Drone versus ground delivery of simulated blood products to an urban trauma center: The Montreal Medi-Drone pilot study
Bibliographic record
Abstract
BACKGROUND: Timely and safe distribution of quality blood products is a major challenge faced by blood banks around the world. Our primary objective was to determine if simulated blood product delivery to an urban trauma center would be more rapidly achieved by unmanned aerial vehicle (UAV) than by ground transportation. A secondary objective was to determine the feasibility of maintaining simulated blood product temperatures within a targeted range. METHODS: In this prospective pilot study, we used two distinct methods to compare UAV flight duration and ground transport times. Simulated blood products included packed red blood cells, platelet concentrate, and fresh frozen plasma. For each blood product type, three UAV flights were conducted. Temperature was monitored during transport using a probe coupled to a data logger inside each simulated blood product unit. RESULTS: All flights were conducted successfully without any adverse events or safety concerns reported. The heaviest payload transported was 6.4 kg, and the drone speed throughout all nine flights was 10 m/s. The mean UAV transportation time was significantly faster than ground delivery (17:06 ± 00:04 minutes vs. 28:54 ± 01:12 minutes, p < 0.0001). The mean ± SD initial temperature for packed red blood cells was 4.4°C ± 0.1°C with a maximum 5% mean temperature variability from departure to landing. For platelet concentrates, the mean ± SD initial temperature was 21.6°C ± 0.5°C, and the maximum variability observed was 0.3%. The mean ± SD initial fresh frozen plasma temperature was -19°C ± 2°C, and the greatest temperature variability was from -17°C ± 2°C to -16°C ± 2°C. CONCLUSIONS: Unmanned aerial vehicle transportation of simulated blood products was significantly faster than ground delivery. Simulated blood product temperatures remained within their respective acceptable ranges throughout transport. Further studies assessing UAV transport of real blood products in populated areas are warranted. LEVEL OF EVIDENCE: Therapeutic/care management, level IV.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".