Rapid point-of-care (POC) diagnosis of bacterial infection diseases provides clinical benefits of prompt initiation of antimicrobial therapy and reduction of the overuse/misuse of unnecessary antibiotics for nonbacterial infections. We present here a POC compatible method for rapid bacterial infection detection in 10 min. We use a large-volume solution scattering imaging (LVSi) system with low magnifications (1–2×) to visualize bacteria in clinical samples, thus eliminating the need for culture-based isolation and enrichment. We tracked multiple intrinsic phenotypic features of individual cells in a short video. By clustering these features with a simple machine learning algorithm, we can differentiate Escherichia coli from similar-sized polystyrene beads, distinguish bacteria with different shapes, and distinguish E. coli from urine particles. We applied the method to detect urinary tract infections in 104 patient urine samples with a 30 s LVSi video, and the results showed 92.3% accuracy compared with the clinical culture results. This technology provides opportunities for rapid bacterial infection diagnosis at POC settings.

中文翻译：

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通过跟踪 30 秒大容量尿液显微镜散射视频中的多种表型特征，在 10 分钟内快速检测尿路感染

细菌感染疾病的快速护理点 (POC) 诊断提供了迅速启动抗菌治疗和减少非细菌感染过度使用/误用不必要抗生素的临床益处。我们在此提出一种 POC 兼容方法，可在 10 分钟内快速检测细菌感染。我们使用低放大倍率（1-2×）的大体积溶液散射成像（LVSi）系统来可视化临床样本中的细菌，从而消除了基于培养的分离和富集的需要。我们在一段短视频中跟踪了单个细胞的多种内在表型特征。通过使用简单的机器学习算法对这些特征进行聚类，我们可以区分大肠杆菌和类似大小的聚苯乙烯珠，区分不同形状的细菌，以及区分大肠杆菌和尿液颗粒。我们应用该方法通过 30 s LVSi 视频检测 104 例患者尿样中的尿路感染，结果与临床培养结果相比，准确率为 92.3%。该技术为 POC 环境下快速细菌感染诊断提供了机会。