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Related Concept Videos

Longitudinal Studies01:26

Longitudinal Studies

Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
Assessment of the Cardiovascular System I: Subjective Data01:23

Assessment of the Cardiovascular System I: Subjective Data

A thorough health history and physical assessment are essential for identifying cardiovascular disease (CVD) symptoms and distinguishing them from other health issues.
Initial Enquiry
Ask the patient about their primary concern and thoroughly explore all reported symptoms.
Medical History
Investigate past illnesses affecting the cardiovascular system, such as angina, anemia, rheumatic fever, congenital heart disease, stroke, thrombophlebitis, dysrhythmias, varicosities
Inquire about symptoms...
Longitudinal Research02:20

Longitudinal Research

Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...

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Updated: Jul 4, 2026

A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program
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A Novel Digital Platform for a Monitored Home-based Cardiac Rehabilitation Program

Published on: April 19, 2019

Longitudinal Psychosocial and Sleep Assessments for Long-Term Cardiovascular Risk Stratification After First

Bhargava Sai Mukkirla, Bebeto Rai, Debarshi Dey

    Medical Principles and Practice : International Journal of the Kuwait University, Health Science Centre
    |July 2, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Longitudinal follow-up measures modestly improved prediction of major adverse cardiovascular events (MACE) after myocardial infarction (MI). Simple clinical and patient-reported data enhance risk assessment beyond the GRACE score.

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    Multi-Modal Home Sleep Monitoring in Older Adults
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    Published on: January 26, 2019

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    Multi-Modal Home Sleep Monitoring in Older Adults
    07:40

    Multi-Modal Home Sleep Monitoring in Older Adults

    Published on: January 26, 2019

    Area of Science:

    • Cardiology
    • Clinical Epidemiology
    • Health Outcomes Research

    Background:

    • The risk of myocardial infarction (MI) extends beyond the acute phase.
    • In-hospital risk scores like the Global Registry of Acute Coronary Events (GRACE) may not fully capture long-term patient vulnerability.
    • Predicting long-term major adverse cardiovascular events (MACE) requires refined prognostic tools.

    Purpose of the Study:

    • To evaluate if longitudinal clinical and patient-reported measures improve MACE prediction in first MI patients.
    • To assess the incremental prognostic value of follow-up data beyond established risk scores.
    • To identify simple, accessible measures for enhanced long-term cardiovascular risk stratification.

    Main Methods:

    • Prospective cohort study of 319 first MI patients in rural South India.
    • MACE defined as cardiovascular death, non-fatal MI, stroke, heart failure hospitalization, or urgent revascularization.
    • Longitudinal data collection included clinical, biochemical, psychosocial (PHQ-9, GAD-7), and sleep variables at 1, 6, and 12 months post-MI.
    • Cox models incorporated GRACE score and follow-up variables; performance assessed using C-index and AUC.

    Main Results:

    • Over 5.8 years median follow-up, 29.5% of patients experienced MACE.
    • The baseline model showed modest improvement over GRACE alone (C-index 0.622 vs. 0.556).
    • The extended model with follow-up data demonstrated higher discrimination (optimism-corrected C-index 0.660).
    • Follow-up sleep quality, psychosocial symptoms, glycemic control, and global longitudinal strain contributed to prediction.

    Conclusions:

    • Longitudinal follow-up measures offer modest incremental prognostic information for MACE beyond the GRACE score.
    • These findings are exploratory and necessitate external validation for clinical application.
    • Simple, patient-centered data collected post-MI can enhance long-term risk assessment.