The efficacy of the non‐stress test in preventing fetal death in post‐term pregnancy
Bibliographic record
Abstract
We conducted a case--control study to examine the efficacy of non-stress testing in preventing fetal death in post-term pregnancy. The analysis was based on data from the 1988 National Maternal and Infant Health Survey, which was a nationally representative sample of live births, fetal deaths and infant deaths that occurred in 1988. Information on whether a woman had non-stress testing was obtained from a questionnaire sent to prenatal care providers and hospitals. Cases were post-term women (with 42 weeks or more gestation) who had fetal deaths. Three post-term controls, who had live births and who delivered at the same time or later than the cases, were randomly chosen and individually matched to each case by maternal race. The proportion of women who had one or more non-stress tests during pregnancy was compared between cases and controls. Non-stress testing was used in 30.9% of the 126 cases and in 28.5% of the 375 controls. The race-adjusted odds ratio for exposure to non-stress test was 1.12 [95% CI 0.72, 1.75]. After controlling for other important confounding variables the odds ratio was 1.05 [95% CI 0.57, 1.91]. These results do not support the efficacy of non-stress testing in post-term pregnancies. A more detailed evaluation of this widely used screening procedure is needed.
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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 | 0.006 | 0.022 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".