Attendance rate and perceived relevance related to type, content, and delivery of current rehabilitation programmes after surgical resection for non-small cell lung cancer
Bibliographic record
Abstract
Background: Surgical resection is the preferred treatment for localised non-small cell lung cancer (NSCLC). Rehabilitation is central in the management of the associated impaired quality of life, high symptom burden, deconditioning, and social-existential vulnerability. Yet, optimal content and delivery of rehabilitation are not yet defined. Therefore, we aimed to investigate the current rehabilitation offers, attendance rate, and perceived relevance related to content or delivery. Moreover, we investigated the current symptom burden in the patients. Methods: We conducted an observational cohort study in patients who had undergone surgical resection for NSCLC 4-6 months earlier at Odense University Hospital, Denmark. We retrieved demographic data from patient registries, and interviewed patients via telephone concerning availability, uptake, and attendance rate of any rehabilitation offer in their local primary care setting; content and delivery; benefits of attending, experienced relevance and "symptom burden generally" (specially developed questions); and "symptom burden here and now" [Edmonton Symptom Assessment Scale (ESAS)]. Results: We approached 128 patients, reached 115, and interviewed the 100 (87%) patients who consented. In total, 88% (88/100) had received a rehabilitation offer, and 75% (66/88) had participated in programmes that either targeted NSCLC (23%) or were general cancer rehabilitation (33%), pulmonary rehabilitation (12%), online (1%), or other (33%). Disease-specific rehabilitation was significantly related to the highest attendance rate and perception of relevance. High attendance (≥75%) was, moreover, significantly related to the offer being delivered by a physiotherapist and having a focus on physical exercise. General symptoms were physically oriented [dyspnoea (65%), pain (47%), fatigue (78%)] and "mild" in ESAS scoring. No differences were observed in any baseline characteristics. Conclusions: Rehabilitation after surgical resection for localised NSCLC is delivered heterogeneously in Denmark. Disease-specific rehabilitation was positively related to attendance rate and to the perceived relevance of the offer.
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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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.003 | 0.000 |
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".