411. Significance of a Known Epidemiological Link to a COVID-19 Index Case and Severity of COVID-19 Infection
Notice bibliographique
Résumé
Abstract Background Several factors have been associated with severity of COVID-19 disease, but there remains a paucity of data surrounding whether the nature of exposure is impactful. Evidence demonstrating the correlation between initial viral exposure dose and disease severity exists for many viral infections. Observational studies have suggested that the exposure context, which can be considered a proxy for magnitude of viral inoculum, may influence severity of COVID-19 infection. We aimed to assess whether having a known exposure, as a proxy for higher inoculum dose to COVID-19, was associated with more severe outcomes for individuals hospitalized with COVID-19. Methods We created a retrospective cohort of community-dwelling adults hospitalized for COVID-19 in south-central Ontario from April 1, 2020 - January 14, 2021. Individuals or next of kin were contacted to ascertain exposure history. The primary outcome was death, intensive care unit (ICU) admission, or mechanical ventilation (MV) within 30 days of admission. A multivariable logistic regression model was used to determine whether a known exposure was associated with worse outcomes. Results 1097 individuals with community acquired COVID-19 required hospitalization; of these, 942 (86%) had available exposure data. In this group, the median age was 65, 44% were women, 84% lived in a private residence, 59% had a frailty score (FS) of 1 – 3 while 40% had a FS of 4 – 9, and 28% had a known exposure. Overall, the primary outcome occurred in 368/942 (39%) patients. Having a known exposure was not associated with worse outcome (OR 1.14, 95% CI 0.84–1.54, p = 0.41). Male gender (OR 1.41, 95% CI 1.06–1.89; p = 0.018), age (OR 1.01/year, 95% CI 1.00–1.03, p = 0.03), frailty (OR 1.22/point, 95% CI 1.09–1.36, p = 0.001) and living with at least one other person (OR 1.57, 95% CI 1.09–2.28, p = 0.017) were all associated with death, ICU admission, or MV within 30 days of admission. Conclusion While having a known exposure to a person with COVID-19 was not associated with worse outcome, the identified increased severity of illness associated with cohabitation suggests context of exposure may have a role in disease severity. This data and future studies can be used to guide public health recommendations to not only minimize transmission, but severity of COVID-19 infection. 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 | 0,000 | 0,004 |
| 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 | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,000 |
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 ».