Evaluating the 4‐hour and 30‐minute rules: effects of room temperature exposure on red blood cell quality and bacterial growth
Bibliographic record
Abstract
BACKGROUND: A 30-minute rule was established to limit red blood cell (RBC) exposure to uncontrolled temperatures during storage and transportation. Also, RBC units issued for transfusion should not remain at room temperature (RT) for more than 4 hours (4-hour rule). This study was aimed at determining if single or multiple RT exposures affect RBC quality and/or promote bacterial growth. STUDY DESIGN AND METHODS: Growth and RT exposure experiments were performed in RBCs inoculated with Serratia liquefaciens and Serratia marcescens. RBCs were exposed once to RT for 5 hours (S. liquefaciens) or five times to RT for 30 minutes (S. marcescens) with periodic sampling for bacterial counts. Noncontaminated units were exposed to RT once (5 hr) or five times (30 min each) and sampled to measure in vitro quality variables. RBC core temperature was monitored using mock units with temperature loggers. Growth and RT exposure experiments were repeated three and at least six times, respectively. Statistical analysis was done using mixed-model analysis. RESULTS: RBC core temperature ranged from 7.3 to 11.6°C during 30-minute RT exposures and the time to reach 10°C varied from 22 to 55 minutes during 5-hour RT exposures. RBC quality was preserved after single or multiple RT exposures. Increased growth of S. liquefaciens was only observed after 2 hours of continuous RT exposure. S. marcescens concentration increased significantly in multiple-exposed units compared to the controls but did not reach clinically important levels. CONCLUSION: Single or multiple RT exposures did not affect RBC quality but slightly promoted bacterial growth in contaminated units. The clinical significance of these results remains unclear and needs further investigation.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".