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Record W4415648929

Presumed successful steroid therapy for suspected thrombotic microangiopathy in a dog.

2025· article· en· W4415648929 on OpenAlexaff
Tanarut Laudhittirut, Abedin Shaban Zadeh, Anthony P. Carr, Elisabeth Snead

Bibliographic record

VenuePubMed · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicComplement system in diseases
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsThrombotic microangiopathyVomitingPlasmapheresisAcute kidney injuryMicroangiopathyRefractory (planetary science)
DOInot available

Abstract

fetched live from OpenAlex

A 2-year-old castrated male Pembroke Welsh corgi dog was presented to the referring veterinarian because of acute onset of vomiting and hyporexia. Despite conservative treatment with intravenous fluids, antiemetics, antibiotics, and antioxidants, the dog rapidly deteriorated, with development of severe pigmenturia and icterus over 24 to 48 h, respectively, prompting referral. A thrombotic microangiopathy (TMA) characterized by nonimmune-mediated hemolytic anemia, thrombocytopenia, and acute kidney injury (AKI), suspected to be from hemolytic uremic syndrome not associated with known prodromal diarrhea, was diagnosed. This is a rarely described disorder in dogs and, unlike those in most previous reports, this dog survived with supportive care for AKI and a short tapering course of glucocorticoids for refractory thrombocytopenia. Steroids have been reported for managing certain TMA syndromes in humans but not in animals. The dog in this case made a full recovery, with no reported relapse over 1 y. Key clinical message: Thrombotic microangiopathy is characterized by nonimmune-mediated hemolytic anemia, thrombocytopenia, and AKI. Corticosteroids may be beneficial for treating canine TMA, based on successful recovery in this rare case of non-diarrheal hemolytic uremic syndrome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.190
Threshold uncertainty score0.650

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.260
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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