Renal dysfunction is a time-varying risk predictor of sudden cardiac death in heart failure.

AIMS: Sudden cardiac death (SCD) is a common mode of death in patients with congestive heart failure (CHF). Implantable cardioverter defibrillator (ICD) implantation is established treatment for SCD prevention, but current eligibility criteria based on left ventricular ejection fraction (LVEF) and New York Heart Association (NYHA) functional class may be due for reconsideration given the increasing effectiveness of pharmacological therapy. We sought to reconsider the risk stratification of SCD in patients with symptomatic CHF. METHODS: In total, 1,676 consecutive patients (74 ± 13 years old; 56% male) with NYHA class II or III CHF between 2008 and 2015 were enrolled for this prospective study. The endpoint was SCD. RESULTS: During a median (interquartile range) follow-up period of 25 (4-70) months, 198 (11.8%) patients suffered SCD. Of those events, 23% occurred within 3 months of discharge. In the adjusted analyses, estimated glomerular filtration rate (eGFR) < 30 ml/min/1.73 m2 [hazard ratio (HR) 1.73, 95% confidence interval (CI) 1.11-2.70, P = 0.01] and LVEF ≤ 35% (HR 2.31, 95% CI 1.47-3.66, P < 0.01) were independent risk predictors of SCD. Addition of eGFR to LVEF significantly improved prediction of SCD in the C-index (P = 0.04), and in two metrics, net reclassification improvement (P = 0.01) and integrated discrimination improvement (P = 0.03). The predictive power of eGFR declined time-dependently over 2 years. CONCLUSIONS: The addition of eGFR to current eligibility criteria may be useful for risk assessment of SCD, although its predictive power wanes over time. Roughly a quarter of the SCD occurred within 3 months after discharge in patients with CHF.

Expert consensus document on automated diagnosis of the electrocardiogram: The task force on automated diagnosis of the electrocardiogram in Japan part 3: Inappropriate internal processing in the automatic diagnosis of electrocardiograms and its problems.

Computer diagnosis of electrocardiograms is widely used to provide useful information in clinical practice and medical checkups. However, it is common for users to be confused by the inappropriate diagnosis. We illustrate some examples of inappropriate automatic diagnoses and discuss the actual situation of inappropriate automatic processing and its problems.

Multicentre, open-label, randomised, controlled trial to compare early intervention with calcimimetics and conventional therapy in preventing coronary artery calcification in patients with secondary hyperparathyroidism (UPCOMING): a study protocol.

INTRODUCTION: Coronary artery and heart valve calcification is a risk factor for cardiovascular death in haemodialysis patients, so calcification prevention should be started as early as possible. Treatment with concomitant calcimimetics and low-dose vitamin D receptor activators (VDRAs) is available, but not enough evidence has been obtained on the efficacy of this regimen, particularly in patients with short dialysis duration. Therefore, this study will evaluate the efficacy and safety of early intervention with upacicalcet, a calcimimetic used to prevent coronary artery calcification in this patient population. METHODS AND ANALYSIS: This multicentre, open-label, randomised, parallel-group controlled study will compare an early intervention group, which received upacicalcet and a low-dose VDRA, with a conventional therapy group, which received a VDRA. The primary endpoint is a change in log coronary artery calcium volume score from baseline to 52 weeks. The main inclusion criteria are as follows: (1) age 18 years or older; (2) dialysis is planned or dialysis duration is less than 60 months; (3) intact parathyroid hormone (PTH) >240 pg/mL or whole PTH level>140 pg/mL; (4) serum-corrected calcium≥8.4 mg/dL and (5) Agatston score >30. The main exclusion criteria are as follows: (1) history of parathyroid intervention or fracture in the past 12 weeks; (2) history of myocardial infarction, stroke or leg amputation in the past 12 weeks; (3) history of coronary angioplasty and (4) heart failure of New York Heart Association class III or worse. ETHICS AND DISSEMINATION: The study will comply with the Declaration of Helsinki and the Japanese Clinical Trials Act. The study protocol has been approved by the Fujita Health University Certified Review Board (file no. CR22-052). Written informed consent will be obtained from all participants. Study results will be presented in academic meetings and peer-reviewed academic journals. TRIAL REGISTRATION NUMBER: jRCTs041220126.

Multifractal foundations of biomarker discovery for heart disease and stroke.

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with nonergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of nonergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are nonergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the nonergodic heart rate variability more ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease.

Prognostic significance of the Holter-derived T-wave variability in patients with ventricular tachyarrhythmias complicating acute coronary syndrome-TWIST study.

BACKGROUND: We aimed to investigate the association between ventricular repolarization instability and sustained ventricular tachycardia and ventricular fibrillation (VT/VF) occurring within 48 h (acute-phase VT/VF) after the onset of acute coronary syndrome (ACS) and the prognostic role of repolarization instability and heart rate variability (HRV) after discharge from the hospital. METHODS: We studied 572 ACS patients with a left ventricular ejection fraction >35%. The ventricular repolarization instability was assessed by the beat-to-beat T-wave amplitude variability (TAV) using high-resolution 24-h Holter ECGs recorded at a median of 11 days from the date of admission. We calculated the HRV parameters including the deceleration capacity (DC) and non-Gaussian index calculated on a 25 s timescale (λ25s). The DC and λ25s were dichotomized based on previous studies' thresholds. RESULTS: Acute-phase VT/VF developed in 43 (7.5%) patients. In-hospital mortality was significantly higher among VT/VF patients (4.7% vs. 0.9%, p = .03). An adjusted logistic model showed that the maximum TAV (odds ratio 1.02, 95% confidence interval [CI] 1.00-1.29, p = .04) was associated with acute-phase VT/VF. During a median follow-up period of 2.1 years, 19 (3.3%) patients had cardiac deaths or resuscitated cardiac arrest. Acute-phase VT/VF (p = .12) and TAV (p = .72) were not significant predictors of survival. An age and sex-adjusted Cox model showed that the DC (p < .01), λ25s (p < .01), and emergency coronary intervention (p < .01) were independent predictors. CONCLUSION: T-wave amplitude variability was associated with acute-phase VT/VF, but the TAV was not predictive of survival post-discharge. The DC, λ25s, and emergency coronary intervention were independent predictors of survival.

Reproducible biomarkers: Leveraging nonlinear descriptors in the face of non-ergodicity.

Any reliable biomarker has to be specific, generalizable, and reproducible across individuals and contexts. The exact values of such a biomarker must represent similar health states in different individuals and at different times within the same individual to result in the minimum possible false-positive and false-negative rates. The application of standard cut-off points and risk scores across populations hinges upon the assumption of such generalizability. Such generalizability, in turn, hinges upon this condition that the phenomenon investigated by current statistical methods is ergodic, i.e., its statistical measures converge over individuals and time within the finite limit of observations. However, emerging evidence indicates that biological processes abound with non-ergodicity, threatening this generalizability. Here, we present a solution for how to make generalizable inferences by deriving ergodic descriptions of non-ergodic phenomena. For this aim, we proposed capturing the origin of ergodicity-breaking in many biological processes: cascade dynamics. To assess our hypotheses, we embraced the challenge of identifying reliable biomarkers for heart disease and stroke, which, despite being the leading cause of death worldwide and decades of research, lacks reliable biomarkers and risk stratification tools. We showed that raw R-R interval data and its common descriptors based on mean and variance are non-ergodic and non-specific. On the other hand, the cascade-dynamical descriptors, the Hurst exponent encoding linear temporal correlations, and multifractal nonlinearity encoding nonlinear interactions across scales described the non-ergodic heart rate variability ergodically and were specific. This study inaugurates applying the critical concept of ergodicity in discovering and applying digital biomarkers of health and disease.

Predictors of in-hospital mortality in elderly patients with heart failure treated with tolvaptan.

Objectives: We conducted an analysis of first-time tolvaptan users (≥80 years old) to determine the factors associated with the prognosis of elderly patients with heart failure. Methods: We retrospectively analyzed 66 consecutive patients with worsening heart failure (aged ≥80 years) who were admitted to Fujita Health University Bantane Hospital from 2011 to 2016 and treated with tolvaptan. Differences between the in-hospital death and survival groups were evaluated. Multivariate logistic regression analysis was also performed to identify the risk factors for mortality. Results: Sixty-six patients were included, and 26 patients died during the index hospitalization. The patients who died had a significantly higher prevalence of ischemic heart disease; a higher heart rate; higher levels of plasma C-reactive protein, blood urea nitrogen (BUN), and creatinine; a lower serum albumin level; and a lower estimated glomerular filtration rate than surviving patients. The proportion of patients requiring early initiation of tolvaptan treatment (within 3 days of admission) was significantly higher in surviving patients. On the basis of multivariate logistic regression analysis, although a high heart rate and high BUN levels were independent factors for in-hospital prognosis, they were not significantly associated with the early use of tolvaptan (≤3 days vs. ≥4 days; odds ratio=0.39; 95% confidence interval=0.07-2.21; p=0.29). Conclusions: This study revealed that a higher heart rate and higher BUN levels were independent factors for in-hospital prognosis in elderly patients who received tolvaptan and that early tolvaptan use may not always be effective in elderly patients.

Circulating miR-20b-5p and miR-330-3p are novel biomarkers for progression of atrial fibrillation: Intracardiac/extracardiac plasma sample analysis by small RNA sequencing.

BACKGROUND: Circulating microRNAs (miRNAs, miR) have been considered as biomarkers reflecting the underlying pathophysiology in atrial fibrillation (AF). Nevertheless, miRNA expression in the peripheral blood samples might not reflect a cardiac phenomenon since most miRNAs are expressed in numerous organs. This study aimed to identify the cardiac-specific circulating miRNAs as biomarkers for AF. METHODS: Plasma samples were obtained from a luminal coronary sinus catheter (CS, cardiac-specific samples) and femoral venous sheath (FV, peripheral samples) in patients with AF and paroxysmal supraventricular tachycardia (control, CTL) undergoing catheter ablation. The circulating miRNA profiles were analyzed by small RNA sequencing. Differently expressed miRNAs between AF and CTL were identified in each sample of the CS and FV; miRNAs exhibiting similar expression patterns in the CS and FV samples were selected as candidates for cardiac-specific biomarkers. The selected miRNAs were related to the outcome of catheter ablation of AF. RESULTS: Small RNA sequencing detected 849 miRNAs. Among the top 30 most differently expressed miRNAs between AF and CTL, circulating hsa-miR-20b-5p, hsa-miR-330-3p, and hsa-miR-204-5p had a similar pattern in the CS and FV samples. Another set of peripheral blood samples was obtained from AF patients undergoing catheter ablation (n = 141). The expression of the miR-20b-5p and miR-330-3p, but not the miR-204-5p, negatively correlated with the echocardiographic left-atrial dimension and was decreased in patients with AF recurrence as compared to those without AF recurrence during a 1-year follow-up. CONCLUSION: Circulating miR-20b-5p and miR-330-3p can be cardiac-specific biomarkers for atrial remodeling progression and arrhythmia recurrence after catheter ablation in AF patients.

Prediction of Short-Term Mortality of Cardiac Care Unit Patients Using Image-Transformed ECG Waveforms.

OBJECTIVE: The early detection of cardiac disease is important because the disease can lead to sudden death and poor prognosis. Electrocardiograms (ECG) are used to screen for cardiac diseases and are useful for the early detection and determination of treatment strategies. However, the ECG waveforms of cardiac care unit (CCU) patients with severe cardiac disease are often complicated by comorbidities and patient conditions, making it difficult to predict the severity of further cardiac disease. Therefore, this study predicts the short-term prognosis of CCU patients to detect further deterioration in CCU patients at an early stage. METHODS: The ECG data (II, V3, V5, aVR induction) of CCU patients were converted to image data. The transformed ECG images were used to predict short-term prognosis with a two-dimensional convolutional neural network (CNN). RESULTS: The prediction accuracy was 77.3%. Visualization by GradCAM showed that the CNN tended to focus on the shape and regularity of waveforms, such as heart failure and myocardial infarction. CONCLUSION: These results suggest that the proposed method may be useful for short-term prognosis prediction using the ECG waveforms of CCU patients. CLINICAL IMPACT: The proposed method could be used to determine the treatment strategy and choose the intensity of treatment after admission to the CCU.

Effect of pulmonary vein isolation on rotor/multiple wavelet dynamics in persistent atrial fibrillation, association with vagal response and implications for adjunctive ablation.

Persistent atrial fibrillation (PeAF) may develop arrhythmogenic substrates of rotors/multiple wavelets. However, the ways in which pulmonary vein isolation (PVI) affects the dynamics of rotor/multiple wavelets in PeAF patients remain elusive. Real-time phase-mapping (ExTRa mapping, EXT) in the whole left atrium (LA) was performed during PeAF before and after PVI (n = 111). The percentage of time in which rotor/multiple wavelets (phase singularities) was observed during each 5-s phase-mapping recording (non-passive activation ratio, %NP) was measured as an index of its burden. The mapping areas showing %NP ≥ 50% were defined as rotor/multiple-wavelet substrates (RSs). Before PVI, RSs were globally distributed in the LA. After PVI, %NP decreased (< 50%) in many RSs (PVI-modifiable RSs) but remained high (≥ 50%) in some RSs, especially localized in the anterior/septum/inferior regions (PVI-unmodifiable RSs, 2.3 ± 1.0 areas/patient). Before PVI, vagal response (VR) to high-frequency stimulation was observed in 23% of RSs, especially localized in the inferior region. VR disappearance after PVI was more frequently observed in PVI-modifiable RSs (79%) than in PVI-unmodifiable RSs (55%, p < 0.05), suggesting that PVI affects autonomic nerve activities and rotor/multiple wavelet dynamics. PVI-unmodifiable RSs were adjunctively ablated in 104 patients. The 1-year AT/AF-free survival rate was 70% in those with PVI alone (n = 115), and 86% in patients with the adjunctive ablation (log-rank test = 7.65, p < 0.01). PVI suppresses not only ectopic firing but also rotor/multiple wavelets partly via modification of autonomic nerve activities. The adjunctive ablation of PVI-unmodifiable RSs improved the outcome in PeAF patients and might be a novel ablation strategy beyond PVI.

A simple proteinuria-based risk score predicts contrast-associated acute kidney injury after percutaneous coronary intervention.

Contrast-associated acute kidney injury (CA-AKI) is a complication of percutaneous coronary intervention (PCI). Because proteinuria is a sentinel marker of renal dysfunction, we assessed its role in predicting CA-AKI in patients undergoing PCI. A total of 1,254 patients undergoing PCI were randomly assigned to a derivation (n = 840) and validation (n = 414) dataset. We identified the independent predictors of CA-AKI where CA-AKI was defined by the new criteria issued in 2020, by a multivariate logistic regression in the derivation dataset. We created a risk score from the remaining predictors. The discrimination and calibration of the risk score in the validation dataset were assessed by the area under the receiver-operating characteristic curves (AUC) and Hosmer-Lemeshow test, respectively. A total of 64 (5.1%) patients developed CA-AKI. The 3 variables of the risk score were emergency procedures, serum creatinine, and proteinuria, which were assigned 1 point each based on the correlation coefficient. The risk score demonstrated a good discriminative power (AUC 0.789, 95% CI 0.766-0.912) and significant calibration. It was strongly associated with the onset of CA-AKI (Cochran-Armitage test, p < 0.0001). Our risk score that included proteinuria was simple to obtain and calculate, and may be useful in assessing the CA-AKI risk before PCI.

Selvester QRS score predicts improvement of LVEF in atrial fibrillation patients with systolic heart failure.

BACKGROUND: Left-ventricular systolic dysfunction (LVSD) comorbid with atrial fibrillation is reversible, but recovery is limited in a subset of patients. The Selvester QRS (S-QRS) score is an electrocardiogram-based assessment that reportedly reflects myocardial scar/damage. We evaluated the predictability of S-QRS score for the recovery of left-ventricular ejection fraction (LVEF) in persistent AF (PeAF) patients with LVSD undergoing catheter ablation (CA). METHOD: CA was performed in 51 PeAF patients with reduced LVEF (<40%); S-QRS scores were measured after restoration of sinus rhythm. LVEF was re-evaluated at one year after CA; LVEF recovery was related to the S-QRS score. RESULTS: The median [interquartile range] S-QRS score was 1 point [0-2]. LVEF increased from 32% [28-37] at baseline to 56% [49-57] at 1 year after CA. Thirty-seven patients achieved normalization of LVEF (≥50%, Group A); 14 patients did not (Group B). Group A had significantly lower S-QRS scores than Group B (0 point [0-2] vs. 2 points [2-3], p < .05). In univariate/multivariate analyses, S-QRS score was an independent predictor of LVEF normalization. In the receiver operating characteristic curve, the cut-off value of S-QRS score was 2 points for prediction of the LVEF normalization (AUC = 0.79). Patients with low S-QRS score (<2 points) had greater LVEF improvement than those with high S-QRS score (≥2 points, ΔLVEF: 23% [17-28] vs. 17% [12-24], p < .05). CONCLUSION: S-QRS scoring noninvasively assesses the improvement of LVEF in PeAF patients with LVSD after CA. A high S-QRS score may indicate underlying myocardial scar/damage associated with unknown etiologies for LVSD other than PeAF.

Automated detection scheme for acute myocardial infarction using convolutional neural network and long short-term memory.

The early detection of acute myocardial infarction, which is caused by lifestyle-related risk factors, is essential because it can lead to chronic heart failure or sudden death. Echocardiography, among the most common methods used to detect acute myocardial infarction, is a noninvasive modality for the early diagnosis and assessment of abnormal wall motion. However, depending on disease range and severity, abnormal wall motion may be difficult to distinguish from normal myocardium. As abnormal wall motion can lead to fatal complications, high accuracy is required in its detection over time on echocardiography. This study aimed to develop an automatic detection method for acute myocardial infarction using convolutional neural networks (CNNs) and long short-term memory (LSTM) in echocardiography. The short-axis view (papillary muscle level) of one cardiac cycle and left ventricular long-axis view were input into VGG16, a CNN model, for feature extraction. Thereafter, LSTM was used to classify the cases as normal myocardium or acute myocardial infarction. The overall classification accuracy reached 85.1% for the left ventricular long-axis view and 83.2% for the short-axis view (papillary muscle level). These results suggest the usefulness of the proposed method for the detection of myocardial infarction using echocardiography.

Systematic Screening for Atrial Fibrillation in Patients at Moderate-to-High Risk of Stroke　- Potential to Increase the Atrial Fibrillation Detection Rate (SCAN-AF).

BACKGROUND: To determine the rate of undiagnosed atrial fibrillation (AF) we screened for AF using an oscillometric blood pressure (BP) monitor device followed by a single-lead handheld electrocardiogram (ECG), with confirmation by 12-lead ECG as the reference standard.Methods and Results: From October 2017 to August 2019, 1,148 patients were enrolled without known AF, who were aged ≥65 years with moderate-to-high stroke risk, at 71 centers in Japan. After exclusion of 7 patients with confirmed AF at the index visit, 1,141 patients were asked to use an oscillometric BP monitor twice daily for 2 weeks (max: 4 weeks) to detect an irregular pulse. The BP monitor detected an irregular pulse in 481 patients, of which 1 patient had confirmed AF. Thereafter, 480 patients were instructed to acquire ECGs twice daily for an additional 2 weeks (max: 4 weeks) using a single-lead handheld ECG device. The handheld ECG device detected irregular rhythm in 41 patients, of which 1 patient had confirmed AF. In total, undiagnosed AF was confirmed in 9 (0.8%) patients of the overall study cohort during the 24-week follow-up period. CONCLUSIONS: Sequential use of a BP monitor and handheld ECG for 4 weeks is a practical strategy for identifying undiagnosed AF in Japanese people at heightened risk of stroke.

Small Dense Low-Density Lipoprotein Cholesterol and Cardiovascular Risk in Statin-Treated Patients with Coronary Artery Disease.

AIM: We investigated the relationship between small dense low-density cholesterol (sdLDL-C) and risk of major adverse cardiovascular events (MACE) in patients treated with high- or low-dose statin therapy. METHODS: This was a prospective case-cohort study within the Randomized Evaluation of Aggressive or Moderate Lipid-Lowering Therapy with Pitavastatin in Coronary Artery Disease (REAL-CAD) study, a randomized trial of high- or low-dose (4 or 1 mg/d pitavastatin, respectively) statin therapy, in patients with stable coronary artery disease (CAD). Serum sdLDL-C was determined using an automated homogenous assay at baseline (randomization after a rule-in period, ＞1 month with 1 mg/d pitavastatin) and 6 months after randomization, in 497 MACE cases, and 1543 participants randomly selected from the REAL-CAD study population. RESULTS: High-dose pitavastatin reduced sdLDL-C by 20% than low-dose pitavastatin (p for interaction ＜0.001). Among patients receiving low-dose pitavastatin, baseline sdLDL-C demonstrated higher MACE risk independent of LDL-C (hazard ratio [95% confidence interval], 4th versus 1st quartile, 1.67 [1.04-2.68]; p for trend=0.034). High-dose (versus low-dose) pitavastatin reduced MACE risk by 46% in patients in the highest baseline sdLDL-C quartile (＞34.3 mg/dL; 0.54 [0.36-0.81]; p=0.003), but increased relative risk by 40% in patients with 1st quartile (≤ 19.5 mg/dL; 1.40 [0.94-2.09]; p=0.099) and did not alter risk in those in 2nd and 3rd quartiles (p for interaction=0.002). CONCLUSIONS: These findings associate sdLDL-C and cardiovascular risk, independent of LDL-C, in statin-treated CAD patients. Notably, high-dose statin therapy reduces this risk in those with the highest baseline sdLDL-C.