The value of a specialist nurse-lead interstitial lung disease clinic, patients' views
Bibliographic record
Abstract
There are a wide range of Interstitial lung diseases, the most common, Idiopathic Pulmonary fibrosis has a cancer like median prognosis of 3-4 years (Ryerson CJ, et al ERJ, 2013;42:750), and a need to focus on symptom management and integrate palliative care early is well documented (Lindell et al, 2010 ), The role of clinical nurses specialist in cancer management is well established, the role in Interstitial Lung Disease Specialist Nurse is less well studied. We have run nurse-lead clinics for Interstitial Lung Disease patients since 2005 in parallel with medical clinics. Nursing appointments are for 30 minutes during which disease monitoring, symptom management with a particular focus on coping with breathlessness, fatigue and end of life issues are addressed. We report patients9 views of the nurse lead clinic using a 10 point questionnaire adapted from a questionnaire developed for auditing Diabetic Nursing services. Questions about quality were on a 4 point scale. Anonymous questionnaires were given to 50 random patients attending the clinic (Idiopathic Pulmonary Fibrosis 42, Hypersensitivity Pneumonitis 8, and Sarcoidosis 1). There was overwhelming support for the nurse lead clinic. More than 90% thought that the best ways to manage their fibrosis had been completely discussed; they had an agreed management plan till the next visit, and definitely felt more confident in managing their breathlessness. All thought that their goals had been completely discussed, that the nurse listened carefully to their concerns and explained things clearly. As a result all thought that the specialist nursing service was very important to them and 90% wanted to be seen at least every 3 months.
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".