Comments on “Proposed US Legislation to Pay Kidney Donors: Counter-productive and Against Global Ethical Standards”
Notice bibliographique
Résumé
In a recent article, Capron et al1 again decried consideration of a reward for kidney donation—in this case, a bill introduced in Congress (H.R.9275) to provide a tax credit to nondirected donors. Yet they accept that there is a shortage of kidneys, do not provide an alternative to increase donation, and, rather than providing a rational argument to make their point, engage in fearmongering, for example, that the bill, which proposes a government-regulated system, would be followed by a “slippery slope” leading to acceptance of individuals buying kidneys, and a competitive increase in price. To support their position, Capron et al provided misleading data, stating we do not need H.R.9275 because donation rates in the United States have risen from 4730 in 1999 to 6866 in 2019. However, they do not acknowledge that all of this increase occurred before 2002 (n = 6241); subsequently, rates have not changed (n = 6292 in 2023),2 and 6000–7000 living donors each year for the past 2 decades have not solved the organ shortage problem. The authors suggest that creating financial neutrality for donors will be sufficient to significantly increase donations. Yet in numerous countries where financial neutrality has been implemented (eg, in Canada, Europe), living donations have not increased and organ shortages continue. The authors state that if the bill is passed, related donors would be “reluctant to provide a kidney for free,” and that many patients would prefer a nondirected donor kidney rather than seeking a kidney from family or friends. However, they do not show why, other than a change from the status quo, this is a problem. If donation rates soar, all candidates benefit, and there will likely still continue to be an advantage—a shorter wait—for donations from family or friends. In addition, currently, 40% of related donors feel pressure (internal and/or external) to donate,3 which is something we think of as a negative when considering informed consent. We know that relatives of those with kidney failure are at risk for kidney failure. To date, Organ Procurement and Transplantation Network and other data suggest that a donor who is a first-degree relative of the recipient is at increased risk.4 Why insist relatives undertake this increased risk? While objecting to H.R.9275, the authors do not provide an alternative option to increase donation, thus accepting that thousands of approved candidates each year will die or become too sick to transplant.2 They argue that H.R.9275 places “personal choice and maximizing transplants above all other values.” There are many “values,” and these often conflict. The bill specifically places “personal choice” (ie, autonomy) and “maximizing transplants” (ie, saving lives) above the alternative—thousands of candidates on the waitlist dying or becoming too sick to transplant. While making their argument, the authors ignore that (1) numerous surveys show that the public favors incentives (reviewed in reference 5), (2) a survey of the ASTS anmembership supported incentives,6 and (3) a joint meeting on the topic by the AST and ASTS concluded that we should eliminate disincentives and move toward trials of incentives.7 Finally, the authors suggest the bill is against global ethical standards. There is no doubt that it is against some people’s standards. However, others worldwide (including many ethicists), especially in the context of the ongoing organ shortage and its consequences, have argued strongly that incentives should be considered.5,8,9
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 | 0,022 | 0,090 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,003 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,009 | 0,009 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,006 | 0,004 |
| Intégrité de la recherche | 0,109 | 0,075 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,009 |
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 ».