The results of the cross-sectional study of platelet aggregative function in children with hemorrhagic syndrome
Bibliographic record
Abstract
Background. Early diagnosis of thrombocytopathies in children is a relevant objective of pediatrics. Diagnostics helps prevent the development of bleeding, chronic posthemorrhagic anemia, reduces the risk of thrombosis. The aim of the study is an assessment of the incidence of platelet aggregation disorders in children with manifestations of hemorrhagic syndrome against the background of chronic pathology. Methods. The study was conducted on the basis of the Research Institute of Pediatrics and Children’s Health, Scientific Center No. 2, Petrovsky National Research Centre of Surgery in the period from January — until December 2022. 62 children were included in the study, of which 50 children were selected (21 boys and 29 girls) aged 2 years 3 months to 17 years 11 months. The median age was 9.4 (7.2; 13.4). Aggregometry was performed using an impedance semiautomatic aggregometer in whole blood. Results. Depending on the diagnosis, the children were divided into the following groups: cardiovascular diseases (CVD), lysosomal storage disorders (LSD), monogenic hereditary diseases (MHD), children with dysplastic syndrome (DS), children with pathology of the nervous system (NS). Hypoaggregation with thrombin-activating peptide (TRAP test) was detected in 28% of cases (n = 14), more often in children from the group with MHD — 10% (n = 5) and with the presenceof DS — 10% (n = 5). Hypoaggregation with adenosine diphosphate (ADP test) was detected in 20% of cases (n = 10), with arachidonic acid (ASPI test) was detected in 14% (n = 7). Hyperaggregation with the TRAP test was detected in 12% (n = 6), with the ADP test detected in 8% of cases (n = 4). Hyperaggregation with ASPI test was detected in 18% of cases (n = 9). Conclusion. The analyzed results of laboratory tests of platelet aggregation function, hypoaggregation with inducers was observed in more than half of the children, hyperaggregation was observed was present in almost half of the patients.
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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 | 0.002 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".