457. Low Rates of COVID-19 in a Vulnerable Population: Learning from Early and Decisive Public Health Policies
Notice bibliographique
Résumé
Abstract Background Disasters, including pandemics, disproportionately affect vulnerable populations. The Downtown Eastside (DTES) neighborhood of Vancouver has high prevalence of mental illness, substance use, infectious disease and homelessness. While studies have described clinical characteristics of COVID-19 patients in other centres worldwide, data is lacking on marginalized groups. We describe the clinical characteristics and outcomes of COVID-19 patients seen at two urban hospitals who care for the vulnerable population in the DTES of Vancouver, British Columbia (BC), Canada. Methods A retrospective chart review was conducted on all COVID-19 patients ≥19 years seen at either centre from January 1 to June 10, 2020. Descriptive statistics assessed demographics, comorbidities, presenting symptoms, laboratory values and outcomes, and were compared between subjects managed as inpatients (died vs. discharged) and outpatients. Results Of 71 COVID-19 subjects, mean age was 57y (SD 20); 36 (51%) were male. Time to presentation, symptoms and laboratory values were similar to other reports. 58 (82%) presented from the community, 3 (4%) from long-term care/rehabilitation centres, and 8 (11%) had no fixed address (NFA) or lived in the DTES. 45 (64%) had a known exposure, 20 (28%) were healthcare workers, 85% involved in direct patient care; 0/20 were admitted to hospital. Of the 8 NFA/DTES subjects, mean age was 46y (SD 13), 50% were male, 5 (63%) were admitted to hospital and all survived. Admitted subjects (n=34) were older (mean age 69 vs 46y, p< 0.001), 62% were male, and had more comorbidities (mean [SD] 3 [3] vs. 1 [2], p< 0.001). Eight (24%) died, 26 (76%) were discharged, 29% developed acute respiratory distress syndrome, 21% secondary infection, 18% renal failure, and 15% cardiac dysfunction. Of patients admitted to intensive care, 5/10 died. Conclusion Our results concur with other studies showing older age and comorbidities contribute to more severe COVID-19 disease. 64% of subjects had a known exposure, and only 11% had NFA/DTES residence. Given that there is no financial barrier to access healthcare in Canada and these hospitals serve our most vulnerable populations, our results may indicate that BC Public Health has done an effective job of tracking and limiting community spread of COVID-19. Disclosures All Authors: No reported disclosures
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.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,002 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».