MétaCan
Menu
← Retour à la cohorte
Enregistrement W3009514716

GRAFT - Generic Rating of Allograft Function Post Transplant

2020· dissertation· en· W3009514716 sur OpenAlexfundno aff
Farid Foroutan

Notice bibliographique

RevueMacSphere (McMaster University) · 2020
Typedissertation
Langueen
DomaineMedicine
ThématiqueAdvanced MRI Techniques and Applications
Établissements canadiensnon disponible
Organismes subventionnairesCanadian Institutes of Health Research
Mots-clésMedicineInternal medicine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background Research on the optimal management of deceased organ donors poses unique challenges including the fact that one deceased donor may provide up to 8 organs for transplantation. Measuring the post-transplant function of these organs – good or bad – represents an attractive way of deciding whether treatment of deceased donors is working well, or not so well. Function, however, is organ-specific. Therefore, to conduct the most efficient and informative research on deceased donor management, we need an outcome measure that works well in all organs. The new outcome measure is called Generic Rating of Allograft Function post-Transplantation (GRAFT). Methods In this thesis, I highlight the methods for developing the cardiac-specific version of the GRAFT instrument. The same methods, however, have and will be applied to other organ-specific versions. The work comprised various study designs and developed novel research tools, all of which have advanced the development of the GRAFT instrument. At first, we developed a simple conceptualization for the instrument. Through regular consultation with research methodologists, biostatisticians and clinical experts, we refined the fundamental conceptualization and then refined the generic instrument, itself. One key concept is that GRAFT ratings should correlate with one-year graft function. To maximize its utility, I developed a heart--specific guide for applying GRAFT in future studies, and other organ-specific guides are underway. Specifically, we developed these guides by identifying the most robust predictors of one-year graft function through the conduct of organ-specific systematic reviews and meta-analyses of prognostic factors. The evidence from these reviews, in consultation with a focus group of organ-specific transplant physicians, lead to refinements of our guides. We subsequently conducted a mixed-methods user testing to assess reliability and usability of the organ-specific guides. In appraising the evidence informing the guides, we developed GRADE guidance and a novel absolute risk calculator to assess our certainty in the body of evidence on prognostic factors informing our guides. Results We developed a 6-point generic rating instrument for classification of graft function to be applied post-transplant across all major solid organs. We designed GRAFT to be applied at the time of discharge, 1-month post-transplant, or at the time of death (whichever occurs first). We classify function as 1) normal, 2A) impaired but likely to gain normal function, 2B) impaired and unlikely to gain normal function, 3A) severely impaired but likely to gain some function, 3B) severely impaired and unlikely to gain some function, and 4) irreversible graft failure. Clinical expert collaborators for each organ type confirmed face validity of the GRAFT instrument. For all organs, we identified a number of prognostic factors that can guide users in classifying organ function post-transplant. In consultation with clinical experts, we determined that the most important factor is graft function as measured by left ventricular ejection fraction (LVEF) or right atrial pressure (RAP). Due to limitations with the quality and quantity of the evidence, however, the heart transplant experts did not rely on the results of their organ group’s systematic review. In turn, we conducted a retrospective cohort study to calculate the best estimate of association between LVEF, RAP, and overall mortality post heart transplant. For the cardiac version of GRAFT, user testing demonstrated high reliability (Kappa of 0.87, 95% CI 0.62 – 1.00) and acceptable usability (system usability score of 75, inter-quartile range of 72.5 – 80). In the process, we developed and published GRADE guidance for assessing certainty in the body of evidence addressing prognostic factors and devised a calculator to transform relative effect of each prognostic factor to absolute risks (http://hiru.mcmaster.ca/AbsoluteRiskCalculator/). Conclusion In this thesis, I advanced the development of an innovative generic instrument for the classification of graft function specifically for the purpose of application in clinical trials of deceased donor interventions. This work is ongoing, but very advanced for heart-specific components, for which I have ensured face validity, and demonstrated reliability and usability. The GRAFT instrument may better facilitate the conduct of future research to improve care of deceased organ donors with a view to improving quality and quantity of organs for transplantation.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,022
score de la tête « metaresearch » (Gemma)0,053
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,022
Score d'incertitude au seuil0,114

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0220,053
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,003
Bibliométrie0,0030,004
Études des sciences et des technologies0,0000,002
Communication savante0,0020,001
Science ouverte0,0020,001
Intégrité de la recherche0,0010,002
Charge utile insuffisante (le modèle a refusé de juger)0,0060,001

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.

Tête enseignante Opus0,014
Tête enseignante GPT0,231
Écart entre enseignants0,216 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2020
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueMacSphere (McMaster University)→Même sujetAdvanced MRI Techniques and Applications→Travaux en français237 207→