Screening of anemic patients poses demanding challenges in extreme point-of-care settings where the gold standard diagnostic technologies are not pragmatic and the alternative point-of-care technologies suffer from compromised accuracy, prohibitive cost, process complexity, or reagent stability issues. As a disruption to this paradigm, here, we report the development of a smartphone-based sensor for rapid screening of anemic patients by exploiting the patterns formed by a spreading drop of blood on a wet paper strip wherein blood attempts to displace a more viscous fluid, on the porous matrix of a paper, leading to “finger-like” projections at the interface. We analyze the topological features of the pattern via smartphone-enabled image analytics and map the same with the relative occupancy of the red blood cells in the blood sample, allowing for label-free screening and classification of blood samples corresponding to moderate to severe anemic conditions. The accuracy of detection is verified by comparing with gold standard reports of hematology analyzer, showing a strong correlation coefficient (R²) of 0.975. This technique is likely to provide a crucial decision-making tool that obviates delicate reagents and skilled technicians for supreme functionality in resource-limited settings.

中文翻译：

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从一滴血在湿纸条上形成的模式，智能手机集成无标签快速筛查贫血

贫血患者的筛查在极端的即时医疗环境中提出了艰巨的挑战，在这些环境中，黄金标准诊断技术不实用，替代的即时医疗技术存在准确性受损、成本过高、过程复杂性或试剂稳定性问题等问题。作为对这种范式的颠覆，我们在此报告了一种基于智能手机的传感器的开发，该传感器通过利用湿纸条上的血滴扩散形成的模式来快速筛查贫血患者，其中血液试图取代更粘稠的液体，在纸的多孔基质上，导致界面处的“手指状”投影。我们通过智能手机支持的图像分析分析模式的拓扑特征，并将其映射到血样中红细胞的相对占有率，允许对与中度至重度贫血状况相对应的血液样本进行无标记筛查和分类。通过与血液分析仪的金标准报告比较验证检测的准确性，显示出很强的相关系数（R ² ) 为 0.975。这种技术可能会提供一种关键的决策工具，它可以在资源有限的环境中避免使用精致的试剂和熟练的技术人员来实现最高功能。