Bibliographic record
Abstract
PURPOSE OF REVIEW: Pulmonary vascular disease (PVD) complicates the course of many cardiovascular, pulmonary and other systemic diseases in children. The physiological sequelae (pulmonary hypertension and elevated pulmonary vascular resistance) can overwhelm the right ventricle and lead to circulatory collapse. Despite the common end-point, the preceding pathophysiology is complex and variable and requires a tailored approach to diagnosis and management. In this article, we will review the most recent evidence and explore an approach to current controversies in the diagnosis and management of common or challenging patient subgroups. RECENT FINDINGS: New methods of interpreting data derived from echocardiography and cardiac magnetic resonance imaging may assist in risk stratification and response to therapy. In specific patient subgroups, standard pharmacological therapies to reduce right ventricle afterload may be overutilized, ineffective and in some cases harmful. In the patient failing pharmacological therapy, new and novel techniques are being explored including temporary extracorporeal mechanical circulatory support, pumpless lung assist devices and novel surgical and catheterization procedures. SUMMARY: PVD is a diverse entity, and attention to the underlying pathophysiology is essential for appropriate management. Despite significant advances in our understanding, the majority of data comes from small uncontrolled studies and must be interpreted with caution.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".