Evaluation of pooled cultures for bacterial detection in whole blood–derived platelets
Bibliographic record
Abstract
BACKGROUND: The BacT/ALERT (bioMérieux) system is highly efficient for bacterial detection in apheresis platelets (PLTs) and whole blood-derived PLTs produced by the buffy-coat method. Detection of bacterial contamination in whole blood-derived PLTs produced by the PLT-rich plasma (PRP) method, however, is problematic. Prestorage pooling of these PLTs is not permitted in some countries including Canada and the United States, and culturing individual units is costly and may significantly reduce the PLT unit content. In this study, the sensitivity and specificity of BacT/ALERT cultures performed on pools derived from PRP PLTs are reported. STUDY DESIGN AND METHODS: The sensitivity of the BacT/ALERT system was evaluated for bacterial detection in PRP PLTs with a dilution effect. Thirty PLT pools were produced with 1 PLT unit previously spiked with bacteria and then pooled with other four nonspiked PLT units. Three bacteria, usually associated with PLT contamination, were selected for spiking. The specificity of this method was evaluated in 40 nonspiked PLT pools. RESULTS: The method was found to be 100 percent specific and 97 percent sensitive. Of the five spiked pools with Streptococcus pneumoniae at levels of less than 2 colony-forming units (CFUs) per mL, four were found to be positive whereas all 25 spiked pools with greater than 9 CFUs per mL of any of the chosen bacteria gave positive results. The mean time of detection was 17 to 19 hours for Staphylococcus epidermidis and 14 to 15 hours for S. pneumoniae and Pseudomonas aeruginosa when spiked with similar bacterial inocula. CONCLUSION: The evaluated system is highly sensitive and specific and may be a feasible method for bacterial detection in PRP PLTs.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".