Long-term imaging analysis of a myocarditis case: Utilizing strain with echocardiography and cardiovascular magnetic resonance findings.

Herein, we report a case of myocarditis in a 27-year-old male with long-term follow-up using longitudinal peak systolic strain (LPSS) measurements with transthoracic echocardiography (TTE) and late gadolinium enhancement (LGE) in cardiovascular magnetic resonance imaging (CMR). On admission, a predominant decrease was observed in the LPSS in the posterolateral segments of the TTE. After a period of two weeks, the values of the LPSS observed in the posterolateral segments were still slightly reduced, which is consistent with the LGE results in CMR. After a duration of 16 months, an improvement was noted in the LPSS and LGE results in all the segments. Moreover, a time-phase discrepancy was observed in the segmental longitudinal strain curve for a period of two weeks from the onset of myocarditis. However, an improvement in the discrepancy was detected after 16 months. Learning objective: Longitudinal peak systolic strain (LPSS) on transthoracic echocardiography (TTE) has predominantly focused on diagnosing the acute phase of myocarditis. Herein, LPSS was evaluated not only in the acute phase but also in the chronic phase. Furthermore, the relationship between the results of segmental LPSS and late gadolinium enhancement was documented. We would like to emphasize the usefulness of LPSS on TTE both for identifying myocarditis and as a tool for the long-term follow-up of patients.

Impact of High-Voltage Device Implantation in Elderly Japanese Patients With Heart Failure as Primary Prevention　- Post Hoc Analysis of HINODE.

BACKGROUND: Despite an increased incidence of chronic heart failure (HF) and sudden cardiac death (SCD), the use of implantable cardioverter-defibrillators (ICDs) and cardiac resynchronization therapy (CRT) is much lower in Japan than in Western countries. The HF Indication and SCD Prevention Trial Japan (HINODE) prospectively assessed the mortality rate, appropriately treated ventricular arrhythmias (VA), and HF in Japanese patients with a higher risk of HF. METHODS AND RESULTS: HINODE consisted of ICD, CRT-defibrillator (CRT-D), pacing, and non-device treatment cohorts. This subanalysis evaluated the impact of the implantation of high-voltage devices (HVD; ICD and CRT-D) in 171 Japanese patients. We compared all-cause mortality, VA, and HF events between elderly (age >70 years at study enrollment) and non-elderly HVD recipients. The estimated survival rate through 24 months in the HVD cohort was 85.8% (97.5% lower control limit 77.6%). The risk of all-cause mortality was increased for the elderly vs. non-elderly (hazard ratio [HR] 2.82; 95% confidence interval [CI] 1.01-7.91; P=0.039), but did not differ after excluding ICD patients with CRT-D indication (HR 2.32; 95% CI 0.79-6.78; P=0.11). There were no differences in VA and HF event-free rates between elderly and non-elderly HVD recipients (P=0.73 and P=0.55, respectively). CONCLUSIONS: Although elderly patients may have a higher risk of mortality in general, the benefit of HVD therapy in this group is comparable to that in non-elderly patients.

Determination of lipid-rich plaques by artificial intelligence-enabled quantitative computed tomography using near-infrared spectroscopy as reference.

BACKGROUND AND AIMS: Artificial intelligence quantitative CT (AI-QCT) determines coronary plaque morphology with high efficiency and accuracy. Yet, its performance to quantify lipid-rich plaque remains unclear. This study investigated the performance of AI-QCT for the detection of low-density noncalcified plaque (LD-NCP) using near-infrared spectroscopy-intravascular ultrasound (NIRS-IVUS). METHODS: The INVICTUS Registry is a multi-center registry enrolling patients undergoing clinically indicated coronary CT angiography and IVUS, NIRS-IVUS, or optical coherence tomography. We assessed the performance of various Hounsfield unit (HU) and volume thresholds of LD-NCP using maxLCBI4mm ≥ 400 as the reference standard and the correlation of the vessel area, lumen area, plaque burden, and lesion length between AI-QCT and IVUS. RESULTS: This study included 133 atherosclerotic plaques from 47 patients who underwent coronary CT angiography and NIRS-IVUS The area under the curve of LD-NCP<30HU was 0.97 (95% confidence interval [CI]: 0.93-1.00] with an optimal volume threshold of 2.30 mm3. Accuracy, sensitivity, and specificity were 94% (95% CI: 88-96%], 93% (95% CI: 76-98%), and 94% (95% CI: 88-98%), respectively, using <30 HU and 2.3 mm3, versus 42%, 100%, and 27% using <30 HU and >0 mm3 volume of LD-NCP (p < 0.001 for accuracy and specificity). AI-QCT strongly correlated with IVUS measurements; vessel area (r2 = 0.87), lumen area (r2 = 0.87), plaque burden (r2 = 0.78) and lesion length (r2 = 0.88), respectively. CONCLUSIONS: AI-QCT demonstrated excellent diagnostic performance in detecting significant LD-NCP using maxLCBI4mm ≥ 400 as the reference standard. Additionally, vessel area, lumen area, plaque burden, and lesion length derived from AI-QCT strongly correlated with respective IVUS measurements.

Impact of Preprocedural Frailty Status in Elderly Transvenous Pacemaker Recipients.

The number of TV-PM implantations in elderly people is increasing. Although frailty syndrome is common in elderly patients, the relationship between the pre-procedural frailty status and clinical outcomes has not been fully elucidated in elderly TV-PM recipients.This study included 103 consecutive patients over 80 years old who were newly implanted with a TV-PM (age 85.7 ± 4.2, 41.7% male). We assessed the relationship between the clinical outcome and predictive factors, especially for the pre-procedural frailty status after the TV-PM implantation. The pre-procedural frailty status was retrospectively assessed from the medical records and classified on the basis of impairments in 3 domains (walking, cognition, and activities of daily living). The primary endpoint was defined as a heart failure admission.During the follow-up period (4.1 ± 2.3 years), 20 patients (19.4%) met the primary endpoint. Frailty syndrome was identified in 40 patients (38.8%). In univariate analysis, the LVEF (HR 0.97, 95% CI 0.96-1.00 P = 0.0492), an RV pacing burden over 40% (HR 1.58, 95% CI 1.00-2.54 P = 0.0473), and presence of a frailty status (HR 1.82, 95% CI 1.13-2.87 P = 0.0134) were found to be statistically significant predictors for the study endpoint. In multivariate analysis, having frailty syndrome was the only predictive factor for a heart failure admission (HR 1.83, 95% CI 1.12-2.93 P = 0.0157).The presence of frailty syndrome and incidence of clinical events were high and a pre-procedural frailty status assessment was key in determining the clinical outcomes in TV-PM recipients over 80 years old.

Rationale and design of the INVICTUS Registry: (Multicenter Registry of Invasive and Non-Invasive imaging modalities to compare Coronary Computed Tomography Angiography, Intravascular Ultrasound and Optical Coherence Tomography for the determination of Severity, Volume and Type of coronary atherosclerosiS).

BACKGROUND: Coronary CT angiography (CCTA) is a first-line noninvasive imaging modality for evaluating coronary artery disease (CAD). Recent advances in CCTA technology enabled semi-automated detection of coronary arteries and atherosclerosis. However, there have been to date no large-scale validation studies of automated assessment of coronary atherosclerosis phenotype and coronary artery dimensions by artificial intelligence (AI) compared to current standard invasive imaging. METHODS: INVICTUS registry is a multicenter, retrospective, and prospective study designed to evaluate the dimensions of coronary arteries, as well as the characteristic, volume, and phenotype of coronary atherosclerosis by CCTA, compared with the invasive imaging modalities including intravascular ultrasound (IVUS), near-infrared spectroscopy (NIRS)-IVUS and optical coherence tomography (OCT). All patients clinically underwent both CCTA and invasive imaging modalities within three months. RESULTS: Patients data are sent to the core-laboratories to analyze for stenosis severity, plaque characteristics and volume. The variables for CCTA are measured using an AI-based automated software and assessed independently with the variables measured at the imaging core laboratories for IVUS, NIRS-IVUS, and OCT in a blind fashion. CONCLUSION: The INVICTUS registry will provide new insights into the diagnostic value of CCTA for determining coronary atherosclerosis phenotype and coronary artery dimensions compared to IVUS, NIRS-IVUS, and OCT. Our findings will potentially shed new light on precision medicine informed by an AI-based coronary CTA assessment of coronary atherosclerosis burden, composition, and severity. (ClinicalTrials.gov: NCT04066062).

Prognostic Impact of Left Atrial Strain in Patients Hospitalized for Acute Heart Failure With Atrial Fibrillation.

BACKGROUND: Patients with atrial fibrillation (AF) and heart failure (HF) have elevated left ventricular end-diastolic pressure in addition to decreased left atrial (LA) function, but there are few reports of useful prognostic indices that can be seen on echocardiography. In this study, we investigated the association between LA reservoir strain (LARS) and prognosis in this group of patients.Methods and Results: We retrospectively enrolled patients with acute HF complicated by AF who were consecutively admitted to hospital between January 2014 and December 2018. A total of 320 patients (mean age 79±12 years, 163 women) were included in the analysis. During a median follow-up of 473 days, 92 cardiovascular deaths and 113 all-cause deaths occurred. In the multivariate analysis, LARS was an independent predictor of all-cause death (hazard ratio [HR] 0.94, 95% confidence interval [CI] 0.90-0.99, P=0.016). Multivariate analysis also showed that the patients in the lowest LARS tertile (<7.16%) had a significantly increased risk of cardiovascular death (HR 1.76, 95% CI 1.05-2.96; P=0.033) and all-cause death (HR 1.90, 95% CI 1.17-3.08; P=0.009) in comparison with patients in the highest LARS tertile (>10.52%). CONCLUSIONS: We found a significant association between LARS and death in patients with AF and HF. Patients with reduced LARS had poor prognosis, suggesting the need for aggressive therapy to improve their LA dysfunction.

Rationale and design of an investigator-initiated, multicenter, prospective, placebo-controlled, double-blind, randomized trial to evaluate the effects of finerenone on vascular stiffness and cardiorenal biomarkers in type 2 diabetes and chronic kidney disease (FIVE-STAR).

BACKGROUND: The overactivation of mineralocorticoid receptor (MR) plays a key pathological role in the progression of cardiovascular and renal diseases by promoting pro-inflammatory and pro-fibrotic signaling. Recently, it has been found that finerenone, a novel nonsteroidal selective MR antagonist, can robustly improve cardiorenal outcomes in patients with type 2 diabetes (T2D) and a wide spectrum of chronic kidney disease (CKD). However, the mechanisms underlying the cardiorenal benefits of finerenone are poorly understood. Further, whether the clinical benefits are mediated by an improvement in vascular stiffness is not confirmed. Therefore, the current study aims to evaluate the effects of finerenone on vascular stiffness as assessed using cardio ankle vascular index (CAVI) and relevant cardiorenal biomarkers in patients with T2D and CKD. METHODS: The Effects of Finerenone on Vascular Stiffness and Cardiorenal Biomarkers in Type 2 Diabetes and Chronic Kidney Disease (FIVE-STAR) is an ongoing, investigator-initiated, multicenter, prospective, placebo-controlled, double-blind, randomized clinical trial in Japan. Its target sample size is 100 subjects. Recruitment will be performed from September 2023 to July 2024. After obtaining informed consent, eligible participants with T2D and CKD (25 mL/min/1.73 m2 ≤ estimated glomerular filtration ratio [eGFR] < 90 mL/min/1.73 m2 and 30 mg/g Cr ≤ urinary albumin-to-creatinine ratio [UACR] < 3500 mg/g Cr) will be equally randomized to receive 24-week treatment with either finerenone (starting dose at 10 mg once daily in participants with a baseline eGFR < 60 mL/min/1.73 m2 or at 20 mg once daily in those with a baseline eGFR ≥ 60 mL/min/1.73 m2) or dose-matched placebo. The primary endpoint is the change from baseline in CAVI at 24 weeks. The secondary endpoints are changes from baseline in UACR at 12 and 24 weeks and relevant serum and urinary biomarkers at 24 weeks. As an exploratory endpoint, proteomic analysis using the Olink® Target 96 panels will be also performed. DISCUSSION: FIVE-STAR is the first trial evaluating the therapeutic impact of finerenone on vascular stiffness and relevant cardiorenal biomarkers in patients with T2D and CKD. This study will provide mechanistic insights on the clinical benefits of finerenone based on recent cardiovascular and renal outcome trials. Trial registration Unique Trial Number, NCT05887817 ( https://clinicaltrials.gov/ct2/show/NCT05887817 ) and jRCTs021230011 ( https://jrct.niph.go.jp/latest-detail/jRCTs021230011 ).

Prognostic Implications of Sarcoidosis Granulomas　- Insights From the Multicenter Registry, the Japanese Cardiac Sarcoidosis Prognostic Study.

Background: Definitions of cardiac sarcoidosis (CS) differ among guidelines. Any systemic histological finding of CS is essential for the diagnosis of CS in the 2014 Heart Rhythm Society statement, but not necessary in the Japanese Circulation Society 2016 guidelines. This study aimed to reveal the differences in outcomes by comparing 2 groups, namely CS patients with or without systemic histologically proven granuloma. Methods and Results: This study retrospectively included 231 consecutive patients with CS. CS with granulomas in ≥1 organs was diagnosed in 131 patients (Group G), whereas CS without any granulomas was diagnosed in the remaining 100 patients (Group NG). Left ventricular ejection fraction (LVEF) was significantly reduced in Group NG compared with Group G (44±13% vs. 50±16%, respectively; P=0.001). However, Kaplan-Meier curves showed that major adverse cardiovascular events (MACE)-free survival outcomes were comparable between the 2 groups (log-rank P=0.167). Univariable analyses showed that significant predictors of MACE were Groups G/NG, histological CS, LVEF, and high B-type natriuretic peptide (BNP) or N-terminal pro BNP concentrations, but none of these was significant in multivariable analyses. Conclusions: Overall risks of MACE were similar between the 2 groups despite different manifestations in cardiac dysfunction. The data not only validate the prognostic value of non-invasive diagnosis of CS, but also show the need for careful observation and therapeutic strategy in patients with CS without any granuloma.

Graves' Disease after mRNA COVID-19 Vaccination, with the Presence of Autoimmune Antibodies Even One Year Later.

A 45-year-old man who had received his second mRNA COVID-19 vaccination one week earlier was presented to the emergency department with chest discomfort. Therefore, we suspected post-vaccination myocarditis; however, the patient showed no signs of myocarditis. After 2 weeks, he revisited the hospital complaining of palpitations, hand tremors, and weight loss. The patient exhibited high free thyroxine (FT4) (6.42 ng/dL), low thyroid-stimulating hormone (TSH) (<0.01 µIU/mL), and high TSH receptor antibody (17.5 IU/L) levels, and was diagnosed with Graves' disease. Thiamazole was administered, and the patient's FT4 levels normalized after 30 days. One year later, the patient's FT4 is stable; however, their TSH receptor antibodies have not become negative and thiamazole has continued. This is the first case report to follow the course of Graves' disease one year after mRNA COVID-19 vaccination.

Risk of Mortality Prediction Involving Time-Varying Covariates for Patients with Heart Failure Using Deep Learning.

Heart failure (HF) is challenging public medical and healthcare systems. This study aimed to develop and validate a novel deep learning-based prognostic model to predict the risk of all-cause mortality for patients with HF. We also compared the performance of the proposed model with those of classical deep learning- and traditional statistical-based models. The present study enrolled 730 patients with HF hospitalized at Toho University Ohashi Medical Center between April 2016 and March 2020. A recurrent neural network-based model (RNNSurv) involving time-varying covariates was developed and validated. The proposed RNNSurv showed better prediction performance than those of a deep feed-forward neural network-based model (referred as "DeepSurv") and a multivariate Cox proportional hazard model in view of discrimination (C-index: 0.839 vs. 0.755 vs. 0.762, respectively), calibration (better fit with a 45-degree line), and ability of risk stratification, especially identifying patients with high risk of mortality. The proposed RNNSurv demonstrated an improved prediction performance in consideration of temporal information from time-varying covariates that could assist clinical decision-making. Additionally, this study found that significant risk and protective factors of mortality were specific to risk levels, highlighting the demand for an individual-specific clinical strategy instead of a uniform one for all patients.

A Possibility of Vasospastic Angina after mRNA COVID-19 Vaccination.

We report a case of vasospastic angina (VSA) following COVID-19 mRNA vaccination. Despite the widespread occurrence of myocarditis, there have been few reports of post-vaccinal VSA. A 41-year-old male patient was referred for chest pain at rest following mRNA vaccination; he had never experienced chest pain prior to vaccination. He was diagnosed by an acetylcholine (Ach) provocation test that showed multivessel vasospasm. After the initiation of treatment with a calcium channel blocker and nitrate, no further exacerbation of chest pain was observed. To our knowledge, this constitutes the first reported case of VSA proven by Ach provocation test after COVID-19 vaccination. The vaccination may increase coronary artery spasticity. VSA should be ruled out in post-vaccine new onset resting chest pain.

Multicenter Registry in the Japanese Cardiac Sarcoidosis Prognostic (J-CASP) Study: Baseline Characteristics and Validation of the Non-invasive Approach Using 18F-FDG PET.

Background: Recent advances in cardiac modalities contribute to the guidelines on the diagnosis of cardiac sarcoidosis (CS) updated by the Japanese Circulation Society. The multicenter registry, Japanese Cardiac Sarcoidosis Prognostic (J-CASP) study tried to reveal recent trends of diagnosis and outcomes in CS patients and to validate the non-invasive diagnostic approach, including cardiac 18F-fluorodeoxyglucose (FDG) study. Methods/results: Databases from 12 hospitals consisting of 231 CS patients (mean age, 64 years; female, 65%; LV ejection fraction, 47%) diagnosed by the guidelines with FDG positron emission tomography (PET) study were integrated to compile clinical information on the diagnostic criteria and outcomes. Cardiac 18F-FDG uptake and magnetic resonance imaging (CMR) was positive identically in the histology-proven and clinically-diagnosed groups. The histology-proven group more frequently had reduce LV ejection fraction, myocardial perfusion abnormality and low-grade electrocardiogram (ECG) abnormality (P=0.003 to 0.016) than did the clinical group. During a 45-month period, the histology-proven group more frequently underwent appropriate implantable cardioverter-defibrillator (ICD) treatment (14% versus 4%, P=0.013) and new electronic device implantation (30% versus 12%, P=0.007) than did clinical group, respectively. There, however, was no difference in all-cause or cardiac mortality or in new hospitalization due to heart failure progression between them. Conclusion: The J-CASP registry demonstrated the rationale and clinical efficacies of non-invasive approach using advanced cardiac imaging modalities in the diagnosis of CS even when histological data were available.

Exploring and Identifying Prognostic Phenotypes of Patients with Heart Failure Guided by Explainable Machine Learning.

Identifying patient prognostic phenotypes facilitates precision medicine. This study aimed to explore phenotypes of patients with heart failure (HF) corresponding to prognostic condition (risk of mortality) and identify the phenotype of new patients by machine learning (ML). A unsupervised ML was applied to explore phenotypes of patients in a derivation dataset (n = 562) based on their medical records. Thereafter, supervised ML models were trained on the derivation dataset to classify these identified phenotypes. Then, the trained classifiers were further validated on an independent validation dataset (n = 168). Finally, Shapley additive explanations were used to interpret decision making of phenotype classification. Three patient phenotypes corresponding to stratified mortality risk (high, low, and intermediate) were identified. Kaplan−Meier survival curves among the three phenotypes had significant difference (pairwise comparison p < 0.05). Hazard ratio of all-cause mortality between patients in phenotype 1 (n = 91; high risk) and phenotype 3 (n = 329; intermediate risk) was 2.08 (95%CI 1.29−3.37, p = 0.003), and 0.26 (95%CI 0.11−0.61, p = 0.002) between phenotype 2 (n = 142; low risk) and phenotype 3. For phenotypes classification by random forest, AUCs of phenotypes 1, 2, and 3 were 0.736 ± 0.038, 0.815 ± 0.035, and 0.721 ± 0.03, respectively, slightly better than the decision tree. Then, the classifier effectively identified the phenotypes for new patients in the validation dataset with significant difference on survival curves and hazard ratios. Finally, age and creatinine clearance rate were identified as the top two most important predictors. ML could effectively identify patient prognostic phenotypes, facilitating reasonable management and treatment considering prognostic condition.

What Should We Do after the COVID-19 Vaccination? Vaccine-Associated Diseases and Precautionary Measures against Adverse Reactions.

COVID-19 vaccines have been used to counteract the global COVID-19 pandemic. While these are effective, adverse reactions have been reported, such as injection-site pain, muscle ache, fever, palpitation, and chest discomfort. The release of inflammatory cytokines, such as interleukin (IL)-6 and IL-1ß, is a potential mechanism for post-vaccine side-effects. Chest discomfort after the vaccination, including myocarditis and acute coronary syndrome, is a particularly serious adverse reaction. It is important to be familiar with the differential diagnoses of chest discomfort and organ-specific diseases associated with COVID-19 vaccines as the preparation for booster shots and vaccinations among children aged 5-11 years begins. High-intensity exercise, alcohol, tobacco smoking, and baths promote inflammatory cytokines, such as IL-6, which may exacerbate the adverse reactions after vaccination. Japanese data show that deaths during baths are the most common for several days after mRNA vaccination. Additionally, alcohol and tobacco smoking were identified as predictive factors of lower antibody titers after vaccination. In this review, we aimed to provide a few recommendations to prevent vaccine-associated disease.

A Novel Non-Invasive Method for Estimating Elevated Pulmonary Vascular Resistance Based on Echocardiographic Assessment of Pulmonary Artery Wave Reflection.

BACKGROUND: Several non-invasive methods for pulmonary vascular resistance (PVR) measurement are proposed, but none are sufficiently accurate for use in clinical practice. This study proposes a new echocardiographic method of pulmonary artery wave reflection and investigates its efficacy in managing patients with pulmonary hypertension.Methods and Results:In total, 83 patients with left heart disease, pulmonary arterial hypertension, and chronic thromboembolic pulmonary hypertension (CTEPH), who underwent Doppler echocardiography and right heart catheterization, were included in the study. Pulmonary artery wave reflection was characterized by separating the pulmonary artery pressure waveform into forward and backward (Pb) waves, based on wave intensity. Pulmonary artery pressure waveforms were estimated from continuous Doppler tracings of tricuspid regurgitation velocity, and flow velocity was measured using pulsed Doppler of the right ventricular outflow tract. Pb-peak was compared with catheter hemodynamic indices, and with PVR by Abbas 2003, 2013 and Haddad in relation to increased catheter PVR. Catheter PVR and Pb were strongly correlated (r=0.77, P<0.001). The areas under the receiver operator characteristic curve for Pb-peak, PVR by Abbas 2003, 2013 and Haddad were 0.91, 0.72, 0.80, and 0.80, respectively, and were used to detect an increase in PVR (>3 Woods units). CONCLUSIONS: This study describes a novel, simple, and non-invasive echocardiography method to assess pulmonary wave reflected pressure to identify patients with pulmonary hypertension due to increased PVR.

Deep Learning-Based Recurrence Prediction of Atrial Fibrillation After Catheter Ablation.

BACKGROUND: Radiofrequency catheter ablation (RFCA) is an effective therapy for atrial fibrillation (AF). However, it the problem of AF recurrence remains. This study investigates whether a deep convolutional neural network (CNN) can accurately predict AF recurrence in patients with AF who underwent RFCA, and compares CNN with conventional statistical analysis.Methods and Results:Three-hundred and ten patients with AF after RFCA treatment, including 94 patients with AF recurrence, were enrolled. Nine variables are identified as candidate predictors by univariate Cox proportional hazards regression (CPH). A CNNSurv model for AF recurrence prediction was proposed. The model's discrimination ability is validated by a 10-fold cross validation method and measured by C-index. After back elimination, 4 predictors are used for model development, they are N-terminal pro-BNP (NT-proBNP), paroxysmal AF (PAF), left atrial appendage volume (LAAV) and left atrial volume (LAV). The average testing C-index is 0.76 (0.72-0.79). The corresponding calibration plot appears to fit well to a diagonal, and the P value of the Hosmer-Lemeshow test also indicates the proposed model has good calibration ability. The proposed model has superior performance compared with the DeepSurv and multivariate CPH. The result of risk stratification indicates that patients with non-PAF, higher NT-proBNP, larger LAAV and LAV would have higher risks of AF recurrence. CONCLUSIONS: The proposed CNNSurv model has better performance than conventional statistical analysis, which may provide valuable guidance for clinical practice.