Current organization of specialist pulmonary hypertension clinics: results of an international survey
Bibliographic record
Abstract
Optimal pulmonary hypertension (PH) management relies on a timely, accurate diagnosis and follow-up in specialized clinics by multidisciplinary teams that have clearly defined responsibilities and protocols. Internationally agreed criteria for expert center staff are lacking, particularly with respect to nurses, who often act as a central component of the team. This survey aimed to evaluate the current organization of PH clinics and the role of nurses. The survey (35 questions) was online February-December 2015 and was advertised at international PH nurse meetings and through international PH organizations to their corresponding clinics. In total, 126 healthcare professionals from 32 countries responded. According to respondents, 54% of clinics managed >200 patients, of whom 49% had a pulmonary arterial hypertension (PAH) diagnosis, on average. In terms of staff, 66% had a dedicated program administrator, 35% had one full-time nurse coordinator/practitioner/specialist, and 57% had a nurse attend outpatient clinic alongside a physician. Crucially, not all centers had a nurse in their team. The role of a nurse coordinator/practitioner/specialist varied with 51% taking patient histories/examinations and 66% managing outpatients. In 34% of clinics, nurses were involved in their own research. Protocols were available for PH therapies (81%), management of heart failure (37%) and pain (26%), and referring patients who did not have PAH/chronic thromboembolic PH back to their specialist (62%). Not all clinics are meeting all of the standards outlined in the latest guidelines with key areas of improvement being level of support from/for nurses, clear protocols, and referral pathways.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".