Multicenter observational study evaluating the impact of platelet transport bags on product wastage
Bibliographic record
Abstract
BACKGROUND: Platelets are the most commonly discarded blood product in Canada, with the most common cause of in-date product loss being improper storage. Transport containers to maintain temperature and extend acceptable return time may represent a method to reduce wastage. The objective of this study was to evaluate the impact of a validated Platelet Transport Bag (PTB) on platelet wastage. STUDY DESIGN AND METHODS: Thirty-six hospitals with the highest platelet discards were invited to participate in a before-after observational study. Hospitals were instructed to utilize a validated 4-h PTB for clinical situations where immediate transfusion was not planned. Five hospitals audited in-date platelet discards from July 2018 to November 2019 to characterize wastage causes. In-date platelet discard data 12 months before and after the start date for each site were analyzed to determine changes in wastage. RESULTS: Of 36 hospital sites, 16 agreed to participate. Pre- and postdiscards were 277 and 301, respectively, for all sites combined. There were no significant before-after change in wastage rate (+0.05%, p = .51). Fifty discards were included in the detailed audit; the most common reasons were return to the blood bank after more than 60 min outside a PTB (n = 17, 34%) and return in a red cell cooler (n = 10, 20%). CONCLUSION: Implementation of PTB did not improve wastage. Common causes of in-date discards were return after 1 h outside of a PTB and placement in a red cell cooler in error. Further research is required to investigate potential strategies to mitigate in-date platelet wastage.
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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 | 0.005 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".