Two‐year experience with aerobic culturing of apheresis and whole blood–derived platelets
Bibliographic record
Abstract
BACKGROUND: Throughout its system of regional centers, Blood Systems implemented culture based bacterial testing with a standardized protocol for both apheresis and whole blood-derived platelets (PLTs). STUDY DESIGN AND METHODS: After a 24-hour hold, 4 mL of PLT product was inoculated into an aerobic bottle (BacT/ALERT, bioMérieux). Cultures were incubated for 24 hours before routine product release to prevent distribution of infected products while minimizing consignee notification, product retrievals, and hospital PLT inventory problems. Initial-positives were further tested (and bacteria identified) by performing cultures from the original component and subcultures from the BacT/ALERT bottle. Results were categorized according to AABB recommended definitions with minor modifications. RESULTS: The rate of true-positive detections from culturing 122,971 apheresis PLTs was 0.017 percent (95% confidence interval [CI], 0.011%-0.026%). All true-positive microorganisms were Gram-positive with a predominance of coagulase-negative Staphylococcus and Bacillus species. Twenty of the 21 true-positive samples (95%) were detected by 24 hours but only 14 (68%) were detected by 18 hours. The false-positive rate due to contamination was 0.1 percent with the majority of isolates being skin or environmental organisms. Results did not differ significantly for whole blood-derived versus apheresis PLTs. CONCLUSION: These data corroborate the fact that the rate of detection of truly contaminated PLT apheresis products in the United States is approximately 1 in 5000 (0.02%); this is lower than the 0.03 to 0.05 percent rates that were generally quoted in the literature before the implementation of prospective bacterial culturing programs.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
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".