Impact of Shipping Temperature and Duration on Umbilical Cord Blood Product Quality: A Machine Learning Approach

Background: Transportation of umbilical cord blood (UCB) units is a critical step in cellular therapy workflows, yet optimal transport conditions remain debated. While cold storage (2–8°C) is traditionally recommended, emerging evidence suggests room temperature (15–25°C) may better preserve product integrity. This study aimed to systematically evaluate the effects of transport time and temperature on UCB quality using statistical modeling, survival analysis, and machine learning. Methods: We analyzed time-stamped quality metrics from UCB units transported under either 2–8°C or 15–25°C. Key outcomes included total CD34+, CD34 + viability, total nucleated cell (TNC) count, TNC viability, and TNC recovery rate. Kaplan–Meier survival curves and time-stratified regression models were used to assess time-dependent degradation. Machine learning classifiers were trained using time and volume to predict quality failure and assess feature importance. Results: Under 2–8°C conditions, all quality metrics declined over time, with significant or borderline-significant degradation observed across multiple volume strata. Survival analysis revealed earlier and more frequent failure events in cold-stored samples. In contrast, UCB units stored at 15–25°C demonstrated superior stability, with minimal quality loss and no median failure time reached for most parameters. Machine learning models achieved high predictive performance under cold storage (AUC up to 0.84), confirming that time strongly predicts degradation at 2–8°C, while models performed less accurately for 15–25°C, reflecting greater robustness. Conclusions: Prolonged transport time is associated with measurable declines in UCB quality, particularly under cold storage. Room temperature conditions (15–25°C) offer enhanced preservation of TNC viability and recovery, even during extended transport durations. These findings support a reevaluation of current logistics protocols and suggest that ambient storage may provide a safer, more reliable alternative to cold transport for UCB products.

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Publication Details

Journal
Clinical Medicine And Health Research Journal
Published
2025-07-14
DOI
https://doi.org/10.18535/cmhrj.v5i04.488
Primary Topic
Digital Imaging for Blood Diseases
Type
article
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article

Impact of Shipping Temperature and Duration on Umbilical Cord Blood Product Quality: A Machine Learning Approach

Chi Chiu Leung, Suet-Ying NG
Clinical Medicine And Health Research Journal
Digital Imaging for Blood Diseases
article

Impact of Shipping Temperature and Duration on Umbilical Cord Blood Product Quality: A Machine Learning Approach

Chi Chiu Leung, Suet-Ying NG
article en

Abstract

Background: Transportation of umbilical cord blood (UCB) units is a critical step in cellular therapy workflows, yet optimal transport conditions remain debated. While cold storage (2–8°C) is traditionally recommended, emerging evidence suggests room temperature (15–25°C) may better preserve product integrity. This study aimed to systematically evaluate the effects of transport time and temperature on UCB quality using statistical modeling, survival analysis, and machine learning. Methods: We analyzed time-stamped quality metrics from UCB units transported under either 2–8°C or 15–25°C. Key outcomes included total CD34+, CD34 + viability, total nucleated cell (TNC) count, TNC viability, and TNC recovery rate. Kaplan–Meier survival curves and time-stratified regression models were used to assess time-dependent degradation. Machine learning classifiers were trained using time and volume to predict quality failure and assess feature importance. Results: Under 2–8°C conditions, all quality metrics declined over time, with significant or borderline-significant degradation observed across multiple volume strata. Survival analysis revealed earlier and more frequent failure events in cold-stored samples. In contrast, UCB units stored at 15–25°C demonstrated superior stability, with minimal quality loss and no median failure time reached for most parameters. Machine learning models achieved high predictive performance under cold storage (AUC up to 0.84), confirming that time strongly predicts degradation at 2–8°C, while models performed less accurately for 15–25°C, reflecting greater robustness. Conclusions: Prolonged transport time is associated with measurable declines in UCB quality, particularly under cold storage. Room temperature conditions (15–25°C) offer enhanced preservation of TNC viability and recovery, even during extended transport durations. These findings support a reevaluation of current logistics protocols and suggest that ambient storage may provide a safer, more reliable alternative to cold transport for UCB products.

Clinical Medicine And Health Research JournalVol. 5(04)
Hong Kong Science and Technology Parks Corporation (HK), Viva Biotech (China) (CN)
Openalex Percentile: Top 85%
Digital Imaging for Blood Diseases
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