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Enregistrement W4388539826 · doi:10.1111/vec.13349

Acute kidney injury in dogs following ingestion of cream of tartar and tamarinds and the connection to tartaric acid as the proposed toxic principle in grapes and raisins

2023· letter· en· W4388539826 sur OpenAlexaboutno aff
Nicola Bates, Zoe Tizzard, John N. Edwards

Notice bibliographique

RevueJournal of Veterinary Emergency and Critical Care · 2023
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueVenomous Animal Envenomation and Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBATESMedicineVeterinary medicineLibrary scienceEngineeringComputer science

Résumé

récupéré en direct d'OpenAlex

Dear Editor, We are very interested in the report of cases of tartaric acid and tartrate poisoning from tamarinds and cream of tartar contributed by Wegenast and colleagues,1 which support the theory that this is the cause of acute kidney injury (AKI) associated with grape and raisin poisoning. We would like to contribute additional supporting data. At the Veterinary Poisons Information Service (VPIS), UK, we have no reported cases involving tamarind but do have cases involving cream of tartar. One dog, an adult Labrador, developed vomiting, inappetence, and AKI after ingestion of an unknown amount of cream of tartar. The dog was euthanized, and results of a urine sample received after euthanasia was positive for Haemophilus haemoglobinophilus, which may have been a confounder. Although dogs appear to be particularly susceptible to AKI from tartrates and tartaric acid,1 cases have also been reported in people, although 10–20 g of sodium tartrate was used previously as a laxative in people. Acute tubular necrosis has been reported after ingestion of tartaric acid2 and fatal tubular nephropathy occurred in an adult male following accidental ingestion of 30 g of tartaric acid.3 Wegenast and colleagues mention that tartaric acid delays gastric emptying, which may explain prolonged retention of dried vine fruits in the stomach. In addition, raisins are hygroscopic and can double or triple in volume on contact with water, and phytobezoars involving raisins have been reported in people.4, 5 Wegenast and colleagues suggest that cooked grapes and raisins are less likely to be implicated in cases of AKI due to thermal decomposition of tartaric acid. In a study comparing thermal decomposition of pure tartaric acid and that in waste samples from the grape juice and wine industries, the peak decomposition of pure tartaric acid occurred at 208°C but was closer to 300°C for the waste products.6 We have fatal cases of AKI in dogs after ingestion of Christmas pudding and fruit cake (including Christmas cake), all of which are rich in dried vine fruits. These baked goods are cooked for a prolonged period, but at a relatively low temperature (usually around 120–140°C), so it is difficult to know if the poor outcome was due to the dose ingested or the low cooking temperature resulting in incomplete decomposition of tartaric acid. Late presentation was a characteristic of these cases and is well recognized as a factor contributing to poor outcome in cases of tartaric acid-containing foods. Interestingly, we have no fatal cases involving other baked goods containing dried vine fruits such as scones or mince pies that are typically cooked for a shorter time at higher temperatures, but generally not above 200°C. We still have a great deal to learn about grape and raisin toxicosis in dogs, but the recognition of tartaric acid as the probable causative agent is a breakthrough. Our data support the findings of Wegenast and colleagues, but data are still lacking, and current treatment advice remains unchanged. Now we need to understand the effect of cooking on vine fruits and other factors that influence the outcome in dogs that ingest tartaric acid-containing foods. We would welcome further well-described case reports, particularly with information on doses ingested. Respectfully,

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,788
Score d'incertitude au seuil0,368

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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 Opus0,018
Tête enseignante GPT0,320
Écart entre enseignants0,302 · 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 tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
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

Citations2
Publié2023
Routes d'admission1
Résumé présentoui

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