To achieve further risk stratification in hypertrophic cardiomyopathy (HCM) patients, we localized and quantified layer-specific LVM fibrosis on MRI in HCM patients using regional layer-specific peak longitudinal strain (PLS) and peak circumferential strain (PCS) in LV myocardium (LVM) on speckle tracking transthoracic echocardiography (TTE). A total of 18 HCM patients (14 males; 58 ± 17 years) underwent 1.5T-MRI and TTE. PLS and PCS in each layer of the LVM (endocardium, epicardium, and whole-layer myocardium) were calculated for 17 AHA-defined lesions. MRI assessment showed that fibrosis was classified as endocardial, epicardial, or whole-layer (= either or both of these). Regional PLS was smaller in fibrotic endocardial lesions than in non-fibrotic endocardial lesions (P = 0.004). To detect LV endocardial lesions with fibrosis, ROC curves of regional PLS revealed an area under the curve (AUC) of 0.609 and a best cut-off point of 13.5%, with sensitivity of 65.3% and specificity of 54.3%. Regional PLS was also smaller in fibrotic epicardial lesions than in non-fibrotic epicardial lesions (P < 0.001). To detect LV epicardial lesions with fibrosis, ROC curves of PLS revealed an AUC of 0.684 and a best cut-off point of 9.5%, with sensitivity of 73.5% and specificity of 55.5%. Using whole-layer myocardium analysis, PLS was smaller in fibrotic lesions than in non-fibrotic lesions (P < 0.001). To detect whole-layer LV lesions with fibrosis, ROC curves of regional PLS revealed an AUC of 0.674 and a best cut-off point of 12.5%, with sensitivity of 79.0% and specificity of 50.7%. There were no significant differences in PCS of LV myocardium (endocardium, epicardium, and whole-layer) between fibrotic and non-fibrotic lesions. Quantitative regional PLS but not PCS in LV endocardium, epicardium, and whole-layer myocardium provides useful non-invasive information for layer-specific localization of fibrosis in HCM patients.
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http://dx.doi.org/10.1536/ihj.17-208 | DOI Listing |
Front Endocrinol (Lausanne)
January 2025
Department of Pediatrics, Hainan Medical University School of Pediatrics, Hainan Women and Children's Medical Center, Haikou, Hainan, China.
Background And Objective: The incidence of central precocious puberty (CPP) in girls increased significantly during the COVID-19 pandemic. This study aimed to explore the impact of perfluorinated endocrine disruptors on CPP through metabolomics analysis in girls from Hainan Province, China.
Methods: Serum samples from 100 girls with CPP and 100 healthy controls were collected.
Background: The genetic determinants of peripartum depression (PPD) are not fully understood. Using a multi-polygenic score approach, we characterized the relationship between genome-wide information and the history of PPD in patients with mood disorders, with the hypothesis that multiple polygenic risk scores (PRSs) could potentially influence the development of PPD.
Methods: We calculated 341 PRSs for 178 parous mood disorder inpatients affected by major depressive disorder (MDD) or bipolar disorder (BD) with ( = 62) and without ( = 116) a history of PPD.
BMC Public Health
January 2025
School of Psychology, Guizhou Normal University, Guiyang, China.
Background: Internet addiction is typically linked with a variety of psychological and behavioral problems, the prevalence of Internet addiction among Chinese college students was higher than that of the general population.
Objective: The present study aimed to test the mediating and moderating effects of socioeconomic status (SES), loneliness, alienation and grade on Internet addiction among Chinese college students.
Methods: Total of 496 college students were studied, partial least square structural equation modeling (PLS-SEM) was conducted to analyze the obtained data.
BMC Health Serv Res
January 2025
Department of Information Technology, Faculty of Information Technology, University of Moratuwa, Moratuwa, Sri Lanka.
The deployment of Health Information Systems (HIS) in Sri Lanka has been low in adoption compared to developed countries. There has been a dearth of studies to identify the factors that improve the adoption of HIS in developing countries. Thus, this study investigates the factors influencing the acceptance of HIS among public healthcare staff.
View Article and Find Full Text PDFBMC Psychol
January 2025
Universidad Nacional de Trujillo, Trujillo, Perú.
Background: In recent years, the adoption of artificial intelligence (AI) has become increasingly relevant in various sectors, including higher education. This study investigates the psychosocial factors influencing AI adoption among Peruvian university students and uses an extended UTAUT2 model to examine various constructs that may impact AI acceptance and use.
Method: This study employed a quantitative approach with a survey-based design.
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