MANAGEMENT OF ENDOCRINE DISEASE: The impact of subclinical hypothyroidism on anthropometric characteristics, lipid, glucose and hormonal profile of PCOS patients: a systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVE: Subclinical hypothyroidism (SCH) is encountered in 10-25% of women with PCOS. To date, it remains unclear whether this coexistence influences the severity of metabolic and hormonal profile of these patients. The purpose of our systematic review is to investigate this potential relation. METHODS: We systematically searched Medline, Scopus, ClinicalTrials.gov, Cochrane Central Register of Controlled Trials (CENTRAL) and Google Scholar databases together with reference lists from included studies. All prospective and retrospective observational cohort studies that investigated the impact of subclinical hypothyroidism on hormonal and metabolic parameters of PCOS patients were included. The methodological quality of studies was assessed with the Ottawa-Newcastle criteria. Statistical meta-analysis was performed with the RevMan 5.3 software. RESULTS: Twelve studies were finally included in the present review, which enrolled 2341 PCOS patients. Among them, 577 had subclinical hypothyroidism, whereas the remaining 2077 were PCOS women with normal thyroid function. The presence of SCH significantly affected HDL (MD -3.92 mg/dL 95% CI: -6.56, -1.29) and triglycerides levels (26.91 mg/dL 95% CI: -3.79, 50.02). HOMA-IR was also affected (MD 0.82 95% CI: 0.15, 1.50). On the other hand, LDL, fasting glucose and 2-h OGTT were not influenced. Similarly, prolactin, FSH, LH, LH/FSH ratio and sex hormone-binding globulin remained unaffected. CONCLUSION: Subclinical hypothyroidism does not influence the hormonal profile of women with PCOS. On the other hand, it results in mild metabolic abnormalities, which are not clinically important in a short-term setting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| 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) | 0.000 | 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".