Publications by authors named "Toshiyuki Ko"

Aim: Although frailty is the result of multifactorial vulnerability, such as physical, cognitive, and socio-psychological factors, the association of multifactor-defined frailty and its components with cardiovascular disease (CVD) has not been investigated. The goal of this paper is to clarify the association between multifactor-defined frailty and its components and CVD in older adults.

Methods: Using a nationwide claims database, we included 66 948 participants aged ≥65 years without a history of CVD who were assessed using a simple questionnaire-based approach covering physical, cognitive, oral, nutritional, and social aspects of frailty.

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Background: Body compositions are closely related to stroke risk. Recently, lean mass index (LMI) has been demonstrated to be a precise indicator of cardiovascular disease (CVD) risk, and the newly proposed formula enabled the simple estimation of LMI without a computed tomography scan. However, little is known about its attribution to a risk of stroke.

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Sudden cardiac death is a catastrophic event, making its prevention important. However, patient selection for primary prevention remains controversial. We report two cases of cardiac conduction disorder initially treated with permanent pacemaker implantation.

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Aims: Sodium-glucose cotransporter-2 (SGLT2) inhibitors have proven kidney protective effects. Given that the SGLT2 inhibitors lower blood pressure (BP), the magnitude of their kidney benefits may vary depending on an individual's BP. Therefore, we investigated whether baseline BP modifies the effect of SGLT2 inhibitors on kidney function.

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Background: Left ventricular reverse remodeling (LVRR) is associated with a good prognosis in patients with dilated cardiomyopathy (DCM), so in this study we examined the achievement rates of LVRR, the time taken to LVRR and the factors associated with LVRR in recent cases of DCM.

Methods And Results: We enrolled 121 patients with DCM. LVRR was defined as a left ventricular ejection fraction ≥40% at follow-up with a ≥10% improvement.

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Aims: To investigate the clinical significance of the modification of the kidney protective effects of sodium-glucose cotransporter-2 (SGLT2) inhibitors by baseline body mass index (BMI).

Methods And Results: We included individuals with SGLT2 inhibitors or dipeptidyl peptidase-4 (DPP4) inhibitors newly prescribed for type 2 diabetes using a nationwide epidemiological cohort and performed propensity score matching (1:2). The primary outcome was the annual eGFR decline, assessed using a linear mixed-effects model, compared between individuals with SGLT2 inhibitors and DPP4 inhibitors.

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Aim: Sleep apnoea syndrome (SAS) is a common sleep disorder associated with heightened cardiovascular risks, yet sex-specific differences in these risks remain unclear.

Methods: This retrospective observational cohort study utilized the JMDC Claims Database, covering >5 million individuals in Japan. We analyzed data from 4,173,702 individuals (2,406,930 men, 1,766,772 women) after excluding those with central SAS, cardiovascular disease, and incomplete lifestyle questionnaire data.

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Study Objectives: Sleep apnea syndrome (SAS) is potentially linked to life-threatening conditions. The decline in kidney function is involved in the development of various diseases; however, it remains unclear whether it is implicated in the onset of SAS. Therefore, this study aimed to investigate the relationship between kidney function and the incidence of SAS.

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Aim: It remains unknown whether sodium-glucose cotransporter 2 inhibitors (SGLT2i) could be associated with incident cancer.

Methods: We analyzed individuals having diabetes and newly prescribed SGLT2i or dipeptidyl peptidase 4 inhibitors (DPP4i) in a large-scale epidemiological database. The primary outcome was the incidence of cancer.

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Article Synopsis
  • Heart failure (HF) is a significant health issue that requires effective diagnostic and prognostic tools to manage patient outcomes.
  • The study introduces TRAITER, a deep learning model that uses image segmentation and Vision Transformer technology to predict HF likelihood and the potential for left ventricular reverse remodeling (LVRR) based on cardiac tissue images.
  • TRAITER demonstrated high accuracy (83.1% for HF diagnosis and 84.2-92.9% for LVRR prediction) and outperformed existing neural network models, aiming to enhance personalized decision-making in HF treatment.
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Background: Approximately 10% of hypertrophic cardiomyopathy (HCM) patients have left ventricular systolic dysfunction (end-stage HCM) leading to severe heart-failure; however, risk stratification to identify patients at risk of progressing to end-stage HCM remains insufficient.

Objectives: In this study, the authors sought to elucidate whether the coexistence of other cardiovascular disease (CVD)-related variants is associated with progression to end-stage HCM in patients with HCM harboring pathogenic or likely pathogenic (P/LP) sarcomeric variants.

Methods: The authors performed genetic analysis of 83 CVD-related genes in HCM patients from a Japanese multicenter cohort.

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Article Synopsis
  • The study examines how declining estimated glomerular filtration rate (eGFR) is linked to an increased risk of depression in a large population, particularly focusing on kidney dysfunction stages.
  • Analyzing data from over 1.5 million individuals without prior depression history, researchers found that a drop in eGFR heightens depression risk, especially as eGFR falls below 65 mL/min/1.73 m.
  • Results indicate that as kidney function declines, the likelihood of developing depression rises significantly, emphasizing the need for mental health evaluations in patients with kidney issues.
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Article Synopsis
  • Clonal hematopoiesis of indeterminate potential (CHIP) is shown to worsen outcomes in patients with nonischemic dilated cardiomyopathy (DCM) despite being well-known for its negative impacts on atherosclerotic disease.
  • Researchers analyzed 198 DCM patients using advanced genetic sequencing to find both germline mutations linked to cardiomyopathy and somatic mutations in CHIP driver genes, discovering 25 CHIP mutations in 22 patients.
  • The study concluded that CHIP is an independent risk factor for cardiac issues in DCM, contributing to worsened heart function and structural damage, and that genetic mutations can help predict patient prognosis.
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Aim: To investigate the clinical significance of body weight changes on kidney outcomes among individuals with diabetes using sodium-glucose cotransporter-2 (SGLT2) inhibitors.

Materials And Methods: This is a retrospective cohort study using a nationwide epidemiological database, and we conducted an analysis involving 11 569 individuals with diabetes who were newly prescribed SGLT2 inhibitors. The main outcome was the rate of decline in estimated glomerular filtration rate (eGFR), determined through a linear mixed-effects model with an unstructured covariance structure.

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Background: While the kidney-protective effects of sodium-glucose co-transporter 2 (SGLT2) inhibitors have attracted much attention, there are limited real-world clinical data examining the effects of SGLT2 inhibitors on kidney function in older individuals. We aimed to compare the kidney outcomes between SGLT2 inhibitor and dipeptidyl peptidase 4 (DPP4) inhibitor use in older adults with diabetes.

Methods: Using a nationwide claims database, we studied 6354 older adults (≥60 years of age) who had diabetes and were newly initiated on SGLT2 inhibitors or DPP4 inhibitors.

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Background: The heart comprises many types of cells such as cardiomyocytes, endothelial cells (ECs), fibroblasts, smooth muscle cells, pericytes, and blood cells. Every cell type responds to various stressors (eg, hemodynamic overload and ischemia) and changes its properties and interrelationships among cells. To date, heart failure research has focused mainly on cardiomyocytes; however, other types of cells and their cell-to-cell interactions might also be important in the pathogenesis of heart failure.

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The integration of multiple omics data promises to reveal new insights into the pathogenic mechanisms of complex human diseases, with the potential to identify avenues for the development of targeted therapies for disease subtypes. However, the extraction of diagnostic/disease-specific biomarkers from multiple omics data with biological pathway knowledge is a challenging issue in precision medicine. In this paper, we present a novel computational method to identify diagnosis-specific trans-omic biomarkers from multiple omics data.

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