Notice bibliographique
Résumé
To the Editor: Drs. Sharif and Montgomery bring to our attention that the unintended consequences of heightened regulatory oversight are unfortunately having negative effects on patients and donors in the United Kingdom as well as the United States.1Sharif A, Montgomery RA. Regulating the risk-reward trade-off in transplantation [published online ahead of print 2019]. Am J Transplant. https://doi.org/10.1111/ajt.15882Google Scholar Personal communication with transplant professionals in other countries such as Canada, Brazil, India, and Mexico reveal that currently there is not as much concern for severe outcome regulations in all countries. The central theme of both Drs. Sharif and Montgomery’s letter and my original viewpoint is that the current oversight regulation has been shown to harm patients by decreasing the potential number of transplants performed in end-stage organ disease patients.1Sharif A, Montgomery RA. Regulating the risk-reward trade-off in transplantation [published online ahead of print 2019]. Am J Transplant. https://doi.org/10.1111/ajt.15882Google Scholar,2Andreoni KA. Now is the time for the Organ Procurement and Transplantation Network to change regulatory policy to effectively increase transplantation in the United States; Carpe Diem [published online ahead of print 2019]. Am J Transplant. https://doi.org/10.1111/ajt.15759Google Scholar The current push toward normative outcomes is a race by many centers to minimize their program’s exposure to risk of patient and graft loss. Drs. Sharif and Montgomery bring up the concept of developing new metrics that may include reducing mortality and organ discard. I both agree with this concept and am also concerned that most new metrics I have seen discussed have their own significant issues for negative influences on patients and programs. An even more disruptive concept may be to completely eliminate public “flagging” of transplant centers unless detailed Membership Professional and Standards Committee (MPSC) investigation finds there to be true patient outcome issues. Patient and graft outcomes will still be followed for safety concerns and regulatory public reporting. But reporting regulations do not define how a “flag” is determined and our current use of simple statistical difference has been shown to be too frequent and random with far too many programs “flagging” over short time periods. Our current system that myopically focuses on punishment of centers whose outcomes are “statistically” different from others appears to be based more on past paranoia than any actual harm to patients.3Schold JD Miller CM Henry ML et al.Evaluation of flagging criteria of United States kidney transplant center performance: how to best define outliers?.Transplantation. 2017; 101: 1373-1380Crossref PubMed Scopus (18) Google Scholar The MPSC would still be able to query centers with outcomes that they feel are not equivalent to the majority. But the removal of the “flag” would take both programmatic and personal negative pressure off transplant centers and their professionals. In simple terms, no other professional community has self-oversight, which deems one-third of their members underperformers in a 3-year period. Any quality professional would acknowledge that such a metric cannot be useful—and in fact, we now see how much real harm to patients this system has created. Transplant patients and professionals directly involved in delivering transplantation care need to drive the removal of these destructive current metrics and creation of useful ones that allow for increased transplantation and innovation in US transplant centers. A 1-year renal allograft deceased donor graft failure rate of 5.3%, down from 9.2% 10 years ago, is remarkable in a very ill patient population with a high prevalence of profound socioeconomic challenges. This outcome is even more spectacular when considering that death on the waiting list without transplant is nearly the same at 5.06% for all patients on the waiting list in 2018.42018 Annual Data Report. Scientific Registry of Transplant Recipients. http://srtr.transplant.hrsa.gov/annual_reports/Default.aspx. Accessed March 23, 2020.Google Scholar We have reached the point of perfection being the enemy of good for our transplant candidates both in the United States and unfortunately in other countries such as the United Kingdom.
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 | 0,008 | 0,069 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,004 | 0,006 |
| Communication savante | 0,007 | 0,007 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,019 | 0,032 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,006 |
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 ».