PrEvention of posttraumatic contractuRes with Ketotifen 2 (PERK 2) – protocol for a multicenter randomized clinical trial
Bibliographic record
Abstract
BACKGROUND: Injuries and resulting stiffness around joints, especially the elbow, have huge psychological effects by reducing quality of life through interference with normal daily activities such as feeding, dressing, grooming, and reaching for objects. Over the last several years and through numerous research results, the myofibroblast-mast cell-neuropeptide axis of fibrosis had been implicated in post-traumatic joint contractures. Pre-clinical models and a pilot randomized clinical trial (RCT) demonstrated the feasibility and safety of using Ketotifen Fumarate (KF), a mast cell stabilizer to prevent elbow joint contractures. This study aims to evaluate the efficacy of KF in reducing joint contracture severity in adult participants with operately treated elbow fractures and/or dislocations. METHODS/DESIGN: A Phase III randomized, controlled, double-blinded multicentre trial with 3 parallel groups (KF 2 mg or 5 mg or lactose placebo twice daily orally for 6 weeks). The study population consist of adults who are at least 18 years old and within 7 days of injury. The types of injuries are distal humerus (AO/OTA type 13) and/or proximal ulna and/or proximal radius fractures (AO/OTA type 2 U1 and/or 2R1) and/or elbow dislocations (open fractures with or without nerve injury may be included). A stratified randomization scheme by hospital site will be used to assign eligible participants to the groups in a 1:1:1 ratio. The primary outcome is change in elbow flexion-extension range of motion (ROM) arc from baseline to 12 weeks post-randomization. The secondary outcomes are changes in ROM from baseline to 6, 24 & 52 weeks, PROMs at 2, 6, 12, 24 & 52 weeks and impact of KF on safety including serious adverse events and fracture healing. Descriptive analysis for all outcomes will be reported and ANCOVA be used to evaluate the efficacy KF over lactose placebo with respect to the improvement in ROM. DISCUSSION: The results of this study will provide evidence for the use of KF in reducing post-traumatic joint contractures and improving quality of life after joint injuries. TRIAL REGISTRATION: This study was prospectively registered (July 10, 2018) with ClinicalTrials.gov reference: NCT03582176.
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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 | 0.018 | 0.016 |
| Meta-epidemiology (narrow) | 0.007 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.058 | 0.011 |
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".