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温度监测输血网络对减少血液浪费的影响。

Impact of a Temperature-Monitored Blood Transfusion Network on Reducing Blood Wastage.

作者信息

Ashraf Fidha, Kalathil Ashik Arshad, Ashraf Chathoth Ashfaq, Luqmani Asad

机构信息

Family Medicine, Ahalia Diabetes Hospital, Palakkad, IND.

Department of Mechanical Engineering, Imperial College London, London, GBR.

出版信息

Cureus. 2025 Aug 2;17(8):e89255. doi: 10.7759/cureus.89255. eCollection 2025 Aug.

Abstract

Lack of availability of blood for transfusion is associated with significant mortality rates across the world. Blood collection and storage can be managed either in centralised or decentralised facilities. India has a decentralised blood bank network supply chain, which results in blood wastage due to the lack of data to decide on the quality and suitability of blood for transfusion. In this study, we introduce a temperature-monitored blood bank supply chain that tracks the temperature log of blood from collection to delivery. An algorithm was developed according to the World Health Organization guidelines () to predict the usability of blood. This research aims to measure the difference in blood wastage by tracking and analysing the end-to-end temperature data. Testing was carried out over a period of two years in two cycles of six months each to evaluate the effectiveness of the solution. It was found that using this solution reduced blood wastage by 68% at the blood storage centre. Statistical analysis using a paired t-test showed a significant reduction in blood wastage, with a p-value of 0.044 and a large effect size (Cohen's d = 1.09). Implementing this methodology at a larger scale can help identify temperature breaches across the blood supply chain and ensure safe blood is available for transfusion.

摘要

全球范围内,输血用血供应不足与显著的死亡率相关。血液采集和储存可在集中式或分散式设施中进行管理。印度拥有一个分散的血库网络供应链,由于缺乏用于判定输血用血质量和适用性的数据,导致了血液浪费。在本研究中,我们引入了一个温度监测的血库供应链,该供应链可追踪血液从采集到交付的温度记录。根据世界卫生组织的指南开发了一种算法来预测血液的可用性。本研究旨在通过追踪和分析端到端的温度数据来衡量血液浪费的差异。在两年时间内分两个周期进行测试,每个周期为期六个月,以评估该解决方案的有效性。结果发现,使用该解决方案可使血库中心的血液浪费减少68%。使用配对t检验进行的统计分析表明,血液浪费显著减少,p值为0.044,效应量较大(科恩d值 = 1.09)。大规模实施该方法有助于识别整个血液供应链中的温度违规情况,并确保有安全的血液可供输血。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/64ae/12401555/47b0aa6f5860/cureus-0017-00000089255-i01.jpg

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