Organ Transplantation in Australia
Notice bibliographique
Résumé
We agree with the authors about the successes of organ transplantation in Australia.1 However, we would like to highlight the lack of access to kidney transplantation and insufficient progress in maximizing graft survival for Indigenous Australians. Indigenous Australians have at least 6 times the age-standardized incidence of end-stage kidney disease requiring renal replacement therapy as non-Indigenous Australians. Among adults aged 25 to 64 years and people from remote areas, rates are up to 15 times higher. Although constituting only 3.0% of the Australian population, over 1 in 10 patients commencing renal replacement therapy each year in Australia are Indigenous. At the end of 2015, 1647 (13.2%) of 12 461 patients receiving dialysis treatment in Australia were Indigenous; in contrast, only 241 (2.3%) of 10 551 patients with a functioning kidney transplant were Indigenous.2 Waitlisting for deceased donor kidney transplantation is uncommon for Indigenous patients. At the end of 2015, 1.9% of all Indigenous dialysis patients were on the waiting list, in contrast to 9.5% of non-Indigenous patients.2 This leads to lower transplantation rates. When all else is equal, Indigenous Australians have a quarter the chance of non-Indigenous patients of receiving a kidney transplant, with rates broadly like those in United States, Canada, and New Zealand.3 Indigenous patients understand the potential advantages of kidney transplantation and want access to this treatment modality, but concerns among kidney specialists about poorer outcomes for Indigenous Australian patients compared with non-Indigenous patients appear to be a major reason for nonreferral for deceased donor waitlisting.4 Posttransplantation outcomes for Indigenous Australians have indeed been worse than those for non-Indigenous Australians. Analysis of national registry data shows that Indigenous kidney transplant recipients, after adjustment for age and comorbidity, had almost twice the risk of death of Indigenous recipients between 2000 and 2012, and a 60% increased chance of losing a kidney transplant.5 Unlike non-Indigenous kidney transplant recipients (in whom cardiac and cancer causes predominate), and in contrast with widespread perceptions that immunosuppressive medication noncompliance is the major problem among Indigenous patients,4 infection has been the dominant cause of death or kidney transplant loss. However, in the presence of inequity in access to kidney transplantation, is it appropriate to adopt a predominantly utilitarian approach to decisions regarding waitlisting? Rather than comparing Indigenous and non-Indigenous transplant outcomes, it would appear fairer to compare the risks and benefits of transplant versus remaining on dialysis for Indigenous patients. National coordination to improve outcomes for Indigenous kidney transplant recipients (involving shared approaches to data collection, immunosuppression, monitoring, and infection prophylaxis for the small number currently transplanted) has been suggested by us as a stepping stone to improved access to the waiting list, but has proven challenging to implement. The Australian transplant community has been capable of achieving incremental but ultimately large improvements in outcome over the last 45 years. Without targeted efforts, Australians will continue to experience 2 tiers of end-stage kidney disease treatment outcomes: among the best in the world for non-Indigenous patients, and something substantially less than that for Indigenous Australians.
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 | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,002 | 0,002 |
| Science ouverte | 0,001 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,025 | 0,003 |
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 ».