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Safe and Successful Restriction of Transfusion in Burn Patients

2006· article· en· W2058752319 on OpenAlexaff
Peter Kwan, Manuel Gómez, Robert Cartotto

Bibliographic record

VenueJournal of Burn Care & Research · 2006
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineBurn centerIncidence (geometry)Blood transfusionRetrospective cohort studySurgeryAnesthesiaBed restHemoglobinMyocardial infarctionInternal medicineEmergency medicinePoison control

Abstract

fetched live from OpenAlex

An acceptable strategy for transfusion of burn patients has not been specifically identified. In 1999, we empirically adopted a hemoglobin (Hb) transfusion trigger of 7.0 g/dl or greater in our burn center. The purpose of this study was to evaluate the effects of this restrictive transfusion strategy. Retrospective comparison of adults with 20% or greater TBSA treated from 1999 to 2004 (restrictive group; REST) with patients treated before our adoption of the restrictive transfusion strategy (1997-1998: liberal group; LIB). The REST group (n = 135, age 42 +/- 17 years, %TBSA burn 37 +/- 14, and 26% incidence of inhalation injury) did not differ significantly from the LIB group (n = 37, age 42 +/- 16 years, %TBSA burn 38 +/- 17, and 35% inhalation injury). The Hb triggering a transfusion was 7.1 +/- 1.2 g/dl in the REST group, compared with 9.2 +/- 2.1 g/dl in the LIB group (P < .001). The REST group received significantly fewer units of blood per day than the LIB Group. Patients in the REST group appeared to have significantly better organ function, and there were no differences between the groups in the incidence of acute myocardial infarction. Mortality at 30 days was significantly lower in the REST group (19% vs 38%; P = .03), as was overall in-hospital mortality (22% vs 46%; P = .003). Transfusion restriction appears to be safe and resulted in fewer transfusions among this group of burn patients. Prospective studies are needed before broadly recommending a transfusion trigger of 7.0 g/dl.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.245

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.349
Teacher spread0.323 · 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 teacher head, 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

Citations59
Published2006
Admission routes1
Has abstractyes

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