MétaCan
Menu
Back to cohort
Record W2418396004

Incidence and significance of the bacterial contamination of blood components.

2002· article· en· W2418396004 on OpenAlexaff
MA Blajchman

Bibliographic record

VenuePubMed · 2002
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsMcMaster University
Fundersnot available
KeywordsSepsisBlood productMedicinePlateletPlatelet transfusionTransfusion reactionBlood transfusionIncidence (geometry)BacteriaBacteremiaIntensive care medicineImmunologyBiologySurgeryAntibioticsMicrobiology
DOInot available

Abstract

fetched live from OpenAlex

A septic reaction occurring during or following the transfusion of cellular blood components was one of the earliest recognized complications of allogeneic blood transfusions. The presence of bacteria in blood products has been a problem for many decades and currently it is probably the most common microbiological cause of transfusion-associated morbidity and mortality. Transfusion-associated sepsis due to contaminated platelet concentrates appears to be much more common than those due to red cells. The overall prevalence of contaminated cellular blood products (red cells and platelets) is approximately one in 3000; however, the transfusion to a recipient of a contaminated blood product may not necessarily be associated with clinically evident morbidity. This is because the majority of contaminated blood product units contain only few bacteria. In other instances, contaminated units may contain large numbers of virulent bacteria as well as endotoxins, and their transfusion may be associated with significant morbidity and even be lethal to the recipient. The prevalence of severe episodes of transfusion-associated sepsis has not been clearly established, but is probably of the order of one in 50,000 per platelet unit and one in 500,000 per red cell unit transfused. As a result of the increased recognition that such transfusion-associated episodes can occur, a variety of measures have been proposed to try to prevent and/or control the risk of transfusion-associated septic reactions.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.761
Threshold uncertainty score0.100

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.024
GPT teacher head0.200
Teacher spread0.176 · 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

Citations87
Published2002
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicBlood transfusion and managementFrench-language works237,207