Prognostic Utility of a New Risk Stratification Protocol for Secondary Prevention in Patients Attending Cardiac Rehabilitation

Abstract

Several risk scores have been used to predict risk after an acute coronary syndrome (ACS), but none of these risk scores include functional class. The aim was to assess the predictive value of risk stratification (RS), including functional class, and how cardiac rehabilitation (CR) changed RS. Two hundred and thirty-eight patients with ACS from an ambispective observational registry were stratified as low (L) and no-low (NL) risk and classified according to exercise compliance; low risk and exercise (L-E), low risk and control (no exercise) (L-C), no-low risk and exercise (NL-E), and no-low risk and control (NL-C). The primary endpoint was cardiac rehospitalization. Multivariable analysis was performed to identify variables independently associated with the primary endpoint. The L group included 56.7% of patients. The primary endpoint was higher in the NL group (18.4% vs. 4.4%, p < 0.001). After adjustment for age, sex, diabetes, and exercise in multivariable analysis, HR (95% CI) was 3.83 (1.51–9.68) for cardiac rehospitalization. For RS and exercise, the prognosis varied: the L-E group had a cardiac rehospitalization rate of 2.5% compared to 26.1% in the NL-C group (p < 0.001). Completing exercise training was associated with reclassification to low-risk, associated with a better outcome. This easy-to-calculate risk score offers robust prognostic information. No-exercise groups were independently associated with the worst outcomes. Exercise-based CR program changed RS, improving classification and prognosis.

It’s Time to Run!

“…Finally, knowing the importance of risk stratification scores in cardiac patients [22,23], Cabrera-Aguilera and colleagues [24] developed an easy-to-calculate score based on cardiopulmonary capacity and left ventricular systolic function with the main goal, of identifying low-risk patients who can safely complete CR in a setting other than the hospital, making CR more accessible to suitable patients.…”

An Index for Evaluating Exercise Capacity Improvement After Cardiac Rehabilitation in Patients After Myocardial Infarction

“…Typically, researchers investigate changes in clinical features after a rehabilitation program separately in subgroups of patients and use peak VO 2 for defining success. 2,14,15,18,20,21 To our knowledge, there is no study on identifying groups of patients based on response to treatment among individuals undergoing cardiac rehabilitation after an AMI.…”

“…The large number of variables measured by CPX-SE allows profiling patients individually 18,19 . Meanwhile, the development of treatment strategies relies on data-driven stratification regarding exercise capacity improvement 20 . This leads to the challenging problem of finding patterns in high-dimensional data with correlated features.…”

“…18,19 Meanwhile, the development of treatment strategies relies on data-driven stratification regarding exercise capacity improvement. 20 This leads to the challenging problem of finding patterns in high-dimensional data with correlated features. Typically, researchers investigate changes in clinical features after a rehabilitation program separately in subgroups of patients and use peak VO 2 for defining success.…”

“…This would help to stratify patients regarding the efficacy of rehabilitation using a subset of CPX-SE outcomes. An accurate method for measuring response to treatment is important in designing efficient rehabilitation programs, improving survival, and lowering the likelihood of rehospitalization in post-MI patients 2,15,20 . Our hypothesis was that patients could be clustered regarding the likelihood of progress in exercise tolerance based on CPX-SE measurements.…”