RESUMO
AIMS: The development and incidence of de-novo heart failure after ST-elevation myocardial infarction (STEMI) in the contemporary era of rapid reperfusion are largely unknown. We aimed to establish the incidence of post-STEMI heart failure, stratified by left ventricular ejection fraction (LVEF) and to find predictors for its occurrence. Furthermore, we investigated the course of left ventricular systolic and diastolic function after STEMI. METHODS AND RESULTS: A total of 1172 all-comer STEMI patients from the CardioLines Biobank were included. Patients were predominantly male (74.5%) and 64 ± 12 years of age. During a median follow-up of 3.7 years (2.0, 5.5) we found a total incidence of post-STEMI heart failure of 10.9%, of which 52.1% heart failure with reduced ejection fraction (HFrEF), 29.4% heart failure with mildly reduced ejection fraction and 18.5% heart failure with preserved ejection fraction (HFpEF). Independent predictors for the development of HFrEF were male sex (ß = 0.97, p = 0.009), lung crepitations (ß = 1.09, p = 0.001), potassium level (mmol/L, ß = 0.43, p = 0.012), neutrophil count (109/L, ß = 0.09, p = 0.001) and a reduced LVEF (ß = 1.91, p < 0.001) at baseline. Independent predictors for the development of HFpEF were female sex (ß = 0.99, p = 0.029), pre-existing kidney failure (ß = 1.95, p = 0.003) and greater left atrial volume index (ß = 0.04, p = 0.033) at baseline. Follow-up echocardiography (median follow-up 20 months) showed an improvement in LVEF (p < 0.001), whereas changes in diastolic function parameters showed both improvement and deterioration. CONCLUSION: In the current era of early STEMI reperfusion, still one in 10 patients develops heart failure, with approximately half of the patients with a reduced and half with a mildly reduced or normal LVEF. Predictors for the development of HFrEF were different from HFpEF.
Assuntos
Insuficiência Cardíaca , Intervenção Coronária Percutânea , Infarto do Miocárdio com Supradesnível do Segmento ST , Volume Sistólico , Humanos , Masculino , Feminino , Insuficiência Cardíaca/fisiopatologia , Insuficiência Cardíaca/epidemiologia , Volume Sistólico/fisiologia , Infarto do Miocárdio com Supradesnível do Segmento ST/fisiopatologia , Infarto do Miocárdio com Supradesnível do Segmento ST/cirurgia , Infarto do Miocárdio com Supradesnível do Segmento ST/complicações , Infarto do Miocárdio com Supradesnível do Segmento ST/epidemiologia , Pessoa de Meia-Idade , Incidência , Intervenção Coronária Percutânea/métodos , Idoso , Função Ventricular Esquerda/fisiologia , Seguimentos , Fatores de Risco , Ecocardiografia , PrognósticoAssuntos
Angioplastia Coronária com Balão , Doença da Artéria Coronariana , Reestenose Coronária , Stents Farmacológicos , Intervenção Coronária Percutânea , Humanos , Resultado do Tratamento , Doença da Artéria Coronariana/diagnóstico por imagem , Doença da Artéria Coronariana/terapia , Angioplastia Coronária com Balão/efeitos adversos , Reestenose Coronária/diagnóstico por imagem , Reestenose Coronária/etiologia , Reestenose Coronária/terapia , Stents , Intervenção Coronária Percutânea/efeitos adversos , Materiais Revestidos BiocompatíveisRESUMO
AIMS: Risk prediction models (RPMs) for coronary artery disease (CAD), using variables to calculate CAD risk, are potentially valuable tools in prevention strategies. However, their use in the clinical practice is limited by a lack of poor model description, external validation, and head-to-head comparisons. METHODS AND RESULTS: CAD RPMs were identified through Tufts PACE CPM Registry and a systematic PubMed search. Every RPM was externally validated in the three cohorts (the UK Biobank, LifeLines, and PREVEND studies) for the primary endpoint myocardial infarction (MI) and secondary endpoint CAD, consisting of MI, percutaneous coronary intervention, and coronary artery bypass grafting. Model discrimination (C-index), calibration (intercept and regression slope), and accuracy (Brier score) were assessed and compared head-to-head between RPMs. Linear regression analysis was performed to evaluate predictive factors to estimate calibration ability of an RPM. Eleven articles containing 28 CAD RPMs were included. No single best-performing RPM could be identified across all cohorts and outcomes. Most RPMs yielded fair discrimination ability: mean C-index of RPMs was 0.706 ± 0.049, 0.778 ± 0.097, and 0.729 ± 0.074 (P < 0.01) for prediction of MI in UK Biobank, LifeLines, and PREVEND, respectively. Endpoint incidence in the original development cohorts was identified as a significant predictor for external validation performance. CONCLUSION: Performance of CAD RPMs was comparable upon validation in three large cohorts, based on which no specific RPM can be recommended for predicting CAD risk.