Short QT syndrome (SQTS) is a very rare inherited arrhythmia characterized by extremely short QT intervals on electrocardiograms and sudden cardiac death in young patients. Among the genotypes of SQTS, gain-of-function variants in the potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene are accountable for SQTS type 2 (SQT2). Pathogenic variants for SQT2 are rare and, among them, the p.Val141Met is relatively prevalent. This review summarizes findings for 5 SQTS patients harboring p.Val141Met we recently encountered and compares them to another 14 patients reported in the literature.

Background: Abdominal aortic aneurysm (AAA) is a vascular disease strongly associated with immune dysregulation and metabolic disturbances. Although lactate metabolism and its associated process, lactylation, have been implicated in various diseases, their specific role in AAA pathogenesis remains poorly understood.

Methods and Results: In this study, we used a multi-faceted approach, integrating single-cell and bulk RNA data analyses, with the objective of elucidating the interrelationship between lactylation and immune response in AAA patients. The result revealed significant heterogeneity in lactylation levels across different immune cell types. Cells with higher lactylation activity exhibited markedly elevated immune response scores. Differential expression and correlation analyses identified 65 lactylation-associated genes, which were further evaluated in the bulk RNA sequencing data to assess their relationship with the immune microenvironment in patients with AAA. Using 113 combinations of machine-learning algorithms, we identified 8 lactylation-related hub genes. The immune infiltration analysis demonstrated that these genes were linked to a multitude of immune cells. The animal experiments corroborated that Tnfsf8, Hist1 h2ag, Cd79b, Cd69, and Bank1 were upregulated in the AAA group, while Rpl36a and Rps29 were downregulated in the AAA group.

Conclusions: This study highlighted a potentially critical link between lactylation and immune dysregulation in AAA, thereby advancing our comprehension of the function of lactylation in AAA.

Background: Preoperative risk assessment is very important to ensure surgical safety and predict postoperative complications. However, no large-scale studies have evaluated the risk of perioperative cardiovascular events in Japan. This study evaluated perioperative cardiovascular events using real-world data. In addition, the applicability of machine learning to risk stratification was examined to develop a predictive model for perioperative cardiovascular events.

Methods and Results: This was an observational cohort study using the Japan Medical Data Center database, which includes claim and health examination data in Japan, between January 2005 and April 2021. In all, 133,634 gastrointestinal surgeries were included in the analysis. The primary outcome was 30-day risk of major adverse cardiovascular events (MACE). The 30-day MACE incidence rate following surgery was 3.8%. Machine learning was used to perform a binary classification task to predict MACE occurrence within 30 days after surgery. A clustering algorithm was developed based on the Shapley additive explanation values obtained from training data, and generalizability was evaluated using test data. Of the variables, age, history of ischemic heart disease or heart failure, history of stroke, diabetes, hypertension, atrial fibrillation, cases of malignancy, and pancreatic biliary surgery were identified as factors associated with MACE occurrence.

Conclusions: A machine learning model built from basic clinical information, comorbidities, and surgical information demonstrated the capacity to stratify MACE risk in patients undergoing gastrointestinal surgery.

The World Health Organization recognizes digital health as a key driver for sustainable health systems. Digital health is broad concept that refers to the use of digital technologies to improve health and healthcare. Mobile health is part of digital health and refers to the use of mobile devices such as smartphones, tablets, and wearable gadgets to deliver health-related services. By proactively utilizing personal health records from mHealth, in conjunction with electronic health records, advanced medical practices can be achieved. This integration facilitates app-based patient education and encouragement, lifestyle modification, and efficient sharing of medical information between hospitals. Beyond emergency care, information sharing enables patients to visit multiple healthcare facilities without redundant tests or unnecessary referrals, reducing the burden on both patients and healthcare providers.

Recent advances in traditional “-omics” technologies have provided deeper insights into cardiovascular diseases through comprehensive molecular profiling. Accordingly, digitalomics has emerged as a novel transdisciplinary concept that integrates multimodal information with digitized physiological data, medical imaging, environmental data, electronic health records, environmental records, and biometric data from wearables. This digitalomics-driven augmented multiomics approach can provide more precise personalized health risk assessments and optimization when combined with conventional multiomics approaches. Artificial intelligence and machine learning (AI/ML) technologies, alongside statistical methods, serve as key comprehensive analytical tools in realizing this comprehensive framework. This review focuses on two promising AI/ML applications in cardiovascular medicine: digital phonocardiography (PCG) and AI text generators. Digital PCG uses AI/ML models to objectively analyze heart sounds and predict clinical parameters, potentially surpassing traditional auscultation capabilities. In addition, large language models, such as generative pretrained transformer, have demonstrated remarkable performance in assessing medical knowledge, achieving accuracy rates exceeding 80% in medical licensing examinations, although there are issues regarding knowledge accuracy and safety. Current challenges to the implementation of these technologies include maintaining up-to-date medical knowledge and ensuring consistent accuracy of outputs, but ongoing developments in fine-tuning and retrieval-augmented generation show promise in addressing these challenges. Integration of AI/ML technologies in clinical practice, guided by appropriate validation and implementation strategies, may notably advance precision cardiovascular medicine through the digitalomics framework.

Time-space network hypertension is a data science approach that connects diverse information related to hypertension within a time-space framework. This field of academic research aims to predict disease onset and direct effective, individualized, optimized treatments by integrating and analyzing the variability of multiple internal biological and external environmental signals as they relate to blood pressure variability across different time phases. By linking time series changes in blood pressure and biological distribution with multi-environmental and physiological information, enabled by advances in digital technology, the time-space network hypertension approach contributes to “digital hypertension” research. This article from Jichi Medical University provides an update on research relating to the time-space network hypertension approach, which is designed to progress hypertension management towards achieving net zero cardiovascular events.

Background: Previous randomized clinical trials did not support a benefit of screening for occult cancer after diagnosis of venous thromboembolism (VTE), although screening may be of potential benefit for selected high-risk patients.

Methods and Results: The COMMAND VTE Registry-2 enrolled consecutive patients with acute symptomatic VTE between 2015 and 2020 from 31 centers across Japan. The 3,706 patients in the registry without known active cancer at the time of VTE diagnosis were divided into 2 groups: those with (n=250) and without (n=3,456) newly diagnosed cancer during the follow-up period. The cumulative incidence of newly diagnosed cancer was 1.5% at 30 days, 3.7% at 1 year, and 7.0% at 3 years. The multivariable Cox proportional hazard model demonstrated that older age (hazard ratio [HR] 1.02 per 1 year increase; 95% confidence interval [CI] 1.01–1.03; P<0.001), a history of cancer (HR 3.57; 95% CI 2.73–4.64; P<0.001), autoimmune disorders (HR 1.48; 95% CI 1.06–2.02; P=0.02), a history of major bleeding (HR 1.64; 95% CI 1.04–2.48; P=0.04), and the absence of transient provoking risk factors for VTE (HR 1.44; 95% CI 1.08–1.92; P=0.01) were independently associated with newly diagnosed cancer.

Conclusions: The incidence of newly diagnosed cancer after VTE diagnosis was 3.7% at 1 year, and several independent risk factors for newly diagnosed cancer after VTE diagnosis were identified.

Takayasu arteritis (TAK) is classified as a large vessel vasculitis and often causes vascular stenosis, occlusion, and aneurysm formation. Although the principal treatment for TAK involves suppressing inflammation with glucocorticoids, the emergence of biological disease-modifying antirheumatic drugs has considerably changed the treatment landscape of TAK in recent years. Several biological disease-modifying antirheumatic drugs, such as tocilizumab (TCZ), have shown promising effects on TAK in clinical studies. Cardiologists and cardiovascular surgeons encounter patients receiving these drugs who require catheterization, endovascular treatment, or cardiovascular surgery. However, in patients treated with glucocorticoids and TCZ, there needs to be greater awareness of more complications than usual after surgery, such as delayed wound healing, systemic infection, and surgical site infection. In addition, in patients receiving TCZ, inflammatory markers, such as C-reactive protein, may not increase when complications arise from infection. Unfortunately, there are no guidelines or solid evidence that have clearly defined the optimal perioperative treatment strategy for patients with TAK who require cardiovascular surgery. This article reviews the evidence and our recent experience supporting the perioperative use of TCZ, and proposes a protocol that can reduce complications in patients with TAK undergoing invasive cardiovascular treatment.

Background: The ONCO DVT study demonstrated potential benefits of extended edoxaban treatment in patients with isolated distal deep vein thrombosis in terms of thrombotic risk. However, the risk-benefit balance in patients with anemia remains unclear.

Methods and Results: This prespecified subgroup analysis included 601 patients, divided into anemia (n=402) and no-anemia (n=199) groups. The primary endpoint was symptomatic recurrent venous thromboembolism (VTE) or VTE-related death. Anemia was defined as hemoglobin <12 g/dL for women and <13 g/dL for men. In the anemia subgroup, the primary endpoint occurred in 3 (1.5%) and 17 (8.4%) patients in the 12- and 3-month edoxaban treatment groups, respectively (odds ratio [OR] 0.17; 95% confidence interval [CI] 0.05–0.58), compared with 0 and 5 (4.9%) patients, respectively, in the no-anemia subgroup (P interaction=0.997). Major bleeding occurred in 26 (13.1%) and 17 (8.4%) patients with anemia in the 12- and 3-month edoxaban treatment groups, respectively (OR 1.64; 95% CI 0.86–3.14), compared with 2 (2.1%) and 5 (4.9%) patients without anemia (OR 0.67; 95% CI 0.26–1.73; P interaction=0.13).

Conclusions: Regardless of the presence of anemia, edoxaban treatment for 12 months was superior to treatment for 3 months in reducing thrombotic events, whereas the risk of major bleeding did not differ significantly between the 2 treatment groups.

Background: Patients with appropriately selected low-risk pulmonary embolism (PE) can be treated at home, although it has been controversial whether applies to patients with cancer, who are considered not to be at low risk.

Methods and Results: The current predetermined companion report from the ONCO PE trial evaluated the 3-month clinical outcomes of patients with home treatment and those with in-hospital treatment. The ONCO PE trial was a multicenter, randomized clinical trial among 32 institutions in Japan investigating the optimal duration of rivaroxaban treatment in cancer-associated PE patients with a score of 1 using the simplified version of the Pulmonary Embolism Severity Index (sPESI). Among 178 study patients, there were 66 (37%) in the home treatment group and 112 (63%) in the in-hospital treatment group. The primary endpoint of a composite of PE-related death, recurrent venous thromboembolism (VTE) and major bleeding occurred in 3 patients (4.6% [0.0–9.6%]) in the home treatment group and in 2 patients (1.8% [0.0–4.3%]) in the in-hospital treatment group. In the home treatment group, there were no cases of PE-related death or recurrent VTE, but major bleeding occurred in 3 patients (4.6% [0.0–9.6%]), and 2 patients (3.0% [0.0–7.2%]) required hospitalization due to bleeding events.

Conclusions: Active cancer patients with PE of sPESI score=1 could be potential candidates for home treatment.