Quality of life is an important indication for second‐line treatment in children with immune thrombocytopenia
Bibliographic record
Abstract
BACKGROUND: The decision to initiate second-line treatment in children with immune thrombocytopenia (ITP) is complex and involves many different factors. METHODS: In this prospective, observational, longitudinal cohort study of 120 children from 21 centers, the factors contributing to the decision to start second-line treatments for ITP were captured. At study entry, clinicians were given a curated list of 12 potential reasons the patient required a second-line treatment. Clinicians selected all that applied and ranked the top three reasons. RESULTS: Quality of life (QOL) was the most frequently cited reason for starting a second-line therapy. Clinicians chose it as a reason to treat in 88/120 (73%) patients, as among the top three reasons in 68/120 (57%), and as the top reason in 32/120 (27%). Additional factors ranked as the top reason to start second-line treatment included severity of bleeding (22/120, 18%), frequency of bleeding (19/120, 16%), and severity of thrombocytopenia (18/120, 15%). Patients for whom QOL (p = .006) or sports participation (p = .02) were ranked reasons were more likely to have chronic ITP, whereas those for whom severity (p = .003) or frequency (p = .005) of bleeding were ranked reasons were more likely to have newly diagnosed or persistent ITP. Parental anxiety, though rarely the primary impetus for treatment, was frequently cited (70/120, 58%) as a contributing factor. CONCLUSION: Perceived QOL is the most frequently selected reason pediatric patients start second-line therapies for ITP. It is critical that studies of treatments for childhood ITP include assessments of their effects on QOL.
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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".