Assessment of clinical probability scores for pulmonary embolism diagnosis during pregnancy and postpartum in women with a history of venous thromboembolism: a Highlow ancillary study
Bibliographic record
Abstract
Background: The value of pretest clinical probability scores in the diagnosis of pulmonary embolism (PE) during pregnancy and postpartum is unknown in women with a history of venous thromboembolism (VTE). Objectives: We evaluate the modified Wells, revised Geneva, and pregnancy-adapted Geneva (PAG) scores for the diagnosis of PE during pregnancy and the postpartum period in women with a history of VTE. Methods: Data from a multicenter randomized trial (Highlow) including 1110 pregnant women with a history of VTE and treated with either weight-adjusted intermediate-dose or fixed low-dose low-molecular-weight heparin subcutaneously once daily until 6 weeks postpartum were used. The modified Wells, revised Geneva, and PAG scores were calculated retrospectively in all women with a clinical suspicion of PE, and their discriminative capacity was assessed. Receiver operating characteristic (ROC) curve analysis was performed for quantitative variables and the optimal threshold defined. Results: There were 102 suspected cases of PE, of which 12 were confirmed events. During pregnancy, the ROC curves showed an area under the curve of 0.68, 0.33, and 0.36 for the Wells, Geneva, and PAG scores, respectively. During postpartum, the ROC curves showed an area under the curve of 0.75, 0.55, and 0.52 for the Wells, Geneva, and PAG scores, respectively. Conclusion: The 3 pretest clinical scores have modest discriminatory power, during both the antepartum and the postpartum period, to classify patients into 3 categories of pretest clinical probability. Further work is required to develop clinical-decision tools to exclude imaging in pregnant women with prior VTE with suspected PE in pregnancy.
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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".