The 10-Year Prognosis and Prevalence of Brugada-Type Electrocardiograms in Elderly Women: A Longitudinal Nationwide Community-Based Prospective Study.

BACKGROUND: Brugada syndrome is a disorder associated with sudden cardiac death and characterized by an abnormal electrocardiogram (ECG). Previous studies were predominantly conducted in men, and the data on long-term prognosis are limited. Information about women, especially elderly women, is lacking. OBJECTIVE: The aim of this study was to investigate the long-term prognosis of the Brugada ECG pattern in elderly women. METHOD: We investigated the 10-year prognosis of the Brugada ECG pattern in elderly women in a nationwide community-based population in Taiwan. Community-dwelling women older than 55 years were prospectively recruited from December 2008 to March 2013 by a stratified random sampling method. All enrolled individuals were followed up annually until April 2019, and the cause of death was documented by citizen death records. RESULTS: Among 2597 women, 60 (2.31%) had a Brugada-type ECG, and this prevalence was higher than the mean global prevalence of 0.23%. One woman had a type 1 ECG (0.04%), whereas 15 (0.58%) and 44 (1.70%) women had type 2 and type 3 ECG patterns, respectively. Cox survival analysis revealed that all-cause mortality and cardiac mortality were similar in the individuals with and without a Brugada-type ECG during a mean follow-up of 96.1 ± 20.5 months. CONCLUSIONS: Our findings suggest that Brugada ECG patterns are not infrequent in elderly women but are not associated with increased risk of mortality in long-term follow-up; these findings may help reduce unnecessary anxiety for physicians, nurses, allied health caregivers, and patients.

Licochalcone A Prevents Platelet Activation and Thrombus Formation through the Inhibition of PLCγ2-PKC, Akt, and MAPK Pathways.

Platelet activation is involved in cardiovascular diseases, such as atherosclerosis and ischemic stroke. Licochalcone A (LA), an active ingredient of licorice, exhibits multiple biological activities such as anti-oxidation and anti-inflammation. However, its role in platelet activation remains unclear. Therefore, the study investigated the antiplatelet mechanism of LA. Our data revealed that LA (2-10 µM) concentration dependently inhibited platelet aggregation induced by collagen, but not thrombin and U46619. LA markedly attenuated collagen-stimulated ATP release, P-selectin secretion, calcium mobilization, and GPIIbIIIa activation, but did not interfere with the collagen binding to platelets. Moreover, LA significantly reduced the activation of PLCγ2, PKC, Akt and MAPKs. Thus, LA attenuates platelet activation, possibly by inhibiting collagen receptor downstream signaling but not by blocking the collagen receptors. In addition, LA prevented adenosine diphosphate (ADP)-induced acute pulmonary thrombosis, fluorescein sodium-induced platelet thrombus formation, and middle cerebral artery occlusion/reperfusion-induced brain injury in mice, but did not affect normal hemostasis. This study demonstrated that LA effectively reduced platelet activation and thrombus formation, in part, through the inhibition of PLCγ2-PKC, Akt, and MAPK pathways, without the side effect of bleeding. These findings also indicate that LA may provide a safe and alternative therapeutic approach for preventing thromboembolic disorders such as stroke.

Nobiletin, a Polymethoxylated Flavone, Inhibits Glioma Cell Growth and Migration via Arresting Cell Cycle and Suppressing MAPK and Akt Pathways.

Nobiletin, a bioactive polymethoxylated flavone (5,6,7,8,3(') ,4(') -hexamethoxyflavone), is abundant in citrus fruit peel. Although nobiletin exhibits antitumor activity against various cancer cells, the effect of nobiletin on glioma cells remains unclear. The aim of this study was to determine the effects of nobiletin on the human U87 and Hs683 glioma cell lines. Treating glioma cells with nobiletin (20-100 µm) reduced cell viability and arrested the cell cycle in the G0/G1 phase, as detected using a 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay and propidium iodide (PI) staining, respectively; however, nobiletin did not induce cell apoptosis according to PI-annexin V double staining. Data from western blotting showed that nobiletin significantly attenuated the expression of cyclin D1, cyclin-dependent kinase 2, cyclin-dependent kinase 4, and E2 promoter-binding factor 1 (E2F1) and the phosphorylation of Akt/protein kinase B and mitogen-activated protein kinases, including p38, extracellular signal-regulated kinase, and c-Jun N-terminal kinase. Our data also showed that nobiletin inhibited glioma cell migration, as detected by both functional wound healing and transwell migration assays. Altogether, the present results suggest that nobiletin inhibits mitogen-activated protein kinase and Akt/protein kinase B pathways and downregulates positive regulators of the cell cycle, leading to subsequent suppression of glioma cell proliferation and migration. Our findings evidence that nobiletin may have potential for treating glioblastoma multiforme.

Prevalence and prognosis of Brugada electrocardiogram patterns in an elderly Han Chinese population: a nation-wide community-based study (HALST cohort).

AIMS: The exact world-wide prevalence of Brugada electrocardiogram (ECG) pattern is still unclear, especially in adults aged 55 years and older. METHODS AND RESULTS: The study was conducted as part of the Healthy Aging Longitudinal Study in Taiwan (HALST). Using a stratified random sampled method, a sample of community-dwelling subjects was recruited from seven community-based regions across Taiwan. All enrolled subjects were follow-up annually and cause of death was documented by citizen death records. A total of 5214 subjects were enrolled (male/female: 2530/2684) with a mean age of 69 ± 8 years. The overall prevalence of Brugada ECG patterns was 3.32%. Four subjects carried spontaneous Type 1 Brugada ECG pattern, 68 carried Type 2, and 101 carried Type 3. Compared with the world-wide average prevalence of Brugada ECG patterns, the prevalence of spontaneous Type 1 Brugada ECG pattern in subjects from the HALST cohort was similar (0.077 vs. 0.07%) and the combined prevalence of Types 2 and 3 Brugada ECG pattern was 10 times higher (3.24 vs. 0.28%) even the mean age of study subjects was significantly higher (69 ± 8 vs. 35 ± 8, P < 0.001). However, all-cause mortality and cardiac mortality rates were not significantly different between subjects with and without Brugada ECG patterns during the 4-year follow-up (log-rank test, P = 0.21, 0.32, respectively). CONCLUSION: The prevalence of Brugada ECG pattern in adults aged 55 years and older in Taiwan was higher than the average world-wide prevalence but was not associated with increased mortality.

Explainable machine learning model for identifying key gut microbes and metabolites biomarkers associated with myasthenia gravis.

Diagnostic markers for myasthenia gravis (MG) are limited; thus, innovative approaches are required for supportive diagnosis and personalized care. Gut microbes are associated with MG pathogenesis; however, few studies have adopted machine learning (ML) to identify the associations among MG, gut microbiota, and metabolites. In this study, we developed an explainable ML model to predict biomarkers for MG diagnosis. We enrolled 19 MG patients and 10 non-MG individuals. Stool samples were collected and microbiome assessment was performed using 16S rRNA sequencing. Untargeted metabolic profiling was conducted to identify fecal amplicon significant variants (ASVs) and metabolites. We developed an explainable ML model in which the top ASVs and metabolites are combined to identify the best predictive performance. This model uses the SHapley Additive exPlanations method to generate both global and personalized explanations. Fecal microbe-metabolite composition differed significantly between groups. The key bacterial families were Lachnospiraceae and Ruminococcaceae, and the top three features were Lachnospiraceae, inosine, and methylhistidine. An ML model trained with the top 1 % ASVs and top 15 % metabolites combined outperformed all other models. Personalized explanations revealed different patterns of microbe-metabolite contributions in patients with MG. The integration of the microbiota-metabolite features and the development of an explainable ML framework can accurately identify MG and provide personalized explanations, revealing the associations between gut microbiota, metabolites, and MG. An online calculator employing this algorithm was developed that provides a streamlined interface for MG diagnosis screening and conducting personalized evaluations.

A Systematic Search and Review of Registered Pharmacological Therapies Investigated to Improve Outcomes after a Stroke.

INTRODUCTION: Stroke burden is largely due to long-term impairments requiring prolonged care and loss of productivity. We aim to identify and assess studies of different registered pharmacological therapies as treatments for improving post-stroke impairments and/or disabilities. METHODS: In a systematic search and review (PROSPERO registration: CRD42022376973), studies of treatments that have been investigated as recovery-enhancing or recovery-promoting treatments in adult patients who had suffered a stroke will be searched for, screened, and reviewed based on the following: participants (P): adult humans, aged 18 years or older, diagnosed with stroke; interventions (I): registered or marketed pharmacological therapies that have been investigated as recovery-enhancing or recovery-promoting treatments in stroke; comparators (C): active or placebo or no comparator; outcomes (O): stroke-related neurological impairments and functional/disability assessments. Data will be extracted from included papers, including patient demographics, study methods, keystroke inclusion criteria, details of intervention and control, and the reported outcomes. RESULT: "The best available studies" based on study design, study size, and/or date of publication for different therapies and stroke subtypes will be selected and graded for level of evidence by consensus. CONCLUSION: There are conflicting study results of pharmacological interventions after an acute stroke to enhance recovery. This systematic search and review will identify the best evidence and knowledge gaps in the pharmacological treatment of post-stroke patients as well as guide clinical decision-making and planning of future studies.

A systematic-search-and-review of registered pharmacological therapies investigated to improve neuro-recovery after a stroke.

Background: Stroke burden is largely due to long-term impairments requiring prolonged care with loss of productivity. We aimed to identify and assess studies of different registered pharmacological therapies as treatments to improve post-stroke impairments and/or disabilities. Methods: We performed a systematic-search-and-review of treatments that have been investigated as recovery-enhancing or recovery-promoting therapies in adult patients with stroke. The treatment must have received registration or market authorization in any country regardless of primary indication. Outcomes included in the review were neurological impairments and functional/disability assessments. "The best available studies" based on study design, study size, and/or date of publication were selected and graded for level of evidence (LOE) by consensus. Results: Our systematic search yielded 7,801 citations, and we reviewed 665 full-text papers. Fifty-eight publications were selected as "the best studies" across 25 pharmacological classes: 31 on ischemic stroke, 21 on ischemic or hemorrhagic stroke, 4 on intracerebral hemorrhage, and 2 on subarachnoid hemorrhage (SAH). Twenty-six were systematic reviews/meta-analyses, 29 were randomized clinical trials (RCTs), and three were cohort studies. Only nimodipine for SAH had LOE A of benefit (systematic review and network meta-analysis). Many studies, some of which showed treatment effects, were assessed as LOE C-LD, mainly due to small sample sizes or poor quality. Seven interventions had LOE B-R (systematic review/meta-analysis or RCT) of treatment effects. Conclusion: Only one commercially available treatment has LOE A for routine use in stroke. Further studies of putative neuroprotective drugs as adjunctive treatment to revascularization procedures and more confirmatory trials on recovery-promoting therapies will enhance the certainty of their benefit. The decision on their use must be guided by the clinical profile, neurological impairments, and target outcomes based on the available evidence. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=376973, PROSPERO, CRD42022376973.

Effects of double filtration plasmapheresis on nocturnal respiratory function in myasthenic patients.

Assessment of respiratory function using combined oximetry-cutaneous capnography has never been evaluated in patients with myasthenia gravis (MG). We investigated the effects of double filtration plasmapheresis (DFPP) on respiratory status in 18 MG patients. Results of combined oximetry and transcutaneous capnography, MG scores, and acetylcholine receptor antibody titers before and after DFPP treatment were compared. The respiratory monitoring was performed at three time periods (morning, afternoon, and sleep). Mean MG score was markedly lower after DFPP treatment (5.7) than before treatment (7.9). Before DFPP, the minimum pulse oximetric saturation (SpO2 ) level obtained during the night session was significantly lower (P = 0.0513 and P = 0.0199) than the levels obtained during the two daytime sessions. A similar phenomenon was noted for maximum transcutaneous carbon dioxide tension (PtcCO2 ). After DFPP treatment, the maximum and mean PtcCO2 levels were significantly higher (P = 0.0056) in the morning than in the afternoon. Of all the respiratory function parameters measured, only minimum SpO2 levels obtained during morning sessions before DFP treatment differed significantly from those obtained after DFPP treatment (P = 0.0322). Overall, however, minimum SpO2 levels as well as mean and maximum PtcCO2 levels improved significantly during sleep after DFPP. In conclusion, we found that respiratory function abnormalities were common in myasthenic patients without clinical respiratory symptoms. DFPP treatment resulted in minimal improvement of respiratory parameters.

A decrease in the percentage of CD3+ cells is correlated with clinical improvement during plasmapheresis in patients with myasthenia gravis.

Plasmapheresis not only removes circulating antibodies but also modulates cellular immunity, including lymphocyte subsets. To investigate the effect of double-filtration plasmapheresis (DFPP) on the ratio of lymphocyte subsets in patients with myasthenia gravis (MG), we examined the percentages of B-cells, T-cells, T helper (Th) cells, T suppressor (Ts) cells, natural killer (NK) cells, NKT cells, and Th/Ts ratio before and after a single DFPP session and after a course of DFPP. A total of 26 patients were recruited; their peripheral blood lymphocyte subsets were assayed using flow cytometry. After a single session of DFPP treatment, the percentages of T-cells (P = 0.0200), Th cells (P = 0.0178), and the Th/Ts ratio (P = 0.0309) decreased significantly, whereas the percentage of NK cells (P = 0.0007) increased significantly. More importantly, after one course of DFPP treatment, the reduced clinical quantitative MG (QMG) score was correlated with the decrease of the percentage of T-cells (r = 0.5005, P = 0.0092). Fourteen thymectomized MG patients had decreased percentages of T-cells (P = 0.0304) and Th cells (P = 0.0444), whereas they had increased NK cells (P = 0.0197) after a single DFPP session. Here, transiently decreased percentages of T-cells after the full DFPP course could enhance the effectiveness of plasmapheresis for MG patients.

Mechanisms of andrographolide-induced platelet apoptosis in human platelets: regulatory roles of the extrinsic apoptotic pathway.

Andrographolide, a novel nuclear factor-κB (NF-κB) inhibitor, is isolated from the leaves of Andrographis paniculata. Platelet activation is relevant to a variety of coronary heart diseases. Our recent studies revealed that andrographolide possesses potent antiplatelet activity by inhibition of the p38 MAPK/(●) HO-NF-κB-ERK2 cascade. Although platelets are anucleated cells, apoptotic machinery apparatus recently has been found to regulate platelet activation and limit platelet lifespan. Therefore, we further investigated the regulatory effects of andrographolide on platelet apoptotic events. In this study, apoptotic signaling events for caspase-3, -8, and Bid were time (10-60 min)- and dose (25-100 µΜ)-dependently activated by andrographolide in human platelets. Andrographolide could also disrupt mitrochondrial membrane potential. In addition, caspase-8 inhibitor (z-IETD-fmk, 50 µΜ) was found to reverse andrographolide-induced caspase-8 activation, whereas the antagonistic anti-Fas receptor (ZB4, 500 ng/mL) and anti-tumor necrosis factor-R1 (H398, 10 µg/mL) monoclonal antibodies did not. In conclusion, this study for the first time demonstrated that andrographolide might limit platelet lifespan by initiating the caspase-8-dependent extrinsic apoptotic pathway, in spite of no direct evidence that death receptors are involved in this process proved. Overall, the various medicinal properties of andrographolide suggest its potential value in treating patients with thromboembolic disorders.

Successful Treatment of Peripartum Cardiomyopathy with Plasmapheresis.

UNLABELLED: Peripartum cardiomyopathy (PPCM) is a rare, life-threatening disease of late pregnancy and early puerperium among previously healthy women. Management of this challenging disease is similar to other forms of systolic heart failure. Unfortunately, only 30% to 50% of patients recover completely. Among the remaining patients, continued poor ejection fraction indicates irreversible cardiomyopathy and portends a poor outcome. Immune complexes, autoantibodies, or toxic proteins are likely causative agents. Herein, we report first two PPCM cases that were successfully managed with plasmapheresis. KEY WORDS: Peripartum cardiomyopathy; Plasmapheresis.

Machine learning strategy for identifying altered gut microbiomes for diagnostic screening in myasthenia gravis.

Myasthenia gravis (MG) is a neuromuscular junction disease with a complex pathophysiology and clinical variation for which no clear biomarker has been discovered. We hypothesized that because changes in gut microbiome composition often occur in autoimmune diseases, the gut microbiome structures of patients with MG would differ from those without, and supervised machine learning (ML) analysis strategy could be trained using data from gut microbiota for diagnostic screening of MG. Genomic DNA from the stool samples of MG and those without were collected and established a sequencing library by constructing amplicon sequence variants (ASVs) and completing taxonomic classification of each representative DNA sequence. Four ML methods, namely least absolute shrinkage and selection operator, extreme gradient boosting (XGBoost), random forest, and classification and regression trees with nested leave-one-out cross-validation were trained using ASV taxon-based data and full ASV-based data to identify key ASVs in each data set. The results revealed XGBoost to have the best predicted performance. Overlapping key features extracted when XGBoost was trained using the full ASV-based and ASV taxon-based data were identified, and 31 high-importance ASVs (HIASVs) were obtained, assigned importance scores, and ranked. The most significant difference observed was in the abundance of bacteria in the Lachnospiraceae and Ruminococcaceae families. The 31 HIASVs were used to train the XGBoost algorithm to differentiate individuals with and without MG. The model had high diagnostic classification power and could accurately predict and identify patients with MG. In addition, the abundance of Lachnospiraceae was associated with limb weakness severity. In this study, we discovered that the composition of gut microbiomes differed between MG and non-MG subjects. In addition, the proposed XGBoost model trained using 31 HIASVs had the most favorable performance with respect to analyzing gut microbiomes. These HIASVs selected by the ML model may serve as biomarkers for clinical use and mechanistic study in the future. Our proposed ML model can identify several taxonomic markers and effectively discriminate patients with MG from those without with a high accuracy, the ML strategy can be applied as a benchmark to conduct noninvasive screening of MG.

Tumor size combined with staging systems for thymoma recurrence prediction: A 28-year experience.

Background: We evaluated a new thymoma prognosis prediction model by combining current staging systems with tumor size. Methods: The clinical records of thymoma patients in a single center between January 1993 and December 2021 were collected, and data on tumor size and stage and recurrence-free survival (RFS) was obtained. The prediction model was designed by combining staging with tumor size. Results: During 28 years, 219 thymoma patients were enrolled. Twenty-seven patients had a median RFS of 8.2 years. Further, 153 patients were categorized into limited stage and 66 patients into advanced stage. The RFS was statistically different between these two groups (P = 0.022). The largest area under the curve (AUC) of receiver operating characteristic (ROC) was the dividing group as 5 cm (AUC: 0.804). Conclusions: Combining tumor staging and size improves thymoma recurrence prediction. Patients with advanced stage and tumor size >5 cm may show a poor prognosis.

Assessing the length of hospital stay for patients with myasthenia gravis based on the data mining MARS approach.

Predicting the length of hospital stay for myasthenia gravis (MG) patients is challenging due to the complex pathogenesis, high clinical variability, and non-linear relationships between variables. Considering the management of MG during hospitalization, it is important to conduct a risk assessment to predict the length of hospital stay. The present study aimed to successfully predict the length of hospital stay for MG based on an expandable data mining technique, multivariate adaptive regression splines (MARS). Data from 196 MG patients' hospitalization were analyzed, and the MARS model was compared with classical multiple linear regression (MLR) and three other machine learning (ML) algorithms. The average hospital stay duration was 12.3 days. The MARS model, leveraging its ability to capture non-linearity, identified four significant factors: disease duration, age at admission, MGFA clinical classification, and daily prednisolone dose. Cut-off points and correlation curves were determined for these risk factors. The MARS model outperformed the MLR and the other ML methods (including least absolute shrinkage and selection operator MLR, classification and regression tree, and random forest) in assessing hospital stay length. This is the first study to utilize data mining methods to explore factors influencing hospital stay in patients with MG. The results highlight the effectiveness of the MARS model in identifying the cut-off points and correlation for risk factors associated with MG hospitalization. Furthermore, a MARS-based formula was developed as a practical tool to assist in the measurement of hospital stay, which can be feasibly supported as an extension of clinical risk assessment.

Utilization of Decision Tree Algorithms for Supporting the Prediction of Intensive Care Unit Admission of Myasthenia Gravis: A Machine Learning-Based Approach.

Myasthenia gravis (MG), an acquired autoimmune-related neuromuscular disorder that causes muscle weakness, presents with varying severity, including myasthenic crisis (MC). Although MC can cause significant morbidity and mortality, specialized neuro-intensive care can produce a good long-term prognosis. Considering the outcomes of MG during hospitalization, it is critical to conduct risk assessments to predict the need for intensive care. Evidence and valid tools for the screening of critical patients with MG are lacking. We used three machine learning-based decision tree algorithms, including a classification and regression tree, C4.5, and C5.0, for predicting intensive care unit (ICU) admission of patients with MG. We included 228 MG patients admitted between 2015 and 2018. Among them, 88.2% were anti-acetylcholine receptors antibody positive and 4.7% were anti-muscle-specific kinase antibody positive. Twenty clinical variables were used as predictive variables. The C5.0 decision tree outperformed the other two decision tree and logistic regression models. The decision rules constructed by the best C5.0 model showed that the Myasthenia Gravis Foundation of America clinical classification at admission, thymoma history, azathioprine treatment history, disease duration, sex, and onset age were significant risk factors for the development of decision rules for ICU admission prediction. The developed machine learning-based decision tree can be a supportive tool for alerting clinicians regarding patients with MG who require intensive care, thereby improving the quality of care.

Get With the Guidelines-Stroke performance indicators: surveillance of stroke care in the Taiwan Stroke Registry: Get With the Guidelines-Stroke in Taiwan.

BACKGROUND: Stroke is a leading cause of death around the world. Improving the quality of stroke care is a global priority, despite the diverse healthcare economies across nations. The American Heart Association/American Stroke Association Get With the Guidelines-Stroke program (GWTG-Stroke) has improved the quality of stroke care in 790 US academic and community hospitals, with broad implications for the rest of the country. The generalizability of GWTG-Stroke across national and economic boundaries remains to be tested. The Taiwan Stroke Registry, with 30 599 stroke admissions between 2006 and 2008, was used to assess the applicability of GWTG-Stroke in Taiwan, which spends ≈ 1/10 of what the United States does in medical costs per new or recurrent stroke. METHODS AND RESULTS: Taiwan Stroke Registry, sponsored by the Taiwan Department of Health, engages 39 academic and community hospitals and covers the entire country with 4 steps of quality control to ensure the reliability of entered data. Five GWTG-Stroke performance measures and 1 safety indicator are applicable to assess Taiwan Stroke Registry quality of stroke care. Demographic and outcome figures are comparable between GWTG-Stroke and Taiwan Stroke Registry. Two indicators (early and discharge antithrombotics) are close to GWTG-Stroke standards, while 3 other indicators (intravenous tissue plasminogen activator, anticoagulation for atrial fibrillation, lipid-lowering medication) and 1 safety indicator fall behind. Preliminary analysis shows that compliance with selected GWTG-Stroke guidelines is associated with better outcomes. CONCLUSIONS: Results suggest that GWTG-Stroke performance measures, with modification for ethnic factors, can become global standards across national and economic boundaries for assessing and improving quality of stroke care and outcomes. GWTG-Stroke can be incorporated into ongoing stroke registries across nations.

Common carotid end-diastolic velocity and intima-media thickness jointly predict ischemic stroke in Taiwan.

BACKGROUND AND PURPOSE: In Asian populations, few studies investigated the association between stroke and common carotid artery intima-media thickness (IMT). Our previous case-control studies showed that low end-diastolic velocity (EDV) in common carotid artery, a potential hemodynamic marker of intracranial resistance, was associated with ischemic stroke. Therefore, we investigated the relationship between both EDV and IMT and incident ischemic stroke in an Asian population. METHODS: Baseline data from 3175 adults (30 years or older) in the Cardiovascular Diseases Risk Factor Two-Township Study were linked to incidental ischemic stroke status derived from insurance claims and death certificate records. Hazard ratios for risk of ischemic stroke for high IMT and low EDV values measured in common carotid artery were calculated using Cox proportional hazard models. RESULTS: With 9.85 years (median) of follow-up, 184 persons had ischemic stroke develop. Compared with the first tertile of IMT, hazard ratios were 2.03 (95% confidence intervals, 1.27-3.25) for the second tertile and 3.87 (95% confidence intervals, 2.36-5.69) for the third tertile. Hazard ratios of EDV were 5.31 (95% confidence intervals, 3.52-7.99; first tertile) and 1.94 (95% confidence intervals, 1.21-3.09; second tertile) compared with the third tertile. The individuals with high IMT and low EDV had >2-fold ischemic stroke risk compared to those with low IMT and high EDV (2.10; 95% confidence intervals, 1.35-3.26) after adjusting for age, sex, and traditional cardiovascular risk. CONCLUSIONS: Common carotid IMT and EDV jointly and independently predicted future ischemic stroke in this Taiwanese population. More prospective studies are required in various ethnic groups to understand the significance and implication of the current findings, particularly with respect to EDV.

Adults with late stage 3 chronic kidney disease are at high risk for prevalent silent brain infarction: a population-based study.

BACKGROUND AND PURPOSE: The close relationship between stroke and chronic kidney disease (CKD) has been well-documented. However, few studies have focused on silent brain infarction (SBI) in CKD. We investigated the prevalence of SBI in different stages of CKD. METHODS: We included 1312 participants aged 30 to 93 years who came from either a random sample of residents or from a group of physically examined subjects in the same community. Basic information, clinical evaluations, laboratory tests, and MRI images were assessed. Subjects were divided into groups 1, 2, 3a, and 3b, corresponding to the estimated glomerular filtration rate (eGFR) levels of ≥ 90.0, 60.0 to 89.9, 45.0 to 59.9, and 30.0 to 44.9 mL/min/1.73 m². RESULTS: The crude prevalence was 4.7%: 2.6% (20 of 759 subjects) in group 1; 6.3% (32 of 506) in group 2; 12.9% (4 of 31) in group 3a; and 37.5% (6 of 16) in group 3b (P<0.001). Additionally, SBI also correlated with age, male sex, hypertension, diabetes, moderate carotid plaque, higher blood pressures, obesity, and levels of triglyceride, high-density lipoprotein cholesterol, high-sensitivity C-reactive protein, and uric acid (all P<0.05). The effects for SBI risk in each eGFR group versus group 1 did not increase except for group 3b (OR, 9.34; P<0.001). CONCLUSIONS: A close association exists between SBI and eGFR. We have found a significant increase in prevalence of SBI when eGFR is between 30.0 and 44.9 mL/min/1.73 m². Adults with late stage 3 CKD are at high risk for prevalent SBI.

Assessment of Sarcopenia and Obesity in Patients with Myasthenia Gravis Using Dual-Energy X-ray Absorptiometry: A Cross-Sectional Study.

Sarcopenia and obesity can negatively impact quality of life and cause chronic fragility, and are associated with neuromuscular diseases, including myasthenia gravis (MG). The long-term consequences of body composition changes in chronic MG remain unknown; we therefore evaluated changes in body composition, including sarcopenia, obesity, lean body mass, and the prevalence of sarcopenic obesity in patients. In this cross-sectional study, 35 patients with MG (mean age: 56.1 years) and 175 matched controls were enrolled. Body fat mass and skeletal muscle mass were measured using whole body dual-energy X-ray absorptiometry. Patients with MG exhibited a higher prevalence of obesity and higher android adiposity and total body fat percentage than those of controls. Although the prevalence of sarcopenia and sarcopenic obesity did not increase with age, there was a decrease in arm and android muscle mass in patients with MG compared with controls. Lower muscle mass percentages were correlated with increased age and MG severity, but not with corticosteroid use. Thus, MG is associated with increased risk for obesity and decreased muscle mass with aging, regardless of corticosteroid use. Therefore, accurate diagnosis of body composition changes in MG could facilitate the application of appropriate therapies to promote health, improve quality of life, and prevent fragility.

Changes in Physical Fitness and Body Composition Associated with Physical Exercise in Patients with Myasthenia Gravis: A Longitudinal Prospective Study.

There is a lack of guidelines for physical exercise in patients with myasthenia gravis (MG). A few pilot studies have shown that exercise can be safely applied to patients with MG. However, how physical exercise affects body composition, disease function, and disease severity remains unknown. In this prospective study, we enrolled 34 patients with MG with stable condition and evaluated the disease severity, physical fitness parameters, and body composition (measured using whole-body dual-energy X-ray absorptiometry (DXA)), before and after conducting a 24-week physical exercise regimen of aerobic and resistance strength training. The outcomes were measured by DXA, quantitative MG (QMG) score, quality of life score, handgrip strength and walking speed. During the training regimen, participants were free to decide how many exercise sessions per week and regularly reported their weekly exercise time. The physical exercise program was well tolerated by the participants, the parameters of the QMG score and handgrip strength improved, and participants' body composition did not change significantly. The high exercise group experienced greater deterioration in muscle mass in the arms, but exhibited a greater improvement in forced vital capacity, walking speed, and symptom severity. The group with low QMG scores improved more in terms of physical fitness, including walking speed. These findings indicate that physical exercise is well tolerated by patients with MG, and is accompanied by improved muscular and physical functions. We propose that physical exercise is safe, effective, and appropriate for patients with well-regulated MG.