Nirmatrelvir-Ritonavir and COVID-19 Mortality and Hospitalization Among Patients With Vulnerability to COVID-19 Complications
Notice bibliographique
Résumé
Importance: Postmarket analysis of individuals who receive nirmatrelvir and ritonavir (Paxlovid [Pfizer]) is essential because they differ substantially from individuals included in published clinical trials. Objective: To examine the association of nirmatrelvir and ritonavir with prevention of death or admission to hospital in individuals with different risks of complications from COVID-19 infection. Design, Setting, and Participants: This is a cohort study of adult patients in British Columbia, Canada, between February 1, 2022, and February 3, 2023. Patients were eligible if they belonged to 1 of 4 higher-risk groups of individuals who received priority for COVID-19 vaccination. Two groups included clinically extremely vulnerable (CEV) people who were severely (CEV1) or moderately immunocompromised (CEV2). CEV3 individuals were not immunocompromised but had medical conditions associated with a high risk for complications from COVID-19. A fourth expanded eligibility (EXEL) group was added to allow wider access to nirmatrelvir and ritonavir for certain other higher-risk individuals who were not in a CEV group, such as those older than 70 years who were unvaccinated. Exposures: Patients with COVID-19 who received nirmatrelvir and ritonavir were matched to patients in the same vulnerability group; who were of the same sex, age, and propensity score for nirmatrelvir and ritonavir treatment; and who were also infected within 1 month of the individual treated with nirmatrelvir and ritonavir. Main Outcomes and Measures: The primary outcome was death from any cause or emergency hospitalization with COVID-19 within 28 days. Results: There were 6866 individuals included in the study, of whom 3888 (56.6%) were female and whose median (IQR) age was 70 (57-80) years. Compared with unexposed controls, treatment with nirmatrelvir and ritonavir was associated with statistically significant relative reductions in the primary outcome in the CEV1 group (560 patients; risk difference [RD], -2.5%, 95% CI, -4.8% to -0.2%) and the CEV2 group (2628 patients; RD, -1.7%; 95% CI, -2.9% to -0.5%). In the CEV3 group, the RD was -1.3%, but the findings were not statistically significant (2100 patients; 95% CI, -2.8% to 0.1%). In the EXEL group, treatment was associated with higher risk of the outcome (RD, 1.0%), but the findings were not statistically significant (1578 patients; 95% CI, -0.9% to 2.9%). Conclusions and Relevance: In this cohort study of 6866 individuals in British Columbia, nirmatrelvir and ritonavir treatment was associated with reduced risk of COVID-19 hospitalization or death in CEV individuals, with the greatest benefit observed in severely immunocompromised individuals. No reduction in the primary outcome was observed in lower-risk individuals, including those aged 70 years or older without serious comorbidities.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».