Quality of life and costs of Filgrastim® (G-CSF) treatment in patients with persistent chronic rhinosinusitis
Bibliographic record
Abstract
This is the first report of the double blind randomized clinical trial, in which we investigated the influence of Filgrastim(r) on the quality of life and treatment costs of chronic sinusitis patients who did not respond to regular treatments.\n\nThe quality of life of 56 patients was assessed 5 times during the 24-week trial with the EuroQol, the SF-36 and the McGill Pain questionnaire. We further controlled for "responsiveness", based on clinical impression.\n\nDirect medical and indirect non-medical costs per patient during the trial were analyzed, based on data from clinical record forms and the hospital information system. We further compared the direct medical costs to the costs of regular treatment.\n\nThe quality of life scores were all below population norm scores. Quality of life scores of the Filgrastim(r) group suggested a better quality of life than the placebo group, although none of the differences were statistically significant. There were indications that controlling for responsiveness increased the power of the design.\n\nThe difference in costs between the trial groups were driven by the Filgrastim(r) costs (Euro 4899). When Filgrastim(r) costs were neglected, no difference in costs remained. Except for Filgrastim(r), total direct costs summed up to Euro 2712 and the indirect costs to Euro 582. Total direct costs of a 24-week regular treatment were three times lower than the costs of the trial treatment.\n\nWhile significantly increasing treatment costs, Filgrastim(r) administration does not lead to a better quality of life of chronic sinusitis patients, although there were s
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".