An update in pulmonary hypertension in systemic lupus erythematosus – do we need to know about it?
Bibliographic record
Abstract
Pulmonary hypertension (PH) is a serious form of pulmonary complication that occurs less frequently in lupus than in other connective tissue diseases like scleroderma; however, it is likely that it is under-recognized in lupus. The symptoms of PH in lupus are non-specific (dyspnea, fatigue, impaired exercise tolerance) and can also be caused by other factors such as pleural or pericardial effusions, interstitial lung disease and many more, making it possible to miss the diagnosis. There are several potential causes of PH in lupus including thromboembolic disease, pulmonary vasculitis, and hypoxia and fibrosis from interstitial lung disease. Endothelin-1 is elevated in lupus and may be associated with PAH. In some studies, pulmonary arterial hypertension (PAH) has been found to be a major cause of mortality in lupus patients. Echocardiograms are a screening tool, but may yield false positives, and a right heart catheterization must be performed to confirm PAH. Early identification is important and can alter the natural history of this dangerous complication of lupus. Treatment of PAH associated with lupus includes standard PAH treatment as well as immunosuppression.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".