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| Name | Class |
|---|---|
| KGK Science Inc. | INDUSTRY |
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The goal of this observational study is to investigate the accuracy of the device in characterizing perimenopausal and menopausal symptoms including vasomotor symptoms, anxiety, sleep quality compared to self-reported symptoms via an app. The main question it aims to answer is:
What is the accuracy of the developed algorithm from the investigational device compared to daily self-report via an app in characterizing perimenopausal symptoms?
Participants will be asked to wear IndentifyHer's wearable non-invasive sensor and complete a daily electronic diary and questionnaires on stress, anxiety, and sleep.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| IndentifyHer's Peri | IndentifyHer's Peri investigational device is a commercial, non-invasive, wearable sensor that works in combination with a digital platform to quantify and profile the frequency and severity of perimenopausal symptoms including hot flashes, night sweats, anxiety, and sleep disturbances. |
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| Measure | Description | Time Frame |
|---|---|---|
| The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing Vasomotor symptoms. | The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing vasomotor symptoms. Questionnaire answers include "not at all" to "extremely". | Day 0 to 14 |
| The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing anxiety | The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing anxiety. Questionnaire answers include "not at all" to "nearly everyday". | Day 0 to 14 |
| The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing sleep quality | The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing sleep quality. Questionnaire answers include "terrible" to "very well". | Day 0 to 14 |
| The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing perimenopausal symptoms considering confounders | The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing perimenopausal symptoms considering confounders of warmer environmental conditions. Questionnaire answers include "not at all" to "nearly all day". | Day 0 to 14 |
| The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing perimenopausal symptoms considering confounders |
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Inclusion Criteria:
Females between 35-55 years of age, inclusive
Self-reported perimenopausal women experiencing hot flushes or night sweats
Individuals of child-bearing potential must confirm they are not pregnant, do not plan to become pregnant, and agree to use a medically approved method of birth control for the duration of the study. Acceptable methods of birth control include:
Agrees to maintain current lifestyle as much as possible throughout the study, including diet, exercise, supplements/medications, and sleep
Provided voluntary and informed consent to participate in the study
Generally healthy as determined by medical history with no unstable diagnosed medical conditions
Exclusion Criteria:
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N/A - virtual study. Participants are recruited online.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Marc Moulin, PhD | Contact | +12267819094;ext=300 | mmoulin@kgkscience.com |
| Name | Affiliation | Role |
|---|---|---|
| David Crowley, MD | KGK Science Inc. | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| KGK Science Inc. | Recruiting | London | Ontario | N6B3L1 | Canada |
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The accuracy of the developed algorithm from the investigational device compared to daily self-report questionnaire via an app in characterizing perimenopausal symptoms considering confounders of an ethnically-diverse study population. Questionnaire answers include "not at all" to "nearly all day". |
| Day 0 to 14 |
| ID | Term |
|---|---|
| D019584 | Hot Flashes |
| ID | Term |
|---|---|
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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