Acute MI, Diabetes Mellitus, Heart Failure, Kidney Disease
Conditions
Brief summary
The primary objective of CHAPERONE solution is to evaluate the efficacy of engaging, assessing, and enabling long term treatment strategy with Health Artificial Intelligence (AI) Chatbot, Copilot, Large Language Model (LLM) and vital sign monitoring device in reducing CKM disease burden using an algorithm obtained from biomarkers and diagnostics utilizing remote sensor driven technology tools, care coordination and patient empowerment.
Detailed description
The interconnectedness between Diabetes, Heart disease and Kidney disease (Cardio Kidney Metabolic) has never been more important to recognize than the present day as the current data on the prevalence of this trifecta suggests an exponential increase in comorbidity, death, poor quality of life and a colossal economic burden on the society. Risk factors such as hypertension, high cholesterol, smoking, prediabetes states, obesity, unhealthy eating habits, lack of exercise, micro particle air pollution, high inflammatory markers, life stressors and genetics play a significant role in triggering the onset of these diseases and their complications. Half a Billion people in the world are expected to be having diabetes by 2023; another 150 million with prediabetes and one billion with hypertension ( Already 130Million in the US have Hypertension now ) Problem of Kidney Disease: More than 37 million Americans have kidney disease and millions more are at risk. According to the Centers for Disease Control and Prevention (CDC), 9 out of 10 people with early kidney disease don't know they have it because it usually has no symptoms until the late stages. Simple blood and urine tests can tell how well the kidneys are working. Diabetes and high blood pressure are the two leading causes of kidney disease. Kidney disease can lead to heart attack, stroke, kidney failure and death. With recent advances in research, Kidney disease can be treated if caught and treated early and it is often possible to slow or stop the progress of kidney disease with diet, exercise, lifestyle modifications and a few newer medications. Besides diabetes and high blood pressure, other common risks for kidney disease include having a family history of kidney disease, Black heritage, Hispanic, Asian American, or Native American. Black Americans are 3.4 times more likely than whites to develop kidney failure if over 60 years of age, and Hispanics are 1.5 times more likely than non- Hispanics to develop kidney failure. There are more than 785,000 people with kidney failure in the United States-an increase of more than 100% since 2000.
Interventions
OTHERCHAPERONE AI
The primary objective of this study is to evaluate the efficacy of treatment strategy on the impact of an intervention that is AI, Machine Learning (ML) based using Chatbot and Copilot with algorithm based intervention in CKM subjects in reducing progression of CKM diseases. This will be based on an algorithm obtained from biomarkers and diagnostics utilizing remote sensor driven technology tools, care coordination and patient empowerment. Improvement of patient outcomes will be measured by reduction of composite of Kidney failure/progression of kidney disease, Heart failure, acute myocardial infarction (AMI) events and diabetes complications and hospitalization as well as all-cause mortality through 30 days, 90 days and 180 days in CKM patients
DEVICECKMiq AI
To evaluate the effect of treatment in: reducing readmission's from cardiovascular causes using an algorithm-based intervention of LIFE ESSENTIAL 8 biomarkers obtained from info graphic resources provided by American Heart Association. Improving subject self-assessed risk score overall well-being as measured by self-assessed Copilot Likert scale at 30 days, 90 days and 180 days from hospitalization. Increasing the number of days alive and outside the hospital from hospitalization through day 30, 90 and Day 180. Reducing the composite of cardiovascular re-hospitalization and cardiovascular mortality from hospitalization through 30, 90 and 180 days. New York Heart Association (NYHA) Class and Kansas City Cardiomyopathy Questionnaire (KCCQ) will be captured.
OTHERQuality of Life
Secondary and tertiary objectives of this study are to evaluate the effect of CHAPERONE intervention in: Improving LIFE ESSENTIAL-8 Score and Health Related Quality of Life (HRQOL) measured with the 12-item Short Form (SF-12) survey, which reflects general health status and leads to 2 scores
Sponsors
Aventyn, Inc.
Dignity Health
Arizona Heart Foundation
Arizona State University
University of Arizona
University of Phoenix College of Nursing
Creighton School of Medicine, Phoenix Arizona
Karolinska University Hospital
Partnership for Economic Innovation Arizona
Kanasu Labs
Intel Corporation
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
TREATMENT
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Men and women over 18 years of age are included * Eligible subjects must have one of the risk factor/ disease component of CKM: * Diabetes with A1C of 7.5 or higher; * or Heart disease with stent placement; * or Coronary Artery Bypass Graft (CABG) in the last 12 months; * or Chronic Kidney Disease (CKD) stage 2- 4 * and, in those with Heart failure, a recent hospitalization within one week of enrollment is required
Exclusion criteria
* Those subjects who are not willing to sign an informed consent
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| CHAPERONE AI Treatment | 30 days, 90 days and 180 days in patients CKM | Improvement of patient outcomes will be measured by reduction of composite of Kidney failure/progression of kidney disease, Heart failure, Acute Mi events and diabetes complications and hospitalization as well as all-cause mortality through 30 days, 90 days and 180 days in patients CKM |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| CHAPERONE AI Reduced Readmissions | 30, 90 and 180 days. | educing readmissions from cardiovascular causes using an algorithm-based intervention of LIFE ESSENTIAL 8 biomarkers obtained from infographic resources provided by American Heart Association , improving subject self-assessed risk score overall well-being as measured by self-assessed Copilot Likert scale at 30 days, 90 days and 180 days from hospitalization Increasing the number of days alive and outside the hospital from hospitalization through day 30, 90 and Day 180. Reducing the composite of cardiovascular re-hospitalization and Cardiovascular mortality from hospitalization through 30, 90 and 180 days. NYHA class and KCCQ will be captured |
Countries
Sweden, United States
Contacts
CONTACTNavin Govind Steering Committtee, MS
CONTACTAditya Vijay, MS
STUDY_CHAIRKris Vijay Study Chair, MD
Aventyn, Inc.
PRINCIPAL_INVESTIGATORZaki Lababidi PI, MD
Gilbert Cardiology
Outcome results
None listed