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Record W2163693207 · doi:10.4314/sokjvs.v10i1.8

Idiopathic pericardial effusion in 2 year old labrador managed with ultrasound-guided pericardiocentesis: Case report

2012· article· en· W2163693207 on OpenAlexaboutno aff
JB Adeyanju, Ronald L. Perry, AS Yakubu, Abdurrahman Hassan Jibril, AZ Hassan

Bibliographic record

VenueSokoto Journal of Veterinary Sciences · 2012
Typearticle
Languageen
FieldMedicine
TopicPericarditis and Cardiac Tamponade
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePericardiocentesisPericardial effusionEffusionPericardiumSurgeryCatheterUltrasoundRadiology

Abstract

fetched live from OpenAlex

A two-year old, 38kg-wt male Labrador was presented for management because of progressive exercise intolerance. At presentation, rectal temperature was 38.5°C, pulse rate was 135 beats per minute (but weak). There was ascites along with oedema of the extremities. The heart sound was muffled and pulsus paradoxus was very mild. The patient was well hydrated. Thoracic radiography revealed a globoid shaped heart occupying most of the equatorial thoracic volume; there was loss of details of cardiac silhouette and there was dorsal deviation of trachea at carina. Ultrasonography revealed a distinct epicardium, pericardium and a very wide anechoic space in between. Blood picture was within normal findings. Idiopathic chronic pericardial effusion was diagnosed. Ultrasound-guided pericardiocentesis was carried out using a 16 gauge over the needle catheter attached to a 3-way stopcock and a 20mls syringe; about 65mls of clear effusate was aspirated. Laboratory analysis of the effusate revealed that it was a transudate. The patient was placed on 3mg/kg furosemide, twice daily for 5 days and the patient returned to gradual exercise during hospitalization. Oedema of the extremities and ascities decreased, the appetite improved and the dog became more active. Thoracic radiography fourth week post pericardiocentesis revealed a normal cardiac silhouette. The cause of pericardial effusion was not known.

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)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.034
GPT teacher head0.309
Teacher spread0.275 · 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
Published2012
Admission routes1
Has abstractyes

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