Haggenmüller Verena, Bogler Lisa, Weber Ann-Charline, Kumar Abhijeet, Bärnighausen Till, Danquah Ina, Vollmer Sebastian
Heidelberg Institute of Global Health, Heidelberg University Hospital, Im Neuenheimer Feld 130.3, 69120, Heidelberg, Germany.
Centre for Modern Indian Studies (CeMIS), University of Goettingen, Waldweg 26, 37073, Göttingen, Germany.
Commun Med (Lond). 2023 Mar 22;3(1):38. doi: 10.1038/s43856-023-00267-z.
The high prevalence of anemia in resource-constrained settings calls for easy-to-use, inexpensive screening tools. The Sanguina Smartphone App, an innovative tool for non-invasive hemoglobin estimation via color-sensitive, algorithm-based analysis of fingernail bed images, was validated in the United States. This study evaluates the performance of the App in a population with different socio-economic, ethnic, demographic and cultural composition in rural Bihar, India.
For 272 mainly adult patients of a private health centre, hemoglobin measurement with the App is compared with the gold standard laboratory blood analysis. For a second sample of 179 children attending pre-schools, hemoglobin measurement with the App is compared to the results of the HemoCue Hb 301, a point-of-care device using a small blood sample, serving as the reference standard for field-based settings.
The App reaches ±4.43 g/dl accuracy and 0.38 g/dl bias of comparator values in the clinic-based sample, and ±3.54 g/dl and 1.30 g/dl, respectively in the pre-school sample. After retraining the algorithm with the collected data, the validity of the upgraded version is retested showing an improved performance (accuracy of ±2.25 g/dl, bias of 0.25 g/dl), corresponding to the results of the original validation study from the United States.
The initial version of the App does not achieve the accuracy needed for diagnosis or screening. After retraining the algorithm, it achieves an accuracy sufficient for screening. The improved version with the potential for further adaptions is a promising easy-to-use, inexpensive screening tool for anemia in resource-constrained point-of-care settings.
资源有限地区贫血的高患病率需要易于使用且价格低廉的筛查工具。Sanguina智能手机应用程序是一种通过对指甲床图像进行基于颜色敏感的算法分析来无创估计血红蛋白的创新工具，已在美国得到验证。本研究评估了该应用程序在印度比哈尔邦农村地区具有不同社会经济、种族、人口和文化构成的人群中的性能。
对于一家私立健康中心的272名主要为成年患者，将该应用程序测量的血红蛋白与金标准实验室血液分析进行比较。对于179名学龄前儿童的第二个样本，将该应用程序测量的血红蛋白与HemoCue Hb 301（一种使用少量血样的即时检测设备，作为现场环境的参考标准）的结果进行比较。
在基于诊所的样本中，该应用程序的比较值准确性达到±4.43 g/dl，偏差为0.38 g/dl；在学龄前儿童样本中，分别为±3.54 g/dl和1.30 g/dl。在用收集到的数据对算法进行重新训练后，对升级版本的有效性进行了重新测试，结果显示性能有所提高（准确性为±2.25 g/dl，偏差为0.25 g/dl），与美国原始验证研究的结果相当。
该应用程序的初始版本未达到诊断或筛查所需的准确性。在对算法进行重新训练后，它达到了足以进行筛查的准确性。具有进一步适应性潜力的改进版本是一种很有前景的、易于使用且价格低廉的资源有限即时检测环境下贫血筛查工具。
