Clinical Trial Details
— Status: Completed
Administrative data
NCT number |
NCT04714905 |
Other study ID # |
4UBUMP01 |
Secondary ID |
|
Status |
Completed |
Phase |
|
First received |
|
Last updated |
|
Start date |
February 23, 2021 |
Est. completion date |
July 3, 2023 |
Study information
Verified date |
August 2023 |
Source |
4YouandMe |
Contact |
n/a |
Is FDA regulated |
No |
Health authority |
|
Study type |
Observational [Patient Registry]
|
Clinical Trial Summary
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.
Description:
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.