Flow cytometric assessment of endothelial and platelet microparticles in preeclampsia and their relation to disease severity and Doppler parameters
Bibliographic record
Abstract
OBJECTIVE: Platelet (P) and endothelial (E) microparticle (MP) levels increase in preeclampsia. However, their relation to the severity of the disease needs to be clarified. The objectives of this study were to compare the levels of EMP and PMP in severe and mild preeclampsia to healthy gravidas to find possible correlations to severity of the disease, Doppler changes, and complications. METHODS: A comparative prospective clinical trial (Canadian Task Force II-1) was conducted on 135 pregnant women divided into three groups: 35 women with severe preeclampsia (group 1), 40 with mild preeclampsia (group 2), and 60 healthy gravids (group 3). Assessment of EMP and PMP was done by flow cytometry using anti-CD31 and anti-CD42b antibodies. RESULTS: Expression of CD31 and CD42b (EMPs) was higher in group 1 compared to groups 2 and 3 with P < 0.001, while expression of CD42b alone (PMPs) did not show a statistically significant difference (P = 0.957). EMPs were correlated positively to umbilical and middle cerebral artery resistance index. There was a significant negative correlation between platelet count and EMPs. Also, EMPs were correlated positively to aspartate transferase and bilirubin levels and were significantly higher with neonatal death. DISCUSSION: The present study revealed a significant association between plasma levels of EMPs and severity of preeclampsia together with poor neonatal outcome as regards birth weight and percent of neonatal death. So, EMPs assay could be a good predictor of maternal and fetal outcomes and in cases with preeclampsia.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".