Püschl Ida Catharina, Bonde Lisbeth, Gerds Thomas Alexander, Tackney Mia Sato, Quest James, Sorensen Bjarke Lund, Macklon Nicholas Stephen
Faculty of Medicine, University of Copenhagen, Copenhagen, Denmark.
Department of Obstetrics and Gynecology and ReproHealth Consortium, Zealand University Hospital, Roskilde, Denmark.
Front Med (Lausanne). 2024 Dec 20;11:1385299. doi: 10.3389/fmed.2024.1385299. eCollection 2024.
This study investigated the efficacy of a digital health solution utilizing smartphone images of colorimetric test-strips for home-based salivary uric acid (sUA) measurement to predict pre-eclampsia (PE), pregnancy-induced hypertension (PIH), and intrauterine growth restriction (IUGR).
495 pregnant women were included prospectively at Zealand University Hospital, Denmark. They performed weekly self-tests from mid-pregnancy until delivery and referred these for analysis by a smartphone-app. Baseline characteristics were obtained at recruitment and pregnancy outcomes from the journals. The mean compliance rate of self-testing was assessed. For the statistical analyses, standard color analyses deduced the images into the red-green-blue (RGB) color model value, to observe the individual, longitudinal pattern throughout the pregnancy for each outcome. Extended color analyses were applied, deducing the images into 72 individual color variables that reflected the four dominant color models. The individual discriminatory ability was assessed by calculating the area under the curve for the outcome of PE, and the outcome of hypertensive pregnancy disorders solely or combined with IUGR at 25 weeks of gestation and for the weekly color change between 20 and 25 weeks of gestation.
Thirty-four women (6.9%) developed PE, 17 (3.4%) PIH, and 10 (2.0%) IUGR. The overall mean compliance rate was 67%, increasing to 77% after updating the smartphone-app halfway through the study. The longitudinal pattern of the RGB value showed a wide within-person variability, and discrimination was not achieved. However, it was noted that all women with IUGR repeatedly had RGB values below 110, contrasting women with non-IUGR. Significant discriminatory ability was achieved for 8.2% of the analyses of individual color variables, of which 27.4% summarized the Hue color variable. However, the analyses lacked consistency regarding outcome group and gestational age.
This study is the first proof-of-concept that digital self-tests utilizing colorimetric sUA measurement for the prediction of PE, PIH, and IUGR is acceptable to pregnant women. The discriminatory ability was not found be sufficient to have clinical value. However, being the first study that compares individual color variables of the four dominant color models, this study adds important methodological insights into the expanding field of smartphone-assisted colorimetric test-strips.
本研究调查了一种数字健康解决方案的有效性，该方案利用比色测试条的智能手机图像进行家庭唾液尿酸（sUA）测量，以预测子痫前期（PE）、妊娠高血压（PIH）和胎儿生长受限（IUGR）。
丹麦西兰大学医院前瞻性纳入了495名孕妇。她们从孕中期到分娩每周进行自我检测，并通过智能手机应用程序将检测结果提交分析。在招募时获取基线特征，并从日志中获取妊娠结局。评估自我检测的平均依从率。在统计分析中，标准颜色分析将图像推导为红-绿-蓝（RGB）颜色模型值，以观察每个结局在整个孕期的个体纵向模式。应用扩展颜色分析，将图像推导为72个反映四种主要颜色模型的个体颜色变量。通过计算妊娠25周时PE结局、单纯或合并IUGR的高血压妊娠疾病结局以及妊娠20至25周期间每周颜色变化的曲线下面积，评估个体的判别能力。
34名女性（6.9%）发生PE，17名（3.4%）发生PIH，10名（2.0%）发生IUGR。总体平均依从率为67%，在研究进行到一半时更新智能手机应用程序后升至77%。RGB值的纵向模式显示个体内部差异较大，未实现判别。然而，值得注意的是，所有IUGR女性的RGB值反复低于110，与非IUGR女性形成对比。对8.2%的个体颜色变量分析具有显著判别能力，其中27.4%总结了色调颜色变量。然而，分析在结局组和孕周方面缺乏一致性。
本研究是首个概念验证，即利用比色sUA测量进行数字自我检测以预测PE、PIH和IUGR，孕妇是可以接受的。未发现判别能力足以具有临床价值。然而，作为第一项比较四种主要颜色模型个体颜色变量的研究，本研究为智能手机辅助比色测试条这一不断扩展的领域提供了重要的方法学见解。
