Fatal false‐negative transfusion infection involving a buffy coat platelet pool contaminated with biofilm‐positive <i>Staphylococcus epidermidis</i>: a case report
Bibliographic record
Abstract
BACKGROUND: Bacterial contamination of platelet concentrates (PCs) poses the major posttransfusion infectious risk in developed countries. The aerobic microorganism most frequently isolated from PCs is coagulase-negative Staphylococcus epidermidis, a normal inhabitant of the human skin, which has been involved in fatal transfusion reactions worldwide. CASE REPORT: In September 2014, a splenectomized elderly male patient, suffering from leukemia, was transfused with two 5-day-old buffy coat platelet (PLT) pools. The patient returned to emergency on the same day with a low-grade fever. He was bacteremic and died on the next day. Microbiology and molecular testing of a blood sample from the patient and one of the PCs yielded the same S. epidermidis strain. Further analysis demonstrated that this S. epidermidis isolate displays a biofilm-positive phenotype in PCs. DISCUSSION: At Canadian Blood Services, PCs are screened for bacterial contamination with the BacT/ALERT system (bioMérieux) at approximately 24 hours postcollection. The implicated PC had been tested and yielded a false-negative culture result. A titration experiment indicated that, at the time of screening, the contaminated PC had a titer of less than 0.74 colony-forming units (CFU)/mL (<227 CFUs/unit) of S. epidermidis. Mathematical models have predicted that up to 70% of PCs contaminated with coagulase-negative staphylococci at concentrations of 0.02 CFU/mL can be missed by BacT/ALERT screening. CONCLUSION: Despite several mitigation strategies, false-negative cultures with current PLT screening practices still occur. This report creates awareness of the pathogenicity of opportunistic S. epidermidis, a low-virulence organism, in susceptible patients who may not develop a typical transfusion reaction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.007 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".