French Canadian cross-cultural adaptation of CAPTSure©, an index for the Clinical Assessment of Post-Thrombotic Syndrome in children
Bibliographic record
Abstract
PURPOSE: Post-thrombotic syndrome (PTS) is the most common complication of deep venous thrombosis (DVT). The index for the Clinical Assessment of Post-Thrombotic Syndrome in children (CAPTSure©) is a clinical tool for the diagnosis and severity rating of PTS in pediatric patients. The purpose of this study was to translate and adapt CAPTSure© for French-speaking patients. METHODS: We conducted a cross-sectional study to perform linguistic and cultural adaptation of CAPTSure©, using a rigorous translation process followed by cognitive debriefings in twenty French-speaking pediatric patients aged up to 18 years old with a history of upper or lower extremity DVT at least 6 months prior. RESULTS: Forward and backward translations were used to produce a pre-final French version of CAPTSure©, followed by cognitive debriefings in twenty participants (median age: 11.5 years, 55% male, median CAPTSure© score: 26). The participants felt that the questionnaire was thorough, with an adequate length. Eight out of fourteen (57%) items in the LE questionnaire and 7/12 (58%) of the items in the UE questionnaire were modified following participants' and a multidisciplinary expert committee's input, leading to the final French version of CAPTSure©. CONCLUSIONS: CAPTSure© was successfully adapted for French-speaking pediatric patients. This will ease the diagnosis and severity rating of PTS in children in clinical practice and allow international research collaborations for additional non-English-speaking patients.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".