Pediatric refractory chronic immune thrombocytopenia: Identification, patients' characteristics, and outcome
Bibliographic record
Abstract
Abstract Refractory chronic immune thrombocytopenia (r‐cITP) is one of the most challenging situations in chronic immune thrombocytopenia (cITP). Pediatric r‐cITP is inconsistently defined in literature, contributing to the scarcity of data. Moreover, no evidence is available to guide the choice of treatment. We compared seven definitions of r‐cITP including five pediatric definitions in 886 patients with cITP (median [min‐max] follow‐up 5.3 [1.0–29.3] years). The pediatric definitions identified overlapping groups of various sizes (4%–20%) but with similar characteristics (higher proportion of immunopathological manifestations [IM] and systemic lupus erythematosus [SLE]), suggesting that they adequately captured the population of interest. Based on the 79 patients with r‐cITP (median follow‐up 3.1 [0–18.2] years) according to the CEREVANCE definition (≥3 second‐line treatments), we showed that r‐cITP occurred at a rate of 1.15% new patients per year and did not plateau over time. In multivariate analysis, older age was associated with r‐cITP. One patient (1%) experienced two grade five bleeding events after meeting r‐cITP criteria and while not receiving second‐line treatment. The cumulative incidence of continuous complete remission (CCR) at 2 years after r‐cITP diagnosis was 9%. In this analysis, splenectomy was associated with a higher cumulative incidence of CCR (hazard ratio: 5.43, 95% confidence interval: 1.48–19.84, p = 7.8 × 10−4). In sum, children with cITP may be diagnosed with r‐cITP at any time point of the follow‐up and are at increased risk of IM and SLE. Second‐line treatments seem to be effective for preventing grade 5 bleeding. Splenectomy may be considered to achieve CCR.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".