Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.
RevueJournal of Clinical and Translational Science · 2024
Typearticle
Langueen
DomaineHealth Professions
ThématiqueFood Security and Health in Diverse Populations
Établissements canadiensSimon Fraser University
Organismes subventionnairesNational Center for Advancing Translational SciencesNational Institute of Environmental Health SciencesNational Institute of Allergy and Infectious DiseasesNational Institute of Mental HealthClinical and Translational Science Center, University of New MexicoClinical and Translational Science Institute, Boston UniversityCenter for Clinical and Translational Sciences, University of Texas Health Science Center at HoustonInstitute for Integration of Medicine and ScienceCenter for Clinical and Translational Science, Mayo ClinicColorado Clinical and Translational Sciences InstituteCenter for Clinical and Translational Science, University of MassachusettsUniversity of Colorado DenverLeonard M. Miller School of MedicineUniversity of California, IrvineUniversity of North Carolina at Chapel HillOregon Clinical and Translational Research InstituteWeill Cornell Medical CollegeClinical and Translational Science Institute, University of FloridaUniversity of Illinois at Urbana-ChampaignUniversity of Oklahoma Health Sciences CenterNational Institutes of HealthUniversity of California, DavisStony Brook UniversityOchsner HealthUniversity of California, San FranciscoLouisiana Clinical and Translational Science CenterGeorgia Clinical and Translational Science AllianceChildren's National HospitalVanderbilt University Medical CenterTranslational Research Institute, University of Arkansas for Medical SciencesNorthShore University HealthSystemUniversity of Texas Health Science Center at HoustonYale Center for Clinical Investigation, Yale School of MedicineMedStar Health Research InstituteRutgers, The State University of New JerseySouthern California Clinical and Translational Science InstituteUniversity of RochesterAurora Health CareUniversity of MiamiUniversity of South CarolinaMontana State UniversityNYU Langone Medical CenterDartmouth CollegeInstitute for Clinical and Translational Research, University of Wisconsin, MadisonPennsylvania State UniversityVanderbilt Institute for Clinical and Translational ResearchUniversity of CincinnatiGeorgetown UniversityInstitute of Clinical and Translational SciencesWake Forest Clinical and Translational Science Institute, Wake Forest School of MedicineGeorgetown-Howard Universities Center for Clinical and Translational ScienceInstitute for Translational Medicine and TherapeuticsUniversity of MichiganUniversity of Southern CaliforniaHarvard CatalystUniversity of OklahomaSchool of Medicine, Indiana UniversityWashington University in St. LouisPenn State Clinical and Translational Science InstituteCase Western Reserve UniversityUniversity of MinnesotaUniversity of California, San DiegoJohns Hopkins UniversityUniversity of California, Los AngelesBill and Melinda Gates FoundationUniversity of WashingtonMichigan Institute for Clinical and Health ResearchUniversity of UtahChildren's Hospital of PhiladelphiaUniversity of PennsylvaniaGeorge Washington UniversityNorthwestern UniversityVanderbilt UniversityAccelerated Innovation Research Initiative Turning Top Science and Ideas into High-Impact ValuesUniversity of ChicagoIrving Medical Center, Columbia UniversityVirginia Commonwealth UniversityTulane UniversityBrown UniversityRush UniversityCincinnati Children's Hospital Medical CenterUniversity of Wisconsin-MadisonYale UniversityLoyola University ChicagoOhio State UniversityWake Forest UniversityCenter for Clinical and Translational ResearchEmory UniversityUniversity of Texas Medical BranchWest Virginia Clinical and Translational Science InstituteUniversity of Nebraska Medical CenterChildren's Hospital ColoradoInstitute of Translational Health SciencesTufts Medical CenterWest Virginia UniversityCarilion Clinic
Mots-clésCoronavirus disease 2019 (COVID-19)Ethnic group2019-20 coronavirus outbreakHealth equitySevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)PandemicCohortMedicineCohort studyGerontologyHuman immunodeficiency virus (HIV)Social distanceDemographyPublic healthFamily medicineVirologySociologyDiseaseOutbreakNursing
Résumé
récupéré en direct d'OpenAlexBackground: Leveraging the National COVID-19 Cohort Collaborative (N3C), a nationally sampled electronic health records repository, we explored associations between individual-level social determinants of health (SDoH) and COVID-19-related hospitalizations among racialized minority people with human immunodeficiency virus (HIV) (PWH), who have been historically adversely affected by SDoH. Methods: We retrospectively studied PWH and people without HIV (PWoH) using N3C data from January 2020 to November 2023. We evaluated SDoH variables across three domains in the Healthy People 2030 framework: (1) healthcare access, (2) economic stability, and (3) social cohesion with our primary outcome, COVID-19-related hospitalization. We conducted hierarchically nested additive and adjusted mixed-effects logistic regression models, stratifying by HIV status and race/ethnicity groups, accounting for age, sex, comorbidities, and data partners. Results: Our analytic sample included 280,441 individuals from 24 data partner sites, where 3,291 (1.17%) were PWH, with racialized minority PWH having higher proportions of adverse SDoH exposures than racialized minority PWoH. COVID-19-related hospitalizations occurred in 11.23% of all individuals (9.17% among PWH, 11.26% among PWoH). In our initial additive modeling, we observed that all three SDoH domains were significantly associated with hospitalizations, even with progressive adjustments (adjusted odds ratios [aOR] range 1.36-1.97). Subsequently, our HIV-stratified analyses indicated economic instability was associated with hospitalization in both PWH and PWoH (aOR range 1.35-1.48). Lastly, our fully adjusted, race/ethnicity-stratified analysis, indicated access to healthcare issues was associated with hospitalization across various racialized groups (aOR range 1.36-2.00). Conclusion: Our study underscores the importance of assessing individual-level SDoH variables to unravel the complex interplay of these factors for racialized minority groups.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
score de la tête « metaresearch » (Codex)0,016
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesÉtudes des sciences et des technologies
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,039
Score d'incertitude au seuil0,998
Scores Codex et Gemma par catégorie
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
Tête enseignante Opus0,436
Tête enseignante GPT0,574
Écart entre enseignants0,138 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle
