Bacterial growth in red blood cell units exposed to uncontrolled temperatures: challenging the 30‐minute rule
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The '30-min rule' requires discarding red blood cells (RBCs) exposed to uncontrolled temperatures for >30 min to ensure safe RBC transfusion. This study was aimed at determining whether multiple room temperature (RT) exposures promote bacterial growth. MATERIALS AND METHODS: Pooled and split RBC units were inoculated with ~1 CFU/ml of Serratia marcescens, Yersinia enterocolitica, Escherichia coli or Staphylococcus epidermidis. Control units remained in storage, while test units were exposed to RT for six 30-min or three 60-min intervals. Bacterial concentrations and endotoxin levels were determined after each exposure and at 42 days of storage. RBC core temperature and RT were monitored in mock units with Escort iLog temperature loggers. A mixed model was used for statistical analyses. RESULTS: Red blood cell core temperature reached 10.7 ± 0.4°C and 14.2 ± 0.2°C during 30- and 60-min exposures, respectively. Staphylococcus epidermidis and E. coli did not grow in either control or exposed RBCs. Yersinia enterocolitica concentration and endotoxin levels were similar in both control and test units. Serratia marcescens concentration and endotoxin levels were higher in exposed units; however, differences between units exposed for 30 min or 60 min were not observed. CONCLUSION: There is no added risk to RBC safety by increasing RT exposures to 60 min with each removal from storage for up to a total of 3 h during RBC shelf life. Therefore, extending the 30-min limitation in RBCs exposed to uncontrolled temperatures to 60 min should be considered by regulatory agencies.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".