MétaCan
Menu
Back to cohort
Record W2888790762 · doi:10.14745/ccdr.v40i18a01

A summary of the Transfusion Error Surveillance System: 2008 - 2011

2014· article· en· W2888790762 on OpenAlexafffundvenueabout
A. Mounchili, S Leduc, Chris Archibald, J Miller, C Hyson

Bibliographic record

VenueCanada Communicable Disease Report · 2014
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsPublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsMedicineBlood transfusionEmergency medicineTransfusion reactionAdverse effectBlood productAgency (philosophy)Medical emergencyIntensive care medicineSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Although Canada has one of the safest blood systems in the world, transfusion errors can occur at any time from the moment of collection through to the transfusion of blood and blood products. The Transfusion Error Surveillance System (TESS) was initiated by the Public Health Agency of Canada (the Agency) to monitor transfusion-related errors occurring at any point in the transfusion chain. OBJECTIVE: To offer an analysis of the TESS data reported from 2008 to 2011. METHODS: Between 2008 and 2011, 12 to 15 hospitals from four provinces participated in the TESS. Reports on all transfusion-related errors were sent electronically on a quarterly basis to the Agency where they were consolidated, cleaned, validated and analyzed. Different types of transfusion errors were categorized by time of discovery (pre- or post-transfusion) and their potential impact on the patient's health. The occurrence rates of different types of errors were calculated using corresponding denominator data. Results were grouped by the transfusion capacity of reporting hospitals. RESULTS: Between 2008 and 2011, a total of 34,088 transfusion-related errors were reported. Of these, 33,622 (98.6%) were detected prior to transfusion. The most commonly reported were errors related to the collection (40.1%) and handling (10.4%) of blood samples. Of the remaining 466 (1.4%) that were detected after transfusion, 66 were of high potential severity and 16 of them resulted in adverse reactions in recipients. Inappropriate / incorrect / no product order accounted for over 56% (n=9) of these errors and the most common adverse reaction was transfusion-associated circulatory overload which occurred in eight (50%) of the patients that developed adverse reactions. CONCLUSION: The TESS data from 2008 to 2011 demonstrates that blood transfusions are both safe and efficient in Canadian hospitals participating in the surveillance and also highlights the most common and most harmful errors that may be targeted for corrective actions.

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)0.004
metaresearch head score (Gemma)0.015
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: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.572
Threshold uncertainty score0.850

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.015
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0080.011
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.012
GPT teacher head0.222
Teacher spread0.210 · 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

Citations2
Published2014
Admission routes4
Has abstractyes

Explore more

Same venueCanada Communicable Disease ReportSame topicBlood transfusion and managementFrench-language works237,207