Better Understanding the Metamorphosis of Pregnancy (BUMP)

Pregnancy Early, Pregnancy Related, Wearables

Pregnancy, Wearables

Pregnancy is a commonly occurring medical event. Women who are pregnant may experience pregnancy-related symptoms and complications. However, there is a relative lack of multi-dimensional data on large populations of pregnant patients. The Study Investigators aim to derive novel insights and deeper understanding of maternal physiology and pathology through the analysis of an unprecedented breadth and depth of data collected from connected devices (i.e., wearables, smart home scale, mobile apps, etc.), additional virtual study assessments and support calls, and information derived from standard of care clinical visits. They will share these insights to empower patients to better care for themselves. The Investigators hope to know how leveraging the data collected from connected devices in addition to information obtained from routine clinical care helps researchers and clinicians better understand pregnancy related symptoms, conditions, and complications.

During pregnancy a woman may experience symptoms that are specific to being pregnant, including nausea, fatigue, shortness of breath, insomnia etc. to much more complicated and serious symptoms. While pregnancy is a commonly occurring medical event that poses health risks to the pregnant woman and fetus, there is limited research on how to prevent and treat symptoms before they become higher risk complications. Utilizing mHealth technology for the collection of objective and subjective measurements and the integration of passive data (from connected devices) will increase understanding of pregnancy and subsequent complications and symptoms as indicative or predictive of particular outcomes. In order to mitigate the risks of pregnancy, pregnant women are monitored closely and frequently through periodic in-clinic visits with their clinician. However, little is known about the progression of symptoms and measurements between clinic visits as continuous data is not collected as part of clinical practice. Symptom trajectories have been historically characterized by sporadic visible data, insufficient to identify transition points. Visible data points are episodic and may (or may not) be captured by monthly clinical assessments during pregnancy, but invisible data points can be captured and more clearly defined through the use of longitudinal, passive data collection by wearing and connecting devices. The Study Investigators aim to detect individual symptom transitions and shift trajectories of health to those which cannot be confined to the standard office clinical visit. They have selected devices which may help track the symptoms including The Oura Ring, the Garmin Venu Sq and the Bodyport scale. The study will follow women anticipating becoming pregnant and those pregnant up to and including 15 weeks.

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United States