296 Case Report: Pacemaker Lead-Induced Fibrosis Resulting in Right Atrial and Tricuspid Stenosis Managed with An Open Surgical Approach
Bibliographic record
Abstract
Abstract Pacemaker leads can result in localised inflammation and, over time, fibrosis. Rarely, this can significantly alter the anatomy of the heart and impair cardiac function. In this case, a fifty-year-old female had undergone pacemaker placement in her teens having experienced symptomatic bradycardia. Due to pacemaker pocket erosion, she had undergone a lead extraction where lead fragments had been left in-situ. Years after a new generator and leads were placed, she presented with symptoms of proximal venous congestion and superior vena cava (SVC) syndrome. A venogram demonstrated completely occluded brachiocephalic and innominate veins with significant adjacent venous collateralization. Computed tomography showed partial obstruction of the SVC and tricuspid stenosis. Initially, a decision was made not to intervene. After developing abdominal distension, she was diagnosed with hepatic congestion and cirrhosis secondary to elevated right sided pressures and right atrial congestion due to tricuspid stenosis. It was concluded that the patient’s symptoms were the result of occluded proximal veins, SVC syndrome, and functional tricuspid stenosis, all of which were likely the result of fibrotic tissue secondary to pacemaker lead-induced inflammation. Due to the severity of her symptoms, the patient accepted the risks associated with surgical management. Intra-operatively, electrocautery was used to debride the fibrotic tissue inhibiting the leaflets of the tricuspid valve. This worked to great effect and additional valve repair/replacement was not necessary. Whilst the patient has been left with SVC syndrome, her tricuspid stenosis symptoms are greatly improved. To our knowledge, such a case has not been previously described.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".