Investigating the relationship between thyroid hormones with the risk level screening tests in the first trimester of pregnancy in hypothyroid women: A case-control study
Bibliographic record
Abstract
Abstract Background The aim of this study was to assess the association between T3, T4, FT3, FT4, TSH, Anti TPO, Free BhCG, B-MOM, P-MOM, and NT-MOM with the risk level of screening tests in the first trimester of pregnancy in hypothyroid and control women. Methods In this case-control study, 82 pregnant women were enrolled. The ELISA method was performed to evaluate the serum levels of T3, free T3, T4, free T4, TSH, and Anti TPO, and the first stage of fetal screening tests including Free BhCG, B-MOM, P-MOM, NT-MOM were done by Electro-chemiluminescent (ECL) method., and finally data analysis was performed with SPSS statistical software. Results The average levels of TSH (p-value = 0.001), TPO (p-value = 0.006), trisomy 21 (p-value < 0.001), and trisomy 13/18 (p-value < 0.001) in the intervention group were significantly higher and PAPP-A was significantly (p-value < 0.001) lower than control group; However, there was no statistical difference between the intervention and control groups in terms of the mean levels of beta-hCG (p-value = 0.297), B-MoM (p-value = 0.202), and NT-MoM (p-value = 0.221). Also, in the intervention with levothyroxine group, the mean serum TSH level was significantly higher in the screen positive group and the medium risk group of DS than the negative screen group (p-value = 0.014). Conclusion: It is suggested to identify hypothyroid pregnant mothers early and make it mandatory to perform timely fetal health screening tests in the first trimester of pregnancy in this group of mothers, with the aim of identifying fetuses at risk of developing chromosomal disorders. This should be the priority of maternal health policy makers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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) | 0.002 | 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".