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Abstract Introduction Hypercholesterolemia is associated with increased inflammation and impaired serotonin neurotransmission, potentially contributing to depressive symptoms. However, the role of statins, particularly pitavastatin, in modulating serotonin transporter (SERT) function within this context remains underexplored. This study aimed to investigate whether pitavastatin counteracts the neurobiological effects of hypercholesterolemia. Methods Low-density lipoprotein receptor knockout (LDLR−/−) mice on a C57BL/6 background were assigned to three groups: a control group fed a standard chow diet, a group fed a high-fat diet (HFD), and a third group fed a high-fat diet supplemented with pitavastatin (HFD + Pita). We evaluated the effects of HFD with or without pitavastatin on lipid profiles, inflammatory markers, and SERT availability using small-animal positron emission tomography (PET) scans with the radioligand 4-[18F]-ADAM over a 20-week period. Results Pitavastatin treatment in HFD-fed mice significantly reduced both total cholesterol and LDL cholesterol levels in HFD-fed mice compared to those on HFD alone. Elevated inflammatory markers such as IL-1α, MCP-1/CCL2, and TNF-α in HFD mice were notably decreased in the HFD + Pita group. PET scans showed reduced SERT availability in the brains of HFD mice; however, pitavastatin improved this in brain regions associated with mood regulation, suggesting enhanced serotonin neurotransmission. Additionally, the sucrose preference test showed a trend towards increased preference in the HFD + Pita group compared to the HFD group, indicating a potential reduction in depressive-like behavior. Conclusion Our findings demonstrate that pitavastatin not only lowers cholesterol and reduces inflammation but also enhances SERT availability, suggesting a potential role in alleviating depressive symptoms associated with hypercholesterolemia. These results highlight the multifaceted benefits of pitavastatin, extending beyond its lipid-lowering effects to potentially improving mood regulation and neurotransmitter function.

Background: Central venous catheterization (CVC) is a critical clinical procedure. To avoid complications, possessing good knowledge regarding the CVC care bundle and skills for the proper insertion and maintenance of CVC are important. Objectives: To evaluate the effectiveness of an educational intervention and the use of an interactive response system in enhancing the CVC bundle care and insertion skills of medical students undergoing critical care medicine training. Materials and Methods: Sixth-year medical students (equivalent to fourth-year students in the United States) engaged in didactic lessons, interactive demonstrations, and simulator training facilitated by a CVC team comprising three thoracic and two vascular surgeons (all with a minimum 5 years of experience in central venous access) during their intensive care unit (ICU) rotation. Self-reported knowledge and confidence levels were assessed using pre-and posttests administered through the Zuvio App, an interactive response system. Results: A total of 60 students underwent the educational intervention, of which 54 completed the pretest and 40 completed the posttest. In the posttest, significant improvement was found in the CVC bundle care competency and understanding (P = 0.002), preprocedural preparation (P = 0.002), insertion procedures (P = 0.004), complications (P = 0.003), and insertion depth decisions (P = 0.001). Staff and students reported that assessment and interaction via the Zuvio App were valuable, practical, and feasible in a clinical setting, providing trainees with an individual competency portfolio of receiving precise medical education. Conclusions: Integrating the training provided by a specialized team with an interactive response system enhanced the knowledge and competency level in CVC insertion among medical students in this study.

Abstract Background Hyperthyroidism is frequently under-recognized and leads to heart failure and mortality. Timely identification of high-risk patients is a prerequisite to effective antithyroid therapy. Since the heart is very sensitive to hyperthyroidism and its electrical signature can be demonstrated by electrocardiography, we developed an artificial intelligence model to detect hyperthyroidism by electrocardiography and examined its potential for outcome prediction. Methods The deep learning model was trained using a large dataset of 47,245 electrocardiograms from 33,246 patients at an academic medical center. Patients were included if electrocardiograms and measurements of serum thyroid-stimulating hormone were available that had been obtained within a three day period. Serum thyroid-stimulating hormone and free thyroxine were used to define overt and subclinical hyperthyroidism. We tested the model internally using 14,420 patients and externally using two additional test sets comprising 11,498 and 596 patients, respectively. Results The performance of the deep learning model achieves areas under the receiver operating characteristic curves (AUCs) of 0.725–0.761 for hyperthyroidism detection, AUCs of 0.867–0.876 for overt hyperthyroidism, and AUC of 0.631–0.701 for subclinical hyperthyroidism, superior to a traditional features-based machine learning model. Patients identified as hyperthyroidism-positive by the deep learning model have a significantly higher risk (1.97–2.94 fold) of all-cause mortality and new-onset heart failure compared to hyperthyroidism-negative patients. This cardiovascular disease stratification is particularly pronounced in subclinical hyperthyroidism, surpassing that observed in overt hyperthyroidism. Conclusions An innovative algorithm effectively identifies overt and subclinical hyperthyroidism and contributes to cardiovascular risk assessment.

Background The electrocardiogram (ECG) may be the most popular test in the management of cardiovascular disease (CVD). Although wide applications of artificial intelligence (AI)-enabled ECG have been developed, an integrating indicator for CVD risk stratification was not investigated. Since mortality may be the most important global outcome, this study aimed to develop a survival deep learning model (DLM) to establish a critical ECG value and explore the associations with various CVD events. Methods We trained a DLM with 451,950 12-lead resting ECGs obtained from 210,552 patients, for whom 23,592 events occurred. The internal validation set included 27,808 patients with one ECG for each patient. The external validations were performed in a community hospital with 33,047 patients and two transnational data sets with 233,647 and 1631 ECGs. We distinguished the cause of mortality and additionally investigated CVD-related outcomes, including new-onset acute myocardial infarction (AMI), stroke (STK), and heart failure (HF). Results The DLM achieved C-indices of 0.858/0.836 in internal/external validation sets by using ECG over a 10-year period. The high-mortality-risk group identified by the proposed DLM presented a hazard ratio (HR) of 14.16 (95% confidence interval (CI): 11.33–17.70) compared to the low-risk group in the internal validation and presented a higher risk of cardiovascular (CV) mortality (HR: 18.50, 95% CI: 9.82–34.84), non-CV mortality (HR: 13.68, 95% CI: 10.76–17.38), AMI (HR: 4.01, 95% CI: 2.24–7.17), STK (HR: 2.15, 95% CI: 1.70–2.72), and HF (HR: 6.66, 95% CI: 4.54–9.77), which was consistent in an independent community hospital. The transnational validation also revealed HRs of 4.91 (95% CI: 2.63–9.16) and 2.29 (95% CI: 2.15–2.44) for all-cause mortality in the SaMi-Trop and Clinical Outcomes in Digital Electrocardiography 15% (CODE15) cohorts. Conclusions The mortality risk by AI-enabled ECG may be applied in passive electronic-health-record-based CVD risk screening, which may identify more asymptomatic and unaware high-risk patients.

BACKGROUND: The B-type natriuretic peptide (BNP) and N-terminal pro-brain natriuretic peptide (pBNP) are predictors of cardiovascular morbidity and mortality. Since the artificial intelligence (AI)-enabled electrocardiogram (ECG) system is widely used in the management of many cardiovascular diseases (CVDs), patients requiring intensive monitoring may benefit from an AI-ECG with BNP/pBNP predictions. This study aimed to develop an AI-ECG to predict BNP/pBNP and compare their values for future mortality. METHODS: The development, tuning, internal validation, and external validation sets included 47,709, 16,249, 4001, and 6042 ECGs, respectively. Deep learning models (DLMs) were trained using a development set for estimating ECG-based BNP/pBNP (ECG-BNP/ECG-pBNP), and the tuning set was used to guide the training process. The ECGs in internal and external validation sets belonging to nonrepeating patients were used to validate the DLMs. We also followed-up all-cause mortality to explore the prognostic value. RESULTS: The DLMs accurately distinguished mild (≥500 pg/mL) and severe (≥1000 pg/mL) an abnormal BNP/pBNP with AUCs of ≥0.85 in the internal and external validation sets, which provided sensitivities of 68.0–85.0% and specificities of 77.9–86.2%. In continuous predictions, the Pearson correlation coefficient between ECG-BNP and ECG-pBNP was 0.93, and they were both associated with similar ECG features, such as the T wave axis and correct QT interval. ECG-pBNP provided a higher all-cause mortality predictive value than ECG-BNP. CONCLUSIONS: The AI-ECG can accurately estimate BNP/pBNP and may be useful for monitoring the risk of CVDs. Moreover, ECG-pBNP may be a better indicator to manage the risk of future mortality.

Abstract Dyskalemias are common electrolyte disorders associated with high cardiovascular risk. Artificial intelligence (AI)-assisted electrocardiography (ECG) has been evaluated as an early-detection approach for dyskalemia. The aims of this study were to determine the clinical accuracy of AI-assisted ECG for dyskalemia and prognostic ability on clinical outcomes such as all-cause mortality, hospitalizations, and ED revisits. This retrospective cohort study was done at two hospitals within a health system from May 2019 to December 2020. In total, 26,499 patients with 34,803 emergency department (ED) visits to an academic medical center and 6492 ED visits from 4747 patients to a community hospital who had a 12-lead ECG to estimate ECG-K+ and serum laboratory potassium measurement (Lab-K+) within 1 h were included. ECG-K+ had mean absolute errors (MAEs) of ≤0.365 mmol/L. Area under receiver operating characteristic curves for ECG-K+ to predict moderate-to-severe hypokalemia (Lab-K+ ≤3 mmol/L) and moderate-to-severe hyperkalemia (Lab-K+ ≥ 6 mmol/L) were >0.85 and >0.95, respectively. The U-shaped relationships between K+ concentration and adverse outcomes were more prominent for ECG-K+ than for Lab-K+. ECG-K+ and Lab-K+ hyperkalemia were associated with high HRs for 30-day all-cause mortality. Compared to hypokalemic Lab-K+, patients with hypokalemic ECG-K+ had significantly higher risk for adverse outcomes after full confounder adjustment. In addition, patients with normal Lab-K+ but dyskalemic ECG-K+ (pseudo-positive) also exhibited more co-morbidities and had worse outcomes. Point-of-care bloodless AI ECG-K+ not only rapidly identified potentially severe hypo- and hyperkalemia, but also may serve as a biomarker for medical complexity and an independent predictor for adverse outcomes.

Abstract Objectives The choice of optimal antithrombotic therapy in atrial fibrillation (AF) patients with acute coronary syndrome (ACS) or percutaneous coronary intervention (PCI) remains controversial. The aim of this longitudinal cohort study is to investigate the prescribing pattern of antithrombotic regimen in different cohorts and its subsequent impact. Setting and design Longitudinal data from the Tri-Service General Hospital-Coronary Heart Disease (TSGH-CHD) registry, between January 2016 and August 2018 was screened. Participants and method Patients with prior history of nonvalvular AF, who had ACS presentation or underwent PCI were selected, and these patients were divided into cohort 1 and cohort 2, according to the index date of antithrombotic prescription before and after the PIONEER AF-PCI study. Primary and secondary outcomes The primary safety endpoints were composites of major bleeding and/or clinically relevant non-major bleeding. The secondary efficacy endpoints included the occurrence of all-cause mortality, stroke/systemic embolization, nonfatal myocardial infarction (MI), and >30-days coronary revascularization. Results A total of 121 patients were included into analysis (cohort 1=35; cohort 2=86). Comparing with cohort 1, the prescription rate of triple antithrombotic therapy (TAT) increased from 17.1 to 38.4%, especially the regimen with dual antiplatelet therapy (DAPT) plus low-dose non-vitamin-K dependent oral anticoagulation (NOAC). However, the prescription rate of dual antithrombotic therapy (DAT) decreased (14.3–10.5%), as well as the prescription rate of DAPT (68.6–51.2%). These changes of antithrombotic prescription across different cohorts were not associated with risk of adverse safety (HR= 0.87; 95% CI, 0.42-1.80, p=0.710) and efficacy outcomes (HR=0.96; 95% CI, 0.40-2.32, p=0.930). Conclusions Entering the NOAC era, the prescription of TAT increased alongside the decrease in DAT. As the prescription rate of DAPT without anticoagulation remained high, future efforts are mandatory to improve the implementation of guidelines and clinical practice.

Background Artificial intelligence-enabled electrocardiogram has become a substitute tool for echocardiography in left ventricular ejection fraction estimation. However, the direct use of artificial intelligence-enabled electrocardiogram may be not trustable due to the uncertainty of the prediction. Objective The study aimed to establish an artificial intelligence-enabled electrocardiogram with a degree of confidence to identify left ventricular dysfunction. Methods The study collected 76,081 and 11,771 electrocardiograms from an academic medical center and a community hospital to establish and validate the deep learning model, respectively. The proposed deep learning model provided the point estimation of the actual ejection fraction and its standard deviation derived from the maximum probability density function of a normal distribution. The primary analysis focused on the accuracy of identifying patients with left ventricular dysfunction (ejection fraction ≤ 40%). Since the standard deviation was an uncertainty indicator in a normal distribution, we used it as a degree of confidence in the artificial intelligence-enabled electrocardiogram. We further explored the clinical application of estimated standard deviation and followed up on the new-onset left ventricular dysfunction in patients with initially normal ejection fraction. Results The area under receiver operating characteristic curves (AUC) of detecting left ventricular dysfunction were 0.9549 and 0.9365 in internal and external validation sets. After excluding the cases with a lower degree of confidence, the artificial intelligence-enabled electrocardiogram performed better in the remaining cases in internal (AUC = 0.9759) and external (AUC = 0.9653) validation sets. For the application of future left ventricular dysfunction risk stratification in patients with initially normal ejection fraction, a 4.57-fold risk of future left ventricular dysfunction when the artificial intelligence-enabled electrocardiogram is positive in the internal validation set. The hazard ratio was increased to 8.67 after excluding the cases with a lower degree of confidence. This trend was also validated in the external validation set. Conclusion The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.

BackgroundProximal protection devices, such as the Mo.Ma system provides better neurological outcomes than the distal filter system in the carotid artery stenting (CAS) procedure. This study first evaluated the safety and efficacy of the Mo.Ma system during CAS in a single tertiary referral hospital from Taiwan. The outcomes of distal vs. proximal embolic protection devices were also studied.MethodsA total of 294 patients with carotid artery stenosis who underwent the CAS procedure were retrospectively included and divided into two groups: 152 patients in the distal filter system group and 142 patients in the Mo.Ma system. The outcomes of interest were compared between the two groups. The factors contributing to occlusion intolerance (OI) in the Mo.Ma system were evaluated.ResultsThe procedure success rates were more than 98% in both groups. No major stroke occurred in this study. The minor stroke rates were 2.8% (4/142) and 4.6% (7/152) in the Mo.Ma system and filter system, respectively (p = 0.419). Patients with hypoalbuminemia significantly predicted the risk of stroke with an odds ratio of 0.08 [95% confidence interval (CI), 0.01–0.68, p = 0.020] per 1 g/day of serum albumin in the filter group. A total of 12 patients developed OI in the Mo.Ma system (12/142, 8%). Low occlusion pressure predicted the occurrence of OI in the Mo.Ma group with the hazard ratios of 0.88 (95% CI: 0.82–0.96) and 0.90 (95% CI: 0.84–0.98) per 1 mmHg of occlusion systolic pressure (OSP) and diastolic pressure (ODP), respectively. We further indicated that patients with an OSP of ≥60 mmHg or an ODP of ≥44 mmHg could tolerate the procedure of occlusion time up to 400 s, while patients with an OSP of

BackgroundAlbumin, an important component of fluid balance, is associated with kidney, liver, nutritional, and cardiovascular diseases (CVD) and is measured by blood tests. Since fluid balance is associated with electrocardiography (ECG) changes, we established a deep learning model (DLM) to estimate albumin via ECG.ObjectiveThis study aimed to develop a DLM to estimate albumin via ECG and explored its contribution to future complications.Materials and MethodsA DLM was trained for estimating ECG-based albumin (ECG-Alb) using 155,078 ECGs corresponding to albumin from 79,111 patients, and another independent 13,335 patients from an academic medical center and 11,370 patients from a community hospital were used for internal and external validation. The primary analysis focused on distinguishing patients with mild to severe hypoalbuminemia, and the secondary analysis aimed to provide additional prognostic value from ECG-Alb for future complications, which included mortality, new-onset hypoalbuminemia, chronic kidney disease (CKD), new onset hepatitis, CVD mortality, new-onset acute myocardial infarction (AMI), new-onset stroke (STK), new-onset coronary artery disease (CAD), new-onset heart failure (HF), and new-onset atrial fibrillation (Afib).ResultsThe AUC to identify hypoalbuminemia was 0.8771 with a sensitivity of 56.0% and a specificity of 90.7% in the internal validation set, and the Pearson correlation coefficient was 0.69 in the continuous analysis. The most important ECG features contributing to ECG-Alb were ordered in terms of heart rate, corrected QT interval, T wave axis, sinus rhythm, P wave axis, etc. The group with severely low ECG-Alb had a higher risk of all-cause mortality [hazard ratio (HR): 2.45, 95% CI: 1.81–3.33] and the other hepatorenal and cardiovascular events in the internal validation set. The external validation set yielded similar results.ConclusionHypoalbuminemia and its complications can be predicted using ECG-Alb as a novel biomarker, which may be a non-invasive tool to warn asymptomatic patients.

BackgroundCertain variables reportedly are associated with a change in left ventricular ejection fraction (LVEF) in heart failure (HF) with reduced ejection fraction (HFrEF). However, literature describing the association between the recovery potential of LVEF and parameters of ventricular remodeling in echocardiography remains sparse.MethodsWe recruited 2,148 HF patients with LVEF < 35%. All patients underwent at least two echocardiographic images. The study aimed to compare LVEF alterations and their association with patient characteristics and echocardiographic findings.ResultsPatients with “recovery” of LVEF (follow-up LVEF ≥ 50%) were less likely to have prior myocardial infarction (MI), had a higher prevalence of atrial fibrillation (Af), were less likely to have diabetes and hypertension, and had a smaller left atrium (LA) diameter, left ventricular end-diastolic diameter (LVEDD) and left ventricular end-systolic diameter (LVESD), both in crude and in adjusted models (adjustment for age and sex). LVEDD cutoff values of 59.5 mm in men and 52.5 mm in women and LVESD cutoff values of 48.5 mm in men and 46.5 mm in women showed a year-to-year increase in the rate of recovery (follow-up LVEF ≥ 50%)/improvement (follow-up LVEF ≥ 35%), p-value < 0.05 in Kaplan–Meier estimates of the cumulative hazard curves.ConclusionsOur study shows that LVEDD and LVESD increments in echocardiography can be predictors of changes in LVEF in in HF patients with LVEF < 35%. They may be used to identify patients who require more aggressive therapeutic interventions.

Abstract The prevalence of mitral valve prolapse (MVP) among middle- and older-aged individuals is estimated to be 2–4% in Western countries. However, few studies have been conducted among Asian individuals and young adults. This study included a sample of 2442 consecutive military adults aged 18–39 years in Hualien, Taiwan. MVP was defined as displacement of the anterior or posterior leaflet of the mitral valve to the mid portion of the annular hinge point > 2 mm in the parasternal long-axis view of echocardiography. Cardiac chamber size and wall thickness were measured based on the latest criteria of the American Society of Echocardiography. The clinical features of participants with MVP and those without MVP were compared using a two-sample t test, and the cardiac structures were compared using analysis of covariance with adjustment for body surface area (BSA). Eighty-two participants were diagnosed with MVP, and the prevalence was 3.36% in the overall population. Compared with those without MVP, participants with MVP had a lower body mass index (kg/m2) (24.89 ± 3.70 vs. 23.91 ± 3.45, p = 0.02) and higher prevalence of somatic symptoms related to exercise (11.0% vs. 4.9%, p = 0.02) and systolic click in auscultation (18.3% vs. 0.6%, p

Patients bitten by Protobothrops mucrosquamatus typically experience significant pain, substantial swelling, and potentially blister formation. The appropriate dosage and efficacy of FHAV for alleviating local tissue injury remain uncertain. Between 2017 and 2022, 29 snakebite patients were identified as being bitten by P. mucrosquamatus. These patients underwent point-of-care ultrasound (POCUS) assessments at hourly intervals to measure the extent of edema and evaluate the rate of proximal progression (RPP, cm/hour). Based on Blaylock’s classification, seven patients (24%) were classified as Group I (minimal), while 22 (76%) were classified as Group II (mild to severe). In comparison to Group I patients, Group II patients received more FHAV (median of 9.5 vials vs. two vials, p-value < 0.0001) and experienced longer median complete remission times (10 days vs. 2 days, p-value < 0.001). We divided the Group II patients into two subgroups based on their clinical management. Clinicians opted not to administer antivenom treatment to patients in Group IIA if their RPP decelerated. In contrast, for patients in Group IIB, clinicians increased the volume of antivenom in the hope of reducing the severity of swelling or blister formation. Patients in Group IIB received a significantly higher median volume of antivenom (12 vials vs. six vials; p-value < 0.001) than those in Group IIA. However, there was no significant difference in outcomes (disposition, wound necrosis, and complete remission times) between subgroups IIA and IIB. Our study found that FHAV does not appear to prevent local tissue injuries, such as swelling progression and blister formation, immediately after administration. When administering FHAV to patients bitten by P. mucrosquamatus, the deceleration of RPP may serve as an objective parameter to help clinicians decide whether to withhold FHAV administration.

BackgroundHeart failure (HF) is a global disease with increasing prevalence in an aging society. However, the survival rate is poor despite the patient receiving standard treatment. Early identification of patients with a high risk of HF is important but challenging. Left ventricular end-diastolic diameter (LV-D) increase was an independent risk factor of HF and adverse cardiovascular (CV) outcomes. In this study, we aimed to develop an artificial intelligence (AI) enabled electrocardiogram (ECG) system to detect LV-D increase early.ObjectiveWe developed a deep learning model (DLM) to predict left ventricular end-diastolic and end-systolic diameter (LV-D and LV-S) with internal and external validations and investigated the relationship between ECG-LV-D and echocardiographic LV-D and explored the contributions of ECG-LV-D on future CV outcomes.MethodsElectrocardiograms and corresponding echocardiography data within 7 days were collected and paired for DLM training with 99,692 ECGs in the development set and 20,197 ECGs in the tuning set. The other 7,551 and 11,644 ECGs were collected from two different hospitals to validate the DLM performance in internal and external validation sets. We analyzed the association and prediction ability of ECG-LVD for CV outcomes, including left ventricular (LV) dysfunction, CV mortality, acute myocardial infarction (AMI), and coronary artery disease (CAD).ResultsThe mean absolute errors (MAE) of ECG-LV-D were 5.25/5.29, and the area under the receiver operating characteristic (ROC) curves (AUCs) were 0.8297/0.8072 and 0.9295/0.9148 for the detection of mild (56 ≦ LV-D < 65 mm) and severe (LV-D ≧ 65 mm) LV-D dilation in internal/external validation sets, respectively. Patients with normal ejection fraction (EF) who were identified as high ECHO-LV-D had the higher hazard ratios (HRs) of developing new onset LV dysfunction [HR: 2.34, 95% conference interval (CI): 1.78–3.08], CV mortality (HR 2.30, 95% CI 1.05–5.05), new-onset AMI (HR 2.12, 95% CI 1.36–3.29), and CAD (HR 1.59, 95% CI 1.26–2.00) in the internal validation set. In addition, the ECG-LV-D presents a 1.88-fold risk (95% CI 1.47–2.39) on new-onset LV dysfunction in the external validation set.ConclusionThe ECG-LV-D not only identifies high-risk patients with normal EF but also serves as an independent risk factor of long-term CV outcomes.

ObjectiveThe biological age progression of the heart varies from person to person. We developed a deep learning model (DLM) to predict the biological age via ECG to explore its contribution to future cardiovascular diseases (CVDs).MethodsThere were 71,741 cases ranging from 20 to 80 years old recruited from the health examination center. The development set used 32,707 cases to train the DLM for estimating the ECG-age, and 8,295 cases were used as the tuning set. The validation set included 30,469 ECGs to follow the outcomes, including all-cause mortality, cardiovascular-cause mortality, heart failure (HF), diabetes mellitus (DM), chronic kidney disease (CKD), acute myocardial infarction (AMI), stroke (STK), coronary artery disease (CAD), atrial fibrillation (AF), and hypertension (HTN). Two independent external validation sets (SaMi-Trop and CODE15) were also used to validate our DLM.ResultsThe mean absolute errors of chronologic age and ECG-age was 6.899 years (r = 0.822). The higher difference between ECG-age and chronological age was related to more comorbidities and abnormal ECG rhythm. The cases with the difference of more than 7 years had higher risk on the all-cause mortality [hazard ratio (HR): 1.61, 95% CI: 1.23–2.12], CV-cause mortality (HR: 3.49, 95% CI: 1.74–7.01), HF (HR: 2.79, 95% CI: 2.25–3.45), DM (HR: 1.70, 95% CI: 1.53–1.89), CKD (HR: 1.67, 95% CI: 1.41–1.97), AMI (HR: 1.76, 95% CI: 1.20–2.57), STK (HR: 1.65, 95% CI: 1.42–1.92), CAD (HR: 1.24, 95% CI: 1.12–1.37), AF (HR: 2.38, 95% CI: 1.86–3.04), and HTN (HR: 1.67, 95% CI: 1.51–1.85). The external validation sets also validated that an ECG-age >7 years compare to chronologic age had 3.16-fold risk (95% CI: 1.72–5.78) and 1.59-fold risk (95% CI: 1.45–1.74) on all-cause mortality in SaMi-Trop and CODE15 cohorts. The ECG-age significantly contributed additional information on heart failure, stroke, coronary artery disease, and atrial fibrillation predictions after considering all the known risk factors.ConclusionsThe ECG-age estimated via DLM provides additional information for CVD incidence. Older ECG-age is correlated with not only on mortality but also on other CVDs compared with chronological age.

Background: In the past decade, Tri-Service General Hospital has trained many actors-background standardized patients (SPs). However, we also have recruited some nonactor SPs since 2010. Reviewing the literature, the reliability of SPs with or without actor background would be the impact factor on high-stakes OSCE has not been well studied. Aim: The purpose of this retrospective observation is to clarify whether a SP with or without a professional actor background will affect the performances of the examination when participating in the Taiwan high-stakes objective structured clinical examination (OSCE). The result will be the policy for selecting which kind of SPs to participate in the high-stack OSCE in our hospital. Methods: In this retrospective observation, we analyzed 74 actor background SPs (A-SPs), and 70 no actor background SPs (NA-SPs) who have participated in each spring test of 2015–2017 Taiwan high-stakes OSCE. The data of SPs performance have come from two parts: one is from the examinee with the global rating of the SPs performance and the other is from the examiner with eight-item checklist for the SPs performance. The scoring of both examinee and examiner is a five-point Likert scale. Results: The results show that there is no significant difference in SPs performance from the examinee scoring in the subsequent 3 years, stable and satisfactory, and let examinees feel like real patients. The scores from examiners also showed that two groups of SPs performed equally well without significant differences. Their performance is reliable and consistent, simulating to be a real patient in both groups. However, only one interest finding, when compared to the different age subdivision of SPs, showed the aged subgroup of A-SPs and NA-SPs with the significant difference in the item of reliability and consistent (4.67 ± 0.53 vs. 4.41 ± 0.50, P < 0.05), the possible reason is related to the less-experienced associate with mild memory decline in aged NA-SPs.Conclusions: Our observation gives the essential information, that the well-trained and experienced SP are necessary for participating in the high-stakes OSCE examination, even without the background of the actor. What we need is a professional SP who not only has excellent professionalism but also has a good personality literacy to engage in his/her work.

Cardiovascular events such as myocarditis following mRNA COVID-19 vaccination are increasing. We present a 67-year-old postmenopausal woman with Takotsubo Syndrome and Graves’ disease after mRNA COVID-19 vaccination. She developed chest pain and shortness of breath one week after vaccination. An electrocardiogram revealed ST elevation in the precordial leads. Coronary angiography revealed the absence of obstructive coronary artery disease, and the left ventriculography showed a typical feature with apical ballooning. Laboratory workup showed the elevation of free T4 and thyrotropin receptor antibodies. It was presumed that Takotsubo Syndrome and Graves’ disease were probably related to the COVID-19 mRNA vaccination. The patient was treated with low-dose bisoprolol, diuretics, carbimazole, and steroid and discharged uneventfully. The mRNA COVID-19 vaccination is still safe and effective to defend against COVID-19 pandemic. However, clinicians should be aware of the possible cardiovascular adverse events other than myocarditis following vaccination.

Diabetes mellitus is a metabolic syndrome that affects millions of people worldwide. Recent studies have demonstrated that protein kinase C (PKC) activation plays an important role in hyperglycemia-induced atherosclerosis. PKC activation is involved in several cellular responses such as the expression of various growth factors, activation of signaling pathways, and enhancement of oxidative stress in hyperglycemia. However, the role of PKC activation in pro-atherogenic and anti-atherogenic mechanisms remains controversial, especially under hyperglycemic condition. In this review, we discuss the role of different PKC isoforms in lipid regulation, oxidative stress, inflammatory response, and apoptosis. These intracellular events are linked to the pathogenesis of atherosclerosis in diabetes. PKC deletion or treatment with PKC inhibitors has been studied in the regulation of atherosclerotic plaque formation and evolution. Furthermore, some preclinical and clinical studies have indicated that PKCβ and PKCδ are potential targets for the treatment of diabetic vascular complications. The current review summarizes these multiple signaling pathways and cellular responses regulated by PKC activation and the potential therapeutic targets of PKC in diabetic complications.

Background: Taiwan is located in a subtropical area where there are approximately 50 kinds of land snakes and six principal kinds of venous snakes. Snakebite envenomation is not an uncommon issue in Taiwan. We design a study to obtain an understanding of the characteristics of snakebites and snakebite patients in a medical center in northern Taiwan. Materials and Methods: This was a retrospective medical records study of an 8-year period. We used the key word “snake” to search the emergency department (ED) diagnosis of all patients and then used antivenom management codes to select patients for inclusion. The species of snake involved, time and site of the bite, geographic data of the patients and patient outcomes were recorded. Results: In total, there were 125 snakebite patients (male 70%, female 30%). The snakes involved were Protobothrops mucrosquamatus (50%), followed by Trimeresurus stejnegeri (7%). The feet and ankles were the most frequently bitten areas (42.4%). The peak months were July and October. The average ED stasis time was 2 hours and 45 minutes, and 65.6% of snakebite patients received antivenom. In patients bitten by P. mucrosquamatus, there was a high surgical rate, 23.8% higher than those reported in other studies. No mortalities or side effects of antivenom were reported in these patients. Conclusion: We propose a clinical flow chart for physicians who are treating patients bitten by P. mucrosquamatus. Snakebites, especially those inflicted by P. mucrosquamatus, induce severe soft tissue swelling, which can mimic compartment syndrome. Antivenom for P. mucrosquamatus is the first and only choice of treatment. The amount of antivenom needs to match the clinical symptoms. Patients bitten by P. mucrosquamatus may need longer observation times than patients bitten by other species of snakes, in addition to toxicologist consultations, sonographic examinations, and measurement of the objective compartment pressure before surgery.

(1) Background: Acute pericarditis is often confused with ST-segment elevation myocardial infarction (STEMI) among patients presenting with acute chest pain in the emergency department (ED). Since a deep learning model (DLM) has been validated to accurately identify STEMI cases via 12-lead electrocardiogram (ECG), this study aimed to develop another DLM for the detection of acute pericarditis in the ED. (2) Methods: This study included 128 ECGs from patients with acute pericarditis and 66,633 ECGs from patients visiting the ED between 1 January 2010 and 31 December 2020. The ECGs were randomly allocated based on patients to the training, tuning, and validation sets, at a 3:1:1 ratio. We used raw ECG signals to train a pericarditis-DLM and used traditional ECG features to train a machine learning model. A human–machine competition was conducted using a subset of the validation set, and the performance of the Philips automatic algorithm was also compared. STEMI cases in the validation set were extracted to analyze the DLM ability of differential diagnosis between acute pericarditis and STEMI using ECG. We also followed the hospitalization events in non-pericarditis cases to explore the meaning of false-positive predictions. (3) Results: The pericarditis-DLM exceeded the performance of all participating human experts and algorithms based on traditional ECG features in the human–machine competition. In the validation set, the pericarditis-DLM could detect acute pericarditis with an area under the receiver operating characteristic curve (AUC) of 0.954, a sensitivity of 78.9%, and a specificity of 97.7%. However, our pericarditis-DLM also misinterpreted 10.2% of STEMI ECGs as pericarditis cases. Therefore, we generated an integrating strategy combining pericarditis-DLM and a previously developed STEMI-DLM, which provided a sensitivity of 73.7% and specificity of 99.4%, to identify acute pericarditis in patients with chest pains. Compared to the true-negative cases, patients with false-positive results using this strategy were associated with higher risk of hospitalization within 3 days due to cardiac disorders (hazard ratio (HR): 8.09; 95% confidence interval (CI): 3.99 to 16.39). (4) Conclusions: The AI-enhanced algorithm may be a powerful tool to assist clinicians in the early detection of acute pericarditis and differentiate it from STEMI using 12-lead ECGs.

BACKGROUND: The ejection fraction (EF) provides critical information about heart failure (HF) and its management. Electrocardiography (ECG) is a noninvasive screening tool for cardiac electrophysiological activities that has been used to detect patients with low EF based on a deep learning model (DLM) trained via large amounts of data. However, no studies have widely investigated its clinical impacts. OBJECTIVE: This study developed a DLM to estimate EF via ECG (ECG-EF). We further investigated the relationship between ECG-EF and echo-based EF (ECHO-EF) and explored their contributions to future cardiovascular adverse events. METHODS: There were 57,206 ECGs with corresponding echocardiograms used to train our DLM. We compared a series of training strategies and selected the best DLM. The architecture of the DLM was based on ECG12Net, developed previously. Next, 10,762 ECGs were used for validation, and another 20,629 ECGs were employed to conduct the accuracy test. The changes between ECG-EF and ECHO-EF were evaluated. The primary follow-up adverse events included future ECHO-EF changes and major adverse cardiovascular events (MACEs). RESULTS: The sex-/age-matching strategy-trained DLM achieved the best area under the curve (AUC) of 0.9472 with a sensitivity of 86.9% and specificity of 89.6% in the follow-up cohort, with a correlation of 0.603 and a mean absolute error of 7.436. In patients with accurate prediction (initial difference < 10%), the change traces of ECG-EF and ECHO-EF were more consistent (R-square = 0.351) than in all patients (R-square = 0.115). Patients with lower ECG-EF (≤35%) exhibited a greater risk of cardiovascular (CV) complications, delayed ECHO-EF recovery, and earlier ECHO-EF deterioration than patients with normal ECG-EF (>50%). Importantly, ECG-EF demonstrated an independent impact on MACEs and all CV adverse outcomes, with better prediction of CV outcomes than ECHO-EF. CONCLUSIONS: The ECG-EF could be used to initially screen asymptomatic left ventricular dysfunction (LVD) and it could also independently contribute to the predictions of future CV adverse events. Although further large-scale studies are warranted, DLM-based ECG-EF could serve as a promising diagnostic supportive and management-guided tool for CV disease prediction and the care of patients with LVD.

Background: Left atrium enlargement (LAE) can be used as a predictor of future cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical electrocardiogram (ECG) changes have been reported in patients with LAE. This study developed a deep learning model (DLM)-enabled ECG system to identify patients with LAE. Method: Patients who had ECG records with corresponding echocardiography (ECHO) were included. There were 101,077 ECGs, 20,510 ECGs, 7611 ECGs, and 11,753 ECGs in the development, tuning, internal validation, and external validation sets, respectively. We evaluated the performance of a DLM-enabled ECG for diagnosing LAE and explored the prognostic value of ECG-LAE for new-onset HTN, new-onset stroke (STK), new-onset mitral regurgitation (MR), and new-onset Afib. Results: The DLM-enabled ECG achieved AUCs of 0.8127/0.8176 for diagnosing mild LAE, 0.8587/0.8688 for diagnosing moderate LAE, and 0.8899/0.8990 for diagnosing severe LAE in the internal/external validation sets. Notably, ECG-LAE had higher prognostic value compared to ECHO-LAE, which had C-indices of 0.711/0.714 compared to 0.695/0.692 for new-onset HTN, 0.676/0.688 compared to 0.663/0.677 for new-onset STK, 0.696/0.695 compared to 0.676/0.673 for new-onset MR, and 0.800/0.806 compared to 0.786/0.760 for new-onset Afib in internal/external validation sets, respectively. Conclusions: A DLM-enabled ECG could be considered as a LAE screening tool and provide better prognostic information for related cardiovascular diseases.

Purpose: To investigate the association of preexisting hypertension at admission with the mortality in patients with systolic heart failure (HF). Method: We prospectively investigated the association of preexisting hypertension with the mortality among 1351 patients with HF in Taiwan during an average 12 months (range: 8 months–18 months) follow-up period. A multivariate cox regression analysis for the overall cohort and a subgroup analysis by age were performed. Results: After adjustment for all potential risk factors, the associations of preexisting hypertension with cardiovascular mortality were significantly reduced in the overall cohort and those aged less than 65 years (hazard ratios (HR): 0.53, 95% confidence intervals (CI): 0.33–0.84, and 0.28, 95% CI: 0.11–0.67, respectively). However, the associations with all-cause mortality were not significantly different in these two groups (HR: 0.77, 95% CI: 0.54–1.09, and 0.59, 95% CI: 0.32–1.07, respectively). Furthermore, the associations were all nonsignificant in the patients aged older than 65 years. Conclusion: Preexisting hypertension have an inverse association with cardiovascular mortality in the Asian patients with systolic HF, particularly for those with younger ages. Keywords: Reverse epidemiology, Pre-existing hypertension, Heart failure

Abstract Background Streptococcus pneumoniae is a respiratory pathogen causing severe lung infection that may lead to complications such as bacteremia. Current polysaccharide vaccines have limited serotype coverage and therefore cannot provide maximal and long-term protection. Global efforts are being made to develop a conserved protein vaccine candidate. PrtA, a pneumococcal surface protein, was identified by screening a pneumococcal genomic expression library using convalescent patient serum. The prtA gene is prevalent and conserved among S. pneumoniae strains. Its protective efficacy, however, has not been described. Mucosal immunization could sensitize both local and systemic immunity, which would be an ideal scenario for preventing S. pneumoniae infection. Methods We immunized BALB/c mice intranasally with a combination of a PrtA fragment (amino acids 144–1041) and Th17 potentiated adjuvant, curdlan. We then measured the T-cell and antibody responses. The protective efficacy conferred to the immunized mice was further evaluated using a murine model of acute pneumococcal pneumonia and pneumococcal bacteremia. Results There was a profound antigen-specific IL-17A and IFN-γ response in PrtA-immunized mice compared with that of adjuvant control group. Even though PrtA-specific IgG and IgA titer in sera was elevated in immunized mice, only a moderate IgA response was observed in the bronchoalveolar lavage fluid. The PrtA-immunized antisera facilitated the activated murine macrophage, RAW264.7, to opsonophagocytose S. pneumoniae D39 strain; however, PrtA-specific immunoglobulins bound to pneumococcal surfaces with a limited potency. Finally, PrtA-induced immune reactions failed to protect mice against S. pneumoniae-induced acute pneumonia and bacterial propagation through the blood. Conclusions Immunization with recombinant PrtA combined with curdlan produced antigen-specific antibodies and elicited IL-17A response. However, it failed to protect the mice against S. pneumoniae-induced infection.

Background/Aims: Hyperlipidemia induces dysfunction in the smooth muscle cells (SMCs) of the blood vessels, and the vascular remodeling that ensues is a key proatherogenic factor contributing to cardiovascular events. Chemokines and chemokine receptors play crucial roles in vascular remodeling. Here, we examined whether the hyperlipidemia-derived chemokine CCL5 and its receptor CCR5 influence vascular SMC proliferation, phenotypic switching, and explored the underlying mechanisms. Methods: Thoracoabdominal aorta were isolated from wild-type, CCL5 and CCR5 double-knockout mice (CCL5–/–CCR5–/–) fed a high-fat diet (HFD) for 12 weeks. Expression of the contractile, synthetic, and proliferation markers were assayed using immunohistochemical and western blotting. The effects of CCL5 and palmitic acid on cultured SMC proliferation and phenotypic modulation were evaluated using flow cytometry, bromodeoxyuridine (BrdU), and western blotting. Results: Wild-type mice fed an HFD showed markedly increased total cholesterol, triglyceride, and CCL5 serum levels, as well as significantly increased CCL5 and CCR5 expression in the thoracoabdominal aorta vs. normal-diet-fed controls. HFD-fed CCL5-/-CCR5-/- mice showed significantly decreased expression of the synthetic phenotype marker osteopontin and the proliferation marker proliferating cell nuclear antigen, and increased expression of the contractile phenotype marker smooth muscle α-actin in the thoracoabdominal aorta vs. wild-type HFD-fed mice. Human aorta-derived SMCs stimulated with palmitic acid showed significantly increased expression of CCL5, CCR5, and synthetic phenotype markers, as well as increased proliferation. CCL5-treated SMCs showed increased cell cycle regulatory protein expression, paralleling increased synthetic and decreased contractile phenotype marker expression. Inhibition of CCR5 activity by the specific antagonist maraviroc or its expression using small interfering RNA significantly inhibited human aortic SMC proliferation and synthetic phenotype formation. Therefore, CCL5 induces SMC proliferation and phenotypic switching from a contractile to synthetic phenotype via CCR5. CCL5-mediated SMC stimulation activated ERK1/2, Akt/p70S6K, p38 MAPK, and NF-κB signaling. NF-κB inhibition significantly reduced CCR5 expression along with CCR5-induced SMC proliferation and synthetic phenotype formation. Conclusions: Hyperlipidemia-induced CCL5/CCR5 axis activation serves as a pivotal mediator of vascular remodeling, indicating that CCL5 and CCR5 are key chemokine-related factors in atherogenesis. SMC proliferation and synthetic phenotype transformation attenuation by CCR5 pharmacological inhibition may offer a new approach to treatment or prevention of atherosclerotic diseases associated with hyperlipidemia.

(1) Background: While an artificial intelligence (AI)-based, cardiologist-level, deep-learning model for detecting acute myocardial infarction (AMI), based on a 12-lead electrocardiogram (ECG), has been established to have extraordinary capabilities, its real-world performance and clinical applications are currently unknown. (2) Methods and Results: To set up an artificial intelligence-based alarm strategy (AI-S) for detecting AMI, we assembled a strategy development cohort including 25,002 visits from August 2019 to April 2020 and a prospective validation cohort including 14,296 visits from May to August 2020 at an emergency department. The components of AI-S consisted of chest pain symptoms, a 12-lead ECG, and high-sensitivity troponin I. The primary endpoint was to assess the performance of AI-S in the prospective validation cohort by evaluating F-measure, precision, and recall. The secondary endpoint was to evaluate the impact on door-to-balloon (DtoB) time before and after AI-S implementation in STEMI patients treated with primary percutaneous coronary intervention (PPCI). Patients with STEMI were alerted precisely by AI-S (F-measure = 0.932, precision of 93.2%, recall of 93.2%). Strikingly, in comparison with pre-AI-S (N = 57) and post-AI-S (N = 32) implantation in STEMI protocol, the median ECG-to-cardiac catheterization laboratory activation (EtoCCLA) time was significantly reduced from 6.0 (IQR, 5.0–8.0 min) to 4.0 min (IQR, 3.0–5.0 min) (p < 0.01). The median DtoB time was shortened from 69 (IQR, 61.0–82.0 min) to 61 min (IQR, 56.8–73.2 min) (p = 0.037). (3) Conclusions: AI-S offers front-line physicians a timely and reliable diagnostic decision-support system, thereby significantly reducing EtoCCLA and DtoB time, and facilitating the PPCI process. Nevertheless, large-scale, multi-institute, prospective, or randomized control studies are necessary to further confirm its real-world performance.

Objective: To investigate the 12-lead surface electrocardiographic (ECG) findings in young male patients with left primary spontaneous pneumothorax (PSP) estimated by the Collins equation. Methods: From 2003 through 2008, 60 young male patients who had left PSP and 61 age-matched unaffected males were included for 12-lead ECG analyses. The PSP size was estimated by the Collins equation. Those with left PSP were divided into two groups: 1) large PSP ≥30% (n = 37), and 2) small PSP

Patients bitten by Naja atra who are treated with bivalent freeze-dried neurotoxic antivenom in Taiwan have an improved survival rate but develop necrotic wound changes. The World Health Organization (WHO) has suggested using the minimum necrotizing dose (MND) of venom as a method of evaluating the neutralization effect of antivenom. The aim of this study was to evaluate the effectiveness of antivenom for the prevention of necrosis based on the MND and clarify which component of the venom of N. atra induces necrosis. The neurotoxins (NTXs) were removed from the crude venom (deNTXs), and different concentrations of deNTXs were injected intradermally into the dorsal skin of mice. After three days, the necrotic lesion diameter was found to be approximately 5 mm, and the MND was calculated. A reduction in the necrotic diameter of 50% was used to identify the MND50. Furthermore, both phospholipase A2 (PLA2) and cytotoxins (CTXs) were separately removed from the deNTXs to identify the major necrosis-inducing factor, and the necrotic lesions were scored. All mice injected with deNTXs survived for three days and developed necrotic wounds. The MND of the deNTXs for mice was 0.494 ± 0.029 µg/g, that of the deNTXs-dePLA2 (major component retained: CTXs) was 0.294 ± 0.05 µg/g, and that of the deNTX-deCTX (major component retained: PLA2) venom was greater than 1.25 µg/g. These values show that CTX is the major factor inducing necrosis. These results suggest that the use of the deNTXs is necessary to enable the mice to survive long enough to develop venom-induced cytolytic effects. CTXs play a major role in N. atra-related necrosis. However, the MND50 could not be identified in this study, which meant that the antivenom did not neutralize venom-induced necrosis.

Background: glycated hemoglobin (HbA1c) provides information on diabetes mellitus (DM) management. Electrocardiography (ECG) is a noninvasive test of cardiac activity that has been determined to be related to DM and its complications. This study developed a deep learning model (DLM) to estimate HbA1c via ECG. Methods: there were 104,823 ECGs with corresponding HbA1c or fasting glucose which were utilized to train a DLM for calculating ECG-HbA1c. Next, 1539 cases from outpatient departments and health examination centers provided 2190 ECGs for initial validation, and another 3293 cases with their first ECGs were employed to analyze its contributions to DM management. The primary analysis was used to distinguish patients with and without mild to severe DM, and the secondary analysis was to explore the predictive value of ECG-HbA1c for future complications, which included all-cause mortality, new-onset chronic kidney disease (CKD), and new-onset heart failure (HF). Results: we used a gender/age-matching strategy to train a DLM to achieve the best AUCs of 0.8255 with a sensitivity of 71.9% and specificity of 77.7% in a follow-up cohort with correlation of 0.496 and mean absolute errors of 1.230. The stratified analysis shows that DM presented in patients with fewer comorbidities was significantly more likely to be detected by ECG-HbA1c. Patients with higher ECG-HbA1c under the same Lab-HbA1c exhibited worse physical conditions. Of interest, ECG-HbA1c may contribute to the mortality (gender/age adjusted hazard ratio (HR): 1.53, 95% conference interval (CI): 1.08–2.17), new-onset CKD (HR: 1.56, 95% CI: 1.30–1.87), and new-onset HF (HR: 1.51, 95% CI: 1.13–2.01) independently of Lab-HbA1c. An additional impact of ECG-HbA1c on the risk of all-cause mortality (C-index: 0.831 to 0.835, p < 0.05), new-onset CKD (C-index: 0.735 to 0.745, p < 0.01), and new-onset HF (C-index: 0.793 to 0.796, p < 0.05) were observed in full adjustment models. Conclusion: the ECG-HbA1c could be considered as a novel biomarker for screening DM and predicting the progression of DM and its complications.

The impact of the coronavirus disease 2019 (COVID-19) pandemic on health-care quality in the emergency department (ED) in countries with a low risk is unclear. This study aimed to explore the effects of the COVID-19 pandemic on ED loading, quality of care, and patient prognosis. Data were retrospectively collected from 1 January 2018 to 30 September 2020 at the ED of Tri-service general hospital. Analyses included day-based ED loading, quality of care, and patient prognosis. Data on triage assessment, physiological states, disease history, and results of laboratory tests were collected and analyzed. The number of daily visits significantly decreased after the pandemic, leading to a reduction in the time to examination. Admitted patients benefitted from the pandemic with a reduction of 0.80 h in the length of stay in the ED, faster discharge without death, and reduced re-admission. However, non-admitted visits with chest pain increased the risk of mortality after the pandemic. In conclusion, the COVID-19 pandemic led to a significant reduction in low-acuity ED visits and improved prognoses for hospitalized patients. However, clinicians should be alert about patients with chest pain due to their increased risk of mortality in subsequent admission.

Statins constitute the mainstay treatment for atherosclerotic cardiovascular disease, which is associated with the risk of new-onset diabetes mellitus (NODM). However, the effects of individual statins on the risk of NODM remain unclear. We recruited 48,941 patients taking one of the three interested statins in a tertiary hospital between 2006 and 2018. Among them, 8337 non-diabetic patients taking moderate-intensity statins (2 mg/day pitavastatin, 10 mg/day atorvastatin, and 10 mg/day rosuvastatin) were included. The pitavastatin group had a higher probability of being NODM-free than the atorvastatin and rosuvastatin groups during the 4-year follow-up (log-rank test: p = 0.038). A subgroup analysis revealed that rosuvastatin had a significantly higher risk of NODM than pitavastatin among patients with coronary artery disease (CAD) (adjusted HR [aHR], 1.47, 95% confidence interval [CI], 1.05–2.05, p = 0.025), hypertension (aHR, 1.26, 95% CI, 1.00–1.59, p = 0.047), or chronic obstructive pulmonary disease (COPD) (aHR, 1.74, 95% CI, 1.02–2.94, p = 0.04). We concluded that compared with rosuvastatin, reduced diabetogenic effects of pitavastatin were observed among patients treated with moderate-intensity statin who had hypertension, COPD, or CAD. Additional studies are required to prove the effects of different statins on the risk of NODM.

Purpose: The present study compared the risk of ischemic stroke in atrial fibrillation (AF) patients receiving digoxin and amiodarone.Methods: A retrospective cohort study was conducted using the longitudinal population-based database of Taiwan’s National Health Insurance program. Patients with AF who received amiodarone or digoxin and were considered to have exposed to study drugs consecutively over 180 days during 2000–2010 were enrolled and divided into three groups: those who received amiodarone, digoxin, and amiodarone plus digoxin. All patients were followed from the index date to the occurrence of ischemic stroke, death, withdrawal from the insurance program, or December 31, 2011. Cox proportional hazard regression models were applied to determine the risk of ischemic stroke and associated risk factors.Results: The amiodarone, digoxin, and amiodarone plus digoxin cohorts comprised 797, 1419, and 376 patients, respectively. Overall, the patients who received digoxin (HR = 1.80; 95% CI = 1.41–2.31) or amiodarone plus digoxin (HR = 2.00; 95% CI = 1.49–2.68) had a higher risk of ischemic stroke, compared with those who received amiodarone. This risk was particularly at CHA2DS2VASc score of 2–5, but disappeared in those who received clopidogrel in the digoxin cohort. The risk of ischemic stroke in the amiodarone plus digoxin cohort did not differ significantly from that in the digoxin cohort (HR = 1.14; 95% CI = 0.90–1.44).Conclusion: Atrial fibrillation patients receiving digoxin are associated with a higher risk of ischemic stroke than are those receiving amiodarone. It is prudent to assess the stroke risk prior to applying treatment strategy for patients with AF.Strengths and Limitations of This Study - This study is a population-based design with a completeness and accuracy of data, national coverage in both study and control cohorts. All insurance claims were double-checked by medical specialists for peer review. - Information about serum levels of the drugs, coagulation status, and types of AF were unavailable in this administrative database.

Background: Revascularization within a 90-min door-to-balloon time is a strict policy enacted in Taiwan. Prompt diagnosis is critical to avoid an unnecessary procedure and catheterization laboratory activation. This study was aimed to investigate the clinical and prognostic characteristics of the patients with ST-elevation myocardial infarction (STEMI) referred for primary percutaneous coronary intervention (PCI) and normal coronary arteries found following coronary angiography (CAG). Materials and Methods: From October 2009 to December 2012, 216 consecutive patients with STEMI referred for primary PCI were enrolled. The data of clinical history, physical examination, laboratory results, electrocardiography, echocardiography, CAG findings, diagnosis, and outcomes were collected and analyzed. Results: A total of 17 patients were proved normal coronaries angiographically. The incidence of the conditions mimicking as STEMI is 7.9%. Alternative diagnosis was coronary spasm (n = 7), peri-myocarditis (n = 6), apical ballooning syndrome (n = 3), anaphylactic shock (n = 1). Compared with STEMI group, patients in normal coronaries group were younger, with a less premature family history of coronary artery disease (CAD), and reported angina. The 30-day mortality rate in the normal coronaries group was 5.9%. Conclusions: Cautiously evaluating CAD risk factors and symptoms of angina and awareness of alternative diagnosis are important to make a prompt diagnosis without compromising accuracy in the patients presenting as suspected STEMI.

Carvedilol (Cav), a nonselective β-blocker with α1 adrenoceptor blocking effect, has been used as a standard therapy for coronary artery disease. This study investigated the effects of Cav on exosome expression and function, ATP-binding cassette transporter A1 (ABCA1) expression, and cholesterol efflux that are relevant to the process of atherosclerosis. Human monocytic (THP-1) cell line and human hepatic (Huh-7) cells were treated with Cav, and cholesterol efflux was measured. Exosomes from cell culture medium or mice serum were isolated using glycan-coated recognition beads. Low-density lipoprotein receptor knockout (ldlr−/−) mice were fed with high-fat diet and treated with Cav. Cav accentuated cholesterol efflux and enhanced the expressions of ABCA1 protein and mRNA in both THP-1 and Huh-7 cells. In addition, Cav increased expression and function of exosomal ABCA1 in THP-1 macrophage exosomes. The mechanisms were associated with inhibition of nuclear factor-κB (NF-κB) and protein kinase B (Akt). In hypercholesterolemic ldlr−/− mice, Cav enhanced serum exosomal ABCA1 expression and suppressed atherosclerosis by inhibiting lipid deposition and macrophage accumulation. Cav halts atherosclerosis by enhancing cholesterol efflux and increasing ABCA1 expression in macrophages and in exosomes, possibly through NF-κB and Akt signaling, which provides mechanistic insights regarding the beneficial effects of Cav on atherosclerotic cardiovascular disease.

Statins inhibiting 3-hydroxy-3-methylglutaryl-CoA reductase are the standard treatment for hypercholesterolemia in atherosclerotic cardiovascular disease (ASCVD), mediated by inflammatory reactions within vessel walls. Several studies highlighted the pleiotropic effects of statins beyond their lipid-lowering properties. However, few studies investigated the effects of statins on T cell activation. This study evaluated the immunomodulatory capacities of three common statins, pitavastatin, atorvastatin, and rosuvastatin, in activated human T cells. The enzyme-linked immunosorbent assay (ELISA) and quantitative real time polymerase chain reaction (qRT-PCR) results demonstrated stronger inhibitory effects of pitavastatin on the cytokine production of T cells activated by phorbol 12-myristate 13-acetate (PMA) plus ionomycin, including interleukin (IL)-2, interferon (IFN)-γ, IL-6, and tumor necrosis factor α (TNF-α). Molecular investigations revealed that pitavastatin reduced both activating protein-1 (AP-1) DNA binding and transcriptional activities. Further exploration showed the selectively inhibitory effect of pitavastatin on the signaling pathways of extracellular signal-regulated kinase (ERK) and p38 mitogen-activated protein kinase (MAPK), but not c-Jun N-terminal kinase (JNK). Our findings suggested that pitavastatin might provide additional benefits for treating hypercholesterolemia and ASCVD through its potent immunomodulatory effects on the suppression of ERK/p38/AP-1 signaling in human T cells.

Cardiovascular disease is one of the leading causes of death and disability in the world. Atherosclerosis, characterized by lipid accumulation and chronic inflammation in the vessel wall, is the main feature of cardiovascular disease. Although the amounts of fruits and vegetables present in the diets vary by country, diets, worldwide, contain large amounts of spices; this may have positive or negative effects on the initiation and development of atherosclerosis. In this review, we focused on the potential protective effects of specific nutrients from spices, such as pepper, ginger, garlic, onion, cinnamon and chili, in atherosclerosis and atherosclerotic cardiovascular disease. The mechanisms, epidemiological analysis, and clinical studies focusing on a variety of spices are covered in this review. Based on the integrated information, we aimed to raise specific recommendations for people with different dietary styles for the prevention of atherosclerotic cardiovascular disease through dietary habit adjustments.

Diabetes mellitus (DM) is a metabolic disease that is increasing worldwide. Furthermore, it is associated with the deregulation of vascular-related functions, which can develop into major complications among DM patients. Endothelial colony forming cells (ECFCs) have the potential to bring about medical repairs because of their post-natal angiogenic activities; however, such activities are impaired by high glucose- (HG) and the DM-associated conditions. Far-infrared radiation (FIR) transfers energy as heat that is perceived by the thermoreceptors in human skin. Several studies have revealed that FIR improves vascular endothelial functioning and boost angiogenesis. FIR has been used as anti-inflammatory therapy and as a clinical treatment for peripheral circulation improvement. In addition to vascular repair, there is increasing evidence to show that FIR can be applied to a variety of diseases, including cardiovascular disorders, hypertension and arthritis. Yet mechanism of action of FIR and the biomarkers that indicate FIR effects remain unclear. MicroRNA-134 (miR-134-5p) was identified by small RNA sequencing as being increased in high glucose (HG) treated dfECFCs (HG-dfECFCs). Highly expressed miR-134 was also validated in dmECFCs by RT-qPCR and it is associated with impaired angiogenic activities of ECFCs. The functioning of ECFCs is improved by FIR treatment and this occurs via a reduction in the level of miR-134 and an increase in the NRIP1 transcript, a direct target of miR-134. Using a mouse ischemic hindlimb model, the recovery of impaired blood flow in the presence of HG-dfECFCs was improved by FIR pretreatment and this enhanced functionality was decreased when there was miR-134 overexpression in the FIR pretreated HG-dfECFCs. In conclusion, our results reveal that the deregulation of miR-134 is involved in angiogenic defects found in DM patients. FIR treatment improves the angiogenic activity of HG-dfECFCs and dmECFCs and FIR has potential as a treatment for DM. Detection of miR-134 expression in FIR-treated ECFCs should help us to explore further the effectiveness of FIR therapy.

Atherosclerosis is a process of imbalanced lipid metabolism in the vascular walls. The underlying pathology mainly involves the deposition of oxidized lipids in the endothelium and the accumulation of cholesterol in macrophages. Macrophages export excessive cholesterol (cholesterol efflux) through ATP-binding cassette transporter A1 (ABCA1) to counter the progression of atherosclerosis. We synthesized novel chalcone derivatives and assessed their effects and the underlying mechanisms on ABCA1 expression in macrophages. Human THP-1 macrophages were treated with synthetic chalcone derivatives for 24 h. In Western blot and flow cytometry analyses, a chalcone derivative, (E)-1-(3,4-diisopropoxyphenyl)-3-(4-isopropoxy-3-methoxyphenyl)prop- 2-en-1-one (1m), was observed to significantly enhance ABCA1 protein expression in THP-1 cells (10 µM, 24 h). Levels of mRNA of ABCA1 and liver X receptor alpha (LXRα) were quantified using a real-time quantitative polymerase chain reaction technique and were found to be significantly increased after treatment with the novel chalcone derivative 1m. Several microRNAs, including miR155, miR758, miR10b, miR145, miR33, and miR106b, which functionally inhibit ABCA1 expression were suppressed after treatment with 1m. Collectively, 1m increases ABCA1 expression in human THP-1 macrophages. The mechanisms involve the activation of the LXRα-ABCA1 pathway and suppression of certain microRNAs that regulate ABCA1 expression.

Background: Thrombomodulin (TM) is a type of cell membrane-bound anticoagulant protein cofactor in the thrombin-mediated activation of protein C. Previous evidence has shown an association between TM polymorphisms and systemic inflammation. Conventional cardiopulmonary bypass (CPB), beating-heart CPB, and off-pump techniques have been widely used in cardiac surgery. However, these techniques may also cause systemic inflammatory responses in the patients. Whether TM polymorphisms are associated with systemic inflammation after cardiac surgery is still unclear. Methods: We analyzed the TM gene C1418T polymorphisms in 347 patients who underwent coronary artery bridge graft (CABG) surgery using allele-specific primers in a PCR assay. The clinical data during the hospital stay were collected and tested for correlations with the TM gene C1418T polymorphisms. Results: We separated the patients into two groups based on their TM C1418T genotype (CC genotype group and CT/TT genotype group). The days spent in an intensive care unit (ICU) and the incidence of fever in the ICU were significantly lower in the beating-heart CPB and off-pump groups than in the conventional CPB group. Additionally, the TM gene C1418T polymorphisms did not affect the early outcomes in patients in the beating-heart CPB and off-pump groups. Interestingly, in the conventional CPB group, patients with the CC genotype had a lower rate of fever, shorter duration of fever, and delay of ICU when compared with the CT/TT genotype. Conclusion: Surgeons may use a patient’s TM gene C1418T polymorphism to predict the strength of systemic inflammation and speculate on early outcomes during hospitalization before conventional CPB is performed.

Migration of vascular smooth muscle cells (VSMCs) into the intima is considered to be a vital event in the pathophysiology of atherosclerosis. Despite substantial evidence supporting the pathogenic role of Toll-like receptor 4 (TLR4) in the progression of atherogenesis, its function in the regulation of VSMC migration remains unclear. The goal of the present study was to elucidate the mechanism by which TLR4 regulates VSMC migration. Inhibitor experiments revealed that TLR4-induced IL-6 secretion and VSMC migration were mediated via the concerted actions of MyD88 and TRIF on the activation of p38 MAPK and ERK1/2 signaling. Neutralizing anti-IL-6 antibodies abrogated TLR4-driven VSMC migration and F-actin polymerization. Blockade of p38 MAPK or ERK1/2 signaling cascade inhibited TLR4 agonist-mediated activation of cAMP response element binding protein (CREB). Moreover, siRNA-mediated suppression of CREB production repressed TLR4-induced IL-6 production and VSMC migration. Rac-1 inhibitor suppressed TLR4-driven VSMC migration but not IL-6 production. Importantly, the serum level of IL-6 and TLR4 endogenous ligand HMGB1 was significantly higher in patients with coronary artery diseases (CAD) than in healthy subjects. Serum HMGB1 level was positively correlated with serum IL-6 level in CAD patients. The expression of both HMGB1 and IL-6 was clearly detected in the atherosclerotic tissue of the CAD patients. Additionally, there was a positive association between p-CREB and HMGB1 in mouse atherosclerotic tissue. Based on our findings, we concluded that, upon ligand binding, TLR4 activates p38 MAPK and ERK1/2 signaling through MyD88 and TRIF in VSMCs. These signaling pathways subsequently coordinate an additive augmentation of CREB-driven IL-6 production, which in turn triggers Rac-1-mediated actin cytoskeleton to promote VSMC migration.