Feasibility of Administering the Patient Reported Outcomes, Burdens and Experiences (PROBE) Questionnaire Through the Canadian Bleeding Disorders Registry (CBDR) and Comparison of Data From the Two Sources
Bibliographic record
Abstract
INTRODUCTION: The Patient Reported Outcomes, Burdens and Experiences (PROBE) questionnaire can be used to measure quality of life in persons with haemophilia (PWH) and is integrated in the Canadian Bleeding Disorders Registry (CBDR). This offers the opportunity to compare the same data inputted by patients in PROBE and their treating team in CBDR. AIM: Our objectives were to assess the feasibility of collecting PROBE data through CBDR and to compare the data collected from these two sources. METHODS: We conducted a prospective observational study among PWH using MyCBDR. Participants were invited to digitally complete the PROBE questionnaire at baseline and to repeat it at 6 and 12 months. Additional data were passively collected through CBDR. Data from PROBE and CBDR were compared using Kappa agreement, intraclass correlation (ICC) and Pearson correlation. RESULTS: A total of 142 PWH participated. Recruitment ratios were 21.1% and 12.0% for the two phases. Retention rates were 40.8% at 6 months and 32.4% at 12 months. Three hundred thirteen subjects were involved in the comparison between PROBE and CBDR data. The agreement was good to very good (κ > 0.75) or the correlation very strong, with the exception of the history of inhibitor (κ = 0.57), recent bleeds (κ = 0.48) and current treatment regimen (κ = 0.57). CONCLUSION: The integration of PROBE with CBDR is feasible and PROBE is a reliable tool for routine PRO data collection. Its use in clinical practice may improve data quality and personalized and patient-centred care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.050 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".