Evaluating Implementation of Health-related Quality of Life Measures for Patients With Primary Ciliary Dyskinesia Supports Development of a Latin American Spanish Questionnaire
Bibliographic record
Abstract
Abstract Rationale: Primary ciliary dyskinesia (PCD) is a life-shortening, genetic disorder affecting 1 in 7500 individuals. PCD inhibits motile cilia activity and impacts the respiratory, auditory, olfactory and reproductive systems. Methods that measure the impact of PCD historically have lacked sensitivity to disease progression and failed to account for changes in a patient's daily physical, respiratory or social functioning. Between 2015 and 2017, quality of life questionnaires (QOL-PCD) for adults (18+), adolescents (13-17) or children with caregiver proxy (6-12) were created to comprehensively assess patient-reported outcomes. In 2023, the BEAT-PCD consensus statement recommended using validated QOL-PCD instruments as a core outcome for clinical trials. Our goal was to evaluate current implementation of the QOL-PCD. Methods: Implementation was assessed using data extracted from completed QOL-PCD requests captured in a REDCap database hosted at BC Children's Hospital in Vancouver, BC. Results: 81% of requests for the QOL-PCD have been successfully fulfilled (47/58). On average, there were 6 QOL-PCD requests per year between 2018 and 2023, however requests increased 136% in 2024. The QOL-PCD is largely accessed for research purposes (74%) rather than clinical monitoring (21%). 62% of completed requests originated from academic institutions. 79% specifically use adult questionnaires, compared to adolescent (66%) and child questionnaires (62%). Approximately 2500 individuals worldwide have/will be assessed using the QOL-PCD, including 1339 adults, 586 teenagers and 594 children. On average, 43 adults, 29 adolescents or 27 children are assessed by each age-specific version request. The QOL-PCD has been distributed most to the USA (10), Germany (5) and Turkey (5), although the QOL has been utilized on every continent. Of 15 available languages, the most common are English (55%) and German (21%). Latin American Spanish is the third most requested language, however there is no validated translated QOL-PCD (Figure 1). Finally, slightly more than half of QOL users (53%) agreed to share anonymous data obtained using the questionnaires, compared to 21% who do not agree. Conclusion: QOL-PCD comprehensively assesses the impact of PCD throughout the lifespan and its use has increased sharply in the past year, likely due to published consensus statements. Questionnaires are largely used for academic research studies, particularly in North America and Europe. Future validated translations of the QOL-PCD, such as Latin American Spanish, may further improve utilization, particularly in the Global South. Outreach to increase access of data captured by QOL users will also facilitate future development of this important tool.
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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 | 0.017 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".