Evaluating an AI Tool for Detecting Thyrotoxic States

Официальное название

Performance Evaluation of the Software Medical Device to Detect the Thyrotoxic State in Patients With Hyperthyroidism

Обзор

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.

Подробное описание

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.

Вмешательства

• Устройство Heart rate-based AI software for detecting thyrotoxicosis
  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.

Первичные конечные точки

• F1 Score for Detection of Thyrotoxicosis Using the Investigational Software [Срок оценки: At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total]

Вторичные конечные точки (2)

• Sensitivity and Specificity of the Software in Detecting Thyrotoxicosis [Срок оценки: At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total]
• Area Under the Receiver Operating Characteristic Curve (AUC) for Thyrotoxicosis Detection [Срок оценки: At weeks 4, 8, and 12 after baseline (Visit 2), up to 12 weeks total]

Критерии участия

Критерии включения

• Adults aged 22 years or older, regardless of sex.
• Individuals who are newly diagnosed with Graves' disease or currently undergoing treatment for it.
• Individuals who have received sufficient explanation about the investigational software and are able to use it appropriately.
• Individuals who voluntarily agree to participate in the study and have signed informed consent, either directly or via a legally authorized representative.

Критерии исключения

• Individuals with cardiac conditions such as arrhythmia or heart failure.
• Individuals taking medications that significantly affect heart rate, including antiarrhythmics or antihistamines. (Intermittent short-acting beta-blockers are allowed.)
• Pregnant or breastfeeding individuals, or those planning pregnancy during the study period or not using appropriate contraception.
• Individuals with significant comorbidities that interfere with follow-up or study compliance.
• Individuals with severe psychiatric disorders, substance use disorder, or alcohol dependence.
• Individuals deemed ineligible at the discretion of the investigator for safety or ethical concerns.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Когортное

Центры проведения

США · 1 центр

• Umesh Masharani — San Francisco

Публикации

• 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. PMID 38036639
• 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. PMID 34674500
• 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. PMID 32886945
• 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. PMID 32525973
• 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. PMID 30006328

Идентификаторы

NCT: NCT07017907 · 01-01-UCSF-001

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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