Rapid detection of fibrinolytic activation in postpartum hemorrhage and acute obstetric coagulopathy using a novel assay
Bibliographic record
Abstract
ABSTRACT: Postpartum hemorrhage (PPH) remains the leading cause of pregnancy-related mortality worldwide. Regardless of the initiating cause, continued bleeding may progress to a systemic coagulopathy. This coagulopathy may be complicated further by profound fibrinolytic activation that progresses to systemic hyperfibrinolysis, a condition that we have termed acute obstetric coagulopathy (AOC). Patients with placental abruption or amniotic fluid embolism are among those at highest risk for AOC. In response to the unmet need for a rapid method to detect fibrinolytic activation in this scenario, we developed a novel assay that we have termed the fibrinolytic activity screening test (FAST). This assay measures endogenously generated plasmin activity in plasma within 5 minutes. Its high sensitivity for the detection of in vivo fibrinolytic activation was confirmed by strong correlation with elevated plasmin-antiplasmin (PAP) complex levels. We analyzed archived plasma samples from 33 women with PPH and 20 pregnant women just before elective cesarean delivery. Of the 33 patients with PPH, 12 had PAP complex levels >25 000 ng/mL, thereby meeting criteria for the diagnosis of AOC. Plasmin activity measured by the FAST assay differentiated AOC from non-AOC PPH (P = .0007) and from pregnant non-PPH control groups (P< .0001) and was strongly correlated with both PAP complex and D-dimer levels. Among patients with PPH for whom viscoelastic whole blood testing (ROTEM) was performed, none of the 18 without AOC or 9 of those with AOC had evidence of ROTEM-defined hyperfibrinolysis. The FAST assay is a rapid tool to detect activation of fibrinolysis associated with AOC in women after delivery.
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 | 0.002 |
| 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".