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Association between the hemoglobin A1c/High-density lipoprotein cholesterol ratio and stroke incidence: a prospective nationwide cohort study in China.
Lipids Health Dis
January 2025
Department of Neurosurgery, The Third Affiliated Hospital of Soochow University, Changzhou, Jiangsu, 213000, China.
Background: Stroke has emerged as an escalating public health challenge among middle-aged and older individuals in China, closely linked to glycolipid metabolic abnormalities. The Hemoglobin A1c/High-Density Lipoprotein Cholesterol (HbA1c/HDL-C) ratio, an integrated marker of glycolipid homeostasis, may serve as a novel predictor of stroke risk.
Methods: Our investigation utilized data from the China Health and Retirement Longitudinal Study cohort (2011-2018).
Predicting bullying victimization among adolescents using the risk and protective factor framework: a large-scale machine learning approach.
BMC Public Health
January 2025
Statistics, Brigham Young University, Provo, 84602, Utah, USA.
Background: Bullying, encompassing physical, psychological, social, or educational harm, affects approximately 1 in 20 United States teens aged 12-18. The prevalence and impact of bullying, including online bullying, necessitate a deeper understanding of risk and protective factors to enhance prevention efforts. This study investigated the key risk and protective factors most highly associated with adolescent bullying victimization.
View Article and Find Full Text PDFMachine Learning-Based predictive model for adolescent metabolic syndrome: Utilizing data from NHANES 2007-2016.
Sci Rep
January 2025
Department of Anesthesiology and Surgical Intensive Care Unit, Kunming Children's Hospital, Kunming, Yunnan, China.
Metabolic syndrome (Mets) in adolescents is a growing public health issue linked to obesity, hypertension, and insulin resistance, increasing risks of cardiovascular disease and mental health problems. Early detection and intervention are crucial but often hindered by complex diagnostic requirements. This study aims to develop a predictive model using NHANES data, excluding biochemical indicators, to provide a simple, cost-effective tool for large-scale, non-medical screening and early prevention of adolescent MetS.
View Article and Find Full Text PDFFecal microbiota transplantation to prevent acute graft-versus-host disease: pre-planned interim analysis of donor effect.
Nat Commun
January 2025
Clinical Research Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Gut microbiota disruptions after allogeneic hematopoietic cell transplantation (alloHCT) are associated with increased risk of acute graft-versus-host disease (aGVHD). We designed a randomized, double-blind placebo-controlled trial to test whether healthy-donor fecal microbiota transplantation (FMT) early after alloHCT reduces the incidence of severe aGVHD. Here, we report the results from the single-arm run-in phase which identified the best of 3 stool donors for the randomized phase.
View Article and Find Full Text PDF[Correlation between uterine volume and intrauterine adhesion: a propensity score matching analysis].
Zhonghua Fu Chan Ke Za Zhi
January 2025
Gynecological Minimally Invasive Center, Beijing Obstetrics and Gynecology Hospital, Capital Medical University, Beijing Maternal and Child Health Care Hospital, Beijing 100006, China.
To investigate the correlation between uterine volume and intrauterine adhesion (IUA). From June 2018 to November 2019, totally 7 007 patients who underwent hysteroscopy in outpatient operating rooms of Gynecological Minimally Invasive Center, Beijing Obstetrics and Gynecology Hospital were retrospectively analyzed Patients of reproductive age with IUA without uterine fibroids and adenomyosis were selected as IUA group, and patients of reproductive age without uterine fibroids and adenomyosis without IUA during the same period were selected as the control group. The propensity score matching (PSM) method was used to perform 1∶1 matching for the two groups of patients, matching variables included age, height, weight, body mass index (BMI), gravidity, parity, and number of abortion curettage.
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