227.2: Organ donation recovery during the first two years of the covid-19 pandemic: a comparison of Canada with Australia, Spain, the United Kingdom, and the United States
Notice bibliographique
Résumé
Introduction: The COVID-19 pandemic challenged organ donation programs around the world, as many health systems shifted resources towards the surge of critically ill COVID-19 patients and limited donation and transplant activity. With signs of health system recovery becoming evident, the aim of this study is to compare organ donation rates between Canada, Australia, Spain, the United Kingdom (UK), and the United States (US) across three periods: pre-pandemic (2019), the first pandemic year (2020), and the second pandemic year (2021). Methods: Patients registered in the Canadian Organ Replacement Register who donated an organ that was utilized for transplantation in Canada between 2019 and 2021 were identified. For the same time period, aggregated donation data from Australia, Spain, UK and US were obtained from the Global Observatory on Donation and Transplantation. Values for deceased donors (DD) (including neurological determination of death (NDD) donors vs. donors after circulatory determination of death (DCD)) and living donors were compared between countries and across years to determine the impact of COVID-19 on organ donation activity. Results: Only the US did not experience a decrease in DD following the onset of COVID-19, instead increasing by 12% between 2019 and 2021. Australia, Canada, Spain, and the UK all experienced decreases in DD in the first year of the pandemic (-14%, -11%, -20%, -23%, respectively), and despite some improvements in Spain and the UK in 2021 (+7% for both compared to 2020), none of these four countries have recovered to pre-pandemic levels (Table 1). Canada and Spain experienced a greater decrease in NDD donors than DCD donors from 2019 to 2021 (Canada: -14% vs. -5%; Spain: -19% vs. -6%, respectively), while the opposite was true for Australia (decrease of -29% in DCD and -18% in NDD). The UK saw a similar level of decrease in both NDD and DCD levels (-18% and -16%, respectively). The only country to experience an increase was the US, with a +4% improvement in NDD donors and +39% improvement in DCD donors from 2019 to 2021 (Table 1).While total living donations in Australia, Canada, Spain, the UK, and the US were all lower in 2021 compared to 2019 (-15%, -3%, -9%, -28%, -11%, respectively) (Table 2), all five countries did experience an increase in living kidney donors in 2021 (+12%, +27%, +25%, +31%, +14%). Further, Canada increased the number of living liver donations in both the first (+14%) and second (+2%) year of the pandemic, while the US had more living liver donations in 2021 compared to 2019 (+10%) (Table 2).Conclusions: The COVID-19 pandemic impacted organ donation on a global scale. While signs of improvement are already apparent, donation recovery has been unique to each country. More detailed data such as number of eligible donors or rate of consent for donation during the pandemic will be required to understand the causes of these differences.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,003 | 0,006 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 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 ».