Reduced Ovarian Reserve in Patients with Takayasu Arteritis
Bibliographic record
Abstract
OBJECTIVE: To assess ovarian reserve markers in patients with Takayasu arteritis (TA). METHODS: Twenty patients with TA and 24 healthy controls were evaluated for ovarian reserve by follicle-stimulating hormone, luteinizing hormone, and estradiol, and antral follicle count (AFC). Anti-Müllerian hormone (AMH) was measured by ELISA using 2 different kits. Demographical data, menstrual abnormalities, disease variables, and treatment were also analyzed. RESULTS: The median current age was similar in patients with TA and controls (31.2 ± 6.1 vs 30.4 ± 6.9 yrs, p = 0.69). The frequencies of decreased levels of AMH in patients with TA were identical using both kits and higher when compared to controls (50% vs 17%, p = 0.02; 50% vs 19%, p = 0.048). A positive correlation was observed between the 2 kits in patients with TA (r = +0.93, p < 0.0001) and in healthy controls (r = +0.93, p < 0.0001). The apparent lower AFC (11 vs 16, p = 0.13) and the higher frequency of low AFC (41% vs 22%, p = 0.29) in TA compared to controls did not reach statistical significance. Other hormones were similar in both groups (p > 0.05). Further evaluation of patients with TA with low AMH levels (< 1.0 ng/ml) versus normal AMH levels (> 1.0 ng/ml) revealed that the frequency of current disease activity (p = 1.0) and the median of erythrocyte sedimentation rate (p = 0.6), C-reactive protein (p = 0.4), prednisone cumulative dose (p = 0.8), and methotrexate cumulative dose (p = 0.8) were comparable in both groups. Cyclophosphamide use was reported in only 1 patient with reduced ovarian reserve, whereas none of the remaining patients received gonadotoxic drugs. CONCLUSION: To the best of our knowledge, our present study was the first to suggest that patients with TA may have diminished ovarian reserve.
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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 | 0.002 |
| 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".