Maternal anxiety associated with fetal echocardiography
Bibliographic record
Abstract
Background: Women awaiting fetal echocardiography (fECHO) report high anxiety. It is unclear if anxiety decreases after performance of fECHO. Methods: At fECHO, subjects’ current (state) vs baseline (trait) anxiety was assessed using the Spielberger State-Trait Anxiety Inventory. Anxiety scores of the pre- and post-fECHO groups were compared. Results: From January 2007 to January 2009, we recruited 84 subjects: 40 pre-fECHO and 44 post-fECHO. Of the post-fECHO group, 30 had normal fetal cardiac structure and function confirmed, 12 were told of an abnormality, and 2 were told to follow up equivocal results. Anxiety scores were compared between the 40 pre-fECHO subjects and the 30 post-fECHO subjects with normal results. The mean state anxiety score of the pre-fECHO group was higher than that of the post-fECHO group (42.1 ± 15.1 vs 30.8 ± 8.5, p < 0.001); there was no difference in trait scores. Neither state nor trait anxiety was associated with maternal age, parity, history of miscarriage or known fetal anomaly. Compared to those with a normal fECHO (N = 30), subjects with an abnormal fECHO result (N = 12) had higher state anxiety (46.8 ± 15.5 vs 30.8 ± 8.5, p = 0.005). There was no difference in anxiety scores between subjects awaiting fECHO and post-fECHO subjects who had an abnormal result. Conclusion: Immediately following normal fECHO, women report low anxiety compared with women awaiting fECHO. Women awaiting fECHO report anxiety levels that are as high as women who are told there is fetal cardiac anomaly.
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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 | 0.000 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".