Mechanical heart valves and pregnancy: Issues surrounding anticoagulation. Experience from two obstetric cardiac centres
Bibliographic record
Abstract
BACKGROUND: Pregnant women with mechanical heart valves are at significant risk of obstetric/cardiac complications. This study compares the anticoagulation management in two obstetric cardiac centres. METHODS: Retrospective case-note review from Chelsea and Westminster/Royal Brompton Hospitals (CR) and Erasmus Medical Centre (EMC). Main outcome measure was mechanical heart valve thrombosis. RESULTS: Nineteen pregnancies from CR and 25 pregnancies from EMC were included. Most women were on low-molecular-weight heparin (LMWH) throughout pregnancy at CR, whereas at EMC most had LMWH in the first trimester and vitamin K antagonists in subsequent trimesters. Peak anti-factor Xa were performed monthly at CR, levels 0.39-1.51 IU/mL (mean 0.82 IU/mL). Anticoagulation management peri-partum was inconsistent. Delivery was mainly by caesarean section at CR (74%) and vaginal delivery at EMC (64%). No maternal deaths and only one mechanical heart valve thrombosis at CR. Two mechanical heart valve thromboses and one maternal death at EMC. CONCLUSION: Peri-partum anticoagulation strategies, anticoagulation monitoring and mode of delivery inconsistencies reported.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".