THE ROLE OF HYPERLEPTINEMIA IN THE GENESIS OF GESTATIONAL HYPERTENSION AND PREECLAMPSIA
Bibliographic record
Abstract
The aim of the study was to determine the association of serum leptin levels in pregnant women with the risk of hypertensive disorders depending on gestational weight gain (GWG). We have studied 190 pregnant women with a normal pre-pregnancy body mass index, who were registered at the City Clinical Perinatal Center, Ivano-Frankivsk, Ukraine. Quantitative determination of leptin in serum was performed by ELISA Kit (CAN-L-4260, Canada). Statistical analyses based on Microsoft Excel statistical analysis package and Statistica 6.0. Gestational hypertension (GH) has developed in 29 (15.3 %), preeclampsia in 39 (20.5 %) cases and 122 (64.2%) pregnant were normotensive. The recommended GWG (11.5-16.0 kg) was diagnosed in 133 (70.0 %), excessive in 57 (30.0 %) patients. The frequency of GH was 2.2-fold (p<0.05) and preeclampsia was 4.2-fold (p<0.001) higher in pregnant with excessive GWG, compared to patients with the recommended GWG. Leptin concentrations in pregnant with GH were 1.5-fold in the third trimester (p<0.01), and with preeclampsia 1.1-fold in the second (p<0.01) and 1.5-fold in the third (p<0.01) trimesters higher compared to normotensive women. Serum leptin concentrations of pregnant with GH and preeclampsia were significantly higher in the group with excessive GWG compared to the recommended, which were detected in the second trimester. A high degree of risk of hyperleptinemia in the groups of pregnant with GH (OR=3.50; 95%CI: 1.48-9.33; p<0.05), and with preeclampsia (6.01; 2.43-15.02) was found in women with excessive GWG. A positive correlation was found between leptin concentration, GWG and body fat percentage in pregnant with GH and preeclampsia in the second and third trimesters. Thus, leptin can be considered a marker of the association between pathological GWG and hypertensive disorders in pregnancy
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".