Notice bibliographique
Résumé
In their case series of acute kidney injury (AKI) associated with coronavirus disease 2019 (COVID-19), Patel et al1Patel N. Rein J.L. Sanchez-Russo L. Winston J. Uribarri J. COVID-19-associated acute kidney injury: a case series.Kidney Med. 2020; 2: 668-669Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar proposed that a hypercatabolic state with muscle breakdown was the cause of AKI as they presented 3 cases that typify hypercatabolic state, with rapid increase in serum urea nitrogen levels, hyperuricemia, and hyperphosphatemia. However, in all 3 cases, the urea-creatinine ratio (UCR) was unchanged and was not elevated, as is observed in a hypercatabolic state.2Haines R.W. Zolfaghari P. Wan Y. Pearse R.M. Puthucheary Z. Prowle J.R. Elevated urea-to-creatinine ratio provides a biochemical signature of muscle catabolism and persistent critical illness after major trauma.Intensive Care Med. 2019; 45: 1718-1731Crossref PubMed Scopus (99) Google Scholar Serum urea nitrogen and creatinine levels (UCR initial/peak: case 1, 17.5/16.2; case 2, 12/13; case 3, 9.7/13) in all 3 cases were essentially unchanged and were not in keeping with a true hypercatabolic state.2Haines R.W. Zolfaghari P. Wan Y. Pearse R.M. Puthucheary Z. Prowle J.R. Elevated urea-to-creatinine ratio provides a biochemical signature of muscle catabolism and persistent critical illness after major trauma.Intensive Care Med. 2019; 45: 1718-1731Crossref PubMed Scopus (99) Google Scholar In addition, the near-normal creatine kinase levels do not support significant muscle breakdown unless these patients had pre-existing cachexia. The hyperuricemia and hyperphosphatemia could very well be the effects of AKI rather than initiating factors; however, their role in perpetuation of AKI can not be excluded. The rapid decrease in serum albumin level is more consistent with a capillary leak syndrome, as seen in severe sepsis-systemic inflammatory response syndrome that I agree results from the various inflammatory cytokines (interleukin 6, tumor necrosis factor, etc). I agree with the authors that better understanding of the factors associated with COVID-19–associated AKI and the role of cytokines is important. The author declares that he has no relevant financial interests. Received August 29, 2020. Accepted September 10, 2020, after editorial review by the Editor-in-Chief. In Reply to ‘COVID-19–Associated Kidney Injury’Kidney MedicineVol. 3Issue 1PreviewWe thank Dr Parmar1 for his careful review of our article.2 We do not agree that the serum urea nitrogen–creatinine ratio, as cited in reference 2, should become the standard definition of a hypercatabolic state.3 In that reference, the ratio was a prespecified outcome, their patients had a different phenotype compared with ours, most did not have acute kidney injury (AKI), and their work did not account for the influence of total parenteral nutrition on urea levels. It is widely known that parenteral nutrition is extensively and intensively used in intensive care units and may contribute significantly to increased serum urea nitrogen levels out of proportion to serum creatinine levels. Full-Text PDF Open Access
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 | 0,000 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,002 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,001 |
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.
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 ».