Integrating specialist palliative care to improve care and reduce suffering: cystic fibrosis (InSPIRe:CF) – study protocol for a multicentre randomised clinical trial
Bibliographic record
Abstract
INTRODUCTION: Cystic fibrosis (CF) is a life-limiting genetic disorder estimated to affect more than 160 000 individuals and their families worldwide. People living with CF commonly experience significant physical and emotional symptom burdens, disruptions to social roles and complex treatment decision making. While palliative care (PC) interventions have been shown to relieve many such burdens in other serious illnesses, no rigorous evidence exists for palliative care in CF. Thus, this study aims to compare the effect of specialist palliative care plus usual CF care vs usual CF care alone on patient quality of life. METHODS AND ANALYSIS: This is a five-site, two-arm, partially masked, randomised superiority clinical trial. 264 adults with CF will be randomly assigned to usual CF care or usual CF care plus a longitudinal palliative care intervention delivered by a palliative care specialist. The trial's primary outcome is patient quality of life (measured with the Functional Assessment of Chronic Illness Therapy-Palliative care instrument). Secondary outcomes include symptom burden, satisfaction with care and healthcare utilisation. Outcomes will be measured at 12 months (primary endpoint) and 15 months (secondary endpoint). In addition, we will conduct qualitative interviews with patient participants, caregivers, and palliative care and CF care team members to explore perceptions of the intervention's impact and barriers and facilitators to dissemination. ETHICS AND DISSEMINATION: Human subjects research ethics approval was obtained from all participating sites, and all study participants gave informed consent. We will publish the results of this trial in a peer-reviewed journal. TRIAL REGISTRATION NUMBER: ISRCTN53323164.
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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 | 0.045 | 0.038 |
| Meta-epidemiology (narrow) | 0.008 | 0.004 |
| Meta-epidemiology (broad) | 0.013 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.009 | 0.009 |
| Insufficient payload (model declined to judge) | 0.107 | 0.021 |
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".