Machine learning for predicting severe dengue in Puerto Rico by Zachary J. Madewell, Dania M. Rodriguez, Maile B. Thayer, Vanessa Rivera-Amill, Gabriela Paz-Bailey, Laura E. Adams, Joshua M. Wong

“…Methods We analyzed data from Puerto Rico’s Sentinel Enhanced Dengue Surveillance System (May 2012–August 2024), using 40 clinical, demographic, and laboratory variables. Nine ML models, including Decision Trees, K-Nearest Neighbors, Naïve Bayes, Support Vector Machines, Artificial Neural Networks, AdaBoost, CatBoost, LightGBM, and XGBoost, were trained using fivefold cross-validation and evaluated with area under the receiver operating characteristic curve (AUC-ROC), sensitivity, and specificity. …”
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Evaluation of bone mineral density and its influencing factors in patients infected with HIV under antiretroviral therapy by Alireza Azarboo, Mahboobeh Hemmatabadi, Noushin Fahimfar, Zahra Faghihi, SeyedAhmad SeyedAlinaghi, Nooshin Shirzad, Ladan Abbasian

“…Pearson’s correlation coefficients identified relationships between BMD and demographic and laboratory predictors. Univariable and multivariable logistic regression models assessed predictors of low lumbar BMD. …”
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Safety evaluation of medroxyprogesterone acetate: a pharmacovigilance analysis using FDA adverse event reporting system data by Luyang Su, Ren Xu, Yanan Ren, Shixia Zhao, Weilan Liu, Zeqing Du

“…Unforeseen significant AEs such as unintended pregnancy (n = 623; ROR, 6.65; ROR025, 6.1; χ2, 2,482.38; PRR, 6.41; EBGM, 5.69; EBGM05, 5.29), bone pain (n = 35; ROR, 13.78; ROR025, 9.4; χ2, 311.2; PRR, 13.75; EBGM, 10.59; EBGM05, 7.69), gait disturbance (n = 34; ROR, 2.82; ROR025, 1.99; χ2, 37.31; PRR, 2.88; EBGM, 2.7; EBGM05, 2.02), dental caries (n = 15; ROR, 23.16; ROR025, 12.32; χ2, 204.26; PRR, 23.14; EBGM, 15.23; EBGM05, 8.98), decrease in blood pressure (n = 15; ROR, 3.88; ROR025, 2.29; χ2, 29.35; PRR, 3.88; EBGM, 3.63; EBGM05, 2.33), and osteonecrosis (n = 9; ROR, 23.44; ROR025, 10.36; χ2, 123.67; PRR, 23.43; EBGM, 15.35; EBGM05, 7.75) were identified as AEs that were not previously outlined in the prescribing information of the medication.ConclusionOur findings align with clinical observations, highlighting the emergence of previously unreported AE signals associated with MPA and their demographic and TTO characteristics. Further pharmaco-epidemiological studies are required to substantiate these observations.…”
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Causes and determinants of infant mortality using verbal autopsy and social autopsy methods in a rural population of Odisha: a community-based matched case-control study by Amit Kumar Satapathy, Arvind Kumar Singh, Priyamadhaba Behera, Debkumar Pal, Abhisek Mishra

“…We used the prevalidated International Network for the Demographic Evaluation of Population and Their Health tool to assess three delays and pathways of care related to infant deaths.Results Most infant deaths (70%) happened during the first day of life, and almost 50% of neonatal deaths occurred during the first week of life. …”
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A cohort study of serum 25-hydroxyvitamin D levels and the risk of hyperlipidaemia in adults by Zi-yue Liu, Sha Liu, Xue Yao, Chun-yang Wang, Yunhao Song, Yan-ming Bi, Jin-Xiu Wang, Yang Li, Ta-la Shi, Wei Mi, Caiyun Chen, Zhi-Yong Hu

“…The relationship between demographic characteristics and the incidence of hyperlipidemia among the study participants was explored.ResultsA total of 1,210 participants were included in this study, with 43.80% being male. …”
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Patterns of general and abdominal obesity and their association with hypertension control in the iranian hypertensive population: insights from a nationwide study by Fataneh Esmaeili, Keyvan Karimi, Samaneh Akbarpour, Mohammadreza Naderian, Shirin Djalalinia, Ozra Tabatabaei-Malazy, Ali Golestani, Nazila Rezaei

“…Multivariate logistic regression models were performed to determine the association between different obesity patterns and uncontrolled HTN, adjusting for confounders including demographic variables, lifestyle factors, and history of metabolic abnormalities. …”
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Birds of a feather? Mis- and dis-information on the social media platform X related to avian influenza by Lauren N. Cooper, Marlon I. Diaz, John J. Hanna, Zachary M. Most, Christoph U. Lehmann, Richard J. Medford

“…Using topic modeling, emotion, sentiment, and user demographic analyses, we were able to describe the population and the HPAI-related topics that users discussed. …”
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Genome assembly of an endemic butterfly (Minois aurata) shed light on the genetic mechanisms underlying ecological adaptation to arid valley habitat by Wenqian Hu, Yi Wang, Xiaoxiao Chen, Jialong Huang, Jingge Kuang, Lei Wang, Kangshan Mao, Liang Dou

“…We also identified 234 positive selected genes in M. aurata, some of which are related to compound eye photoreceptor development, osmotic stress, and light stimulus response. Demographic analysis indicated that the effective population size of M. aurata decreased around 0.4 and 0.04 million years ago, respectively, coinciding with the localized sub-glaciation. …”
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Eating difficulties among Nigerian community-dwelling stroke survivors: prevalence, correlates, and association with quality of life by Adekola B. Ademoyegun, Adebukola G. Ibitoye, Wasiu A. Rasaq, Oluwafunmilayo A. Adeniyi, David O. Fabuluje, Israel A. Ojo, Taofeek O. Awotidebe, Chidozie E. Mbada

“…The Minimal Eating Observation Form– version II and WHOQOL-BREF were used to collect data on EDs and QoL respectively. Socio-demographic, stroke-related, and clinical characteristics of patients were assessed using structured questionnaires. …”
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Transfer from long-term care to acute care and risk of new permanent cognitive or physical disability among long-term care residents in Canada: protocol for a retrospective cohort... by Sharon Kaasalainen, Daniel I McIsaac, Steven Hawken, Daniel Kobewka, Peter Tanuseputro, Amy Hsu, Robert Talarico, Colleen Webber, Ramtin Hakimjavadi, Celeste Fung, Mary M Scott, Doug Manuel, Christina Y Yin, Jackie Kierulf, Frank Molnar, Sandy Shamon, Aliza Moledina

“…We will use health administrative data from the Continuing Care Reporting System (CCRS), National Ambulatory Care Reporting System (NACRS) and Registered Persons Databases (RPDB), which include data on emergency department visits, hospitalisations, demographic information and mortality. All participants will be followed until 31 March 2023. …”
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Work–health–personal life conflicts in naive patients with chronic hepatitis B receiving initial treatment in China: a qualitative study by Li Zhang, Ying Chen, Ying Li, Hongmei Wang, Lin Zhu, Xiaoyang Lu, Yingjing Zheng, Donald Patrick, Fengjiao Xu, Mengna Song, Xiao Cheng, Boyan Chen

“…Semistructured interviews were used to collect the experience of work–health–personal life conflicts (WHPLCs), and a brief questionnaire was used to collect demographic and clinical information. SPSS V.21.0 was used for descriptive analysis and Dedoose (V.7.5.9) was used to code and analyse interview transcripts. …”
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Alterations of interhemispheric functional connectivity in patients with hypertensive retinopathy using voxel-mirrored homotopic connectivity: a resting state fMRI study by Xue-Lin Wang, Yu Chen, Jin-Yu Hu, Hong Wei, Qian Ling, Liang-Qi He, Cheng Chen, Yi-Xin Wang, Yan-Mei Zeng, Xiao-Yu Wang, Qian-Min Ge, Xu Chen, Yi Shao

“…Differences in the demographic and clinical characteristics of the HR and HC groups were analyzed by independent sample t-tests. …”
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A Community-Based Intervention for Mental Health and Wellbeing in Pregnancy and Postpartum: One Healthy Start Site’s Story by Sampson M, Xu W, York FN, Roberson J

“…Using data from the standardized HS tools (required for all sites), aggregate demographic data and screening results of depression and interpersonal violence were assessed. …”
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Association of social frailty, sarcopenia, and oral frailty with depressive symptoms in Chinese older adults: a cross-sectional study by Yuanhao Sun, Huan Liu, Xiangdong Li, Lin Zhang, Wenwen Xu, Hairong liu, Ting Yuan

“…Methods This research utilized a cross-sectional design and used convenience sampling to select participants from Anhui Province, China. Demographic questionnaire, SARC-F (Strength, Assistance with walking, Rising from a chair, Climbing stairs, and Falls), OFI-8 (Oral Frailty Index-8), the HALFT (Help, Participation, Loneliness, Financial, Talk) scale, and PHQ-9 (Patient Health Questionnaire-9) were used to conduct the survey. …”
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Development of an Integrated Model of Planning and Management in Free Zones with an Emphasis on Environmental Pressures by Mohammad Javad Amiri, Vahid Moghaddamzadeh, Gholamreza Nabi Bidhendi

“…The research surveyed a demographic comprising 290 managers, officials, and decision-making experts affiliated with the Aras Free Zone. …”
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April 15th war and hemodialysis patients in Sudan: a cross-sectional study by Malaz Hassan Dafaalla Idrees, Moez Mohammed Ibrahim Bashir, Balqees Abdeen Ahmed Mohamed, Amal Essam Ali Ahmed, Hamid Mohieldin Mohamed Abdalla, Kamil Mirghani Ali Shaaban

“…The questionnaire encompassed five primary domains: demographic data, healthcare access (Levesque’s Conceptual Framework of Access), physical implications, psychological impact (Generalized Anxiety Disorder scale and Patient health questionnaire), and quality of life (Kidney disease quality of life 36 scales). …”
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Genetic insights into MIS-C Post-COVID-19 in Kuwaiti children: investigating monogenic factors by Mohammed Dashti, Hessa AlKandari, Hessa AlKandari, Md Zubbair Malik, Rasheeba Nizam, Sumi Elsa John, Sindhu Jacob, Arshad Channanath, Fouzeyah Othman, Safa Al-Sayed, Osama Al-Hindi, Mona Al-Mutari, Thangavel Alphonse Thanaraj, Fahd Al-Mulla

“…Recent studies suggest that genetic predispositions, particularly monogenic forms, could significantly influence the immune responses to SARS-CoV-2 in MIS-C.MethodsWe analysed 24 children under 12 years old, all of whom met the criteria provided by the World Health Organization, 2020 for MIS-C diagnosis, from the Paediatric COVID-19 Registry in Kuwait (PCR-Q8). Demographic and clinical data were collected from medical records, and exome sequencing was performed on the children and their parents to identify rare exonic variants. …”
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Prevalence and associated factors of multidimensional poverty among rural households in East Gojjam zone, Northern Ethiopia: a community-based cross-sectional study by Amare Wubishet Ayele, Yeshiwas Ewinetu, Asefa Delesho, Yirsie Alemayehu, Hayimro Edemealem

“…Conclusion Approximately 37% of rural household’s experience moderate to severe MP, and living standards dimension accounted for the largest contribution. Various socio-demographic, agro-ecological, and related factors have been identified to rural MP. …”
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Pemanfaatan Aplikasi Pengiriman Makanan Pasca Penurunan Level Pembatasan Kegiatan Masyarakat Akibat Covid-19 Di Indonesia by Wan Ahmad Gazali Kodri, Dwiza Riana, Sri Hadianti

“…The questionnaire consists of 17 demographic questions and 38 indicator questions. A Likert scale with five rating levels was used to evaluate the indicator questions. …”
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Trends and future predictions of chronic kidney disease due to diabetes mellitus type 2 attributable to dietary risks: insights based on GBD 2021 data by Ming Xu, Ming Xu, Hongxia Wei, Hongxia Wei, Dongqing Lv, Dongqing Lv, Yanhong Wei, Yanhong Wei, Ziang Liu, Ziang Liu, Yi Zhang, Yi Zhang, Yunfeng Liu, Yunfeng Liu, Yunfeng Liu

“…Geographic disparities in T2DM trends are evident, with the most significant increases in age-standardized mortality rates (ASMR) and age-standardized DALY rates (ASDR) observed in regions such as high-income North America and Central Latin America. Socio-demographic index (SDI) is negatively correlated with the CKD-T2DM burden attributable to dietary risk factors.ConclusionPublic health interventions that target dietary changes can significantly reduce the global burden of CKD-T2DM.…”
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