Impact of levothyroxine therapy on obstetric, neonatal and childhood outcomes in women with subclinical hypothyroidism diagnosed in pregnancy: a systematic review and meta-analysis of randomised controlled trials
Bibliographic record
Abstract
OBJECTIVE: To determine in women with subclinical hypothyroidism diagnosed in pregnancy whether levothyroxine treatment compared with control, impacts important obstetrical or childhood outcomes (specifically IQ) in randomised controlled trials. DESIGN: Systematic review and meta-analysis. STUDY ELIGIBILITY CRITERIA: Randomised trials which met all the following were included: (1) reported original data of women with subclinical hypothyroidism diagnosed in pregnancy (by any prespecified study definition); (2) randomised to either levothyroxine or control (placebo or no treatment); (3) reported obstetrical outcomes and/or childhood neurodevelopmental outcomes and (4) published from 1980 to January 2018 in either English or French language. DATA SOURCES: Medline, EMBASE, CINAHL, Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials and ClinicalTrials.gov. OUTCOME MEASURES: Cochrane Risk of Bias Tool (Modified) for Quality Assessment of Randomised Controlled Trials RESULTS: Three trials of low to unclear risk of bias with 1837 participants were included. Two studies were meta-analysed for maternal and neonatal outcomes and two studies for childhood IQ. No statistically significant differences were found for any clinical outcomes with levothyroxine therapy compared with control. LIMITATIONS: Only three trials were identified for inclusion. CONCLUSIONS: This review, based on three randomised trials in women with subclinical hypothyroidism diagnosed in pregnancy, found no evidence of benefit of levothyroxine therapy on obstetrical, neonatal, childhood IQ or neurodevelopmental outcomes. Current trial evidence does not support the treatment of subclinical hypothyroidism diagnosed in pregnancy. PROSPERO REGISTRATION NUMBER: CRD4201707980.
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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 | 0.019 | 0.053 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.024 | 0.034 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".