Neutropaenia following intravenous immunoglobulin therapy in paediatric patients with immune thrombocytopaenia
Bibliographic record
Abstract
Introduction Immune thrombocytopaenia (ITP), previously known as idiopathic thrombocytopaenic purpura, is an acquired autoimmune disorder characterised by immune-mediated platelet destruction. It has been observed that some paediatric patients with ITP treated with intravenous immunoglobulin (IVIG) developed neutropaenia. The aim of the study was to investigate the association between IVIG therapy and neutropaenia in paediatric ITP. Material and methods The retrospective cohort study involved 123 children (79 girls, 44 boys) with immune thrombocytopaenia, aged 8.03 ±4.55 (0.8–17.9) years (mean ± standard deviation; range) who underwent IVIG in the Department of Haematology and Paediatric Oncology in Zabrze between April 2014 and December 2021. Correlations between age, sex, weight of patients, total IVIG dose, and neutrophil/platelet counts on administration day and 1, 2, and 3 days after IVIG treatment from official medical records were analysed. Results The mean total dose of IVIG was 1.7 ±0.48 g/kg BW. A significant increase in platelet level was observed usually on the first (67.5%) or second (20.3%) day after initial administration of intravenous immunoglobulins. After the course of IVIG, neutropaenia was observed in 50 subjects (40.7%). The neutropaenia occurred mostly (54%) on the first day after administration of IVIG. There was a positive correlation between the onset of neutropaenia and lower age of patients (p < 0.05). What is more, the decrease in the neutrophil count was more distinct in the group of subjects with neutropaenia. Conclusions Intravenous immunoglobulin therapy in children with ITP can lead to neutropaenia. However, patients benefit noticeably from IVIG therapy, and neutropaenia in this case tends to be a transient, self-limiting condition.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 | 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".