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Pre-analytical stability of blood samples transported by drone versus ground: a pilot study
Marie Brionne1, Laure Peyro-Saint-Paul2, Jean-Jacques Dutheil2
1Hematology Laboratory, Caen Normandie University Hospital, France.
Objectives:
Pre-analytical conditions are critical to ensure the reliability of laboratory results, as emphasized by ISO 15189 standards. Drone transport has emerged as a promising alternative to conventional logistics, but its impact on sample integrity remains insufficiently characterized. This pilot study aimed to assess the pre-analytical stability of blood samples transported by drone versus ground transport.
Methods:
In this prospective study, 30 healthy volunteers were included. Six blood tubes per participant were collected simultaneously and assigned to ground or drone transport (20 min). A panel of 23 biochemical, hematological, and hemostatic parameters was analyzed. Agreement between transport modalities was assessed using paired comparisons, coefficients of variation, intraclass correlation coefficients (ICC), Pearson correlation, and Bland-Altman analysis.
Results:
No clinically meaningful differences were observed between transport modalities. Mean values and variability were comparable across parameters. Most analytes showed excellent agreement, with ICC and Pearson correlation coefficients >0.90. Although ALT and LDH showed statistically significant differences (p = 0.039), these were small and clinically negligible. Bland-Altman analysis confirmed minimal bias for ALT (-0.63 U/L), whereas LDH exhibited wider limits of agreement, suggesting increased sensitivity to transport-related factors (-9.7 U/L). No hemolysis, temperature deviation, or safety incidents were observed.
Conclusions:
Drone transport ensures robust pre-analytical stability of blood samples across a wide range of laboratory parameters. However, analyte-specific variability, particularly for LDH, highlights the need for targeted validation. These findings support the integration of drone-based logistics into laboratory workflows, while emphasizing the importance of analyte-dependent evaluation.
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