single-photon emission computed tomography (MPS) and exercise ECG (Ex-ECG) carry prognostic information in patients with stable chest pain. However, it is not fully understood if combining the findings of MPS and Ex-ECG improves risk prediction. Current guidelines no longer recommend Ex-ECG for diagnostic evaluation of chronic coronary syndrome, but Ex-ECG could still be of incremental prognostic importance. Methods and Results This study comprised 908 consecutive patients (age 63.3±9.4 years, 49% male) who performed MPS with Ex-ECG. Subjects were followed for 5 years. The end point was a composite of cardiovascular death, acute myocardial infarction, unstable angina, and unplanned percutaneous coronary intervention. National registry data and medical charts were used for end point allocation. Combining the findings of MPS and Ex-ECG resulted in concordant evidence of ischemia in 72 patients or absence of ischemia in 634 patients. Discordant results were found in 202 patients (MPS-/Ex-ECG+, n=126 and MPS+/Ex-ECG-, n=76). During follow-up, 95 events occurred. Annualized event rates significantly increased across groups (MPS-/Ex-ECG- =1.3%, MPS-/Ex-ECG+ =3.0%, MPS+/Ex-ECG- =5.1% and MPS+/Ex-ECG+ =8.0%). In multivariable analyses MPS was the strongest predictor regardless of Ex-ECG findings (MPS+/Ex-ECG-, hazard ratio [HR], 3.0, P =0.001 or MPS+/Ex-ECG+, HR,4.0, P <0.001). However, an abnormal Ex-ECG almost doubled the risk in subjects with normal MPS (MPS-/Ex-ECG+, HR, 1.9, P =0.04). Conclusions In patients with chronic coronary syndrome, combining the results from MPS and Ex-ECG led to improved risk prediction. Even though MPS is the stronger predictor, there is an incremental value of adding data from Ex-ECG to MPS, especially in patients with normal MPS.
Keyphrases
- heart rate variability
- heart rate
- end stage renal disease
- computed tomography
- acute myocardial infarction
- percutaneous coronary intervention
- newly diagnosed
- chronic kidney disease
- blood pressure
- coronary artery disease
- healthcare
- prognostic factors
- patient reported outcomes
- peritoneal dialysis
- heart failure
- big data
- clinical practice
- electronic health record
- artificial intelligence
- coronary artery
- health information