Keeler Bruce Lauryn, González Dalila, Dasgupta Subhasis, Smarr Benjamin L
UC San Diego Health Department of Biomedical Informatics, University of California San Diego, San Diego, CA, USA.
Bioinformatics and Systems Biology, University of California San Diego, San Diego, CA, USA.
NPJ Digit Med. 2024 Aug 12;7(1):207. doi: 10.1038/s41746-024-01183-9.
In the United States, normal-risk pregnancies are monitored with the recommended average of 14 prenatal visits. Check-ins every few weeks are the standard of care. This low time resolution and reliance on subjective feedback instead of direct physiological measurement, could be augmented by remote monitoring. To date, continuous physiological measurements have not been characterized across all of pregnancy, so there is little basis of comparison to support the development of the specific monitoring capabilities. Wearables have been shown to enable the detection and prediction of acute illness, often faster than subjective symptom reporting. Wearables have also been used for years to monitor chronic conditions, such as continuous glucose monitors. Here we perform a retrospective analysis on multimodal wearable device data (Oura Ring) generated across pregnancy within 120 individuals. These data reveal clear trajectories of pregnancy from cycling to conception through postpartum recovery. We assessed individuals in whom pregnancy did not progress past the first trimester, and found associated deviations, corroborating that continuous monitoring adds new information that could support decision-making even in the early stages of pregnancy. By contrast, we did not find significant deviations between full-term pregnancies of people younger than 35 and of people with "advanced maternal age", suggesting that analysis of continuous data within individuals can augment risk assessment beyond standard population comparisons. Our findings demonstrate that low-cost, high-resolution monitoring at all stages of pregnancy in real-world settings is feasible and that many studies into specific demographics, risks, etc., could be carried out using this newer technology.
在美国，正常风险的妊娠通过建议的平均14次产前检查进行监测。每隔几周进行一次检查是护理标准。这种低时间分辨率以及依赖主观反馈而非直接生理测量的情况，可以通过远程监测得到加强。迄今为止，尚未对整个孕期的连续生理测量进行特征描述，因此几乎没有比较基础来支持特定监测能力的发展。可穿戴设备已被证明能够检测和预测急性疾病，通常比主观症状报告更快。可穿戴设备也已被使用多年来监测慢性疾病，如连续血糖监测仪。在此，我们对120名个体整个孕期产生的多模式可穿戴设备数据（Oura Ring）进行了回顾性分析。这些数据揭示了从月经周期到受孕再到产后恢复的清晰妊娠轨迹。我们评估了妊娠未超过孕早期的个体，并发现了相关偏差，证实了连续监测能提供新信息，甚至在妊娠早期就能支持决策制定。相比之下，我们未发现35岁以下人群与“高龄产妇”的足月妊娠之间存在显著偏差，这表明对个体内连续数据的分析可以加强风险评估，超越标准的人群比较。我们的研究结果表明，在现实环境中对孕期各阶段进行低成本、高分辨率监测是可行的，并且可以使用这种新技术开展许多针对特定人口统计学、风险等方面的研究。
