Fibrinogen estimates are influenced by methods of measurement and hemodilution with colloid plasma expanders
Bibliographic record
Abstract
BACKGROUND: Measurement of plasma fibrinogen is often required in critically ill patients or massively bleeding patients being resuscitated with colloid plasma expander. This study aimed at evaluating different assays of plasma fibrinogen after in vitro dilution with commonly used plasma expanders and challenged the hypothesis that levels of fibrinogen are estimated significantly higher in plasma diluted with colloid plasma expander compared with isotonic saline. STUDY DESIGN AND METHODS: Fibrinogen measurements were established in plasma samples each diluted in vitro to 30 or 50% with isotonic saline, hydroxyethyl starch (HES) 130/0.4, and human albumin. Fibrinogen levels were assessed using an antigen determination, three photo-optical Clauss methods, one mechanical Clauss method, a prothrombin-derived method, and viscoelastic measurement through thromboelastometry. RESULTS: Measurement of fibrinogen levels was significantly different when performed on alternate analytical platforms. By 30 and 50% dilution with HES 130/0.4 coagulation analyzers using the photo-optical Clauss methods significantly overestimated levels of fibrinogen. Dilution with human albumin did not affect fibrinogen levels except from one analyzer by 50% dilution level. Viscoelastic measurement of fibrin polymerization was reduced at both dilution levels and appeared to reflect the impairment of fibrin polymerization induced by HES 130/0.4 and to a lesser extent human albumin. CONCLUSION: This study demonstrated that different automated coagulation analyzers revealed significantly different levels of fibrinogen. The presence of colloid plasma expander gave rise to erroneous high levels of fibrinogen returned from some coagulation analyzers employing the method of Clauss.
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".