Bleeding manifestations and management of children with persistent and chronic immune thrombocytopenia: data from the Intercontinental Cooperative ITP Study Group (ICIS)
Bibliographic record
Abstract
Long-term follow-up of children with immune thrombocytopenia (ITP) indicates that the majority undergo remission and severe thrombocytopenia is infrequent. Details regarding bleeding manifestations, however, remain poorly categorized. We report here long-term data from the Intercontinental Cooperative ITP Study Group Registry II focusing on natural history, bleeding manifestations, and management. Data on 1345 subjects were collected at diagnosis and at 28 days, 6, 12, and 24 months thereafter. Median platelet counts were 214 × 10(9)/L (interquartile range [IQR] 227, range 1-748), 211 × 10(9)/L (IQR 192, range 1-594), and 215 × 10(9)/L (IQR 198, range 1-598) at 6, 12, and 24 months, respectively, and a platelet count <20 × 10(9)/L was uncommon (7%, 7%, and 4%, respectively). Remission occurred in 37% of patients between 28 days and 6 months, 16% between 6 and 12 months, and 24% between 12 and 24 months. There were no reports of intracranial hemorrhage, and the most common site of bleeding was skin. In patients with severe thrombocytopenia we observed a trend toward more drug treatment with increasing number of bleeding sites. Our data support that ITP is a benign condition for most affected children and that major hemorrhage, even with prolonged severe thrombocytopenia, is rare.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".