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Record W1903784535 · doi:10.1186/cc4516

Cost-effectiveness analysis of recombinant activated factor VII as adjunctive therapy for bleeding control in severely injured trauma patients in Germany

2006· article· en· W1903784535 on OpenAlexaff
Rolf Rossaint, Peter Choong, Kenneth D Boffard, Bruno Riou, Sandro Rizoli, Yoram Kluger, Michael Cronquist Christensen, Rolf Lefering, Sara Morris

Bibliographic record

VenueCritical Care · 2006
Typearticle
Languageen
FieldMedicine
TopicHemophilia Treatment and Research
Canadian institutionsWomen's College HospitalSunnybrook Health Science Centre
FundersJapan Society for the Promotion of ScienceBundesministerium für Bildung und ForschungGovernment of the United KingdomEngineering and Physical Sciences Research CouncilLilly DeutschlandEli Lilly and Company
KeywordsMedicineIncidence (geometry)Acute respiratory distressRespiratory distressBlunt traumaCause of deathEmergency medicineSignificant differenceIntensive care medicineInternal medicineAnesthesiaSurgeryLung

Abstract

fetched live from OpenAlex

Uncontrollable bleeding is a leading cause of death in trauma patients and a major cause of preventable morbidity and mortality. Recombinant activated factor VII (rFVIIa) has been shown to decrease the need for red blood cell transfusion among severely injured blunt trauma patients. A significant difference in the incidence of acute respiratory distress syndrome was also observed relative to standard care together with a nonsignificant difference in mortality. While safety and efficacy of rFVIIa in trauma patients has been demonstrated, little is known about its cost-effectiveness.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.052
GPT teacher head0.388
Teacher spread0.336 · 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 designObservational
Domainnot available
GenreEmpirical

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
Published2006
Admission routes1
Has abstractyes

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