Smartphone Application to PREDICT Real-Time Cardiovascular Risk for Heart Attack and Stroke
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- The protocol lists: Smartphone application Antshrike.
- Who it may be relevant to
- Registry conditions: Myocardial Infarction (MI), Stroke. Basic parameters: 40 years — 79 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- United States
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Official title
Prospective Study of the Diagnostic Accuracy of a Smartphone Application to PREDICT Real-Time Cardiovascular Risk for Heart Attack and Stroke (PREDICT-HS)
Overview
To assess the diagnostic accuracy of a smartphone application in predicting heart attack or stroke within 3-4 days in high-risk patients.
Interventions
- Device Smartphone application Antshrike
All participants will wear a smart watch that has an application Antshrike, which will collect demographic data, health history, lifestyle factors, and biobehavioral data for 18 months.
Primary outcome measures
- Number of ASCVD events [Time frame: Baseline through 18 months]
Eligibility criteria
Inclusion criteria
- Be able to provide electronic or written informed consent and be able to effectively communicate and understand the study procedures, risks, and required activities.
- Age 40 to 79 years.
- Be willing to wear a smartwatch continuously for 18 months and comfortable with using wearable devices or other technologies that monitor their data over time.
- Established ASCVD or at an increased risk for a first MACE (i.e., no prior major ASCVD event), defined as anyone of the following:
i) Evidence of atherosclerotic CAD on CT or invasive coronary angiogram defined as a coronary artery stenosis ≥ 20% but <50% in the left main coronary artery or a stenosis ≥ 20% but <70% in any other major coronary artery.
ii) Coronary artery calcium score ≥ 100 Agatston units.
iii) High estimated10-year ASCVD risk ≥ 20% by pooled cohort equation.
iv) Intermediate estimated 10-year ASCVD risk 7.5% to <20% by pooled cohort equation with at least 2 of the following risk-enhancing factors:
- A first degree relative with history of premature ASCVD (males, age <55 years; females, age <65 years).
- History of premature menopause before age 40.
- History of maternal pregnancy complications (defined as a history of either preeclampsia, gestational hypertension, or gestational diabetes).
- South Asian ancestry.
- Chronic inflammatory disorders (defined as either rheumatoid arthritis, systemic lupus erythematosus, psoriasis covering ≥10% of body surface area, Crohn's disease, ulcerative colitis, or HIV/AIDS).
- High-sensitivity C-reactive protein (hsCRP) ≥2 mg/L documented in the 12 months preceding the screening visit, and, in absence of any underlying acute or inflammatory conditions.
- Lipoprotein (a) ≥50 mg/dL or ≥125 nmol/L at any time before the screening visit.
- Estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2.
- Ankle branchial index (ABI) <0.9 with no symptoms of intermittent claudication.
- Metabolic syndrome: increased waist circumference, elevated triglycerides, elevated blood pressure, elevated glucose, and low HDL-C are factors
i. Diabetes
Exclusion criteria
- The 10-year ASCVD risk <7.5%.
- Elevated troponin at baseline.
- Cognitive impairment.
- Neurological disorders that would impair their ability to provide informed consent or adhere to study protocols.
- Metastatic cancer or active cancer undergoing chemotherapy.
- Terminal illness.
- Pregnant women or women of childbearing potential not using contraception.
- Current or past major psychiatric disorders (e.g., schizophrenia, bipolar disorder, severe depression) that could affect physiological or biometric data.
- Surgical or medical condition, which in the opinion of the Investigator, may place the participant at higher risk from his/her participation in the study, or is likely to prevent the participant from complying with the requirements of the study or completing the study.
- Unwillingness or inability to comply with study procedures, including adherence to study visits, fasting blood draws and compliance with study protocol.
- Residing in an inpatient facility or bedbound
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Allocation
- N/A
- Model
- Single group
- Masking
- Open label
- Primary purpose
- Other
Study locations
United States · 1 center
- Stanford University — Stanford
Publications
- Turakhia MP, Desai M, Hedlin H, Rajmane A, Talati N, Ferris T, Desai S, Nag D, Patel M, Kowey P, Rumsfeld JS, Russo AM, Hills MT, Granger CB, Mahaffey KW, Perez MV. Rationale and design of a large-scale, app-based study to identify cardiac arrhythmias using a smartwatch: The Apple Heart Study. Am Heart J. 2019 Jan;207:66-75. doi: 10.1016/j.ahj.2018.09.002. Epub 2018 Sep 8. PMID 30392584
- Perez MV, Mahaffey KW, Hedlin H, Rumsfeld JS, Garcia A, Ferris T, Balasubramanian V, Russo AM, Rajmane A, Cheung L, Hung G, Lee J, Kowey P, Talati N, Nag D, Gummidipundi SE, Beatty A, Hills MT, Desai S, Granger CB, Desai M, Turakhia MP; Apple Heart Study Investigators. Large-Scale Assessment of a Smartwatch to Identify Atrial Fibrillation. N Engl J Med. 2019 Nov 14;381(20):1909-1917. doi: 10.1056/ PMID 31722151
Identifiers
NCT: NCT07735338 · 86331