Search

Background: Heart failure should be diagnosed as early as possible. Although deep learning models can predict one or more echocardiographic findings from electrocardiograms (ECGs), such analyses are not comprehensive. Objectives: This study aimed to develop a deep learning model for comprehensive prediction of echocardiographic findings from ECGs. Methods: We obtained 229,439 paired ECG and echocardiography data sets from 8 centers. Six centers contributed to model development and 2 to external validation. We identified 12 echocardiographic findings related to left-sided cardiac abnormalities, valvular heart diseases, and right-sided cardiac abnormalities. These findings were predicted using convolutional neural networks, and a composite label was analyzed using logistic regression. A positive composite label indicated positivity in any of the 12 findings. Results: For the composite findings label, the area under the receiver-operating characteristic curve was 0.80 (95% CI: 0.80-0.81) on hold-out validation and 0.78 (95% CI: 0.78-0.79) on external validation. The composite findings label applying logistic regression had an area under the receiver-operating characteristic curve of 0.80 (95% CI: 0.80-0.81) with accuracy of 73.8% (95% CI: 73.2-74.4), sensitivity of 81.1% (95% CI: 80.5-81.8), and specificity of 60.7% (95% CI: 59.6-61.8). Conclusions: We have developed convolutional neural network models that predict a wide range of echocardiographic findings, including left-sided cardiac abnormalities, valvular heart diseases, and right-sided cardiac abnormalities from ECGs and created a model to predict a composite findings label by logistic regression analysis. This model has potential to serve as an adjunct for early diagnosis and treatment of previously undetected cardiac disease.

Background: Traditional pacemaker implantation often poses risks, such as perforation when positioning atrial leads at the right atrial appendage (RAA). Recent advancements in delivery catheters have enabled atrial lead placement in the right atrial septum, potentially mitigating RAA-related complications. However, the performance of lumenless leads in this context remains unclear. Objective: This study was performed to assess the performance of lumenless leads as atrial leads. Methods: Forty-four consecutive patients undergoing pacemaker implantation with lumenless atrial leads were enrolled. Lead implantation was performed using a 3830 SelectSecure lead and C315HIS-sheath. Pacing parameters were collected immediately after screwing, 3 and 5 minutes later, at the end of the procedure, and at every 6-month follow-up. Results: Lead parameters including P-wave, pacing threshold, and impedance significantly improved over time. The threshold levels from 2.00 ± 0.72 V/0.4 msec immediately after screwing to 1.45 ± 0.57 V/0.4 msec at 5 minutes, 0.95 ± 0.38 V/0.4 msec at the end of the procedure, and 0.78 ± 0.39 V/0.4 msec at discharge. Initially, threshold levels were >2.5 V/0.4 msec in 15 cases; however, they decreased to 1 V), lead revision, or battery depletion was observed. Conclusion: Lumenless lead placement in the right atrium results in threshold decrease over time. Therefore, allowing a waiting period instead of immediately repositioning the lead may be more effective when thresholds are high after screwing.

Abstract Hypertension is a significant contributor to premature mortality, and the regular monitoring of blood pressure (BP) enables the early detection of hypertension and cardiovascular disease. There is an urgent need for the development of highly accurate cuffless BP devices. We examined BP measurements based on a target spectral camera’s recordings and evaluated their accuracy. Images of 215 adults’ palms and faces were recorded, and BP was measured. The camera captured RGB wavelength data at 640 × 480 pixels and 150 frames per second (fps). These recordings were analyzed to extract pulse transit time (PTT) values between the face and palm, a key parameter for estimating BP. Continuous BP measurements were taken using a CNAPmonitor500 for validation. Three frequency wavelengths were measured from video images. A machine learning model was constructed to determine hypertension, defined as a systolic BP of 130 mmHg or higher or a diastolic BP of 80 mmHg or higher, using the visualized data. The discrimination between hypertension and normal BP was 95.0% accurate within 30 s and 90.3% within 5 s, based on the captured images. The results of heartbeat-by-heartbeat analyses can be used to determine hypertension based on only one second of camera footage or one heartbeat. The data extracted from a video recorded by a target spectral camera enabled accurate hypertension diagnoses, suggesting the potential for simplified BP monitoring.

Abstract Background The risk of subsequent cardiovascular disease (CVD) is high in cancer survivors. Although metabolic syndrome is an established risk factor for CVD, its association with cancer survivors has not yet been established. This study aimed to clarify whether metabolic syndrome is associated with subsequent CVD risk in patients with cancer using a nationwide epidemiological dataset. Methods We retrospectively analysed 53 510 patients with a history of breast, colorectal, or stomach cancer, which is reportedly a major site for developing cancer in Japan. Study participants were categorized into two groups based on the presence of metabolic syndrome, defined using the Japanese criteria (high waist circumference and ≥2 metabolic parameters including elevated blood pressure, elevated triglycerides, reduced high‐density lipoprotein cholesterol, or elevated fasting plasma glucose). The clinical outcomes were collected between 2005 and 2021. The primary endpoint was defined as the composite CVD outcome, including myocardial infarction, angina pectoris, stroke, and heart failure. Results The median patient age was 54 years, and 37.5% of the patients were men. Metabolic syndrome was observed in 5558 (10.4%) patients. Over a mean follow‐up period of 973 ± 791 days, 3085 composite CVD outcomes were recorded. Multivariable Cox regression analyses showed that metabolic syndrome was associated with a greater risk of developing CVD events (HR = 1.29, 95% CI = 1.15–1.45). Metabolic syndrome was also associated with an increased risk of CVD in patients with a follow‐up period ≥1 year (HR = 1.33, 95% CI = 1.15–1.53). This relationship was also observed when metabolic syndrome was defined according to the International Diabetes Federation criteria (HR = 1.34, 95% CI = 1.21–1.49) and the National Cholesterol Education Program Adult Treatment Panel III criteria (HR = 1.32, 95% CI = 1.19–1.46). Subgroup analyses showed that the relationship between metabolic syndrome and incident CVD was more pronounced in the non‐obese participants than in the obese participants. Conclusions Metabolic syndrome is associated with a greater risk of developing CVD, even among cancer survivors.

Abstract Risk factors for pacemaker-induced cardiomyopathy (PICM) have been previously reported, including a high burden of right ventricular pacing, lower left ventricular ejection fraction, a wide QRS duration, and left bundle branch block before pacemaker implantation (PMI). However, predicting the development of PICM remains challenging. This study aimed to use a convolutional neural network (CNN) model, based on clinical findings before PMI, to predict the development of PICM. Out of a total of 561 patients with dual-chamber PMI, 165 (mean age 71.6 years, 89 men [53.9%]) who underwent echocardiography both before and after dual-chamber PMI were enrolled. During a mean follow-up period of 1.7 years, 47 patients developed PICM. A CNN algorithm for prediction of the development of PICM was constructed based on a dataset prior to PMI that included 31 variables such as age, sex, body mass index, left ventricular ejection fraction, left ventricular end-diastolic diameter, left ventricular end-systolic diameter, left atrial diameter, severity of mitral regurgitation, severity of tricuspid regurgitation, ischemic heart disease, diabetes mellitus, hypertension, heart failure, New York Heart Association class, atrial fibrillation, the etiology of bradycardia (sick sinus syndrome or atrioventricular block) , right ventricular (RV) lead tip position (apex, septum, left bundle, His bundle, RV outflow tract), left bundle branch block, QRS duration, white blood cell count, haemoglobin, platelet count, serum total protein, albumin, aspartate transaminase, alanine transaminase, estimated glomerular filtration rate, sodium, potassium, C-reactive protein, and brain natriuretic peptide. The accuracy, sensitivity, specificity, and area under the curve of the CNN model were 75.8%, 55.6%, 83.3% and 0.78 respectively. The CNN model could accurately predict the development of PICM using clinical findings before PMI. This model could be useful for screening patients at risk of developing PICM, ensuring timely upgrades to physiological pacing to avoid missing the optimal intervention window.

Abstract Clinical predictors for pacemaker-induced cardiomyopathy (PICM) (e.g., a wide QRS duration and left bundle branch block at baseline) have been reported. However, factors involved in the development of PICM in patients with preserved left ventricular ejection fraction (LVEF) remain unknown. This study aimed to determine the risk factors for PICM in patients with preserved LVEF. The data of 113 patients (average age: 71.3 years; men: 54.9%) who had echocardiography before and after pacemaker implantation (PMI) among 465 patients undergoing dual-chamber PMI were retrospectively analyzed. Thirty-three patients were diagnosed with PICM (18.0/100 person-years; 95% CI 12.8–25.2). A univariate Cox regression analysis showed that an estimated glomerular filtration rate (eGFR) ≤ 30 mL/min/1.73 m2 (HR 3.47; 95% CI 1.48–8.16) and a past medical history of coronary artery disease (CAD) (HR 2.76; 95% CI 1.36–5.60) were significantly associated with the onset of PICM. After adjusting for clinical variables, an eGFR ≤ 30 mL/min/1.73 m2 (HR 2.62; 95% CI 1.09–6.29) and a medical history of CAD (HR 2.32; 95% CI 1.13–4.80) were independent risk factors for developing PICM. A medical history of CAD and low eGFR are independent risk factors for PICM in patients with preserved LVEF at baseline. These results could be helpful in predicting a decreased LVEF by ventricular pacing before PMI. Close follow-up by echocardiography is recommended to avoid a delay in upgrading to physiological pacing, such as cardiac resynchronization therapy or conduction system pacing.

Background There are few data on sex differences in the association between schizophrenia and the development of cardiovascular disease (CVD). We sought to clarify the relationship of schizophrenia with the risk of developing CVDs and to explore the potential modification effect of sex differences. Methods and Results We conducted a retrospective analysis using the JMDC Claims Database between 2005 and 2022. The study population included 4 124 508 individuals aged 18 to 75 years without a history of CVD or renal replacement therapy. The primary end point is defined as a composite end point that includes myocardial infarction, angina pectoris, stroke, heart failure, atrial fibrillation, and pulmonary thromboembolism. During a mean follow‐up of 1288±1001 days, we observed 182 158 composite end points. We found a significant relationship of schizophrenia with a greater risk of developing composite CVD events in both men and women, with a stronger association observed in women. The hazard ratio for the composite end point was 1.63 (95% CI, 1.52–1.74) in women and 1.42 (95% CI, 1.33–1.52) in men after multivariable adjustment (P for interaction=0.0049). This sex‐specific difference in the association between schizophrenia and incident CVD was consistent for angina pectoris, heart failure, and atrial fibrillation. Conclusions Our analysis using a large‐scale epidemiologic cohort demonstrated that the association between schizophrenia and subsequent CVD events was more pronounced in women than in men, suggesting the clinical importance of addressing schizophrenia and tailoring the CVD prevention strategy based on sex‐specific factors.

Background Atrial fibrillation (AF) progression is closely related to heart failure occurrence, and catheter ablation carries a beneficial effect for heart failure prevention. Recently, particular attention has been given to left atrial (LA) function and functional reserve in the pathogenesis linking AF and heart failure, although its significance and reversibility is not well studied. Methods and Results We prospectively investigated 164 patients with AF with normal left ventricular systolic function and free from heart failure who underwent first catheter ablation and pre‐/postprocedural echocardiography. Conventional and speckle‐tracking echocardiography were performed at rest and during passive leg lifting to assess LA size, LA reservoir strain (LARS), and functional reserve calculated as passive leg lifting‐LARS – rest‐LARS. Patients were categorized into 3 AF subtypes: paroxysmal AF (N=95), persistent AF (PeAF; N=50), and long‐standing persistent AF (LS‐PeAF; N=19). The PeAF and LS‐PeAF groups had larger LA size and reduced LARS compared with the paroxysmal AF group (all P

The generalization of deep neural network algorithms to a broader population is an important challenge in the medical field. We aimed to apply self-supervised learning using masked autoencoders (MAEs) to improve the performance of the 12-lead electrocardiography (ECG) analysis model using limited ECG data. We pretrained Vision Transformer (ViT) models by reconstructing the masked ECG data with MAE. We fine-tuned this MAE-based ECG pretrained model on ECG-echocardiography data from The University of Tokyo Hospital (UTokyo) for the detection of left ventricular systolic dysfunction (LVSD), and then evaluated it using multi-center external validation data from seven institutions, employing the area under the receiver operating characteristic curve (AUROC) for assessment. We included 38,245 ECG-echocardiography pairs from UTokyo and 229,439 pairs from all institutions. The performances of MAE-based ECG models pretrained using ECG data from UTokyo were significantly higher than that of other Deep Neural Network models across all external validation cohorts (AUROC, 0.913-0.962 for LVSD, p < 0.001). Moreover, we also found improvements for the MAE-based ECG analysis model depending on the model capacity and the amount of training data. Additionally, the MAE-based ECG analysis model maintained high performance even on the ECG benchmark dataset (PTB-XL). Our proposed method developed high performance MAE-based ECG analysis models using limited ECG data.

ABSTRACT Aims/Introduction Little is known about the relationship between cardiovascular health (CVH) metrics and the risk of developing prediabetes or diabetes. We examined the association of CVH metrics with the annual risk of developing prediabetes or diabetes. Materials and Methods We carried out this study including 403,857 participants aged 18–71 years with available data on fasting plasma glucose (FPG) data for five consecutive years and with normal FPG (

Abstract Background Although weight loss in heart failure (HF) is a detrimental condition known as cachexia, weight gain caused by fluid retention should also be considered harmful. However, studies with sufficient number of patients examining the impact of weight change and its interval on in‐hospital mortality in HF have not been conducted thus far. We sought to elucidate the association of weight change with in‐hospital mortality in patients with HF. Methods This retrospective observational study used data from the Diagnosis Procedure Combination database, a nationwide inpatient health claims database in Japan. In total, 48 234 patients repeatedly hospitalized for HF (median 82 [74–87] years; 46.4% men) between 2010 and 2018 were included. Weight change was derived from body weight at the first and second admissions. Results The median weight change and interval between two hospitalizations were −3.1 [−8.3 to −1.8] % and 172 [67–420] days, with 66.9% of overall cohort experiencing any weight loss. As a result of multivariable‐adjusted logistic regression analysis, weight loss +5.0% were associated with increased in‐hospital mortality (adjusted odds ratio [OR] [95% confidence interval]: 1.46 [1.31–1.62], P

Ieki et al. train a deep learning model to estimate patients’ age from chest X-ray images. X-ray age is found to be an indicator of poor prognosis in patients with heart failure and patients admitted to the intensive care unit with cardiovascular disease.

Background Elevated left atrial (LA) pressure predisposes individuals to the initiation and persistence of atrial fibrillation (AF), and LA hypertension is associated with AF recurrence after catheter ablation (CA). However, the exact frequency and factors associated with LA hypertension are unknown, and its noninvasive estimation is challenging. This study aimed to investigate the prevalence and determinants of LA hypertension in patients with AF who underwent first CA. Methods and Results We examined 183 patients with AF who underwent conventional and speckle‐tracking echocardiography before CA to assess LA size, reservoir strain, and stiffness. Direct LA pressure was measured at the time of CA, and LA hypertension was defined as mean LA pressure >15 mm Hg. Thirty‐three (18.0%) patients exhibited LA hypertension. Patients with LA hypertension had a significantly larger LA volume index (40.2 [28.4–52.1] versus 34.1 [26.9–42.4] mL/m2, P=0.025), reduced LA reservoir strain (15.1 [10.4–21.7] versus 22.7 [14.4–32.3] %, P=0.002) and increased LA stiffness (0.69 [0.34–0.99] versus 0.36 [0.24–0.54], P

We sought to clarify the incidence of major adverse cardiac events (MACE) after the initiation of immune checkpoint inhibitors (ICIs). We analyzed the JMDC Claims Database between 2005 and 2021. The study included 2972 patients with no history of cardiovascular disease and a prescription for an ICI. The primary outcome was the incidence of MACE, including myocarditis, pericarditis, Takotsubo cardiomyopathy, atrio-ventricular block, heart failure, myocardial infarction, and stroke. The median age of study participants was 59 (Q1-Q3 53–65) years, and 2163 participants (72.8%) were male. Lung cancer was the most common cancer site (n = 1603). Among ICIs, programmed cell death-1 (PD-1) was most frequently used, and a combination ICI treatment was conducted in 110 patients (3.7%). During a mean follow-up of 358 ± 327 days, 419 MACE events were recorded. The incidence rate of myocarditis, pericarditis, Takotsubo cardiomyopathy, atrio-ventricular block, heart failure, myocardial infarction, and stroke was 3.4, 142.3, 10.3, 17.2, 1191.2, 55.2, and 278.5 per 10,000 person-years, respectively. The incidence of cardiovascular events was higher within 180 days after the initial prescription of ICI. The continuation rate of ICI after MACE was 38.4%. In conclusion, our analysis of a nationwide epidemiological dataset demonstrated the incidence of MACE after the initiation of ICI treatment. The incidence of heart failure was higher than expected, and the continuation rate of ICI treatment after MACE was low. Our results indicated the importance of monitoring and prevention of cardiovascular events in cancer patients requiring ICI treatment.

Abstract Little is known regarding the relationship between self-reported gait speed and the subsequent risk of heart failure (HF) and cardiovascular disease (CVD). We sought to clarify the clinical utility of self-reported gait speed in primary CVD prevention settings. This is an observational cohort study using the JMDC Claims Database, which is an administrative health claims database. Data were collected between January 2005 and April 2020. Medical records of 2,655,359 participants without a prior history of CVD were extracted from the JMDC Claims Database. Gait speed was assessed using information from questionnaires provided at health check-ups, and study participants were categorized into fast or slow gait speed groups. The primary outcome was HF. The secondary outcomes included myocardial infarction (MI), angina pectoris (AP), and stroke. The median age was 45.0 years, and 55.3% of participants were men. 46.1% reported a fast gait speed. The mean follow-up period was 1180 ± 906 days. HF, MI, AP, and stroke occurred in 1.9%, 0.2%, 1.9%, and 1.0% of participants, respectively. Multivariable Cox regression analyses showed that, compared with slow gait speed, fast gait speed was associated with a lower incidence of HF, MI, AP, and stroke. The discriminative predictive ability for HF significantly improved by adding self-reported gait speeds to traditional risk factors (net reclassification improvement 0.0347, p

Abstract Background There have been scarce data comparing cardiovascular outcomes between individual sodium-glucose cotransporter-2 (SGLT2) inhibitors. We aimed to compare the subsequent cardiovascular risk between individual SGLT2 inhibitors. Methods We analyzed 25,315 patients with diabetes mellitus (DM) newly taking SGLT2 inhibitors (empagliflozin: 5302, dapagliflozin: 4681, canagliflozin: 4411, other SGLT2 inhibitors: 10,921). We compared the risks of developing heart failure (HF), myocardial infarction (MI), angina pectoris (AP), stroke, and atrial fibrillation (AF) between individual SGLT2 inhibitors. Results Median age was 52 years, and 82.5% were men. The median fasting plasma glucose and HbA1c levels were 149 (Q1-Q3:127–182) mg/dL and 7.5 (Q1-Q3:6.9–8.6) %. During a mean follow-up of 814 ± 591 days, 855 HF, 143 MI, 815 AP, 340 stroke, and 139 AF events were recorded. Compared with empagliflozin, the risk of developing HF, MI, AP, stroke, and AF was not significantly different in dapagliflozin, canagliflozin, and other SGLT inhibitors. For developing HF, compared with empagliflozin, hazard ratios of dapagliflozin, canagliflozin, and other SGLT2 inhibitors were 1.02 (95% confidence interval [CI] 0.81–1.27), 1.08 (95% CI 0.87–1.35), and 0.88 (95% CI 0.73–1.07), respectively. Wald tests showed that there was no significant difference in the risk of developing HF, MI, AP, stroke, and AF among individual SGLT2 inhibitors. We confirmed the robustness of these results through a multitude of sensitivity analyses. Conclusion The risks for subsequent development of HF, MI, AP, stroke, and AF were comparable between individual SGLT2 inhibitors. This is the first study comparing the wide-range cardiovascular outcomes of patients with DM treated with individual SGLT2 inhibitors using large-scale real-world data.

Background Limited evidence is available on sex differences about the association between hypertension and incident atrial fibrillation (AF). Methods and Results We used a nationwide health checkup and claims database to analyze 3 383 738 adults (median age, 43 (36–51) years, 57.4% men). We investigated the relationship between hypertension and incident AF in men and women using a Cox regression model. We used restricted cubic spline functions to identify the association of blood pressure (BP) as a continuous parameter with incident AF. We categorized the men and women into 4 groups according to the 2017 American College of Cardiology/American Heart Association BP guidelines. During a mean follow‐up of 1199±950 days, 13 263 AF diagnoses were recorded. The incidence (95% CI) of AF was 15.8 (15.5–16.1) per 10 000 person‐years in men and 6.1 (5.9–6.3) per 10 000 person‐years in women. Compared with normal BP, elevated BP, stage 1 hypertension, and stage 2 hypertension were associated with an increased risk AF in both men and women. However, the hazard ratios were greater in women than in men, and the P value for interactions in the multivariable model was 0.0076. The models using restricted cubic spline showed that the risk of AF associated with elevated systolic BP increased steeply above an approximate threshold of systolic BP of 130 mm Hg in men and 100 mm Hg in women. Although our primary findings were consistent across subgroup analyses, this association was most significant in younger individuals. Conclusions Although the incidence of AF was higher in men, the association between hypertension and incident AF was more pronounced in women than in men, suggesting a potential sex difference in the relationship between hypertension and incident AF.

Introduction Data are lacking on the extent to which patients with non-valvular atrial fibrillation (AF) who are aged ≥80 years benefit from ablation treatment. The question pertains especially to patients’ postablation quality of life (QoL) and long-term clinical outcomes.Methods and analysis We are initiating a prospective, registry-based, multicentre observational study that will include patients aged ≥80 years with non-valvular AF who choose to undergo treatment by catheter ablation and, for comparison, such patients who do not choose to undergo ablation (either according to their physician’s advice or their own preference). Study subjects are to be enrolled from 52 participant hospitals and three clinics located throughout Japan from 1 June 2022 to 31 December 2023, and each will be followed up for 1 year. The planned sample size is 660, comprising 220 ablation group patients and 440 non-ablation group patients. The primary endpoint will be the composite incidence of stroke/transient ischaemic attack (TIA) or systemic embolism (SE), another cardiovascular event, major bleeding and/or death from any cause. Other clinical events such as postablation AF recurrence, a fall or bone fracture will be recorded. We will collect standard clinical background information plus each patient’s Clinical Frailty Scale score, AF-related symptoms, QoL (Five-Level Version of EQ-5D) scores, Mini-Mental State Examination (optional) score and laboratory test results, including measures of nutritional status, on entry into the study and 1 year later, and serial changes in symptoms and QoL will also be secondary endpoints. Propensity score matching will be performed to account for covariates that could affect study results.Ethics and dissemination The study conforms to the Declaration of Helsinki and the Ethical Guidelines for Clinical Studies issued by the Ministry of Health, Labour and Welfare, Japan. Results of the study will be published in one or more peer-reviewed journals.Trial registration number UMIN000047023.

Background There have been limited data examining the age‐dependent relationship of wide‐range risk factors with the incidence of each subtype of cardiovascular disease (CVD) event. We assessed age‐related associations between modifiable risk factors and the incidence of CVD. Methods and Results We analyzed 3 027 839 participants without a CVD history enrolled in the JMDC Claims Database (mean age, 44.8±11.0 years; 57.6% men). Each participant was categorized as aged 20 to 49 years (n=2 008 559), 50 to 59 years (n=712 273), and 60 to 75 years (n=307 007). Using Cox proportional hazards models and the relative risk reduction, we identified associations between risk factors and incident CVD, consisting of myocardial infarction, angina pectoris, stroke, and heart failure (HF). We assessed whether the association of risk factors for developing CVD would be modified by age category. Over a mean follow‐up of 1133 days, 6315 myocardial infarction, 56 447 angina pectoris, 28 079 stroke, and 56 369 HF events were recorded. The incidence of myocardial infarction, angina pectoris, stroke, and HF increased with age category. Hazard ratios of obesity, hypertension, and diabetes in the multivariable Cox regression analyses for myocardial infarction, angina pectoris, stroke, and HF decreased with age category. The relative risk reduction of obesity, hypertension, and diabetes for CVD events decreased with age category. For example, the relative risk reduction of hypertension for HF decreased from 59.2% in participants aged 20 to 49 years to 38.1% in those aged 60 to 75 years. Conclusions The contribution of modifiable risk factor to the development of CVD is greater in younger compared with older individuals. Preventive efforts for risk factor modification may be more effective in younger people.

Background Hypertension and diabetes frequently coexist. However, little is known about the interaction between high blood pressure (BP) and hyperglycemia in the development of cardiovascular disease (CVD). Methods and Results We conducted an observational cohort study that included 3 336 363 patients (median age, 43 years old; men, 57.2%). People taking BP‐ or glucose‐lowering medications or those with prior history of CVD were excluded. We defined stage 1 hypertension as having systolic BP of 130 to 139 mm Hg or diastolic BP of 80 to 89 mm Hg and stage 2 hypertension as having systolic BP of ≥140 mm Hg or diastolic BP of ≥90 mm Hg. We defined prediabetes as having fasting plasma glucose of 100 to 125 mg/dL and diabetes as having fasting plasma glucose of ≥126 mg/dL. Over a mean follow‐up period of 1185 ± 942 days, 5665 myocardial infarction, 52 475 angina pectoris, 25 436 stroke, 54 508 heart failure, and 12 932 atrial fibrillation events occurred. The BP and fasting plasma glucose categories additively increased the risk of myocardial infarction, angina pectoris, stroke, heart failure, and atrial fibrillation. However, the relative risk of stage 1 and stage 2 hypertension developing into CVD was attenuated with deteriorating glycemic status. Similarly, the relative risk of prediabetes and diabetes developing into CVD was attenuated with increasing BP. For example, the relative risk reduction of stage 2 hypertension for heart failure was 53.5% in individuals with normal fasting plasma glucose, 46.4% in those with prediabetes, and 37.2% in those with diabetes. The robustness of our findings was confirmed using a multitude of sensitivity analyses. Conclusions Although hypertension and hyperglycemia additively increase the risk of developing CVD, the relative contribution of hypertension to the development of CVD decreased with deteriorating glycemic status and that of hyperglycemia was attenuated with increasing BP. Our results indicate a potential interaction between hypertension and hyperglycemia in the development of CVD.

Cardiac immune cells play various roles in the maintenance of homeostasis and diseases in the heart. Here the authors show that cardiac resident macrophages are a critical regulator of cardiac impulse conduction through amphiregulin production, contributing to the prevention of sudden death.

Background The prevalence of hypertension subtypes changes with age. However, little is known regarding the age‐dependent association of hypertension subtypes with incident heart failure (HF). Methods and Results We conducted an observational cohort study including 2 612 570 people (mean age, 44.0 years; 55.0% men). No participants were taking blood pressure–lowering medications or had a known history of cardiovascular disease. Participants were categorized as aged 20 to 49 years (n=1 825 756), 50 to 59 years (n=571 574), or 60 to 75 years (n=215 240). We defined stage 1 hypertension as systolic blood pressure (SBP) 130 to 139 mm Hg or diastolic blood pressure (DBP) 80 to 89 mm Hg and stage 2 hypertension as SBP ≥140 mm Hg or DBP ≥90 mm Hg. Among participants with stage 2 hypertension, isolated diastolic hypertension was defined as SBP

Abstract Background Hospital volume is known to be associated with outcomes of patients requiring complicated medical care. However, the relationship between hospital volume and prognosis of hospitalized patients with heart failure (HF) remains not fully understood. We aimed to clarify the impact of hospital volume on clinical outcomes of hospitalized HF patients using a nationwide inpatient database. Methods and results We studied 447,818 hospitalized HF patients who were admitted from January 2010 and discharged until March 2018 included in the Japanese Diagnosis Procedure Combination database. According to the number of patients, patients were categorized into three groups; those treated in low-, medium-, and high-volume centers. The median age was 81 years and 238,192 patients (53%) were men. Patients who had New York Heart Association class IV symptom and requiring inotropic agent within two days were more common in high volume centers than in low volume centers. Respiratory support, hemodialysis, and intra-aortic balloon pumping were more frequently performed in high volume centers. As a result, length of hospital stay was shorter, and in-hospital mortality was lower in high volume centers. Lower in-hospital mortality was associated with higher hospital volume. Multivariable logistic regression analysis fitted with generalized estimating equation indicated that medium-volume group (Odds ratio 0.91, p = 0.035) and high-volume group (Odds ratio 0.86, p = 0.004) had lower in-hospital mortality compared to the low-volume group. Subgroup analysis showed that this association between hospital volume and in-hospital mortality among overall population was seen in all subgroups according to age, presence of chronic renal failure, and New York Heart Association class. Conclusion Hospital volume was independently associated with ameliorated clinical outcomes of hospitalized patients with HF.

Objectives This study aimed to assess whether adults with proteinuria were at a higher risk of incident colorectal cancer (CRC) than those without proteinuria using a large-scale population-based database.Design A retrospective observational study.Setting The JMDC Claims Database, an administrative health claims database, was used. Data were collected between 2005 and 2020.Participants We selected records of participants (n=3 543 705) who underwent health check-ups, including physical examinations, blood tests and urine dipstick tests. We excluded participants who were aged

Coronary angiography (CAG) is still considered the reference standard for coronary artery assessment, especially in the treatment of acute coronary syndrome (ACS). Although aging causes changes in coronary arteries, the age-related imaging features on CAG and their prognostic relevance have not been fully characterized. We hypothesized that a deep neural network (DNN) model could be trained to estimate vascular age only using CAG and that this age prediction from CAG could show significant associations with clinical outcomes of ACS. A DNN was trained to estimate vascular age using ten separate frames from each of 5,923 CAG videos from 572 patients. It was then tested on 1,437 CAG videos from 144 patients. Subsequently, 298 ACS patients who underwent percutaneous coronary intervention (PCI) were analysed to assess whether predicted age by DNN was associated with clinical outcomes. Age predicted as a continuous variable showed mean absolute error of 4 years with R squared of 0.72 (r = 0.856). Among the ACS patients stratified by predicted age from CAG images before PCI, major adverse cardiovascular events (MACE) were more frequently observed in the older vascular age group than in the younger vascular age group (p = 0.017). Furthermore, after controlling for actual age, gender, peak creatine kinase, and history of heart failure, the older vascular age group independently suffered from more MACE (hazard ratio 2.14, 95% CI 1.07 to 4.29, p = 0.032). The vascular age estimated based on CAG imaging by DNN showed high predictive value. The age predicted from CAG images by DNN could have significant associations with clinical outcomes in patients with ACS.

Background Studies of the association of hypertension with incident colorectal cancer (CRC) may have been confounded by including individuals taking antihypertensive medication, at high risk for CRC (ie, colorectal polyps and inflammatory bowel disease), or with shared risk factors (eg, obesity and diabetes). We assessed whether adults with untreated hypertension are at higher risk for incident CRC compared with those with normal blood pressure (BP), and whether any association is evident among individuals without obesity or metabolic abnormalities. Methods and Results Analyses were conducted using a nationwide health claims database collected in the JMDC Claims Database between 2005 and 2018 (n=2 220 112; mean age, 44.1±11.0 years; 58.4% men). Participants who were taking antihypertensive medications or had a history of CRC, colorectal polyps, or inflammatory bowel disease were excluded. Each participant was categorized as having normal BP (systolic BP [SBP]

Patients with hypertrophic cardiomyopathy (HCM) are prohibited from engaging in intensive exercise, to avoid sudden death. Given that patients with HCM, even those without left-ventricular outflow tract obstruction at rest, potentially have exercise-induced obstruction, reasonable monitoring methods during exercise are required. We present the case of a woman with HCM with exercise-induced obstruction whose hemodynamics during stress echocardiography were under observation using noninvasive cardiac output monitoring. Stroke volume declined during exercise before the manifest elevation of the left-ventricular outflow tract pressure gradient. As shown here, a noninvasive monitoring method can be useful in monitoring hemodynamics during exercise in HCM patients. Résumé: Les patients atteints d’une cardiomyopathie hypertrophique (CMH) se voient interdire la pratique d’activités physiques intenses, sous peine de mort subite. Étant donné le risque d’obstruction induite par l’effort auquel sont exposés les patients atteints de CMH, même ceux qui ne présentent pas d’obstruction de la voie d’éjection ventriculaire gauche au repos, des méthodes de surveillance raisonnables doivent être employées durant l’activité physique. Nous présentons le cas d’une femme atteinte de CMH ayant présenté une obstruction induite par l’effort et dont les paramètres hémodynamiques durant une échocardiographie à l’effort étaient surveillés au moyen d’un dispositif non invasif de mesure du débit cardiaque. Le volume d’éjection a diminué durant l’effort avant même que l’élévation du gradient de pression dans la voie d’éjection ventriculaire gauche puisse être observée. Comme nous l’expliquons ici, il peut être utile d’avoir recours à une méthode non invasive pour surveiller les paramètres hémodynamiques durant l’effort chez les patients atteints d’une CMH.

This report presents a new hybrid lead extraction technique combined with transatrial laser lead extraction and surgical removal of calcified lesions in a 50-year-old man with superior vena cava syndrome and bilateral subclavian vein occlusion caused by an abandoned lead, which had been infected for 11 years. (Level of Difficulty: Intermediate.)

BackgroundDevelopment of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials.Methods and findingsA modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d-1 (95% CI: 1.06 to 1.27 d-1), 0.777 d-1 (0.716 to 0.838 d-1), and 0.450 d-1 (0.378 to 0.522 d-1) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation.ConclusionsIn this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

Objective The current status of surgical treatment for infective endocarditis (IE) among very elderly people is unclear.Methods We extracted data on patients in Japan with community-acquired IE who were admitted and discharged between April 2010 and February 2018 using a nationwide inpatient, the Diagnosis Procedure Combination database. We divided patients into three groups: non-elderly (

Intravascular ultrasound (IVUS) is a diagnostic modality used during percutaneous coronary intervention. However, specialist skills are required to interpret IVUS images. To address this issue, we developed a new artificial intelligence (AI) program that categorizes vessel components, including calcification and stents, seen in IVUS images of complex lesions. When developing our AI using U-Net, IVUS images were taken from patients with angina pectoris and were manually segmented into the following categories: lumen area, medial plus plaque area, calcification, and stent. To evaluate our AI’s performance, we calculated the classification accuracy of vessel components in IVUS images of vessels with clinically significantly narrowed lumina (< 4 mm2) and those with severe calcification. Additionally, we assessed the correlation between lumen areas in manually-labeled ground truth images and those in AI-predicted images, the mean intersection over union (IoU) of a test set, and the recall score for detecting stent struts in each IVUS image in which a stent was present in the test set. Among 3738 labeled images, 323 were randomly selected for use as a test set. The remaining 3415 images were used for training. The classification accuracies for vessels with significantly narrowed lumina and those with severe calcification were 0.97 and 0.98, respectively. Additionally, there was a significant correlation in the lumen area between the ground truth images and the predicted images (ρ = 0.97, R2 = 0.97, p < 0.001). However, the mean IoU of the test set was 0.66 and the recall score for detecting stent struts was 0.64. Our AI program accurately classified vessels requiring treatment and vessel components, except for stents in IVUS images of complex lesions. AI may be a powerful tool for assisting in the interpretation of IVUS imaging and could promote the popularization of IVUS-guided percutaneous coronary intervention in a clinical setting.

Background The 2017 American College of Cardiology (ACC)/American Heart Association (AHA) guidelines lowered the threshold of blood pressure (BP) for hypertension to 130/80 mm Hg. However, the clinical significance of isolated diastolic hypertension (IDH) according to the cutoff value of the 2017 ACC/AHA guidelines was uncertain. Methods and Results We analyzed the claims database of Japan Medical Data Center (a nationwide epidemiological database). We excluded individuals who were aged

Background: Whether acute-phase cardiac rehabilitation (CR) is beneficial for short-term improvement in activities of daily living (ADL) in patients hospitalized for acute heart failure (AHF) remains unclear. Aim: To investigate the association of acute-phase initiation of CR with short-term improvement in ADL in patients hospitalized for AHF. Methods: We retrospectively analyze data from the Diagnosis Procedure Combination Database, a nationwide inpatient database. Patients hospitalized for HF between January 2010 and March 2018 are included. Propensity score matching and generalized linear models are built to examine the association between improvement in ADL and acute-phase CR initiation, defined as the initiation of CR within two days of admission. Results: Among 306,826 eligible patients, CR is initiated in 45,428 patients (14.8%) within two days of hospital admission. Propensity score matching creates 45,427 pairs. CR initiation within two days of hospital admission is associated with ADL improvement (risk ratio: 1.018; 95% confidence interval: 1.004–1.032), particularly in elderly patients, females, and individuals with low ADL at admission, body mass index of 18.5–24.9 kg/m2, and New York Heart Association class IV. Conclusions: Our analyses highlight the possibility that acute-phase CR initiation may result in short-term improvement in ADL in patients hospitalized for AHF.

Context: There have been insufficient data on the threshold of body mass index (BMI) for developing diabetes mellitus (DM) and the relationship between change in BMI and the subsequent risk of DM. Objective: We sought to clarify the association of BMI and its change with incident DM. Methods: We conducted a retrospective observational cohort study using the JMDC Claims Database between 2005 and 2021. We included 3 400 303 individuals without a prior history of DM or usage of glucose-lowering medications. The median age was 44 years, and 57.5% were men. We categorized the study participants into 4 groups: underweight (BMI < 18.5 kg/m²), normal weight (BMI 18.5-24.9 kg/m²), overweight (BMI 25.0-29.9 kg/m²), and obese (BMI ≥ 30 kg/m²). According to the change in BMI from the initial health check-up to the health check-up 1 year after that, we divided the study participants into 3 groups: ≤-5.0%, -5.0% to +5.0%, and ≥+5.0%. Results: The risk of developing DM increased steeply after BMI exceeded approximately 20 to 21 kg/m². Compared with participants with stable BMI (-5.0% to +5.0%), the relative risk for DM among those whose BMI had increased by 5.0% or more was 1.33 (95% CI 1.31-1.36). In contrast, the relative risk for DM among those whose BMI decreased by 5.0% or more was 0.82 (95% CI 0.80-0.84). Moreover, people classified as normal weight, overweight, and obese reduced the risk of developing DM when they reduced their BMI, whereas the risk of developing DM for people classified as underweight increased when they reduced their BMI. Conclusion: Our findings offer novel insights into improving an optimal bodyweight management strategy to prevent the development of DM. [ABSTRACT FROM AUTHOR]