Impact of frequent premature ventricular contractions on pregnancy outcomes
Bibliographic record
Abstract
OBJECTIVES: To determine cardiac and fetal/neonatal event rates among pregnant women with premature ventricular contractions (PVCs) and compare with control groups. METHODS: Prospective case-control cohort study: 53 consecutive pregnancies in 49 women referred to the St. Paul's Hospital between 2010 and 2016 with PVC burden >1% in women without underlying cardiac disease. Maternal cardiac and fetal/neonatal outcomes were compared with two pregnant control groups: (1) supraventricular tachycardia (SVT) group of 53 women referred for a history of SVT/SVT in the current pregnancy and (2) low-risk group of 53 women with no cardiac disease. RESULTS: The maximal PVC burden was 9.2% (range 1.1%-58.7%). Six of 53 (11%) pregnancies were complicated by a maternal cardiac event: heart failure n=1 and sustained ventricular tachycardia requiring therapy n=5 as compared with no cardiac events in both control groups. All women with an adverse event had a PVC burden >5%. Seven (13%) pregnancies were complicated by an adverse fetal and/or neonatal event and this was similar to the normal control group (5 (9%), P=0.45) and significantly less than the SVT group (16 (30%), P=0.03). The adverse fetal event was driven by small for gestational age neonates and preterm delivery. CONCLUSIONS: In our cohort of pregnant women with a structurally normal heart and 'high' PVC burden, we found an adverse maternal event rate of 11%, and all events were successfully managed with medical therapy. The rate of adverse fetal events in the PVC group was similar to the normal control group.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 |
| 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".