Risk Assessment after ST-Segment Elevation Myocardial Infarction : can Biomarkers Improve the Performance of Clinical Variables?

Introduction: Myocardial infarction with ST-segment elevation (STEMI) is the coronary artery disease associated with the highest risk of morbimortality; however, this risk is heterogeneous, usually being evaluated by clinical scores. Risk assessment is a key factor in personalized clinical management of patients with this disease. Aim: The aim of this study was to assess whether some new cardiac biomarkers considered alone, combined in a multibiomarker model or in association with clinical variables, improve the short- and long-term risk stratification of STEMI patients. Materials and Methods: This was a retrospective observational study of 253 patients with STEMI. Blood samples were obtained before or during the angiography. The assessed biomarkers were C-terminal fragment of insulin-like growth factor binding protein-4 (CT-IGFBP4), high sensitive cardiac troponin T (hs-cTnT), N-terminal fragment of probrain natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15); they reflect different cardiovascular (CV) physiopathological pathways and underlying pathologies. We registered in-hospital and follow-up mortalities and their causes (cardiovascular and all-cause) and major adverse cardiac events (MACE) during a two year follow-up. Discrimination, survival analysis, model calibration, and reclassification of the biomarkers were comprehensively evaluated. Results and Discussion: In total, 55 patients (21.7%) died, 33 in-hospital and 22 during the follow-up, most of them (69.1%) from CV causes; 37 MACE occurred during follow-up. Biomarkers showed good prognostic ability to predict mortality, alone and combined with the multibiomarker model. A predictive clinical model based on age, Killip-Kimball class, estimated glomerular filtration rate (eGFR), and heart rate was derived by multivariate analysis. GDF-15 and NT-proBNP significantly improved risk assessment of the clinical model, as shown by discrimination, calibration, and reclassification of all the end-points except for all-cause mortality. The combination of NT-proBNP and hs-cTnT improved CV mortality prediction. Conclusions: GDF-15 and NT-proBNP added value to the usual risk assessment of STEMI patients

Electrophysiological effects of selective atrial coronary artery occlusion in humans

Background-The arrhythmogenesis of ventricular myocardial ischemia has been extensively studied, but models of atrial ischemia in humans are lacking. This study aimed at describing the electrophysiological alterations induced by acute atrial ischemia secondary to atrial coronary branch occlusion during elective coronary angioplasty.; Methods and Results-Clinical data, 12-lead ECG, 12-hour Holter recordings, coronary angiography, and serial plasma levels of high-sensitivity troponin T and midregional proatrial natriuretic peptide were prospectively analyzed in 109 patients undergoing elective angioplasty of right or circumflex coronary arteries. Atrial coronary branches were identified and after the procedure patients were allocated into two groups: atrial branch occlusion (ABO, n= 17) and atrial branch patency (non-ABO, n= 92). In comparison with the non-ABO, patients with ABO showed: (1) higher incidence of periprocedural myocardial infarction (20% versus 53%, P= 0.01); (2) more frequent intra-atrial conduction delay (19% versus 46%, P= 0.03); (3) more marked PR segment deviation in the Holter recordings; and (4) higher incidence of atrial tachycardia (15% versus 41%, P= 0.02) and atrial fibrillation (0% versus 12%, P= 0.03). After adjustment by a propensity score, ABO was an independent predictor of periprocedural infarction (odds ratio, 3.4; 95% confidence interval, 1.01-11.6, P< 0.05) and atrial arrhythmias (odds ratio, 5.1; 95% confidence interval, 1.2-20.5, P= 0.02).; Conclusions-Selective atrial coronary artery occlusion during elective percutaneous transluminal coronary angioplasty is associated with myocardial ischemic damage, atrial arrhythmias, and intra-atrial conduction delay. Our data suggest that atrial ischemic episodes might be considered as a potential cause of atrial fibrillation in patients with chronic coronary artery disease.Peer ReviewedPostprint (author's final draft

Growth differentiation factor 15 as mortality predictor in heart failure patients with non-reduced ejection fraction

Altres ajuts: This study was supported by Fundació d'Investigació Sant Pau (G-60136934).The prognostic value of biomarkers in patients with heart failure (HF) and mid-range (HFmrEF) or preserved ejection fraction (HFpEF) has not been widely addressed. The aim of this study was to assess whether the prognostic value of growth differentiation factor 15 (GDF-15) is superior to that of N-terminal pro-brain natriuretic peptide (NT-proBNP) in patients with HFmrEF or HFpEF. Heart failure patients with either HFpEF or HFmrEF were included in the study. During their first visit to the HF unit, serum samples were obtained and stored for later assessment of GDF-15 and NT-proBNP concentrations. Patients were followed up by the HF unit. The main endpoint was all-cause mortality. A total of 311 patients, 90 (29%) HFmrEF and 221 (71%) HFpEF, were included. Mean age was 72 ± 13 years, and 136 (44%) were women. No differences were found in GDF-15 or NT-proBNP concentrations between both HF groups. During a median follow-up of 15 months (Q1-Q3: 9-30 months), 98 patients (32%) died, most (71%) of cardiovascular causes. Patients who died had higher median concentrations of GDF-15 (4085 vs. 2270 ng/L, P 65 years (P 4330 ng/L), and survival curves were evaluated using the Kaplan-Meier technique. Patients in the highest tertile had the poorest 5 year survival, at 16%, whereas the lowest tertile had the best survival, of 78% (P < 0.001). Growth differentiation factor 15 was superior to NT-proBNP for assessing prognosis in patients with HFpEF and HFmrEF. GDF-15 emerges as a strong, independent biomarker for identifying HFmrEF and HFpEF patients with worse prognosis

A Mobile App (mHeart) to Detect Medication Nonadherence in the Heart Transplant Population : Validation Study

Medication nonadherence in heart transplant recipients (HTxR) is related to graft loss and death. mHeart is a mobile app that uses electronic patient-reported outcome measures (ePROMs) to identify and manage medication nonadherence in the outpatient heart transplant (HTx) population. The study primarily aimed to validate mHeart to measure medication nonadherence in early stage HTxR by assessing the psychometric properties of ePROMs. The secondary aims were to (1) measure patient satisfaction with the mHeart tool and its usability and (2) explore the impact of a theory-based treatment on medication nonadherence rates to determine its scalability to larger research. A prospective study was conducted in the outpatient clinic of a tertiary hospital. All consecutive early stage HTxR (0.7, P <.001). Reproducibility was moderate (Haynes-Sackett κ=0.6, P <.002) or poor (Morisky-Green-Levine κ=0.3, P =.11) because of unexpected improved medication adherence rates during the test-retest period. According to responsiveness, the theory-based multifaceted intervention program improved medication nonadherence by 16% to 26% (P <.05). A burden analysis showed that ePROMs could potentially overcome traditional on-site limitations (eg, automatic recording of ePROM responses in the hospital information system). The mean score for overall patient satisfaction with the mHeart approach was 9 (SD 2; score range: 0-10). All 100% (29/29) of patients surveyed reported that they would recommend the mHeart platform to other HTxR. ePROMs adhered to the quality standards and successfully identified medication nonadherence in the HTx population, supporting their widespread use. The theory-based intervention program showed a promising improvement in medication adherence rates and produced excellent patient satisfaction and usability scores in HTxR

Phase angle by electrical bioimpedance is a predictive factor of hospitalisation, falls and mortality in patients with cirrhosis

The phase angle is a versatile measurement to assess body composition, frailty and prognosis in patients with chronic diseases. In cirrhosis, patients often present alterations in body composition that are related to adverse outcomes. The phase angle could be useful to evaluate prognosis in these patients, but data are scarce. The aim was to analyse the prognostic value of the phase angle to predict clinically relevant events such as hospitalisation, falls, and mortality in patients with cirrhosis. Outpatients with cirrhosis were consecutively included and the phase angle was determined by electrical bioimpedance. Patients were prospectively followed to determine the incidence of hospitalisations, falls, and mortality. One hundred patients were included. Patients with phase angle¿=¿4.6° (n¿=¿31) showed a higher probability of hospitalisation (35% vs 11%, p¿=¿0.003), falls (41% vs 11%, p¿=¿0.001) and mortality (26% vs 3%, p¿=¿0.001) at 2-year follow-up than patients with PA¿>¿4.6° (n¿=¿69). In the multivariable analysis, the phase angle and MELD-Na were independent predictive factors of hospitalisation and mortality. Phase angle was the only predictive factor for falls. In conclusion, the phase angle showed to be a predictive marker for hospitalisation, falls, and mortality in outpatients with cirrhosis.Postprint (published version

Prognostic value of discharge heart rate in acute heart failure patients: more relevant in atrial fibrillation?

[Abstract] Aims. The prognostic impact of heart rate (HR) in acute heart failure (AHF) patients is not well known especially in atrial fibrillation (AF) patients. The aim of the study was to evaluate the impact of admission HR, discharge HR, HR difference (admission-discharge) in AHF patients with sinus rhythm (SR) or AF on long- term outcomes. Methods. We included 1398 patients consecutively admitted with AHF between October 2013 and December 2014 from a national multicentre, prospective registry. Logistic regression models were used to estimate the association between admission HR, discharge HR and HR difference and one- year all-cause mortality and HF readmission. Results. The mean age of the study population was 72 ± 12 years. Of these, 594 (42.4%) were female, 655 (77.8%) were hypertensive and 655 (46.8%) had diabetes. Among all included patients, 745 (53.2%) had sinus rhythm and 653 (46.7%) had atrial fibrillation. Only discharge HR was associated with one year all-cause mortality (Relative risk (RR) = 1.182, confidence interval (CI) 95% 1.024–1.366, p = 0.022) in SR. In AF patients discharge HR was associated with one year all cause mortality (RR = 1.276, CI 95% 1.115–1.459, p ≤ 0.001). We did not observe a prognostic effect of admission HR or HRD on long-term outcomes in both groups. This relationship is not dependent on left ventricular ejection fraction. Conclusions. In AHF patients lower discharge HR, neither the admission nor the difference, is associated with better long-term outcomes especially in AF patients

A simple validated method for predicting the risk of hospitalization for worsening of heart failure in ambulatory patients : the Redin-SCORE

Prevention of hospital readmissions is one of the main objectives in the management of patients with heart failure (). Most of the models predicting readmissions are based on data extracted from hospitalized patients rather than from outpatients. Our objective was to develop a validated score predicting 1-month and 1-year risk of readmission for worsening of in ambulatory patients. A cohort of 2507 ambulatory patients with chronic was prospectively followed for a median of 3.3 years. Clinical, echocardiographic, , and biochemical variables were used in a competing risk regression analysis to construct a risk score for readmissions due to worsening of . Thereafter, the score was externally validated using a different cohort of 992 patients with chronic ( registry). Predictors of 1-month readmission were the presence of elevated natriuretic peptides, left ventricular (LV) HF signs, and estimated glomerular filtration rate () 26 mm/m 2, heart rate >70 b.p.m., signs, and 5% event rate) for 1-month readmission. Likewise, low-risk (7.8%), intermediate-risk (15.6%) and high-risk groups (26.1%) were identified for 1-year readmission risk. The C-statistics remained consistent after the external validation (<5% loss of discrimination). The Redin- predicts early and late readmission for worsening of using proven prognostic variables that are routinely collected in outpatient management of chronic

A 3-biomarker 2-point-based risk stratification strategy in acute heart failure

[Abstract] Introduction and Objectives: Most multi-biomarker strategies in acute heart failure (HF) have only measured biomarkers in a single-point time. This study aimed to evaluate the prognostic yielding of NT-proBNP, hsTnT, Cys-C, hs-CRP, GDF15, and GAL-3 in HF patients both at admission and discharge. Methods: We included 830 patients enrolled consecutively in a prospective multicenter registry. Primary outcome was 12-month mortality. The gain in the C-index, calibration, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) was calculated after adding each individual biomarker value or their combination on top of the best clinical model developed in this study (C-index 0.752, 0.715–0.789) and also on top of 4 currently used scores (MAGGIC, GWTG-HF, Redin-SCORE, BCN-bioHF). Results: After 12-month, death occurred in 154 (18.5%) cases. On top of the best clinical model, the addition of NT-proBNP, hs-CRP, and GDF-15 above the respective cutoff point at admission and discharge and their delta during compensation improved the C-index to 0.782 (0.747–0.817), IDI by 5% (p < 0.001), and NRI by 57% (p < 0.001) for 12-month mortality. A 4-risk grading categories for 12-month mortality (11.7, 19.2, 26.7, and 39.4%, respectively; p < 0.001) were obtained using combination of these biomarkers. Conclusion: A model including NT-proBNP, hs-CRP, and GDF-15 measured at admission and discharge afforded a mortality risk prediction greater than our clinical model and also better than the most currently used scores. In addition, this 3-biomarker panel defined 4-risk categories for 12-month mortality.Instituto de Salud Carlos III; RD06-0003-0000Instituto de Salud Carlos III; RD12/0042/000

A 3-Biomarker 2-Point-Based Risk Stratification Strategy in Acute Heart Failure

Altres ajuts: ISCIII/RD06-0003-0000Altres ajuts: ISCIII/RD12/0042/0002Introduction and Objectives: Most multi-biomarker strategies in acute heart failure (HF) have only measured biomarkers in a single-point time. This study aimed to evaluate the prognostic yielding of NT-proBNP, hsTnT, Cys-C, hs-CRP, GDF15, and GAL-3 in HF patients both at admission and discharge. Methods: We included 830 patients enrolled consecutively in a prospective multicenter registry. Primary outcome was 12-month mortality. The gain in the C-index, calibration, net reclassification improvement (NRI), and integrated discrimination improvement (IDI) was calculated after adding each individual biomarker value or their combination on top of the best clinical model developed in this study (C-index 0.752, 0.715-0.789) and also on top of 4 currently used scores (MAGGIC, GWTG-HF, Redin-SCORE, BCN-bioHF). Results: After 12-month, death occurred in 154 (18.5%) cases. On top of the best clinical model, the addition of NT-proBNP, hs-CRP, and GDF-15 above the respective cutoff point at admission and discharge and their delta during compensation improved the C-index to 0.782 (0.747-0.817), IDI by 5% (p < 0.001), and NRI by 57% (p < 0.001) for 12-month mortality. A 4-risk grading categories for 12-month mortality (11.7, 19.2, 26.7, and 39.4%, respectively; p < 0.001) were obtained using combination of these biomarkers. Conclusion: A model including NT-proBNP, hs-CRP, and GDF-15 measured at admission and discharge afforded a mortality risk prediction greater than our clinical model and also better than the most currently used scores. In addition, this 3-biomarker panel defined 4-risk categories for 12-month mortality

Risk Assessment after ST-Segment Elevation Myocardial Infarction: Can Biomarkers Improve the Performance of Clinical Variables?

Introduction: Myocardial infarction with ST-segment elevation (STEMI) is the coronary artery disease associated with the highest risk of morbimortality; however, this risk is heterogeneous, usually being evaluated by clinical scores. Risk assessment is a key factor in personalized clinical management of patients with this disease. Aim: The aim of this study was to assess whether some new cardiac biomarkers considered alone, combined in a multibiomarker model or in association with clinical variables, improve the short- and long-term risk stratification of STEMI patients. Materials and Methods: This was a retrospective observational study of 253 patients with STEMI. Blood samples were obtained before or during the angiography. The assessed biomarkers were C-terminal fragment of insulin-like growth factor binding protein-4 (CT-IGFBP4), high sensitive cardiac troponin T (hs-cTnT), N-terminal fragment of probrain natriuretic peptide (NT-proBNP), and growth differentiation factor 15 (GDF-15); they reflect different cardiovascular (CV) physiopathological pathways and underlying pathologies. We registered in-hospital and follow-up mortalities and their causes (cardiovascular and all-cause) and major adverse cardiac events (MACE) during a two year follow-up. Discrimination, survival analysis, model calibration, and reclassification of the biomarkers were comprehensively evaluated. Results and Discussion: In total, 55 patients (21.7%) died, 33 in-hospital and 22 during the follow-up, most of them (69.1%) from CV causes; 37 MACE occurred during follow-up. Biomarkers showed good prognostic ability to predict mortality, alone and combined with the multibiomarker model. A predictive clinical model based on age, Killip–Kimball class, estimated glomerular filtration rate (eGFR), and heart rate was derived by multivariate analysis. GDF-15 and NT-proBNP significantly improved risk assessment of the clinical model, as shown by discrimination, calibration, and reclassification of all the end-points except for all-cause mortality. The combination of NT-proBNP and hs-cTnT improved CV mortality prediction. Conclusions: GDF-15 and NT-proBNP added value to the usual risk assessment of STEMI patients