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Record W4417013939 · doi:10.1182/blood-2025-1348

The score settles it? maybe not: Navigating postpartum VTE prophylaxis

2025· article· en· W4417013939 on OpenAlexaboutno aff
Jennifer McIntosh, Kristen Corrao, Faisal Shahjehan, Ryan Hanson, Lisa Baumann Kreuziger

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicVenous Thromboembolism Diagnosis and Management
Canadian institutionsnot available
Fundersnot available
KeywordsIncidence (geometry)PregnancyMedical historyRisk factorFamily historyCohortGestationPostpartum period

Abstract

fetched live from OpenAlex

Abstract Background: The risk of venous thromboembolism (VTE) increases during pregnancy and continues to rise throughout pregnancy with maximum risk in the postpartum period. The guidelines that stratify patients into VTE risk categories are conflicting. Aims: (1) Evaluate the incidence of postpartum VTE (VTE within 3 months of delivery) over 1 year. (2) Determine the number of patients that would have received VTE prophylaxis based on different society recommendations. (3) Determine the number of patients with VTE that would possibly been prevented with different society recommendations. Methods: Characteristics of 3190 patients who underwent delivery at our medical center were investigated for incidence and risk factors for VTE. Data was collected using the International Classification of Diseases codes and by chart review. Descriptive statistics were calculated. Results: The incidence of postpartum VTE in our patient cohort (n=3190) was 0.25% (8/3190). Most patients were aged ≥30 (66.6%), white (61%) and had BMI >30 (61.1%). The number of patients who had previous history of cancer, lupus, inflammatory bowel disease and sickle cell disease were 77 (2.4%), 12 (0.4%), 25 (0.8%), and 2 (0.1%), respectively. Sixteen (0.5%) patients had a history of provoked VTE, and 76 (2.4%) patients had a family history of VTE. The proportion of patients who had cesarean delivery, postpartum hemorrhage, pre-eclampsia, and multiple gestation pregnancy were 571 (17.9%), 340 (10.7%), 295 (9.2%), and 40 (1.3%), respectively. 46 (1.4%) patients had prolonged hospitalization of >3 days, who were deemed to have decreased mobility, which is an important risk factor for VTE. Mechanical prophylaxis was used postpartum in 465 patients (14.4%), low molecular weight heparin in 55 patients (1.7%), and other anticoagulation in 20 patients (0.6%). Two of the patients with a VTE event within 90 days postpartum received prophylaxis in our cohort. The percentage of patients who would have received pharmacologic VTE prophylaxis based on Royal College of Obstetricians and Gynecologists (RCOG) risk factors criteria, Society of Obstetricians and Gynaecologists of Canada (SOGC), and ’Eubanks’ risk scoring criteria was 61.3% (n=1954), 33.8% (n=1077), and 15% (n=513), respectively. RCOG predicted 7 of the 8 VTE events compared to only 2 of the VTE events predicted by Eubanks. Sensitivity of RCOG was high at 87.5% whereas specificity of Eubanks was high at 0.84. SOGC predicted 4 of the VTE events with a specificity of 0.67 and sensitivity of 0.50. Conclusion: The number of postpartum patients recommended to receive peripartum anticoagulation varies widely depending on the risk scoring tool employed. Optimized risk stratification for peripartum VTE prophylaxis is needed.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.040
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.007
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.040
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.013
GPT teacher head0.280
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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