Quality of Life in Children Requiring Antithrombotic Therapy: Development of a Measure
Bibliographic record
Abstract
Measurement of quality of life (QOL) has been accepted as an important outcome measure in therapeutic clinical trials. Long-term antithrombotic therapy is hypothesized to induce treatment dissatisfaction and influence QOL. Health-related quality of life (HRQOL) can be measured by an inventory developed specific to the patient condition. Pediatric QOL inventory for children on long-term antithrombotic therapy should assess constructs salient for this population. Creation of an HRQOL measurement inventory requires rigor and methodological adherence. Identification and evaluation of QOL constructs is critical to improve care and is accepted as the "gold standard" measurement for patient-centered outcomes in clinical research. The use of a valid and reliable HRQOL inventory specific for the antithrombotic therapy is required for upcoming clinical trials as it will provide a method to measure change in HRQOL specific to the antithrombotic agent. In this way, it will be possible to provide the child/family with information to make safe and effective therapeutic choices, define future antithrombotic therapy research strategies, and inform decision makers to change policies to improve health care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".