Heart or Lungs? Uncovering the Causes of Exercise Intolerance in a Patient with Chronic Cardiopulmonary Disease
Bibliographic record
Abstract
A 52-year-old woman was referred for potential mitral valve replacement because of severe stenosis and moderate regurgitation secondary to rheumatic heart disease. She denied smoking tobacco; however, she had been exposed to biomass smoke (indoor cooking) for more than 30 years. Moreover, she reported having had pulmonary tuberculosis treated with standard chemotherapy 20 years before. Her mitral stenosis had been treated with percutaneous mitral balloon commissurotomy (PMBC) 15 years ago. Her functional performance had declined in the past few years. An echocardiographic mitral valvuloplasty outcome prediction score, however, indicated poor outcome for repeated PMBC (Wilkins score = 10). The remaining alternative (prosthetic valve replacement) is associated with higher morbidity and mortality than PMBC. In this context, the following was the clinical challenge: Is this patient’s functional limitation related primarily to cardiocirculatory impairment secondary to severe mitral stenosis or, alternatively, to her respiratory comorbidities? In the first scenario, prosthetic valve replacement could still be considered to improve her symptoms. Alternatively, if coexistent respiratory impairment contributes importantly to her breathing discomfort, the procedure would not be indicated.
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 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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".