scholarly journals Diagnosing and sports counselling of athletes with myocarditis

2019 ◽  
Vol 67 (2) ◽  
Keyword(s):  
Risk Stratification ◽  
Tissue Characterization ◽  
T2 Mapping ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Individual Risk ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction ◽  
Characterization Methods ◽  
Imaging Tool

Myocarditis is defined as an inflammation of the heart muscle and its presentation, especially in athletes, is heterogeneous. Underlying causes include in most of the cases viruses, and less often bacteria, toxins, vasculitic diseases or pharmaceutical agents. Cardiac magnetic resonance (CMR) imaging is the primary imaging tool to diagnose myocarditis following laboratory test, electrocardiogram and echocardiography. In certain cases, endomyocardial biopsy is required, especially in unclear cases with reduced systolic left ventricular ejection fraction. Although, athletes and sport physicians face the dilemma of significant performance decline in competitive athletes against the risk of adverse cardiac events, currently abstinence from competitive sports is recommended for at least 3–6 months in myocarditis. Sports recommendations are currently based mainly on autopsy studies and experts’ opinions and better risk stratification tools are imperatively needed. New tissue characterization methods, namely T1 mapping and T2 mapping in CMR continue to improve sensitivity and specificity of diagnosing myocarditis and may further enhance individual risk assessment. In the future, sports physicians may be able to rely more on these novel noninvasive tissue characterisation methods in risk stratification and sports restriction recommendations of athletes with suspected myocarditis.

scholarly journals Prognostic Significance of CMR Findings in Patients with Known Coronary Artery Disease – Experience from a South Asian Country

2020 ◽  
Vol 10 ◽  
pp. 75
Author(s):  
Syed Waqar Ahmed ◽  
Fateh Ali Tipoo Sultan ◽  
Safia Awan ◽  
Imran Ahmed
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Stratification ◽  
South Asian ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction ◽  
Artery Disease

Objectives: South Asians (SA) have a higher burden of coronary artery disease (CAD) and are known to have a worse prognosis compared to other ethnicities. Therefore, it is imperative to improve the risk stratification of SA patient with CAD and to seek out newer prognostic markers beyond the conventional echocardiography.The aim of this study was to investigate whether variables obtained by cardiac magnetic resonance (CMR) improve risk stratification of South Asian patients with known CAD. Material and Methods: We retrospectively analyzed 147 patients with evidence of CAD that had a CMR at our center between January 2011 and January 2019. LV volumes and regional wall motions were acquired by cine images, while infarct size (IS) was measured by late gadolinium enhancement. At a mean follow-up of 3.36 ± 2.22 years, cardiac events (non-fatal myocardial infarction, hospitalization due to heart failure, life-threatening arrhythmia, or cardiac death) occurred in 49 patients. An IS ≥35%, left ventricular ejection fraction (LVEF) ≤31%, and a wall motion score index (WMSI) ≥1.9 were strongly associated with follow-up cardiac events (P < 0.001). Patients that had none or less than 3 of these factors, showed a lower risk of cardiac events (HR 0.22 CI [0.11–0.44] P < 0.001 and HR 0.12 CI [0.04–0.32] P < 0.001, respectively) compared to those with all three factors. Conclusion: Integration of CMR derived factors such as IS and WMSI with LVEF can improve the prognostication of the SA population with CAD. Better risk stratification of patients can lead to improved and cost-effective therapeutic strategies to ameliorate the prognosis of these patients.

scholarly journals Galectin 3 and Galectin 3 Binding Protein Improve the Risk Stratification after Myocardial Infarction

2019 ◽  
Vol 8 (5) ◽  
pp. 570
Author(s):  
Giulia Gagno ◽  
Laura Padoan ◽  
Elisabetta Stenner ◽  
Alessandro Beleù ◽  
Fabiana Ziberna ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
Risk Stratification ◽  
Roc Curve ◽  
Binding Protein ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction ◽  
All Cause Mortality ◽  
Galectin 3

Background: Acute myocardial infarction (AMI) survivors are at risk of major adverse cardiac events and their risk stratification is a prerequisite to tailored therapeutic approaches. Biomarkers could be of great utility in this setting. Methods: We sought to evaluate the utility of the combined assessment of Galectin 3 (Gal-3) and Galectin 3 binding protein (Gal-3bp) for post-AMI risk stratification in a large, consecutive population of AMI patients. The primary outcomes were: Recurrent angina/AMI and all-cause mortality at 12 months after the index event. Results: In total, 469 patients were included. The median Gal-3bp was 9.1 μg/mL (IQR 5.8–13.5 μg/mL), while median Gal-3 was 9.8 ng/mL (IQR 7.8–12.8 ng/mL). During the 12 month follow-up, 34 patients died and 41 had angina pectoris/reinfarction. Gal-3 was associated with all-cause mortality, while Gal-3bp correlated with the risk of angina/myocardial infarction even when corrected for other significant covariates. The final multivariable model for mortality prediction included patients’ age, left ventricular ejection fraction (LVEF), Gal-3, and renal function. The ROC curve estimated for this model has an area under the curve (AUC) of 0.84 (95%CI 0.78–0.9), which was similar to the area under the ROC curve obtained using the GRACE score 1-year mortality. Conclusions: The integrated assessment of Gal-3 and Gal-3bp could be helpful in risk stratification after AMI.

scholarly journals The Role of AI in Characterizing the DCM Phenotype

2021 ◽  
Vol 8 ◽  
Author(s):  
Clint Asher ◽  
Esther Puyol-Antón ◽  
Maleeha Rizvi ◽  
Bram Ruijsink ◽  
Amedeo Chiribiri ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Risk Stratification ◽  
Dilated Cardiomyopathy ◽  
Tissue Characterization ◽  
Left Ventricular ◽  
Muscle Disease ◽  
Left Ventricular Ejection ◽  
Ventricular Ejection Fraction ◽  
Care Assessment

Dilated Cardiomyopathy is conventionally defined by left ventricular dilatation and dysfunction in the absence of coronary disease. Emerging evidence suggests many patients remain vulnerable to major adverse outcomes despite clear therapeutic success of modern evidence-based heart failure therapy. In this era of personalized medical care, the conventional assessment of left ventricular ejection fraction falls short in fully predicting evolution and risk of outcomes in this heterogenous group of heart muscle disease, as such, a more refined means of phenotyping this disease appears essential. Cardiac MRI (CMR) is well-placed in this respect, not only for its diagnostic utility, but the wealth of information captured in global and regional function assessment with the addition of unique tissue characterization across different disease states and patient cohorts. Advanced tools are needed to leverage these sensitive metrics and integrate with clinical, genetic and biochemical information for personalized, and more clinically useful characterization of the dilated cardiomyopathy phenotype. Recent advances in artificial intelligence offers the unique opportunity to impact clinical decision making through enhanced precision image-analysis tasks, multi-source extraction of relevant features and seamless integration to enhance understanding, improve diagnosis, and subsequently clinical outcomes. Focusing particularly on deep learning, a subfield of artificial intelligence, that has garnered significant interest in the imaging community, this paper reviews the main developments that could offer more robust disease characterization and risk stratification in the Dilated Cardiomyopathy phenotype. Given its promising utility in the non-invasive assessment of cardiac diseases, we firstly highlight the key applications in CMR, set to enable comprehensive quantitative measures of function beyond the standard of care assessment. Concurrently, we revisit the added value of tissue characterization techniques for risk stratification, showcasing the deep learning platforms that overcome limitations in current clinical workflows and discuss how they could be utilized to better differentiate at-risk subgroups of this phenotype. The final section of this paper is dedicated to the allied clinical applications to imaging, that incorporate artificial intelligence and have harnessed the comprehensive abundance of data from genetics and relevant clinical variables to facilitate better classification and enable enhanced risk prediction for relevant outcomes.

Risk stratification in hf with mid-range LVEF: the role of cardiopulmonary exercise testing

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
B.M.L Rocha ◽  
G.J Lopes Da Cunha ◽  
P.M.D Lopes ◽  
P.N Freitas ◽  
F Gama ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Exercise Testing ◽  
Primary Endpoint ◽  
Prognostic Significance ◽  
Cardiopulmonary Exercise Testing ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Ventricular Ejection Fraction ◽  
Cardiopulmonary Exercise

Abstract Background Cardiopulmonary exercise testing (CPET) is recommended in the evaluation of selected patients with Heart Failure (HF). Notwithstanding, its prognostic significance has mainly been ascertained in those with left ventricular ejection fraction (LVEF) &lt;40% (i.e., HFrEF). The main goal of our study was to assess the role of CPET in risk stratification of HF with mid-range (40–49%) LVEF (i.e., HFmrEF) compared to HFrEF. Methods We conducted a single-center retrospective study of consecutive patients with HF and LVEF &lt;50% who underwent CPET from 2003–2018. The primary composite endpoint of death, heart transplant or HF hospitalization was assessed. Results Overall, 404 HF patients (mean age 57±11 years, 78.2% male, 55.4% ischemic HF) were included, of whom 321 (79.5%) had HFrEF and 83 (20.5%) HFmrEF. Compared to the former, those with HFmrEF had a significantly higher mean peak oxygen uptake (pVO2) (20.2±6.1 vs 16.1±5.0 mL/kg/min; p&lt;0.001), lower median minute ventilation/carbon dioxide production (VE/VCO2) [35.0 (IQR: 29.1–41.2) vs 39.0 (IQR: 32.0–47.0); p=0.002) and fewer patients with exercise oscillatory ventilation (EOV) (22.0 vs 46.3%; p&lt;0.001). Over a median follow-up of 28.7 (IQR: 13.0–92.3) months, 117 (28.9%) patients died, 53 (13.1%) underwent heart transplantation, and 134 (33.2%) had at least one HF hospitalization. In both HFmrEF and HFrEF, pVO2 &lt;12 mL/kg/min, VE/VCO2 &gt;35 and EOV identified patients at higher risk for events (all p&lt;0.05). In Cox regression multivariate analysis, pVO2 was predictive of the primary endpoint in both HFmrEF and HFrEF (HR per +1 mL/kg/min: 0.81; CI: 0.72–0.92; p=0.001; and HR per +1 mL/kg/min: 0.92; CI: 0.87–0.97; p=0.004), as was EOV (HR: 4.79; CI: 1.41–16.39; p=0.012; and HR: 2.15; CI: 1.51–3.07; p&lt;0.001). VE/VCO2, on the other hand, was predictive of events in HFrEF but not in HFmrEF (HR per unit: 1.03; CI: 1.02–1.05; p&lt;0.001; and HR per unit: 0.99; CI: 0.95–1.03; p=0.512, respectively). ROC curve analysis demonstrated that a pVO2 &gt;16.7 and &gt;15.8 mL/kg/min more accurately identified patients at lower risk for the primary endpoint (NPV: 91.2 and 60.5% for HFmrEF and HFrEF, respectively; both p&lt;0.001). Conclusions CPET is a useful tool in HFmrEF. Both pVO2 and EOV independently predicted the primary endpoint in HFmrEF and HFrEF, contrasting with VE/VCO2, which remained predictive only in latter group. Our findings strengthen the prognostic role of CPET in HF with either reduced or mid-range LVEF. Funding Acknowledgement Type of funding source: None

Abstract 13785: Left Ventricular Contractile Entropy in 99mTc-Sestamibi SPECT is a Novel Prognostic Predictor in Patients with Non-ischemic Dilated Cardiomyopathy

Circulation ◽  
2014 ◽  
Vol 130 (suppl_2) ◽  
Author(s):  
Naoaki Kano ◽  
Takahiro Okumura ◽  
Akinori Sawamura ◽  
Naoki Watanabe ◽  
Hiroaki Mori ◽  
...  
Keyword(s):  
Dilated Cardiomyopathy ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Sampling Point ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction ◽  
Qrs Duration ◽  
Non Ischemic Dilated Cardiomyopathy ◽  
The Mean ◽  
99Mtc Sestamibi

Background: It has been reported that mechanical dispersion of myocardial contraction is increased in failing myocardium. However little is known about the association between contractile entropy evaluated by myocardial scintigraphy and prognosis in patients with non-ischemic dilated cardiomyopathy (NIDCM). Purpose: We aimed to investigate the prognostic value of contractile entropy in patients with NIDCM. Methods: Forty-seven patients (38 male, 55.1 years) with NIDCM were performed gated 99mTc-sestamibi myocardial perfusion SPECT (GMPS) and endomyocardial biopsy. Entropy was automatically calculated as a result of contractile phase analysis for each myocardial sampling point from GMPS, and it reflects a dispersion of global mechanical contraction. All patients were allocated into two groups based on the median of entropy; HE-group: entropy≥0.61 and LE-group: entropy<0.61. All patients were followed up at the mean of 2.8 years. Results: The mean QRS duration, left ventricular ejection fraction (LVEF) and plasma brain natriuretic peptide (BNP) levels were 114 msec, 35% and 225 pg/mL, respectively. Although there were no significant differences in QRS duration and plasma BNP levels between the two groups, LVEF was lower in the HE-group than in the LE-group (31.1% vs 39.8%, p=0.002). In Kaplan-Meier survival analysis, cardiac event rate was significantly higher in the HE-group (Figure). Cox proportional hazard analysis revealed that the HE-group was a significant determinant of cardiac events (Hazard Ratio: 7.66; 95%CI: 0.070-2.532; p=0.033). The mRNA expression level of sarcoplasmic endoplasmic reticulum Ca2+ ATPase (SERCA2a) in biopsy specimens was significantly lower in the LE-group (p=0.015). Conclusion: Contractile entropy, reflecting an impairment of global left ventricular contraction, might be useful to predict a poor prognosis in patients with NIDCM.

scholarly journals Serum autotaxin level predicts future cardiac events in patients with dilated cardiomyopathy

2021 ◽  
Vol 42 (Supplement_1) ◽  
Author(s):  
T Araki ◽  
T Okumura ◽  
T Mizutani ◽  
Y Kimura ◽  
S Kazama ◽  
...  
Keyword(s):  
Survival Analysis ◽  
Dilated Cardiomyopathy ◽  
Volume Fraction ◽  
Left Ventricular ◽  
Cox Proportional Hazards ◽  
Left Ventricular Ejection ◽  
Myocardial Inflammation ◽  
Prognostic Impact ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction

Abstract Background Autotaxin (ATX) has been reported to promote myocardial inflammation and subsequent cardiac remodeling through lysophosphatidic acid (LPA) production. However, the prognostic impact of ATX has not been clarified in dilated cardiomyopathy (DCM). Purpose We aimed to investigate the prognostic impact of ATX in patients with DCM. Methods We enrolled 104 DCM patients (49.8 years, 76 males). The subjects underwent blood sampling, echocardiography, cardiac catheterization, and endomyocardial biopsy. Gender differences in serum ATX levels have been reported, thus we divided the subjects into two groups using median serum ATX levels for men and women: High-ATX group and Low-ATX group. All patients were followed up by expert cardiologists. The cardiac event was defined as a composite of cardiac death and hospitalization for worsening heart failure. Results Eighty-nine percent of the subjects were classified as New York Heart Association functional class I or II. Female patients had higher serum ATX levels than male patients, with median values of 257.0 ng/mL and 203.5 ng/mL, respectively (Figure A). The average left ventricular ejection fraction and brain natriuretic peptide levels were 30.6% and 122.5 pg/mL. In survival analysis, cumulative event-free probability was significantly lower in High ATX group (p=0.007, Figure B). In Cox proportional hazards analysis, High-ATX was one of the independent predictors of composite cardiac events (Hazards Ratio, 2.575; p=0.043). On the other hand, high sensitive C-reactive protein and collagen volume fraction in myocardial samples were not significant predictors. Conclusion High serum ATX level was associated with poor prognosis in patients with DCM. FUNDunding Acknowledgement Type of funding sources: None. Gender difference in autotaxin levels Survival analysis of cardiac events

Beyond ejection fraction: Novel clinical approaches towards sudden cardiac death risk stratification in patients with dilated cardiomyopathy

2021 ◽  
Vol 17 ◽  
Author(s):  
Issa Pour-Ghaz ◽  
Mark Heckle ◽  
Ikechukwu Ifedili ◽  
Sharif Kayali ◽  
Christopher Nance ◽  
...  
Keyword(s):  
Sudden Cardiac Death ◽  
Ejection Fraction ◽  
Risk Stratification ◽  
Cardiac Death ◽  
Ventricular Tachyarrhythmia ◽  
Total Mortality ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Ventricular Ejection Fraction ◽  
Icd Therapy

: Implantable cardioverter-defibrillator (ICD) therapy is indicated for patients at risk for sudden cardiac death due to ventricular tachyarrhythmia. The most commonly used risk stratification algorithms use left ventricular ejection fraction (LVEF) to determine which patients qualify for ICD therapy, even though LVEF is a better marker of total mortality than ventricular tachyarrhythmias mortality. This review evaluates imaging tools and novel biomarkers proposed for better risk stratifying arrhythmic substrate, thereby identifying optimal ICD therapy candidates.

Predicting mortality for patients with heart failure beyond oxygen consumption: a prognostic risk score

2021 ◽  
Author(s):  
Hanaa Shafiek ◽  
Andres Grau ◽  
Jaume Pons ◽  
Pere Pericas ◽  
Xavier Rossello ◽  
...  
Keyword(s):  
Heart Failure ◽  
Chronic Heart Failure ◽  
Risk Score ◽  
Cardiac Transplantation ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Functional Evaluation ◽  
Cardiac Events ◽  
Ventricular Ejection Fraction

Background: Cardiopulmonary exercise test (CPET) is a crucial tool for the functional evaluation of cardiac patients. We hypothesized that VO2 max and VE/VCO2 slope are not the only parameters of CPET able to predict major cardiac events (mortality or cardiac transplantation urgently or elective). Objectives: We aimed to identify the best CPET predictors of major cardiac events in patients with severe chronic heart failure and to propose an integrated score that could be applied for their prognostic evaluation. Methods: We evaluated 140 patients with chronic heart failure who underwent CPET between 2011 and 2019. Major cardiac events were evaluated during follow-up. Univariate and multivariate logistic regression analysis were applied to study the predictive value of different clinical, echocardiographic and CPET parameters in relation to the major cardiac events. A score was generated and c-statistic was used for the comparisons. Results: Thirty-nine patients (27.9%) died or underwent cardiac transplantation over a median follow-up of 48 months. Five parameters (maximal workload, breathing reserve, left ventricular ejection fraction, diastolic dysfunction and non-idiopathic cardiomyopathy) were used to generate a risk score that had better risk discrimination than NYHA dyspnea scale, VO2 max, VE/VCO2 slope > 35 alone, and combined VO2 max and VE/VCO2 slope (p= 0.009, 0.004, < 0.001 and 0.005 respectively) in predicting major cardiac events. Conclusions: A composite score of CPET and clinical/echocardiographic data is more reliable than the single use of VO2max or combined with VE/VCO2 slope to predict major cardiac events.

Abstract 16457: Markers of Diabetes and Renal Function Extend Sudden Death Risk Assessment Beyond the Ejection Fraction

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Kumar Narayanan ◽  
Audrey Uy-Evanado ◽  
Carmen Teodorescu ◽  
Kyndaron Reinier ◽  
Karen Gunson ◽  
...  
Keyword(s):  
Ejection Fraction ◽  
Risk Stratification ◽  
Serum Creatinine ◽  
Glycosylated Hemoglobin ◽  
Left Ventricular ◽  
Metropolitan Region ◽  
Left Ventricular Ejection ◽  
Ventricular Ejection Fraction ◽  
Catchment Population ◽  
Risk Stratification Model

Introduction: Although diabetes and renal dysfunction are known to be associated with SCD risk, the cumulative risk of objective laboratory markers in combination with left ventricular ejection fraction (LVEF) has not been previously evaluated. Hypothesis: Addition of glycosylated hemoglobin (HbA1C) and serum creatinine levels to LVEF can improve the SCD risk stratification model. Methods: As part of a large, prospective, ongoing study of SCD in a Northwestern US metropolitan region (catchment population about 1 million), SCD cases were compared with controls with coronary artery disease (CAD) and no SCD from the same geographic location. HbA1C, serum creatinine levels and LVEF (all prior and unrelated to the SCD event for cases) were obtained for all subjects. Odds ratios for SCD associated with abnormal HbA1C (≥ 7%) and creatinine (≥ 1.5 mg/dL) levels was calculated. Cumulative odds and improvement in model performance on addition of elevated lab markers to low LVEF (≤ 35%) was assessed. Results: 243 SCD cases (68.7 ± 13.2 yrs; 62.1% male) and 159 CAD controls (66.2 ± 9.9 yrs; 65.6% male) with appropriate lab values and LVEF information were evaluated. The mean HbA1C (7.3 ± 2.3 vs. 6.6 ± 1.5%) and creatinine (1.8 ± 1.7 vs. 1.2 ± 0.7 mg/dL) levels were significantly higher in cases. Cases were significantly more likely to have HbA1C ≥ 7% (49.4 vs. 27.7%; p<0.0001) or creatinine ≥ 1.5 mg/dL (39.1% vs. 13.8%) (all p<0.0001). After adjustment for age, sex and low LVEF, high HbA1C (OR 2.3, 95% CI 1.4-3.6; p=0.001) and high creatinine (OR 3.3, 95% CI 1.9-5.7; p<0.0001) were independently associated with SCD; LVEF ≤ 35% was associated as well (OR 1.8, 95% CI 1.1-3.2; p=0.05). As compared to neither lab marker being high, elevation of one marker (OR 2.4, 95% CI 1.5-3.9) or both markers (OR 7.9, 95% CI 3.5-17.6) was associated with progressive increase in SCD odds. Addition of lab markers to a risk stratification model with only LVEF improved model discrimination significantly (AUC 0.613 vs. 0.709; p=0.01). Conclusions: HbA1C and serum creatinine improved the SCD risk stratification model when added to LVEF. Further investigation is warranted before clinical use, including consideration of competing risks that influence overall mortality.

New techniques for risk assessment in sudden cardiac death

ESC CardioMed ◽  
2018 ◽  
pp. 2327-2330
Author(s):  
Juan Fernandez-Armenta ◽  
Antonio Berruezo ◽  
Juan Acosta ◽  
Diego Penela
Keyword(s):  
Risk Assessment ◽  
Sudden Cardiac Death ◽  
Left Ventricular Ejection Fraction ◽  
Ejection Fraction ◽  
Cardiac Death ◽  
Left Ventricular ◽  
Ventricular Ejection ◽  
Left Ventricular Ejection ◽  
Individual Risk ◽  
Ventricular Ejection Fraction

Risk stratification for sudden cardiac death (SCD) is one of the main objectives of clinical arrhythmology. Despite increased knowledge of the fundamental basis and predictors of SCD, the estimation of individual risk remains challenging. To date, symptomatic heart failure and reduced left ventricular ejection fraction are the main variables used to identify patients at high risk of SCD who could potentially benefit from preventive therapies. Beyond left ventricular ejection fraction, new diagnostic tools have been proposed to better stratify patients at risk of SCD. Among them, cardiovascular magnetic resonance imaging, which allows direct visualization of the arrhythmogenic substrate, is considered particularly promising. Genetic testing and serum biomarkers may also have a role in SCD risk assessment.

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