Association of thyroid function test abnormalities with preeclampsia: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Preeclampsia is a life-threatening disorder during pregnancy and postpartum periods. Preeclampsia can affect the activity of many organs. It is very important because if this disorder is associated with changes in thyroid function, it can affect the results of maternal and fetal tests. Accordingly, the aim of this meta-analysis study was to assess the abnormalities in thyroid function tests in preeclampsia. METHODS: Studies were selected through a systematic search of the MEDLINE/PubMed, Scopus, Web of Science Core Collection, and Google Scholar databases in 31st August 2021. Also, reference lists of review articles and relevant studies were manual-searched to identify other potentially eligible studies. English studies that compared TSH, T4 and T3 of normal pregnant with preeclamptic women (Known to be normotensive before pregnancy; gestational age 20 week or more; singleton pregnancy; no previous history of thyroid dysfunction) were screened. Data sets were screened for eligibility by two independent reviewers. Articles were assessed by the Newcastle-Ottawa Scale. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used for quality assessment of evidence on outcome levels. RESULTS: After reviewing 886 published studies, 63 observational studies were selected and used for this meta-analysis. The study population included 21,528 pregnant women. The findings revealed that TSH (SMD = 1.70, 95%CI: 1.39 to 2.02; p < 0.001) was significantly higher in preeclamptic women. TT4 (SMD = -0.82, 95%CI: -1.16, -0.49; p < 0.001), TT3 (SMD = -0.88, 95%CI: -1.36 to -0.41; p < 0.001) and FT3 (SMD = -0.59, 95%CI: -0.91 to -0.27; p < 0.001) were less in preeclamptic women. There was no statistically significant difference in FT4 between two groups (SMD = 0.002, 95%CI: -0.27 to 0.27; p = .990). The results of publication bias and sensitivity analysis confirmed the reliability and stability of this meta-analysis. The quality of evidence was regarded as moderate, low, and very low for these risk factors according to the GRADE approach. CONCLUSIONS: Findings of this meta-analysis indicated preeclamptic women were more at risk of changes in thyroid function tests. In order to prevent thyroid disorders, it is recommended that thyroid function tests be performed in women with pre-eclampsia.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.040 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".