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Record W4407378321 · doi:10.1111/vox.13806

Preliminary determination of bacterial contamination of whole blood units in a Ghanaian blood bank: Providing evidence to improve transfusion safety

2025· article· en· W4407378321 on OpenAlexaff
Nana Benyin Aidoo, Sandra Ramírez‐Arcos, L. Gillard, Daniel Azumah, Angela Adatsi

Bibliographic record

VenueVox Sanguinis · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood transfusion and management
Canadian institutionsCanadian Blood ServicesUniversity of Ottawa
Fundersnot available
KeywordsSerratia marcescensStaphylococcusCitrobacter freundiiContaminationMicrobiologyMedicineCitrobacterSerratiaEnterobacterCoagulaseBacteriaAntibioticsAntimicrobialAntibiotic resistanceProvidenciaStaphylococcus aureusBiologyEnterobacteriaceaeEscherichia coliPseudomonas

Abstract

fetched live from OpenAlex

BACKGROUND AND OBJECTIVES: Transfusion-associated bacterial sepsis poses a significant risk to patient safety. This study aimed to determine the rate of bacterial contamination of whole blood (WB) collected at the Cape Coast Teaching Hospital (CCTH) as a quality control and quality assurance activity. MATERIALS AND METHODS: One-hundred and three WB units collected between January and April of 2018 were screened for bacterial contamination. Bacteria isolated from positive cultures were identified and subjected to antimicrobial testing. WB recipients were followed up for clinical symptoms. RESULTS: Of the 103 WB units tested, 33 (32%) were contaminated with bacteria. Gram-positive organisms accounted for 67% of the isolates, including coagulase-negative Staphylococcus, Staphylococcus aureus and Bacillus spp., while Gram-negative bacteria comprised 33% of the isolates, with Citrobacter freundii, Serratia marcescens, Escherichia coli and Providencia stuartii being identified. Resistance to antibiotics varied between species. No septic transfusion events were reported involving WB units tested in this study. CONCLUSION: The high percentage of contaminated WB units collected at the CCTH provided evidence-based data for the implementation of improved donor skin disinfection processes and the use of blood diversion pouches in 2019. These approaches allowed CCTH to comply with Ghanaian regulatory entities.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.171
Threshold uncertainty score0.647

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 head0.016
GPT teacher head0.273
Teacher spread0.257 · 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 designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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