Background: Whereas high body mass index (BMI) is reportedly a risk factor for cardiovascular events in Western countries, low BMI has been reported as a risk factor for cardiovascular death in Asia, including Japan. Although subarachnoid hemorrhage (SAH) is a highly fatal disease and common cause of disability, few cohort studies have examined the associations between BMI and SAH in Japan. This study investigated the associations between BMI and incidence of SAH using prospective data from Japanese community residents.
Methods: Data were analyzed from 12,490 participants in the Jichi Medical School Cohort Study. Participants were categorized into 5 BMI groups: ≤18.5, 18.6-21.9, 22.0-24.9, 25.0-29.9, and ≥30.0 kg/m. Multivariate-adjusted hazard ratios (HR) and 95% confidence intervals (CI) were calculated using Cox proportional hazard model with BMI of 22.0-24.9 kg/m as the reference category.
Results: During the mean follow-up period of 10.8 years, 55 participants (13 men, 42 women) experienced SAH. BMI ≥30.0 kg/m was associated with significantly higher risk for SAH (HR, 5.98; 95% CI, 2.25-15.87). BMI ≤18.5 kg/m showed a nonsignificant tendency toward high risk of SAH (HR, 2.51; 95% CI, .81-7.79).
Conclusions: High BMI was a significant risk factor for SAH. Lower BMI showed a nonsignificant tendency toward higher risk of SAH. Our results suggest a J-shaped association between BMI and risk of SAH incidence.
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http://dx.doi.org/10.1016/j.jstrokecerebrovasdis.2017.03.029 | DOI Listing |
BMC Infect Dis
January 2025
School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, India.
Background: Mpox is a viral zoonotic disease that has seen a resurgence in recent years, with outbreaks reaching beyond its traditional endemic zones in Central and West Africa to parts of Europe and North America. The relationship between human immunodeficiency virus (HIV) infection and mpox outcomes, particularly hospitalization rates, remains underexplored despite the known immunosuppressive effects of HIV. This systematic review and meta-analysis aimed to clarify the association between HIV infection and the likelihood of hospitalization in mpox cases.
View Article and Find Full Text PDFAging Clin Exp Res
January 2025
Centre for Precision Health, Edith Cowan University, Perth, WA, Australia.
Background: Inflammation and maladaptive immune mechanisms have been substantiated as integral components in the critical pathological processes of the injury cascade in ischemic stroke (IS). This study aimed to explore the associations between six systemic inflammatory indices and IS in a Chinese population.
Methods: This was a case-control study based on the retrospective review of electronic medical records from two hospitals in Shandong Province, China.
J Clin Hypertens (Greenwich)
January 2025
SR Sanjeevani Hospital, Siraha, Kalyanpur, Nepal.
Sex hormone-binding globulin (SHBG) regulates sex hormone availability and is influenced by metabolic factors. Variations in SHBG levels during pregnancy may affect the development of hypertensive disorders such as gestational hypertension (GH) and preeclampsia (PE). This systematic review and meta-analysis explores the potential of SHBG as a biomarker for predicting GH and PE.
View Article and Find Full Text PDFTranspl Int
January 2025
Mental Diseases Unit, Azienda Socio Sanitaria Territoriale Grande Ospedale Metropolitano Niguarda, Milan, Italy.
Patients with severe alcoholic hepatitis SAH may suffer of undiagnosed psychiatric illnesses, typically depression. Assessment of prevalence and potential impact of psychiatric disturbances on alcohol relapse after LT, were the main objectives of this study. One hundred consecutive patients with SAH from April 2016 to May 2023 were analyzed.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Neurosurgery, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Background: Delayed cerebral ischemia (DCI) is a primary contributor to death after subarachnoid hemorrhage (SAH), with significant incidence. Therefore, early determination of the risk of DCI is an urgent need. Machine learning (ML) has received much attention in clinical practice.
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