Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
This observational study aims to evaluate the performance of a software-based medical device, Glandy HYPER, in detecting the thyrotoxic state in patients with hyperthyroidism. The device utilizes heart rate data collected from commercially available wearable devices and compares it with thyroid function test results. The study will enroll patients diagnosed with Graves' disease, monitoring their heart rate during sleep and correlating these measurements with free T4 levels obtained through serial blood testing. No investigational device output will be disclosed to participants, and the study will not alter standard clinical care.
This is a single-center, prospective observational study designed to validate the performance of Glandy HYPER, a software medical device that analyzes sleep heart rate data from wearable devices in conjunction with thyroid function test (TFT) results to detect thyrotoxicosis. The study targets adults aged 22 or older with newly diagnosed or currently treated Graves' disease.
Each participant will wear a smartwatch (Apple or Samsung, depending on their smartphone OS) to measure heart rate during sleep over a 12-week period. Blood samples for TFTs will be collected at four separate visits (baseline and at 4, 8, and 12 weeks). The primary endpoint is the F1 score between the investigational device's output and the diagnosis of thyrotoxicosis based on free T4 values. Secondary endpoints include sensitivity, specificity, and area under the curve (AUC) of the device's performance.
Data from the wearable device and TFTs will be used to create multiple evaluation-reference data pairs per patient, enabling within-subject validation across different time points. The study does not involve any investigational treatment or alteration to standard care and is classified as non-significant risk (NSR). The output of the software device will not influence clinical decisions during the trial.
The study also aims to assess the generalizability of the software's performance by comparing results from this U.S.-based cohort with prior studies conducted in Korea.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Glandy HYPER Validation Cohort | articipants diagnosed with Graves' disease who are either newly diagnosed or currently under treatment. All participants will wear a commercially available smartwatch (Apple or Samsung) to measure sleep heart rate, and undergo thyroid function testing (free T4 and TSH) at baseline and follow-up visits over 12 weeks. No therapeutic intervention will be applied, and data from wearable devices will be used solely for observational performance evaluation of the investigational software. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Heart rate-based AI software for detecting thyrotoxicosis | Device | A software-based investigational medical device that uses artificial intelligence to detect the thyrotoxic state in patients with hyperthyroidism. The device analyzes resting heart rate data collected from wearable devices along with thyroid function test results (free T4 and TSH). The device is not FDA-approved and will be used solely for observational performance evaluation without influencing clinical care. |
| Measure | Description | Time Frame |
|---|---|---|
| F1 Score for Detection of Thyrotoxicosis Using the Investigational Software | The F1 score will be calculated to evaluate the performance of the AI-based investigational software in detecting thyrotoxic states. The device's output, derived from wearable heart rate data and reference data, will be compared against the diagnosis based on serum free T4 concentration at each time point. Each participant contributes multiple data pairs (evaluation-reference combinations) based on serial visits (V2-V5), and the F1 score will be calculated for each case and summarized across all cases. | At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total |
| Measure | Description | Time Frame |
|---|---|---|
| Sensitivity and Specificity of the Software in Detecting Thyrotoxicosis | The sensitivity and specificity of the investigational AI software will be calculated by comparing its output to the diagnosis of thyrotoxicosis based on serum free T4 levels. Results will be computed for each evaluation-reference data pair and summarized across all participants, with 95% confidence intervals. | At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Adults aged 22 years and older with a confirmed diagnosis of Graves' disease, including both newly diagnosed and currently treated individuals. Participants will be recruited from a single center in the United States. All participants must be able to use a wearable device and provide informed consent.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Jun An | Contact | +82 10-2849-0041 | jun.an@thyroscope.com | |
| Jae Hoon Moon, MD, PhD | Contact | +82-10-5105-9815 | jaehoon.moon@thyroscope.com |
| Name | Affiliation | Role |
|---|---|---|
| Umeshi Masharani, MD | University of California, San Francisco | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Umesh Masharani | Recruiting | San Francisco | California | 94143 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 38036639 | Background | Shin K, Kim J, Park J, Oh TJ, Kong SH, Ahn CH, Moon JH, Kim MJ, Moon JH. A machine learning-assisted system to predict thyrotoxicosis using patients' heart rate monitoring data: a retrospective cohort study. Sci Rep. 2023 Nov 30;13(1):21096. doi: 10.1038/s41598-023-48199-x. | |
| 34674500 | Background | Kim KH, Lee J, Ahn CH, Yu HW, Choi JY, Lee HY, Lee WW, Moon JH. Association between Thyroid Function and Heart Rate Monitored by Wearable Devices in Patients with Hypothyroidism. Endocrinol Metab (Seoul). 2021 Oct;36(5):1121-1130. doi: 10.3803/EnM.2021.1216. Epub 2021 Oct 21. |
Not provided
Not provided
The individual participant data (IPD) collected in this study will not be shared with other researchers due to privacy concerns and the sensitive nature of the biometric and clinical data involved. Data are collected solely for regulatory and scientific validation purposes and will be handled in accordance with applicable privacy regulations.
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Term |
|---|---|
| D006111 | Graves Disease |
| D006980 | Hyperthyroidism |
| D013971 | Thyrotoxicosis |
| ID | Term |
|---|---|
| D005094 | Exophthalmos |
| D009916 | Orbital Diseases |
| D005128 | Eye Diseases |
| D006042 | Goiter |
Not provided
Not provided
Not provided
Not provided
Not provided
Serum samples obtained from venous blood draws will be retained for thyroid function testing, specifically for the measurement of free T4 and TSH levels. Each sample will be centrifuged to isolate serum and stored at ≤ -70°C until analysis. No genetic or genomic testing will be performed on the retained samples.
|
| Area Under the Receiver Operating Characteristic Curve (AUC) for Thyrotoxicosis Detection | The AUC will be calculated to assess the diagnostic performance of the investigational software in distinguishing thyrotoxicosis from euthyroid and hypothyroid states, using free T4 levels as the reference. The AUC will be calculated per case and summarized across all evaluable cases. | At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total |
| 32886945 | Background | Steinberger E, Pilz S, Trummer C, Theiler-Schwetz V, Reichhartinger M, Benninger T, Pandis M, Malle O, Keppel MH, Verheyen N, Grubler MR, Voelkl J, Meinitzer A, Marz W. Associations of Thyroid Hormones and Resting Heart Rate in Patients Referred to Coronary Angiography. Horm Metab Res. 2020 Dec;52(12):850-855. doi: 10.1055/a-1232-7292. Epub 2020 Sep 4. |
| 32525973 | Background | Griffith ML, Bischoff LA, Baum HBA. Approach to the Patient With Thyrotoxicosis Using Telemedicine. J Clin Endocrinol Metab. 2020 Aug 1;105(8):dgaa373. doi: 10.1210/clinem/dgaa373. |
| 30006328 | Background | Lee JE, Lee DH, Oh TJ, Kim KM, Choi SH, Lim S, Park YJ, Park DJ, Jang HC, Moon JH. Clinical Feasibility of Monitoring Resting Heart Rate Using a Wearable Activity Tracker in Patients With Thyrotoxicosis: Prospective Longitudinal Observational Study. JMIR Mhealth Uhealth. 2018 Jul 13;6(7):e159. doi: 10.2196/mhealth.9884. |
| D013959 |
| Thyroid Diseases |
| D004700 | Endocrine System Diseases |
| D001327 | Autoimmune Diseases |
| D007154 | Immune System Diseases |