Different collagenase delivery for Dupuytren disease in public hospitals
Bibliographic record
Abstract
Background: The delivery protocol of collagenase Clostridium histolyticum (collagenase) injection for Dupuytren’s disease is variable, due to limited evidence for any one approach and widespread ‘off-label’ delivery occurring in Australia. As such, this preliminary study aimed to assess whether different collagenase delivery protocols for treating Dupuytren’s disease have an impact on effectiveness and safety. It was hypothesised that different collagenase delivery would affect outcomes. Methods: This preliminary, prospective study included a consecutive cohort of adult patients with Dupuytren’s disease being treated with collagenase within two Australian public hospitals to determine whether different collagenase delivery protocols impact on effectiveness and safety. The therapeutic effect was measured objectively using the total passive extension deficit (TPED), clinical success and clinical improvement. Three patient-reported outcome measures (PROMs) were used: Unité Rhumatologique des Affections de la Main (URAM), the Southampton Dupuytren’s Scoring Scheme and the Canadian Occupational Patient-Specific Functional Scale (PSFS). Results: The delivery of collagenase was variable at both clinics. The number of patients treated with collagenase at Institute I and Institute II was 49 and 18, respectively. Clinical success was achieved in 42 per cent of the Institute I and 35 per cent of the Institute II cohort. A statistically significant reduction in all three PROMs was observed for both cohorts. No significant differences between effectiveness or safety was found when comparing the two cohorts. Conclusion: The delivery of collagenase was variable at Institutes I and II, but these differences did not appear to impact the effectiveness or safety of collagenase delivery.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".