Functional ovarian reserve in women with Sickle Cell disease: A systematic review
Bibliographic record
Abstract
With the improvement in survival and the reduction in morbidity related to sickle cell disease (SCD), aspects related to reproductive health are emerging as a priority in the care of affected people. We conducted a systematic review looking for evidence describing the functional ovarian reserve levels in women with sickle cell disease. To locate studies, a search was performed in electronic databases, in addition to preprint servers and reference lists of selected publications. Two independent reviewers searched, and the risk of bias in the selected studies was assessed using the Newcastle-Ottawa scale. 1,086 records were initially retrieved, and one article was identified after consulting the reference lists of the screened articles, only four articles met the eligibility criteria. The quality of evidence was rated very low due to the design of the studies; however, the risk of bias was considered low. These are recent studies published between 2015 and 2021, whose main methodology was a cross-sectional or case-control study. All studies reported lower anti-mullerian hormone levels in women with sickle cell disease. Although lower, anti-mullerian hormone levels were within the normal range in young women with sickle cell disease only with supportive care, in those who used hydroxyurea, a decrease in ovarian reserve was observed. support insufficient evidence support a causal relationship between sickle cell disease and reduced ovarian reserve. From anti-mullerian hormone values a trend towards lower levels in women with sickle cell disease compared to healthy women, as reported in the four studies evaluated. Studies that analyze the ovarian reserve based on imaging and biochemical parameters are an important future focus.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".