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Record W3118558779

Paroxysmal atrial fibrillation in a dog that was presented for neck wounds.

2021· article· en· W3118558779 on OpenAlexaff
Samuel J Hornsey, Anthony P. Carr, Jennifer M. Loewen

Bibliographic record

VenuePubMed · 2021
Typearticle
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMedicineAtrial fibrillationCardiologyInternal medicineHeart rateAnesthesiaSinus rhythmBlood pressure
DOInot available

Abstract

fetched live from OpenAlex

A 12-year-old spayed female German shorthaired pointer dog sustained extensive bite wounds around the neck. At presentation, atrial fibrillation was identified with a rapid ventricular response rate of 300 beats per minute (bpm). The ventricular response rate rapidly decreased to 130 bpm following administration of hydromorphone and oxygen. Based on the rate, antiarrhythmic therapy was not initiated. The heart rhythm converted back to sinus rhythm by the time of the first recheck evaluation 2 days later, and the dog remained in sinus rhythm at all subsequent evaluations. With the resolution of the arrhythmia, paroxysmal atrial fibrillation was suspected. The underlying etiology of the arrhythmia was not determined; however, imbalances in autonomic tone associated with trauma and/or direct trauma to the heart were hypothesized. Key clinical message: This report indicates a possible role of imbalances in autonomic tone due to trauma in the development of paroxysmal atrial fibrillation and suggests that it should be a differential diagnostic consideration in patients with atrial fibrillation following trauma. Primary treatment of atrial fibrillation may not be needed in these cases if the ventricular response rate is not rapid, or if there is spontaneous conversion to sinus rhythm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.000

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 head0.098
GPT teacher head0.320
Teacher spread0.222 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venuePubMed→Same topicAtrial Fibrillation Management and Outcomes→French-language works237,207→