Prescision Medicine in Obstructive Sleep Apnea, Cardiovascular and Cerebrovascular Disease: AI Electrocardiogram Patch Does it All

Sleep Apnea, Obstructive Clinical Trial

Official title:

Prescision Medicine in Obstructive Sleep Apnea, Cardiovascular and Cerebrovascular Disease: AI Electrocardiogram Patch Does it All

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05566860
• Other study ID #: 20220111R
• Status: Recruiting
• Phase: N/A
• Start date: June 23, 2022
• Est. completion date: December 31, 2024

Study information

• Verified date: September 2022
• Source: Shin Kong Wu Ho-Su Memorial Hospital
• Contact: Ying-Shuo Hsu
• Phone: 00886918361831
• Email: sulisky[@]gmail.com
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

Obstructive Sleep apnea(OSA) is a disease with multiple causes, and treatments are very diverse. Patients and doctors have a lot of choices. The concept of precision medicine is needed to intervene so that doctors and patients can have directions in this huge map and won't get lost. In this OSA maze, we have already walked through some feasible passages, but we are far from reaching the end.

At present, the research direction of artificial intelligence for OSA is mostly focused on how to accurately screen, but less attention is paid on how to accurately treat and conveniently follow the effectiveness of treatment to increase patient compliance.

We can already analyze the results of electrocardiogram patches to predict the severity of sleep apnea. We have also been able to analyze the results of electrocardiogram patches for three consecutive nights, and found postural sleep apnea that could not be detected in laboratory sleep examinations, and help doctors provide appropriate intervention to improve patients' sleep apnea, severity and quality of sleep. We have also found that precision sleep endoscopy can be used to predict the outcome of sleep apnea patients after surgery and the effectiveness of treatment with an intraoral nagative airway pressure device.

Therefore, in the future, with artificial intelligence(AI), ECG patches are able to be used for follow patients' treatment effectiveness.

Others include the treatment of weight loss drugs and bariatric surgery for obese patients, the control of environmental temperature and humidity, and the training of oropharyngeal and tongue muscle strength, all of which require the diagnosis and follow up of AI ECG patches from beginning to end.

According to the latest research, nocturnal hypertension is more relevant to the prognosis of cardiovascular problems and cerebrovascular disease that may occur in the future. This is also the problem that we are most concerned about in the treatment of sleep apnea. ECG patches also have the potential to provide us with information about nocturnal hypertension. Studies have also shown that ECG patches test results are highly correlated with nocturnal hypertension. Therefore, the improvement of nocturnal hypertension can also be used as an important indicator of the effectiveness for our treatment of sleep apnea.

Therefore, the goal of this project is to develop AI algorithm to make ECG patches more helpful to patients with sleep apnea, and to make better treatment decisions that are most suitable for patients, such as postural therapy, bariatric surgery for obese patients, environmental temperature and humidity control, oropharyngeal tongue muscle strength training, and accompany with sleep endoscope for the selection of intraoral negative pressure devices and surgery, and finally use AI ECG patches for the patient for three consecutive nights to evaluate the improvement of nocturnal hypertension and sleep apnea, and to achieve the goal of precision medicine in OSA.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 80
• Est. completion date: December 31, 2024
• Est. primary completion date: June 30, 2023
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: 18 Years to 80 Years

Eligibility

Inclusion Criteria:

• patients with snoring and obstructive sleep apnea

Exclusion Criteria:

Patients who are not suitable for anesthesia and surgical risks, including:

• serious cerebrovascular and cardiovascular diseases

• serious metabolic disorders

• serious respiratory diseases

Related Conditions & MeSH terms

• Apnea
• Cerebrovascular Disorders
• Sleep Apnea Syndromes
• Sleep Apnea, Obstructive

Intervention

Procedure:
• Positional Therapy
After the a forementioned sleep endoscopy, if the patient has postural sleep apnea, he was treated with positional therapy for three months.
• Intraoral Negative Pressure Therapy
If the patient is effective with intraoral negative pressure therapy (iNAP), this therapy was used for three months.
• Oral Appliances
If the patient is effective with oral appliances use, it was used be for three months.
• Surgery
If the interventions mentioned above are ineffective, or the patient does not want to try the above treatments, surgery is required. The surgical patients were divided into three groups according to their body weight. One group was overweight patients (BMI>32) who were treated with upper airway surgery and/or bariatric surgery, and/or postoperative diet education; the other group was overweight people with a BMI between 27 and 32, upper airway surgery and/or bariatric surgery, and/or postoperative diet education will be done; if the weight is normal with the BMI is less than 27, or those patients who are overweight but are not willing receive above mentioned weight loss treatment, upper airway surgery will be done.
• Tongue Muscle Strength Training
If the tongue strength of the aforementioned patient is insufficient, it is recommended that the patient need to do tongue muscle strength training at the same time for three months. If the ambient temperature and humidity have an impact, we will recommend patients to control the ambient temperature and humidity and use the ECG patch to track the changes before and after three months.

Locations

Country	Name	City	State
Taiwan	Shin Kong Wu Ho-Su Memorial Hospital	Taipei

Sponsors (2)

Lead Sponsor	Collaborator
Shin Kong Wu Ho-Su Memorial Hospital	National Yang Ming Chiao Tung University

Country where clinical trial is conducted

Taiwan, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	single-lead ECG monitoring patch with 3-axis ac-celerometer	total record time, total sleep time, sleep efficiency, sleep latency, wake after sleep onset, ECG-derived respiration, cyclic variation of heart rate, heart rate variability (mean HR, SD, TP, HF, LF, VL, Kurtosis, Skewness)	The ECG patches will track changes before and three months after treatment.
Secondary	Home Sleep Test (HST)	recording time (start, end), AHI, AHI supine, AHI non-supine, events totals (apnea, hypopnea), AI obstructive, ODI, lowest oxygen saturation	The HST will track changes before and three months after treatment.
Secondary	Polysomnography (PSG)	AHI, REM AHI, total sleep time, events totals (obstructive apnea, hypopnea), lowest oxygen saturation, PLM index, ESS	The PSG test will track changes before and three months after treatment.