The impact of endometriosis on embryo implantation in IVF procedures
Bibliographic record
Abstract
Embryo implantation is the most important event in the achievement of conception. In the presence of any endometrial disease, this process can be hampered. The endometriosis is linked to causing infertility. It is a chronic uterine disease that is dependent on estrogens and is associated with reduced fecundity. The objective of this study was to investigate the impact of endometriosis on embryo implantation in patients undergoing IVF. This is a case-control study, with case to control ratio of 5:1. The study included 50 patients with endometriosis and 10 patients without endometriosis served as control. The endometriosis was diagnosed by symptoms, pelvic and transvaginal ultrasound examinations. The serum estrogen levels, fertilization rate and implantation rate were determined. Since the presence of a haemorrhagic cyst was suspected at the ultrasonographic finding of masses parallel to the ovaries, measurement of the CA 125 marker was carried out for differential diagnosis. The data were recorded in Excel sheets and analysed using statistical functions of Excel. The significance level was set at 0.05%. Most of the patients in endometriosis group (68%) had elevated CA125 Levels and 56 % had high E 2 level. In the control, only one patient had high E2 level. In the endometriosis group, 31.67% had positive pregnancy test, while 90% patients without endometriosis had positive pregnancy test. These differences were statistically significant. These data reveal that the patients with endometriosis had significantly higher levels of E2 and CA125 marker in blood and had significantly lower implantation rates as compared to those in the control group.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".