Clinical trial NCT05566860: Prescision Medicine in Obstructive Sleep Apnea, Cardiovascular and Cerebrovascular Disease: AI Electrocardiogram Patch Does it All
Official title: Prescision Medicine in Obstructive Sleep Apnea, Cardiovascular and Cerebrovascular Disease: AI Electrocardiogram Patch Does it All
Study type: INTERVENTIONAL
Overall status: UNKNOWN
Phase: NA
Conditions: Sleep Apnea, Obstructive
Keywords: obstructive sleep apnea
ECG patch
precision medicine
cardiovascular disease
cerebrovascular disease
sleep environment
sleep endoscope
postural therapy
oral appliance
intraoral negative airway pressure
sleep surgery
obesity
bariatric surgery
Lead sponsor: Shin Kong Wu Ho-Su Memorial Hospital
Sponsor class: OTHER
Collaborators: name: National Yang Ming Chiao Tung University
First posted: 2022-10-04
Enrollment: 80
Sex: ALL
Minimum age (years): 18
Maximum age (years): 80
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: NON_RANDOMIZED
Intervention model: SEQUENTIAL
Primary purpose: TREATMENT

Brief 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.


Eligibility criteria: 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

Primary outcomes:
measure: single-lead ECG monitoring patch with 3-axis ac-celerometer
timeFrame: The ECG patches will track changes before and three months after treatment.
Secondary outcomes:
measure: Home Sleep Test (HST)
timeFrame: The HST will track changes before and three months after treatment.
measure: Polysomnography (PSG)
timeFrame: The PSG test will track changes before and three months after treatment.
Other outcomes:
Locations:
city: Taipei
country: Taiwan
facility: Shin Kong Wu Ho-Su Memorial Hospital
Study officials:
References: