Artificial Intelligence, Coronary Heart Disease, Sleep Apnea
Conditions
Keywords
artificial intelligence
Brief summary
The present study is trying to find out whether artificial intelligence assisted follow-up strategy will improve secondary prevention in CABG patients. In addition, we will test whether rural patients may have more benefits under the new follow-up strategy based on the artificial intelligence device compared with urban patients.
Detailed description
There are a large population of coronary heart disease patients in China, which needs more attention to optimize the secondary prevention and improve the prognosis. Secondary prevention has been showing the effects of improving symptoms, preventing disease progression, improving prognosis, and reducing mortality in patients received coronary artery bypass grafting (CABG) surgery. In this study, we are trying to evaluate the effectiveness of artificial intelligence (AI) assisted follow-up strategy on secondary prevention for patients received CABG surgery. And we are trying to find out whether there is difference in secondary prevention of coronary heart disease between urban and rural patients.
Interventions
We will use a new portable artificial intelligence assisted device to monitor the patients' postoperative heart rate and sleep quality, guiding the following follow-up process
Sponsors
Study design
Eligibility
Inclusion criteria
1. Age between 18-70, male or female 2. Received isolated CABG procedure due to coronary artery disease 3. Having a smartphone and are willing to cooperate 4. Signing written informed consent
Exclusion criteria
1. Patients undergoing CABG + valve replacement surgery 2. Postoperative hospital stays more than 10 days (Due to limited postoperative follow-up time and unstable condition such as incision infection, angina, etc.) 3. Patients with lung, liver, and kidney failure (Due to organ dysfunction which needs more professional health care and not suitable for this trial) 4. Patients with Urinary system diseases (Getting up during sleep, which will interfere with sleep monitoring) 5. Patients mentally or legally disabled 6. Breastfeeding or pregnant women 7. End-stage disease, estimated survival time is less than 3 months 8. Participate in other perioperative intervention studies at the same time
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Heart rate | 35 days | The average heart rate during the first 35 days postoperatively |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Average Pulse oxygen saturation | 35 days | The average pulse oxygen saturation during the sleep will be evaluated by the sleep monitor device automatically. |
| Minimum pulse oxygen saturation | 35 days | The pulse oxygen saturation during the sleep will be recorded by the sleep monitor device and the minimum pulse oxygen saturation will be analyzed. |
| Pain score | 35 days | It will be evaluated with the visual analogue scale from 0 to 10. Zero is the lowest level of pain and 10 is the highest level of pain. |
| Duration of different sleep stages | 35 days | It includes duration of falling asleep, light sleep, and deep sleep period |
| Re-admission rate | 35 days | It is defined as re-admission between discharge to 35 days after surgery. |
| All-cause mortality | 35 days | refers to the incidence of death from the day of surgery to the end of the trial, regardless of the cause. |
| Total cost of medical expenses | 35 days | It refers to the total medical expenses for CABG surgery and the following follow-up process. |
| Medication compliance | 35 days | It will be evaluated with Morisky Medication Adherence Scale (MMAS-4). The patients will receive four questions, which are answered by Yes or No ((Yes=0 and No=1) through the scoring system. Zero is the lowest level of medication adherence and 4 is the highest level of medication adherence. |
Countries
China