Successful treatment of pacemaker-induced stricture and thrombosis of the cranial vena cava in two dogs by use of anticoagulants and balloon venoplasty
Bibliographic record
Abstract
CASE DESCRIPTION: 2 castrated male Labrador Retrievers (dogs 1 and 2) were evaluated 3 to 4 years after placement of a permanent pacemaker. Dog 1 was evaluated because of a large volume of chylous pleural effusion. Dog 2 was admitted for elective replacement of a pacemaker. CLINICAL FINDINGS: Dog 1 had mild facial swelling and a rapidly recurring pleural effusion. Previously detected third-degree atrioventricular block had resolved. Cranial vena cava (CVC) syndrome secondary to pacemaker-induced thrombosis and stricture of the CVC was diagnosed on the basis of results of ultrasonography, computed tomography, and venous angiography. Dog 2 had persistent third-degree atrioventricular block. Intraluminal caval stricture and thrombosis were diagnosed at the time of pacemaker replacement. Radiographic evidence of pleural effusion consistent with CVC syndrome also was detected at that time. TREATMENT AND OUTCOME: Dog 1 improved after treatment with unfractionated heparin and a local infusion of recombinant tissue-plasminogen activator. Balloon venoplasty was performed subsequently to relieve the persistent caval stricture. In dog 2, balloon dilatation of the caval stricture was necessary to allow for placement of a new pacing lead. Long-term anticoagulant treatment was initiated in both dogs. Long-term (> 6 months) resolution of clinical signs was achieved in both dogs. CLINICAL RELEVANCE: Thrombosis and stricture of the CVC are possible complications of a permanent pacemaker in dogs. Findings suggested that balloon venoplasty and anticoagulation administration with or without thrombolytic treatment can be effective in the treatment of dogs with pacemaker-induced CVC syndrome.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".