Independent Predictor Of Major Adverse Cardiac Events Research Articles

Prognostic impact of new-onset atrial fibrillation in myocardial infarction with and without improved ejection fraction.

Improvement in left ventricular ejection fraction (impEF) often presents in contemporary acute myocardial infarction (AMI) patients. New-onset atrial fibrillation (NOAF) during AMI is an important predictor of subsequential heart failure (HF), while its impact on the trajectory of post-MI left ventricular ejection fraction (LVEF) and prognostic implication in patients with and without impEF remains undetermined. We aimed to investigate the prognostic impacts of NOAF in AMI patients with and without impEF. Consecutive AMI patients without a prior history of AF between February 2014 and March 2018 with baseline LVEF≤40% and had ≥1 LVEF measurement after baseline were included. ImpEF was defined as a baseline LVEF≤40% and a re-evaluation showed both LVEF>40% and an absolute increase of LVEF≥10%. Persistently reduced EF (prEF) was defined as the second measurement of LVEF either ≤40% or an absolute increase of LVEF<10%. The primary endpoint was a major adverse cardiac event (MACE) that was composed of cardiovascular death and HF hospitalization. Cox regression analysis and competing risk analysis were performed to assess the association of post-MI NOAF with MACE. Among 293 patients (mean age: 66.6±11.3years, 79.2% of males), 145 (49.5%) had impEF and 67 (22.9%) developed NOAF. Higher heart rate (odds ratio [OR]: 0.84, 95% confidence interval [CI]: 0.73-0.97; P=0.015), prior MI (OR: 0.25, 95% CI: 0.09-0.69; P=0.008), and STEMI (OR: 0.40, 95% CI: 0.21-0.77; P=0.006) were independent predictors of post-MI impEF. Within up to 5years of follow-up, there were 22 (15.2%) and 53 (35.8%) MACE in patients with impEF and prEF, respectively. NOAF was an independent predictor of MACE in patients with impEF (hazard ratio [HR]: 7.34, 95% CI: 2.49-21.59; P<0.001) but not in those with prEF (HR: 0.78, 95% CI: 0.39-1.55; P=0.483) after multivariable adjustment. Similar results were obtained when accounting for the competing risk of all-cause death (subdistribution HR and 95% CIs in impEF and prEF were 6.47 [2.32-18.09] and 0.79 [0.39-1.61], respectively). The NOAF was associated with an increased risk of cardiovascular outcomes in AMI patients with impEF.

Risk Stratification Using Right Ventricular Longitudinal Strain Ratio Derived from 13N-Ammonia PET in Patients with Ischemic Heart Disease.

Purpose To investigate whether right ventricular (RV) myocardial strain ratio (RVMSR) assessed using nitrogen 13 ammonia (13N-NH3) PET can predict cardiovascular events in patients with ischemic heart disease (IHD). Materials and Methods This retrospective study included 480 consecutive patients (mean age, 66 years ± 12 [SD]; 334 males and 146 females) with IHD who underwent 13N-NH3 PET. RVMSR was defined as the ratio of RV strain during stress to that at rest. The primary end point was major adverse cardiac events (MACEs), defined as cardiac death or heart failure hospitalization. The ability of RVMSR to predict MACE was assessed using receiver operating characteristic (ROC) curve and Kaplan-Meier analyses. Cox proportional hazards regression analysis was used to calculate hazard ratios (HRs) with 95% CIs. Results ROC curve analysis identified a sensitivity and specificity of 84% and 82%, respectively, for predicting MACE from RVMSR. Patients with reduced RVMSR (<110.2) displayed a significantly higher rate of MACE than those with a preserved RVMSR (34 of 240 vs four of 240; P < .001). Cox proportional hazards regression analysis of imaging parameters, including myocardial flow reserve, indicated that RVMSR was an independent predictor of MACE (HR, 0.94 [95% CI: 0.92, 0.97]; P < .001). Conclusion RVMSR was an independent predictor of MACE and has potential to aid in the risk stratification of patients with IHD. Keywords: Right Ventricular Myocardial Strain Ratio, Myocardial Flow Reserve, Ischemic Heart Disease, 13N-Ammonia Positron Emission Tomography Supplemental material is available for this article. © RSNA, 2024.

Association between Glycemic Gap at Admission and In-Hospital Outcome in Patients with Diabetes with Acute Myocardial Infarction

Background: Acute hyperglycemia predicts adverse outcomes in patients with acute myocardial infarction (AMI), but it has a major disadvantage because the association is diminished in patients with diabetes mellitus (DM). Recent studies introduced a more accurate predictor, the glycemic gap (the difference between admission blood glucose and the estimated average glucose), that could anticipate adverse outcomes in patients with diabetes with AMI. Aims: This study aimed to determine the association between glycemic gap and clinical outcome in diabetic patients presenting with AMI to a tertiary hospital in Bangladesh. Methods: Two hundred twenty diabetic patients hospitalized with AMI were included in this study from the Department of Cardiology of Chittagong Medical College Hospital from March 2023 to February 2024. Admission blood glucose and HbA1c were measured, and the glycemic gap was calculated. Patients were prospectively followed during their hospital stay to obtain data regarding major adverse cardiac events (MACEs). Results: The mean (±SD) age of the patients was 56.5 (±10.1) years and 63.6% of them were male. MACEs included in-hospital death, cardiac arrest, cardiogenic shock, arrhythmia and left ventricular failure were observed in 6.4%, 3.6%, 19.5%, 5.5%, and 30.5% of the patients, respectively. Ninety-nine (45%) patients had one or more MACEs. Median (IQR) glycemic gap values were 38.5 (31.9-47.3) and 71.0 (61.0-84.3) in patients without any MACEs and patients with one or more MACEs, respectively (p&lt;0.001). Median (IQR) glycemic gap values were 90.6 (86.0-97.9) and 52.6 (36.1-69.3) in expired and survived patients, respectively (p&lt;0.001). The area under the receiver operating characteristics curve (AUROC) for admission glycemic gap values to predict in-hospital mortality was 0.895[95% confidence interval (CI) 0.768-1.000, p&lt;0.001] and with the best cut-off value of 80.16, glycemic gap had sensitivity and specificity of 92.9% and 89.8%, respectively.The Area Under ROC for admission glycemic gap values to predict MACEs was 0.926 (95% CI 0.874-0.958) and with the best cut-off value of 53.19, glycemic gap had a sensitivity and specificity of 94.9% and 84.3%, respectively. Glycemic gap was an independent predictor of MACEs [odds ratio (OR): 1.11, 95% CI 1.08-1.14, p &lt;0.001] and in-hospital mortality (OR: 1.09, 95% CI 1.05-1.14, p &lt;0.001). Conclusions: Elevated glycemic gap was significantly associated with an increased in-hospital mortality and other MACEs. So, glycemic gap can be used to assess the prognosis of hospitalized AMI patients with diabetes.

Angiography-based Fractional Flow Reserve for the Prediction of Clinical Outcomes After Drug-coated Balloon or Plain Old Balloon Angioplasty.

AccuFFRangio is a novel method for fast computation of fractional flow reserve (FFR) based on coronary angiography and computational fluid dynamics. The association between the AccuFFRangio and clinical outcomes after drug-coated balloon (DCB) or plain old balloon angioplasty (POBA) remains to be investigated. This study included consecutive patients who underwent balloon angioplasty from December 2016 to October 2020. AccuFFRangio was calculated retrospectively based on the post-procedural angiography obtained immediately after angioplasty. The primary endpoint was major adverse cardiac events (MACE), defined as a composite of all-cause death, vessel-related myocardial infarction, and repeat target vessel revascularization. A total of 169 patients were retrospectively analyzed in this study. Post-procedural AccuFFRangio (hazard ratio [HR] per 0.1 increase 0.33, 95% confidence interval [CI] 0.22-0.48, p < 0.001) was an independent predictor for MACE at 2-year follow-up. Post-procedural AccuFFRangio ≤ 0.87 was determined as the optimal cutoff value to predict MACE with an area under the curve (AUC) of 0.872 (95% CI 0.813-0.919, p < 0.001). AccuFFRangio measured immediately after balloon angioplasty is a promising predictor of unfavorable clinical outcomes.

Efficacy of revascularization in CTO patients based on hibernating myocardium therapy.

The effectiveness of percutaneous coronary intervention (PCI) for chronic total occlusion (CTO) is still uncertain, especially for patients with ischemic left ventricular dysfunction. This study aimed to assess hibernating myocardium (HM), as determined by single-photon emission computed tomography (SPECT) and 18F-FDG positron emission tomography (PET), and to compare the benefits of PCI and optimal medical therapy (OMT). A retrospective study collected data from 332 patients with CTO and ischemic left ventricular dysfunction. The study compared patients who underwent PCI or OMT via propensity score matching (PSM) analysis which was performed with a 1:2 matching protocol using the nearest neighbour matching algorithm. The primary endpoint of the study was the occurrence of major adverse cardiac events (MACE), defined as a composite of cardiac death, readmission for worsening heart failure (WHF), revascularization and myocardial infarction (MI). After PSM, there were a total of 246 individuals in the PCI and OMT groups. Following Cox regression, hibernating myocardium/total perfusion defect (HM/TPD) was identified as an independent risk factor (hazard ratio (HR): 1.03, 95% confidence interval (CI): 1.008-1.052, p = .007). The cut-off value of HM/TPD was 38%. The results of the subgroup analysis suggest that for patients with HM/TPD >38%, the OMT group had a greater risk of MACE (p = .035). A sensitivity analysis restricting patients with single-vessel CTO lesions, HM/TPD remained an independent predictor (HR 1.025, 95% CI 1.008-1.043, p = .005). HM/TPD is an independent predictor of MACE, and for patients with HM/TPD > 38%, CTO-PCI had a lower risk of MACE compared with OMT. However, further validation is still needed through large-scale studies.

Prognostic Value of Microvascular Resistance Reserve Measured Immediately After PCI in Stable Coronary Artery Disease.

Microvascular resistance reserve (MRR) has been proposed as a specific metric to quantify coronary microvascular function. The long-term prognostic value of MRR measured in stable patients immediately after percutaneous coronary intervention (PCI) is unknown. This study sought to determine the prognostic value of MRR measured immediately after PCI in patients with stable coronary artery disease. This study included 502 patients with stable coronary artery disease who underwent elective PCI and coronary physiological measurements, including pressure and flow estimation using a bolus thermodilution method after PCI. MRR was calculated as coronary flow reserve divided by fractional flow reserve times the ratio of mean aortic pressure at rest to that at maximal hyperemia induced by hyperemic agents. An abnormal MRR was defined as ≤2.5. Major adverse cardiac events (MACEs) were defined as a composite of all-cause mortality, any myocardial infarction, and target-vessel revascularization. During a median follow-up of 3.4 years, the cumulative MACE rate was significantly higher in the abnormal MRR group (12.5 versus 8.3 per 100 patient-years; hazard ratio 1.53 [95% CI, 1.10-2.11]; P<0.001). A higher all-cause mortality rate primarily drove this difference. On multivariable analysis, a higher MRR value was independently associated with lower MACE and lower mortality. When comparing 4 subgroups according to MRR and the index of microcirculatory resistance, patients with both abnormal MRR and index of microcirculatory resistance (≥25) had the highest MACE rate. An abnormal MRR measured immediately after PCI in patients with stable coronary artery disease is an independent predictor of MACE, particularly all-cause mortality.

Shifting the Paradigm: How Stress Hyperglycemia Alters the Landscape of Heart Failure Management.

Background Acute decompensated heart failure (ADHF) significantly contributes to global morbidity. Stress hyperglycemia (SHGL), although commonly observed in non-diabetic ADHF patients, remains underexplored. This study investigates the predictive value of SHGL for major adverse cardiac events (MACEs) and its impact on coronary intervention outcomes. Methods In this prospective observational study at a tertiary care center, 650 non-diabetic ADHF patients admitted for coronary intervention between April 2021 and April 2022 were assessed. SHGL was defined by random blood sugar levels >140 mg/dl. We monitored the incidence of MACEs, including cardiac death, non-fatal myocardial infarction, and heart failure rehospitalization, alongside the success rates of coronary revascularizations over 12 months. Results SHGL was present in 54% of patients (n=352) and was significantly associated with increased MACEs (p<0.001), higher rehospitalization rates (p<0.01), and lower success in revascularization (p<0.05). Using logistic regression, SHGL, age >65, and prior heart failure hospitalization were identified as independent predictors of MACEs. Statistical analyses were performed using two-tailed Mann-Whitney U tests, with significance levels set at p<0.05 for noteworthy findings and p<0.01 or p<0.001 for highly significant findings. Conclusions SHGL significantly impacts coronary intervention outcomes and the future prognosis of heart failure in non-diabetic ADHF patients, identifying it as a critical, modifiable risk factor. These findings advocate integrating SHGL management into ADHF care, emphasizing the need for further research to develop standardized treatment protocols. Proper management of SHGL could potentially improve patient outcomes, highlighting the importance of metabolic control in heart failure management.

Clinical impact of complex percutaneous coronary intervention in the pre-TAVR workup

Introduction and objectivesIn patients undergoing percutaneous coronary intervention (PCI) in the workup for transcatheter aortic valve replacement (TAVR), the clinical impact of coronary revascularization complexity remains largely unknown. This study sought to examine the impact of PCI complexity on clinical outcomes after TAVR in patients undergoing PCI in the preprocedural workup. MethodsThis was a multicenter study including consecutive patients scheduled for TAVR with concomitant significant coronary artery disease. Complex PCI was defined as having at least 1 of the following features: 3 vessels treated, ≥ 3 stents implanted, ≥ 3 lesions treated, bifurcation with 2 stents implanted, total stent length >60mm, or chronic total occlusion. The rates of major adverse cardiac events (MACE), including cardiovascular mortality, myocardial infarction, and coronary revascularization were evaluated. ResultsA total of 1550 patients were included, of which 454 (29.3%) underwent complex PCI in the pre-TAVR workup. After a median follow-up period of 2 [1-3] years after TAVR, the incidence of MACE was 9.6 events per 100 patients-years. Complex PCI significantly increased the risk of cardiovascular death (HR, 1.44; 95%CI, 1.01-2.07), nonperiprocedural myocardial infarction (HR, 1.52; 95%CI, 1.04-2.21), and coronary revascularization (HR, 2.46; 95%CI, 1.44-4.20). In addition, PCI complexity was identified as an independent predictor of MACE after TAVR (HR, 1.44; 95%CI, 1.09-1.83; P=.009). ConclusionsIn TAVR candidates with significant coronary artery disease requiring percutaneous treatment, complex revascularization was associated with a higher risk of MACE. The degree of procedural complexity should be considered a strong determinant of prognosis in the PCI-TAVR population.

Artificial intelligence-assisted measurements of coronary computed tomography angiography parameters such as stenosis, flow reserve and fat attenuation for predicting major adverse cardiac events in patients with coronary arterial disease.

Advancements in artificial intelligence (AI) offer promising tools for improving diagnostic accuracy and patient outcomes in cardiovascular medicine. This study explores the potential of AI-assisted measurements in enhancing the prediction of major adverse cardiac events (MACE) in patients with coronary artery disease (CAD). We conducted a retrospective cohort study involving patients diagnosed with CAD who underwent coronary computed tomography angiography (CCTA). Participants were classified into MACE and non-MACE groups based on their clinical outcomes. Clinical characteristics and AI-assisted measurements of CCTA parameters, including CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI), were collected. Both univariate and multivariable logistic regression analyses were performed to identify independent predictors of MACE, which were used to build predictive models. Statistical analyses revealed three independent predictors of MACE: severe stenosis, CT-FFR ≤ 0.8, and mean FAI (P < 0.05). Seven predictive models incorporating various combinations of these predictors were developed. The model combining all three predictors demonstrated superior performance, as evidenced by the receiver operating characteristic (ROC) curve, with an area under the curve (AUC) of 0.811 (95% CI 0.774 - 0.847), a sensitivity of 0.776, and a specificity of 0.726. Our findings suggest that AI-assisted CCTA analysis, particularly using FFR and FAI, could significantly improve the prediction of MACE in CAD patients, thereby potentially aiding clinical decision-making.

Predischarge Peak Atrial Longitudinal Strain and Plasma N-terminal Pro-hormone Brain Natriuretic Peptide as a Predictor of Short-term Rehospitalization and Cardiovascular Mortality in Patients with Acute Heart Failure

Context: The postacute heart failure (AHF) rehospitalization rate is attributed to persistent hemodynamic congestion despite clinical improvement. Peak atrial longitudinal strain (PALS), utilizing speckle tracking echocardiography technology, shows potential in post-AHF prognosis. Meanwhile, N-terminal pro-hormone brain natriuretic peptide (NT-proBNP) remains a known biomarker of intracardiac congestion. Aims: This study aimed to determine the relationship between predischarge PALS and NT-proBNP as predictors of major adverse cardiac event (MACE) in patients after AHF hospitalization. Settings and Design: This study is a prospective cohort study, conducted in Prof. Dr. I G.N.G Ngoerah Hospital, Bali, Indonesia. Subjects and Methods: The study included hospitalized AHF patients, collecting demographic data, comorbidities, therapies, and echocardiographic measures before discharge. Predischarge PALS and NT-proBNP were taken within 24 h before discharge. The main outcome was MACE, defined as rehospitalization and cardiovascular mortality within 90 days. Statistical Analysis Used: Comparative statistical analyses was done using independent t-test for continuous variables (Mann–Whitney U test for variables with abnormal distribution) and Chi-squared tests. Receiver operating characteristic (ROC) used in determining optimal threshold values of predischarge PALS and NT-proBNP as a predictor of MACE. Kaplan–Meier curves were employed to gauge event-free survival differences between these cohorts. Then, independent Cox regression was used to identify the predictors of MACE. Results: The study enrolled 67 patients with varying ejection fraction (EF) (16 – heart failure with preserved ejection fraction, 10 – heart failure with mildly reduced ejection fraction, and 41 – heart failure with reduced ejection fraction; mean age: 56.88 ± 14.57 years). Over the 90-day follow-up, 21 patients (31.3%) encountered MACE. Both PALS (area under the curve [AUC] 0.816) and NT-proBNP (AUC 0.856) before discharge served as predictors of MACE. There was no significant AUC difference between ROC curves (area difference: 0.039, P = 0.553). The regression model highlighted that PALS and NT-proBNP level before discharge acted as independent predictors of MACE, irrespective of EF, average E/e’, or estimated predischarge pulmonary capillary wedge pressure. Conclusions: Predischarge PALS is comparable to NT-proBNP levels as independent predictors of short-term MACE after AHF hospitalization.

Significance of fragmented QRS and predictors of outcome in ST-elevation myocardial infarction

Abstract Background: Fragmented QRS (fQRS) might be associated with certain characteristics in ST-elevation myocardial infarction (STEMI) patients and inhospital adverse events. Materials and Methods: A sum of 500 patients were gone over retrospectively. Patients with STEMI, all undergone percutaneous coronary intervention, were grouped as fQRS (−) and fQRS (+). Characteristics of the patients, major adverse cardiac event (MACE), death in hospital, nonfatal myocardial infarction (MI), stent thrombosis, slow flow myocardial perfusion, development of ventricular tachycardia (VT) and fibrillation, cardiogenic shock and cardiopulmonary arrest were filtered. Results: FQRS (−) group was composed of 207 patients whose mean age was 61.1 ± 12.1, whereas 293 patients were there in fQRS (+) with a mean age of 66.7 ± 10.6 (P &lt; 0.001). Thrombolysis in MI (TIMI) (P &lt; 0.01), the global registry of acute coronary events (GRACE) (P &lt; 0.01) scores, white blood cell count, neutrophil/lymphocyte ratio, MACE and the ratio of death in hospital and VT in the hospital were significantly higher in fQRS (+) group (P &lt; 0.001, for remaining all). In multivariate logistic regression analysis, TIMI scores above 2 and GRACE scores above 109 were determined as independent predictors of MACE in the entire patient group (odds ratio [OR]: 2.022; 95% confidence interval [CI]; 1.321–3.424, P = 0.003; OR: 1.712; 95% CI: 1.156–2.804, P = 0.008). Conclusion: FQRS (+) and fQRS (−) patients markedly differ from each other in terms of certain demographic and clinical features and TIMI and GRACE scores have a significant predictive value for MACE in all STEMI patients’ group.

Diabetic kidney disease as an independent predictor of long-term adverse outcomes in patients with coronary artery disease and diabetic mellitus.

Diabetic kidney disease (DKD) had been proposed as a contributor in the pathogenesis of coronary artery disease (CAD). However, the relationship of DKD and the long-term adverse outcomes in patients with CAD after percutaneous coronary intervention (PCI) was still undiscovered. Approximately 892 patients with CAD enrolled from January 2012 to December 2016. The patients were divided into two groups, the DKD group (n = 341) and the None DKD group (n = 551). The primary outcome was major adverse cardiac events (MACE) after PCI. The average follow-up time was 1,897 ± 1,276 days. Baseline data showed that some factors were significantly different between the two groups, including age, body mass index, gender (female), hypertension, smoking, stroke history, heart failure, duration of diabetic mellitus (DM), low-density lipoprotein cholesterol, urinary protein/creatinine ratio, serum creatinine, hemoglobin, platelet, antiplatelet, beta blocker, statin, antihypertensive drugs, and insulin (all p < 0.005). There were significant differences between the two groups in MACE, 40.3% vs. 52.2% (p = 0.001), and in cardiovascular death events and all-cause death events (5.6% vs. 20.5%, p < 0.001 and 4.4% vs. 13.5%, p < 0.001, respectively). In the DKD group, the risk of MACE was elevated to 141.9% [hazard ratio (HR) = 1.419, 95% confidence interval (CI): 1.164-1.730, p = 0.001] in the Cox univariable regression analyses; after adjusting co-variables, the Cox multivariable regression analyses demonstrated that DKD was an independent predictor for MACE (HR = 1.291, 95% CI: 1.027-1.624, p = 0.029) in patients with CAD after PCI, as well as in cardiovascular death events (HR = 2.148, 95% CI: 1.292-3.572, p = 0.003) and all-cause death events (HR = 2.229, 95% CI: 1.325-3.749, p = 0.003). This study suggests that DKD is an independent and novel predictor of long-term adverse outcomes in patients with CAD and DM who underwent PCI.

Spherization indices measured by resting SPECT improve risk stratification in patients with ischemia with non-obstructive coronary artery disease (INOCA)

BackgroundThe prevalence of ischemia with non-obstructive coronary artery disease (INOCA) is substantial, but its risk stratification has been suboptimal. Resting SPECT myocardial perfusion imaging (MPI) could provide useful heart information including spherical indices. We aimed to evaluate the prognostic value of spherical indices in individuals with INOCA.ResultsDuring a median follow-up of 47.2 ± 20.8 months, 49 (17.2%) patients experienced major adverse cardiac events (MACE). Compared to those without MACE, those with MACE had a higher shape index (SI) (0.60 ± 0.07 vs. 0.58 ± 0.06; P = 0.028) and a lower E2 (eccentricity index calculated by the QPS) (0.81 ± 0.05 vs. 0.83 ± 0.04; P = 0.019). MACE event-free survival analysis revealed significant differences in the SI and E2 among all patients (all log-rank P < 0.01). Multivariate Cox analysis showed abnormal SI (HR: 2.73, 95% CI 1.44–5.18, P = 0.002) and E2 (HR: 1.94, 95% CI 1.08–3.48, P = 0.026) were both independent predictors for MACE when they were put into the same model, respectively. The incorporation of the SI into the baseline model demonstrated a significant improvement in the predictive accuracy for MACEs (P = 0.026), whereas E2 did not exhibit a similar improvement (P > 0.05).ConclusionFor patients with INOCA, spherical indices (especially the SI) were associated with long-term MACE, which could be a preferable indicator for risk stratification and prognostic prediction.

Long-term prognosis and prognostic factors after primary prophylactic implantable cardioverter-defibrillator therapy

BackgroundLittle is known regarding which patients with ischemic cardiomyopathy (ICM) should be considered for prophylactic therapies, such as an implantable cardioverter-defibrillator (ICD), in the primary percutaneous intervention era. The aim of this study was to investigate the influence of non-sustained ventricular tachycardia (NSVT) on major adverse cardiac events (MACE) in heart failure with reduced ejection fraction (HFrEF) patients. MethodsWe retrospectively analyzed patients of ICM and non-ICM who underwent ICD implantation at our institute from October 2006 to August 2020. MACE were defined as composite outcome of cardiovascular death, heart failure hospitalization, and appropriate ICD therapies. ResultsA total of 167 patients were enrolled [male, 138 (83 %); age, 62.1 ± 11.7 years; left ventricular ejection fraction, 23.5 ± 6.1 %; left ventricular diastolic diameter, 67.4 ± 9.0 mm; atrial fibrillation, 47 (28 %); NSVT, 124 (74 %); use of class III antiarrhythmic drugs, 55 (33 %); ischemic cardiomyopathy, 56 (34 %); cardiac resynchronization therapy, 73 (44 %)]. The median follow-up duration was 61 months. MACE occurred with 71 patients (43 %). When comparing baseline characteristics of the patients, left ventricular ejection fraction (p = 0.02) and atrial fibrillation (p = 0.04) were significantly associated with MACE. The multivariable Cox analysis for the target variable MACE identified atrial fibrillation (hazard ratio 2.00; 95 % confidence index 1.18–3.37; p = 0.01) as an independent predictor for MACE. ConclusionsPrior NSVT before ICD implantation was not an independent predictor of future MACE in patients with HFrEF with primary prophylactic ICD. In contrast, atrial fibrillation was associated with worse prognosis. To predict the prognosis of patients with primary prophylactic ICD, these factors should be assessed as comprehensive risk stratification factors for MACE.

Fractal Analysis of Left Ventricular Trabeculae in Patients with End-Stage Renal Disease: A Random Survival Tree Analysis.

The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. To evaluate the prognostic value of LV trabecular complexity in patients with end-stage renal disease (ESRD). Prospective outcome study. 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. 3.0T, steady-state free precession (SSFP) and modified Look-Locker imaging sequences. All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low- and high-risk groups based on scores derived from the RF model and survival compared. Receiver operating characteristic curve analysis; Kaplan-Meier survival analysis with log rank tests; Harrel's C-index to assess model performance. A P value <0.05 was considered statistically significant. Fifty-five patients (26.57%) experienced MACE during a median follow-up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C-index: 0.81) had significantly better discrimination than the Cox regression model (C-index: 0.74). Participants of the external validation dataset classified into the high-risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low-risk group. LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. 2 TECHNICAL EFFICACY: Stage 2.

Clinical characteristics and prognosis of patients with hypertrophic cardiomyopathy and heart failure with preserved ejection fraction.

Whether heart failure with preserved ejection fraction (HFpEF) is associated with an increased risk of developing systolic dysfunction and a poor prognosis in hypertrophic cardiomyopathy (HCM) patients is unknown. We aimed to assess risk factors for the development of end-stage (ES) heart failure (HF) (ejection fraction < 50%) and compare the prognosis of different HF phenotypes. This retrospective study was conducted on patients with HCM in China between January 2009 and February 2023. Patients were stratified into three different groups: HCM-non-HF, HCM-HFpEF and HCM-heart failure with reduced ejection fraction (HCM-HFrEF). The primary outcome was a composite of major adverse cardiac events (MACEs), including all-cause deaths, HF hospitalization, sudden cardiac death and ventricular tachycardia. Of 3,620 HCM patients enrolled, 1,553 (42.9%) had non-HF, 1,666 (46.0%) had HFpEF, and 579 patients (11.1%) had HFrEF at baseline. During the median follow-up period of 4.0 years (IQR 1.4-9.4 years), patients with HCM-HFpEF exhibited a higher incidence of ES-HF than those with HCM-non-HF (12.4% vs. 2.7%, P < 0.001). HFpEF was an independent risk factor for ES-HF development (HR 3.84, 2.54-5.80, P < 0.001). MACEs occurred in 26.9% with a higher incidence in HCM-HFpEF than HCM-non-HF (36.6% vs 12.2%, P < 0.001). HFpEF was an independent predictor of MACEs (HR 2.13, 1.75-2.59, P < 0.001). HFpEF is common in HCM. Compared to non-HF, it increases the risk of LVEF decline and poor prognosis. It may aid in risk stratification and need close echocardiography follow-up.

Optimized gated a SPECT-derived myocardial salvage index: its prognostic significance in predicting major adverse cardiac events following acute myocardial infarction percussion.

Estimate myocardial salvage index (MSI) using a single-gated Single-Photon Emission Computed Tomography (SPECT) myocardial perfusion imaging (GSMPI) early after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI) and compare its predictive value with the traditional method especially for post-PCI left ventricular ejection fraction (LVEF) improvement and major adverse cardiac events (MACEs). GSMPI was performed in 62 patients with AMI early after PCI (3-10days). The MSI and the conventional parameters were obtained, including total perfusion deficit, LVEF, peak ejection rate (PER), and peak filling rate (PFR). The new calculation method (scoring evaluation method means the extent of abnormality is the percentage of the total scores of abnormal segments divided by the sum of the maximum scores of all myocardial segments using 4-point and 5-point scale semi-quantitative scoring method) and the reference method (number evaluation method means the extent of abnormality is the percentage of the number of abnormal segments divided by the total number of myocardial segments) were applied to acquire the MSI. We compared the predictive ability of the 2 methods based on the area under the receiver operating characteristic curve for LVEF improvement 6months after PCI using MSI. The Kaplan-Meier method was used for depicting survival curves for predicting MACEs by the 2 methods. Cox proportional-hazards regression was applied to confirm the independent predictors of MACEs. The MSI obtained by the new method indicated stronger prognostic significance in LVEF improvement [area under the curve (AUC): 0.793, 95% confidence interval (CI) 0.620-0.912, P < .001] compared with the reference method (AUC: 0.634, 95%CI 0.452-0.792, P = .187). Delong's test revealed a statistically significant difference in AUCs between the 2 methods (P < .05, 95%CI 0.003-0.316). The diagnostic value of the scoring evaluation method was higher than that of the number evaluation method. The Cox prevalence of MACEs was substantially higher in the < median MSI group than in the ≥ median MSI group (hazard ratio: 0.172; 95% CI 0.041-0.724; P < .05] using the new method, whereas no considerable differences were observed between the 2 groups using the reference method (P = .12). Further, the multivariate Cox regression analysis revealed that MSI was an independent indicator for predicting MACEs (P < .05). The MSI obtained from a simple GSMPI early after PCI, using the scoring evaluation method, was a reliable prognostic indicator for predicting LVEF improvement and MACEs in AMI. It remarkably improved the prognostic value compared with the previous reference methods.

Left Ventricular-Arterial Coupling as an Independent Predictor of Adverse Events in Young Patients with ST Elevation Myocardial Infarction-A 3D Echocardiographic Study.

Left ventricular-arterial coupling (VAC) is a key determinant of global cardiovascular performance, calculated as the ratio between arterial elastance (EA) and left ventricular end-systolic elastance (EES). Over the years, acute myocardial infarction (STEMI) has remained an important cause of morbidity and mortality worldwide. Although, until recently, it was considered a disease occurring mostly in older patients, its prevalence in the young population is continuously rising. In this study, we aimed to investigate the role of 3D VAC and its derived indices in predicting adverse outcomes in young patients with STEMI. We prospectively enrolled 84 young patients (18-51 years) with STEMI who underwent primary PCI and 28 healthy age and sex-matched controls. A 3D echocardiography was used for non-invasive measurements of end-systolic elastance (EES), arterial elastance (EA), and VAC (EA/EES). The occurrence of major adverse cardiac events (MACE) was assessed one year after the index STEMI. Out of 84 patients, 15.4% had adverse events at 12 months follow-up. Patients were divided into two groups according to the presence or absence of MACE. There were no significant differences in arterial elastance between the two groups. EA was higher in the MACE group but without statistical significance (2.65 vs. 2.33; p = 0.09). EES was significantly lower in the MACE group (1.25 ± 0.34 vs. 1.91 ± 0.56. p < 0.0001) and VAC was higher (2.2 ± 0.62 vs. 1.24 ± 0.29, p < 0.0001). ROC analysis showed that VAC has a better predictive value for MACE (AUC 0.927) compared with EA or EEA but also compared with a classical determinant of LV function (LVEF and LVGLS). A VAC value over 1.71 predicts unfavourable outcome with 83.3% sensitivity and 97.1% specificity. In both univariate and multivariate COX regression analysis, VAC remained an independent predictor for MACE and demonstrated incremental prognostic value over LVEF and LVGLS in the proposed statistical models. In conclusion, 3D VAC is an independent predictor of adverse events in young patients with STEMI at a 12 month follow-ups and could be used for a more accurate risk stratification in the acute phase.

Prognostic value of mid-term cardiovascular magnetic resonance follow-up in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study

BackgroundThe prognostic value of follow-up cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) patients is unclear. We aimed to investigate the prognostic value of cardiac function, structure, and tissue characteristics at mid-term CMR follow-up. MethodsThe study population was a prospectively enrolled cohort of DCM patients who underwent guideline-directed medical therapy with baseline and follow-up CMR, which included measurement of biventricular volume and ejection fraction, late gadolinium enhancement, native T1, native T2, and extracellular volume. During follow-up, major adverse cardiac events (MACE) were defined as a composite endpoint of cardiovascular death, heart transplantation, and heart-failure readmission. ResultsAmong 235 DCM patients (median CMR interval: 15.3 months; interquartile range: 12.5–19.2 months), 54 (23.0%) experienced MACE during follow-up (median: 31.2 months; interquartile range: 20.8–50.0 months). In multivariable Cox regression, follow-up CMR models showed significantly superior predictive value than baseline CMR models. Stepwise multivariate Cox regression showed that follow-up left ventricular ejection fraction (LVEF; hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.91–0.96; p < 0.001) and native T1 (HR, 1.01; 95% CI, 1.00–1.01; p = 0.030) were independent predictors of MACE. Follow-up LVEF ≥ 40% or stable LVEF < 40% with T1 ≤ 1273 ms indicated low risk (annual event rate < 4%), while stable LVEF < 40% and T1 > 1273 ms or LVEF < 40% with deterioration indicated high risk (annual event rate > 15%). ConclusionsFollow-up CMR provided better risk stratification than baseline CMR. Improvements in the LVEF and T1 mapping are associated with a lower risk of MACE.

A pilot study of S100A4, S100A8/A9, and S100A12 in dilated cardiomyopathy: novel biomarkers for diagnosis or prognosis?

Circulating biomarkers can provide important information for the diagnosis and prognosis of dilated cardiomyopathy (DCM). We explored novel biomarkers for the diagnosis and prognosis of DCM to improve clinical decision-making. A total of 238 DCM patients and 65 control were consecutively enrolled at Zhongshan Hospital between January 2017 and January 2019. In the screening set, four DCM patients and four controls underwent measurements of serum proteomic analysis. Seventy-six differentially expressed circulating proteins were screened by data-independent acquisition proteomics, and three of these proteins (S100A4, S100A8/A9, and S100A12) were validated by multiple-reaction monitoring-mass spectrometry. In the validation set, subsequently, a total of 234 DCM patients and 61 control subjects were evaluated by enzyme-linked immunosorbent assay. Circulating S100A4, S100A8/A9, and S100A12 were significantly increased in DCM patients (P<0.001). These three proteins were significant positively correlated with other parameters, such as Lg (NT-proBNP), IL-1β, TGF-β, CRP, left ventricular end-diastolic diameter, and left ventricular end-systolic diameter, whereas they were negatively correlated with left ventricular ejection fraction, respectively (P<0.05). The receiver operator characteristic curve showed the combination of S100A4, S100A8/A9, and S100A12 [area under curve (AUC) 0.88, 95% confidence interval (CI) 0.84-0.93] was better than single S100A4 (AUC 0.74, 95% CI 0.68-0.81), S100A8/A9 (AUC 0.82, 95% CI 0.77-0.88), or S100A12 (AUC 0.80, 95% CI 0.72-0.88) in the diagnosis of DCM (P<0.01). After a median follow-up period of 33.5months, 110 patients (47.01%) experienced major adverse cardiac events (MACEs), including 46 who had cardiac deaths and 64 who had heart failure rehospitalizations. Kaplan-Meier analysis indicated that the DCM patients with ≥75th percentile level of S100A4 had a significantly higher incidence of MACEs than those with <75th percentile level of S100A4 (61.40% vs. 42.37%, P<0.05). There were no significant differences of MACE rate among DCM patients with different concentrations of S100A8/A9 and S100A12 (P>0.05). Cox proportional hazards regression analysis revealed that S100A4 [≥75th percentile vs. <75th percentile: hazard ratio (HR) 1.65; 95% CI 1.11-2.45] remained significant independent predictors for MACEs (P<0.05); however, S100A8/A9 and S100A12 were not independent factors for predicting MACE (P≥0.05). S100A4, S100A8/A9, and S100A12 may be additional diagnostic tools for human DCM recognition, and the combination of these three indicators helped to improve the accuracy of a single index to diagnose DCM. Additionally, S100A4 was identified as a significant predictor of prognosis in patients with DCM.