Combined hormone therapy in postmenopausal women with features of metabolic syndrome. Results from a population-based study of Swedish women: Women’s Health in the Lund Area study
Bibliographic record
Abstract
OBJECTIVE: To delineate the influence of hormone therapy (HT) on features of metabolic syndrome with special reference to the composition and mode of administration of three specific HT regimens, all containing estradiol (E2) + norethisterone. DESIGN: The Women's Health in the Lund Area project screened all women (n = 10,766), born between 1935 and 1945. Complete data were obtained from 6,917 women. Those at or above defined cutoff limits were considered positively screened (n = 3,593) for metabolic syndrome. All of them were invited to undergo an oral glucose tolerance test; 2,923 women accepted. After excluding 200 women with impaired fasting glucose, 2,723 women were included in the present analysis. Serum lipids were determined by conventional standard methods at the department of clinical chemistry of Lund University Hospital. RESULTS: According to World Health Organization criteria, 2,123 women had normal glucose tolerance and 600 women had impaired glucose tolerance (IGT). IGT was less common (P = 0.001) among users of a transdermal patch [CYC-TRANS; E2 50 microg + norethisterone acetate (NETA) 250microg] compared with the two-combined oral regimen [CON-O (continuous oral E2 2 mg + NETA 1 mg) + CYC-O (sequential oral E2 2 mg + NETA 1 mg)]. Furthermore, IGT was more common among CON-O users when compared with either the CYC-O + CYC-TRANS group (P = 0.002) or the CYC-TRANS only group (P = 0.001). There were no significant differences between CYC-O versus CYC-TRANS or CON-O. Serum levels of total cholesterol were higher in the CYC-TRANS group than in the combined CON-O + CYC-O group (P < 0.05); they also were higher (P = 0.05) when comparing the CYC-O + CYC-TRANS versus CON-O as well as higher in CYC-TRANS versus CON-O (P < 0.05). Serum high-density lipoprotein cholesterol levels were higher in the CYC-O (P = 0.001), CYC-TRANS (P < 0.05), and the CYC-O + CYC-TRANS (P = 0.001) groups when compared with the CON-O users. There were no differences in the mean age, blood pressure (systolic and diastolic), body mass index, waste-hip ratio, or the rate of cigarette and alcohol consumption between the different hormone regimens. CONCLUSION: The risk of having a pathological glucose load was lower in transdermal versus oral users of HT. Transdermal HT could be regarded as first-line treatment in women at risk of developing diabetes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".