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Mounting evidence indicates the worsening of maternal mental health conditions during the COVID-19 pandemic. Mental health conditions are the leading cause of preventable death during the perinatal and postpartum periods. Our study sought to detect space-time patterns in the distribution of maternal mental health conditions in pregnant women before (2016-2019) and during (2020-2021) the COVID-19 pandemic in North Carolina, USA. Using the space-time Poisson model in SaTScan, we performed univariate and multivariate cluster analysis of emergency department (ED) visits for perinatal mood and anxiety disorders (PMAD), severe mental illness (SMI), maternal mental disorders of pregnancy (MDP), suicidal thoughts, and suicide attempts during the pre-pandemic and pandemic periods. Clusters were adjusted for age, race, and insurance type. Significant multivariate and univariate PMAD, SMI, and MDP clustering persisted across both periods in North Carolina, while univariate clustering for both suicide outcomes decreased during the pandemic. Local relative risk (RR) for all conditions increased drastically in select locations. The number of zip code tabulation areas (ZCTAs) included in clusters decreased, while the proportion of urban locations included in clusters increased for non-suicide outcomes. Average yearly case counts for all maternal mental health outcomes increased during the pandemic. Results provide contextual and spatial information concerning at-risk maternal populations with a high burden of perinatal mental health disorders before and during the pandemic and emphasize the necessity of urgent and targeted expansion of mental health resources in select communities.
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http://dx.doi.org/10.1016/j.healthplace.2024.103307 | DOI Listing |
Hum Brain Mapp
September 2025
Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, Georgia, USA.
Investigating neuroimaging data to identify brain-based markers of mental illnesses has gained significant attention. Nevertheless, these endeavors encounter challenges arising from a reliance on symptoms and self-report assessments in making an initial diagnosis. The absence of biological data to delineate nosological categories hinders the provision of additional neurobiological insights into these disorders.
View Article and Find Full Text PDFInt J Dermatol
September 2025
Department of Dermatology, Emory University School of Medicine, Atlanta, Georgia, USA.
Stroke
September 2025
Brain Language Laboratory, Freie Universität Berlin, Germany (A.-T.P.J., M.R.O., A.S., F.P.).
Background: Intensive language-action therapy treats language deficits and depressive symptoms in chronic poststroke aphasia, yet the underlying neural mechanisms remain underexplored. Long-range temporal correlations (LRTCs) in blood oxygenation level-dependent signals indicate persistence in brain activity patterns and may relate to learning and levels of depression. This observational study investigates blood oxygenation level-dependent LRTC changes alongside therapy-induced language and mood improvements in perisylvian and domain-general brain areas.
View Article and Find Full Text PDFStroke
September 2025
Department of Medicine, University of Melbourne, Parkville, Victoria, Australia. (V.Y., B.C.V.C., L.C., L.O., M.W.P.).
Background: To assess the efficacy and safety of tenecteplase in patients presenting within 24 hours of symptom onset with a large vessel occlusion and target mismatch on perfusion computed tomography.
Methods: ETERNAL-LVO was a prospective, randomized, open-label, blinded end point, phase 3, superiority trial where adult participants with a large vessel occlusion, presenting within 24 hours of onset with salvageable tissue on computed tomography perfusion, were randomized to tenecteplase 0.25 mg/kg or standard care across 11 primary and comprehensive stroke centers in Australia.