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Enregistrement W4229865766 · doi:10.1093/ndt/gfr469

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2011· article· en· W4229865766 sur OpenAlexaff
Michael Zappitelli, Stuart L. Goldstein

Notice bibliographique

RevueNephrology Dialysis Transplantation · 2011
Typearticle
Langueen
DomaineMedicine
ThématiqueAcute Kidney Injury Research
Établissements canadiensMcGill University Health Centre
Organismes subventionnairesnon disponible
Mots-clésMedicine

Résumé

récupéré en direct d'OpenAlex

Sir, We thank Dr Liborio for the thoughtful evaluation of acute kidney injury (AKI) definition in children. Indeed, the author is correct in noting that the relationship between estimated glomerular filtration rate (eGFR) and serum creatinine (SCr) is not quite linear; a ‘linear relationship’ is indirectly assumed by equivocating pRIFLE R, I and F AKI to AKIN Stages 1, 2 and 3 AKI, respectively. Rather, the GFR–SCr relationship is closer to that of a logarithmic curve. The author is also correct in noting that if we consider the pRIFLE definition as the ‘gold standard’ for defining AKI, the AKIN definition would misclassify all patients with a 33–49% SCr rise as not having AKI (when they do by pRIFLE) and would misclassify all patients with a three to four times SCr rise from baseline as having AKI (when they do not by pRIFLE). However, several things must be considered, including issues related to physiology of acute illness and the history of AKI definition, which may question the extent to which the pRIFLE definition really is a better ‘gold standard’ than the AKIN definition is. Assuming that pRIFLE is a ‘better’ AKI definition than the AKIN also assumes that the relationship between SCr and eGFR is similar in hospitalized patients as it is in stable, non-hospitalized patients, from which these equations were derived. Given the fluid shifts, recent changes in nutrition status in chronically ill patients, medication provided and other factors, it is quite likely that this is not the case. However, a benefit of the pRIFLE definition (which is based on eGFR) does allow for more meaningful interpretation of renal function in children, in whom SCr alone is difficult to interpret across age groups due to its strong relation to muscle mass. From a historical perspective, the original RIFLE criteria derived for adults included the possibility of using either eGFR or SCr criteria to define AKI [ 1 ]. Subsequently, the pRIFLE definition [ 2 ] was proposed prior to the AKIN consensus definition [ 3 ]; this likely indirectly led to the assumption that pRIFLE is a better definition against which all future child AKI definitions must be compared. The decision to use change in eGFR using the cut-offs of 25, 50 and 75%, to define the pRIFLE (as opposed to change in SCr) was somewhat empirical and not based on evidence that these cut-offs are in fact associated with worse outcomes in a linear graded fashion. It is possible that the pRIFLE R criterion (25% decrease in eGFR or a 1.33 × increase in SCr) is too sensitive, from the perspective of evaluating the relationship of AKI with outcome; similarly, it is possible that there is little difference between a three versus four times increase in SCr, when considering AKI-outcome associations. Ultimately, the only way to answer the question as to which definition is better and what SCr cut-offs are most important, is to determine whether these minor differences actually lead to change in the conclusion of AKI-outcome associations. AKI biomarker studies, which provide information on actual renal tubular injury, may also help to decipher this issue. Until then, we propose that it is perhaps wiser to be consistent with AKI definition and that studies always clearly specify what definition is used, how it is used and how baseline SCr is defined, so that results may be compared across studies and a clearer understanding of how to best define AKI can be inferred. Finally, when considering that in recent years, studies of AKI in adults appear to be more commonly using the AKIN staging definition, it may be worthwhile to adhere to or at least describe this definition in children as well, particularly when attempting to place pediatric AKI findings in the greater context of AKI research. Conflict of interest statement . None declared.

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)0,005
score de la tête « metaresearch » (Gemma)0,051
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesCharge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,977
Score d'incertitude au seuil0,000

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,051
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0010,001
Études des sciences et des technologies0,0050,003
Communication savante0,0070,005
Science ouverte0,0020,004
Intégrité de la recherche0,0450,044
Charge utile insuffisante (le modèle a refusé de juger)0,0230,017

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 Opus0,037
Tête enseignante GPT0,300
Écart entre enseignants0,263 · 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.

Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

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
Publié2011
Routes d'admission1
Résumé présentnon

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