Differences in the Association of Lifestyle-Related Modifiable Risk Factors with Incident Cardiovascular Disease Between Individuals with and without Diabetes.

AIMS: Individuals with diabetes have a high risk of developing cardiovascular disease (CVD). Little was known whether the association between modifiable risk factors and incident CVD would change according to the presence of diabetes. METHODS: In this study, we analyzed 4,132,006 individuals including 173,262 individuals (4.2%) with diabetes registered in the JMDC Claims Database, and compared the association between modifiable risk factors and risk of CVD between individuals with and without diabetes. RESULTS: The median age was 44 years, and 57.5% were men. Multivariable Cox regression analyses showed that the relationship of obesity, hypertension, and dyslipidemia with incident CVD was attenuated in individuals with diabetes, whereas that of non-ideal eating habits, smoking, and physical inactivity with incident CVD was pronounced in those with diabetes. The hazard ratio per 1-point increase in non-ideal lifestyle-related factors was 1.03 [95% confidence interval (CI) 1.03-1.04] in individuals with non-diabetes, whereas 1.09 [95% CI 1.07-1.11] in individuals with diabetes (p-value for interaction < 0.001). Further, hazard ratios for developing CVD were 1.02 [95% 1.01-1.04] in individuals not having diabetes, whereas 1.09 [95% CI 1.04-1.13] in individuals having diabetes for the increase of lifestyle-related factor after 1-year follow-up (p-value for interaction 0.007). CONCLUSION: Our analysis utilizing a nationwide epidemiological dataset presented that the relationship of lifestyle-related factors with incident CVD would be pronounced in people having diabetes, suggesting that the maintenance of a healthy lifestyle would play a more important role in the development of CVD in individuals having diabetes. (244 words).

Our investigation utilizing a nationwide epidemiological cohort showed a pronounced relationship of lifestyle-related factors with incident CVD in individuals with diabetes. The HRs (95% CI) for the occurrence of CVD events showed a progressive increase with each additional lifestyle-related factor. This trend was more prominent among individuals with diabetes than those without diabetes. The association between changes in the number of lifestyle-related factors over a year and the risk of developing CVD was also more pronounced in individuals with diabetes. These results suggest that maintaining healthy lifestyle habits would be more important for the CVD prevention in individuals having diabetes.

Comparison of incident hypertension between SGLT2 inhibitors vs. DPP4 inhibitors.

Although several randomized clinical trials have reported the potential benefit of sodium-glucose cotransporter 2 inhibitors (SGLT2i) in reducing blood pressure (BP), whether SGLT2i can reduce incident hypertension is unknown. We analyzed individuals with diabetes who were newly prescribed SGLT2i or dipeptidyl peptidase 4 inhibitors (DPP4i) in a large-scale epidemiological database. The primary outcome was the incidence of hypertension. A propensity score matching algorithm was employed to compare the subsequent development of hypertension between the SGLT2i and DPP4i groups. After propensity score matching, 5708 well-balanced pairs of SGLT2i and DPP4i users were identified. SGLT2i administration was associated with a reduced risk of hypertension (HR 0.91, 95% CI: 0.84-0.97). The advantage of SGLT2i use over DPP4i use for incident hypertension was generally consistent in several sensitivity analyses, and subgroup analyses showed that SGLT2i use was significantly associated with a lower risk of hypertension in men, patients with baseline HbA1c of <7.5%, and baseline systolic blood pressure ≥127 mmHg. Our investigation using nationwide real-world data demonstrated the potential advantage of SGLT2i over DPP4i in reducing the development of hypertension in individuals with diabetes.

Awareness of Being Prescribed Antihypertensive Medications and Cardiovascular Outcomes.

BACKGROUND: Hypertension is a major cause of cardiovascular disease (CVD). In patients with hypertension, unawareness of the disease often results in poor blood pressure control and increases the risk of CVD. However, data in nationwide surveys regarding the proportion of unaware individuals and the implications of such on their clinical outcomes are lacking. We aimed to clarify the association between unawareness of being prescribed antihypertensive medications among individuals taking antihypertensive medications and the subsequent risk of developing CVD.Methods and Results: This retrospective cohort study analyzed data from the JMDC Claims Database, including 313,715 individuals with hypertension treated with antihypertensive medications (median age 56 years). The primary endpoint was a composite of myocardial infarction, angina pectoris, stroke, heart failure, and atrial fibrillation. Overall, 19,607 (6.2%) individuals were unaware of being prescribed antihypertensive medications. During the follow-up period, 33,976 composite CVD endpoints were documented. Despite their youth, minimal comorbidities, and the achievement of better BP control with a reduced number of antihypertensive prescriptions, unawareness of being prescribed antihypertensive medications was associated with a greater risk of developing composite CVD. Hazard ratios of unawareness of being prescribed antihypertensive medications were 1.16 for myocardial infarction, 1.25 for angina pectoris, 1.15 for stroke, 1.36 for heart failure, and 1.28 for atrial fibrillation. The results were similar in several sensitivity analyses, including the analysis after excluding individuals with dementia. CONCLUSIONS: Among individuals taking antihypertensive medications, assessing the awareness of being prescribed antihypertensive medications may help identify those at high risk for CVD-related events.

Unawareness of being prescribed medications for diabetes and incident cardiovascular disease.

BACKGROUND: Some patients with diabetes are unaware that they are prescribed medications for diabetes. The purpose of this study is to determine, using a Japanese nationwide epidemiologic database, the association between unawareness of being prescribed medication for diabetes and the risk of developing cardiovascular disease (CVD) in patients with diabetes. METHODS: This observational cohort study analyzed data from the JMDC Claims Database between 2005 and 2022, including 94,048 patients with diabetes treated with medications. The primary endpoint was a composite endpoint including myocardial infarction (MI), stroke, heart failure (HF), and atrial fibrillation (AF). RESULTS: We identified 7561 composite CVD endpoints during a mean follow-up of 1199 ±â€¯902 days. Overall, 7779 (8.3 %) patients were unaware of being prescribed medications for diabetes. Those who did not know they were prescribed drugs were younger and had better glycemic control, but these individuals were at higher risk of developing combined CVD [hazard ratio (HR) 1.13, 95 % confidence interval (95 % CI) 1.04-1.22]. HRs of unawareness of being prescribed medications for diabetes were 1.33 (95 % CI 1.06-1.68) for MI, 1.13 (95 % CI 0.97-1.31) for stroke, 1.10 (95 % CI 1.00-1.21) for HF, and 1.19 (95 % CI 0.97-1.47) for AF, respectively. CONCLUSIONS: In patients with diabetes taking medications for diabetes, even if they are young and have good glycemic control, unawareness of being prescribed medications for diabetes was associated with a greater risk of developing CVD. It is important that they receive adequate education from their healthcare providers to accurately identify their treatment status.

Sex Differences in the Relationship Between Schizophrenia and the Development of Cardiovascular Disease.

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.

Machine learning in cardiology: Clinical application and basic research.

Machine learning is a subfield of artificial intelligence. The quality and versatility of machine learning have been rapidly improving and playing a critical role in many aspects of social life. This trend is also observed in the medical field. Generally, there are three main types of machine learning: supervised, unsupervised, and reinforcement learning. Each type of learning is adequately selected for the purpose and type of data. In the field of medicine, various types of information are collected and used, and research using machine learning is becoming increasingly relevant. Many clinical studies are conducted using electronic health and medical records, including in the cardiovascular area. Machine learning has also been applied in basic research. Machine learning has been widely used for several types of data analysis, such as clustering of microarray analysis and RNA sequence analysis. Machine learning is essential for genome and multi-omics analyses. This review summarizes the recent advancements in the use of machine learning in clinical applications and basic cardiovascular research.

Development of non-bias phenotypic drug screening for cardiomyocyte hypertrophy by image segmentation using deep learning.

The number of patients with heart failure and related deaths is rapidly increasing worldwide, making it a major problem. Cardiac hypertrophy is a crucial preliminary step in heart failure, but its treatment has not yet been fully successful. In this study, we established a system to evaluate cardiomyocyte hypertrophy using a deep learning-based high-throughput screening system and identified drugs that inhibit it. First, primary cultured cardiomyocytes from neonatal rats were stimulated by both angiotensin II and endothelin-1, and cellular images were captured using a phase-contrast microscope. Subsequently, we used a deep learning model for instance segmentation and established a system to automatically and unbiasedly evaluate the cardiomyocyte size and perimeter. Using this system, we screened 100 FDA-approved drugs library and identified 12 drugs that inhibited cardiomyocyte hypertrophy. We focused on ezetimibe, a cholesterol absorption inhibitor, that inhibited cardiomyocyte hypertrophy in a dose-dependent manner in vitro. Additionally, ezetimibe improved the cardiac dysfunction induced by pressure overload in mice. These results suggest that the deep learning-based system is useful for the evaluation of cardiomyocyte hypertrophy and drug screening, leading to the development of new treatments for heart failure.

The complement C3-complement factor D-C3a receptor signalling axis regulates cardiac remodelling in right ventricular failure.

Failure of the right ventricle plays a critical role in any type of heart failure. However, the mechanism remains unclear, and there is no specific therapy. Here, we show that the right ventricle predominantly expresses alternative complement pathway-related genes, including Cfd and C3aR1. Complement 3 (C3)-knockout attenuates right ventricular dysfunction and fibrosis in a mouse model of right ventricular failure. C3a is produced from C3 by the C3 convertase complex, which includes the essential component complement factor D (Cfd). Cfd-knockout mice also show attenuation of right ventricular failure. Moreover, the plasma concentration of CFD correlates with the severity of right ventricular failure in patients with chronic right ventricular failure. A C3a receptor (C3aR) antagonist dramatically improves right ventricular dysfunction in mice. In summary, we demonstrate the crucial role of the C3-Cfd-C3aR axis in right ventricular failure and highlight potential therapeutic targets for right ventricular failure.

Prediction of Serious Adverse Events of Patients with Hypertrophic Cardiomyopathy by Magnetic Resonance.

Although it is well known that patients with hypertrophic cardiomyopathy (HCM) have serious adverse events, such as life-threatening arrhythmia and heart failure, the prediction of such evens is still difficult. Recently, it has been reported that one of the causes of these serious adverse events is microvascular dysfunction, which can be noninvasively evaluated by employing cardiac magnetic resonance (CMR) imaging.We analyzed 32 consecutive HCM patients via CMR imaging and myocardial scintigraphy and divided them into two groups: ventricular tachycardia (VT) group and non-VT group. Myocardial perfusion studies were conducted quantitatively using the QMass® software, and each slice image was divided into six segments. The time-intensity curve derived from the perfusion image by CMR imaging was evaluated, and the time to 50% of the peak intensity (time 50% max) was automatically calculated for each segment.Although no difference was observed in various parameters of myocardial scintigraphy between the two groups, the VT group exhibited a higher mean of time 50% max and wider standard deviation (SD) of time 50% max in each segment than the non-VT group. The cutoff values were obtained by the receiver operating characteristic curves derived from the mean of time 50% max and SD of time 50% max. The two groups divided by the cutoff values exhibited significant differences in the occurrence of serious adverse events.CMR imaging may be useful for predicting serious adverse events of patients with HCM.

Anti-senescent drug screening by deep learning-based morphology senescence scoring.

Advances in deep learning technology have enabled complex task solutions. The accuracy of image classification tasks has improved owing to the establishment of convolutional neural networks (CNN). Cellular senescence is a hallmark of ageing and is important for the pathogenesis of ageing-related diseases. Furthermore, it is a potential therapeutic target. Specific molecular markers are used to identify senescent cells. Moreover senescent cells show unique morphology, which can be identified. We develop a successful morphology-based CNN system to identify senescent cells and a quantitative scoring system to evaluate the state of endothelial cells by senescence probability output from pre-trained CNN optimised for the classification of cellular senescence, Deep Learning-Based Senescence Scoring System by Morphology (Deep-SeSMo). Deep-SeSMo correctly evaluates the effects of well-known anti-senescent reagents. We screen for drugs that control cellular senescence using a kinase inhibitor library by Deep-SeSMo-based drug screening and identify four anti-senescent drugs. RNA sequence analysis reveals that these compounds commonly suppress senescent phenotypes through inhibition of the inflammatory response pathway. Thus, morphology-based CNN system can be a powerful tool for anti-senescent drug screening.

Peripheral pulmonary stenosis with Noonan syndrome treated by balloon pulmonary angioplasty.

Noonan syndrome is known to have various cardiovascular defects, which include pulmonary artery stenosis. Pulmonary artery stenosis is characterized by obstruction of pulmonary artery blood flow that can cause elevated pulmonary artery pressure and ventilation-perfusion inequality, which can cause dyspnea on exertion and eventually, heart failure. Although the etiology of pulmonary artery stenosis related to congenital diseases is still unknown, balloon pulmonary angioplasty has being reported to be effective to selected patients with Alagille and Williams syndromes, but not from Noonan syndrome despite of modest prevalence of pulmonary artery stenosis. Here, we report the first Noonan syndrome patient with pulmonary artery stenosis who underwent successful balloon pulmonary angioplasty. The strategy used in balloon pulmonary angioplasty was planned with careful morphologic evaluation by computed tomographic angiography, and performed with scoring balloons in a graded approach with multiple sessions. After balloon pulmonary angioplasty, we confirmed maintained dilation of lesions and symptom alleviation, suggesting that balloon pulmonary angioplasty can be performed safely on pulmonary artery stenosis in a Noonan syndrome patient.

Successful Surgical Treatment Combined With Infliximab in a Patient With Acute Aortic Regurgitation Caused by Behçet Disease.

Standard aortic valve replacement for aortic regurgitation caused by Behçet disease (BD) is frequently complicated by postoperative recurrent prosthetic valve detachment. Tumour necrosis factor (TNF) α is known to be associated with higher inflammation activities. Therefore, the concomitant use of immunomodulatory agents with TNFα inhibitors may be the key to a better outcome. This is a case report of a 46-year-old woman with severe acute aortic regurgitation due to BD. Immunosuppressive therapy including the TNFα inhibitor infliximab, which has not been reported for perioperative use to date, resulted in the prompt remission of inflammation, leading to the success of Bentall surgery.

Clinical Scenario Classification for Characterization and Outcome Prediction of Acute Decompensated Heart Failure Under Contemporary Phenotyping.

Background: The concept of Clinical Scenario (CS) classification has been widely utilized to aid in choosing appropriate management strategies for acute decompensated heart failure (ADHF). Methods and Results: The West Tokyo-Heart Failure (WET-HF) Registry is a multicenter, prospective cohort registry enrolling consecutive hospitalized ADHF patients. Based on systolic blood pressure (SBP) at admission, 4,000 patients enrolled between 2006 and 2017 were classified into 3 groups: CS1, SBP ≥140 mmHg; CS2, 100≤SBP<140 mmHg; and CS3, SBP <100 mmHg. The CS1 group had a high rate of fluid retention such as leg edema, and the largest reduction in body weight at discharge. In-hospital diuretics use was the most frequent in CS1. Although the primary endpoint of long-term all-cause death and/or ADHF re-hospitalization was more common in more advanced CS, there was no significant difference between the 3 CS groups in patients with HF with preserved ejection fraction (HFpEF; P=0.10). Although more advanced CS was associated with larger left ventricular (LV) chamber size in HF with reduced EF (HFrEF), it was associated with smaller LV size in HFpEF. Conclusions: The long-term prognostic value of CS classification was limited in HFpEF. Whereas CS was closely associated with degree of LV remodeling in HFrEF, a smaller LV chamber might be associated with a lower cardiovascular functional reserve in HFpEF.

Various Cardiac Abnormalities Caused by Bacterial Myocarditis.

A 69-year-old woman without any past disease history was hospitalized for heart failure. After hospitalization, she showed myocardial infarction, atrioventricular dissociation, and cardiac dysfunction, and finally she passed away despite intensive care. Autopsy revealed that the cardiac abnormalities were due to bacterial myocarditis possibly resulting from urinary tract infection by E. coli. Although bacterial myocarditis is rare in developed countries, we should consider its possibility when patients show various cardiac abnormalities with bacterial infection.

Adrenal insufficiency causes life-threatening arrhythmia with prolongation of QT interval.

A 63-year-old woman who had hypopituitarism was re-admitted to our hospital because of fever, diarrhea and disturbance of consciousness with life-threatening arrhythmia due to prolongation of the QT interval. She has been treated with hydrocortisone consequently, and has shown few ventricular arrhythmias with normalization of the QT interval. There have been several reports showing the case of prolonged QT interval with adrenal insufficiency, but there are few reports of isolated adrenocorticotropic hormone deficiency without any electrolytes imbalance that showed polymorphic ventricular tachycardia associated with QT prolongation. We discuss some possible mechanisms of how adrenal insufficiency causes life-threatening arrhythmia. Since lack of glucocorticoid hormone might induce prolongation of the QT interval, patients with adrenal insufficiency should be paid attention as candidates of lethal arrhythmias particularly when exposed to excessive stresses.