Clinical and Echocardiographic Features of Primary Infundibular Stenosis with Intact Ventricular Septum in Dogs
Bibliographic record
Abstract
Abstract Background:Primary infundibular stenosis is a rare congenital defect in which the right ventricle is divided into a proximal “high-pressure” chamber and a distal “low-pressure” chamber. The condition can be misdiagnosed as ventricular septal defect or valvular pulmonic stenosis and the disease severity underestimated. The purpose of this study was to provide a detailed clinical and echocardiographic description of this anomaly in a series of dogs. Hypothesis:Several anatomic forms of infundibular stenosis exist. High resolution two-dimensional echocardiography could differentiate 3 gross anatomic substrates. Knowledge of the anatomy of the obstructing lesion could influence options for corrective interventions. Animals:Thirteen dogs examined at the Ontario Veterinary College teaching hospital from 1994 to 2005 with an ultrasound diagnosis of subpulmonic stenasis. Methods:A retrospective review was made of case records from 1994 to 2005. Results:Thirteen dogs were identified as having primary infundibular stenosis, with apparent increased prevalence in Golden Retrievers (8/13, 62%) and Siberian Huskies (3/13, 23%). Three types of infundibular lesions were identified by ultrasound in 11/13 dogs: a fibrous diaphragm (6), fibromuscular (4), and muscular obstruction (1). Two dogs with a fibrous diaphragm underwent direct surgical dilation without the use of cardiopulmonary bypass or inflow occlusion, resulting in substantial reduction of the severity of stenosis. Conclusion and Clinical Importance: Accurate determination of the severity of the stenosis and the anatomy of the obstructing lesion are important in devising a treatment strategy. Recognition of the fibrous diaphragm by echocardiography identifies a subset of dogs potentially amenable to surgical dilation without the need for cardiopulmonary bypass.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".