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Related Experiment Videos

INVEST substudies: design and patient characteristics.

M Keltai1, J A Johnson, P R Kowey

  • 1Hungarian Institute of Cardiology, Budapest.

Clinical Cardiology
|November 20, 2001
PubMed
Summary

The International Verapamil SR/trandolapril Study (INVEST) established a large database for hypertension research. Substudies analyzed ambulatory blood pressure monitoring, depression, and genetic factors to predict patient outcomes.

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Area of Science:

  • Cardiology
  • Hypertension Research
  • Genetics

Background:

  • The International Verapamil SR/trandolapril Study (INVEST) generated a comprehensive database for hypertension research.
  • Hypertension is a significant risk factor for cardiovascular disease, necessitating further investigation into its underlying mechanisms and effective management strategies.

Purpose of the Study:

  • To review the design and status of several substudies within the INVEST trial.
  • To explore various factors influencing hypertension, including blood pressure variability, mental health, and genetic predispositions.
  • To provide insights into predicting patient outcomes and treatment responses in hypertensive individuals.

Main Methods:

  • Ambulatory blood pressure monitoring (ABPM) was employed for objective, masked blood pressure recordings during daily activities.

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  • A depression substudy enrolled 2,393 patients to assess quality of life, energy levels, and fatigue.
  • A genotyping substudy collected genomic DNA from approximately 15,000 patients to examine gene polymorphisms associated with hypertension outcomes.

    • Main Results:

    • ABPM data will elucidate the role of nocturnal hypertension and circadian irregularities in hypertensive disease development.
    • Quality-of-life data from the depression substudy will offer insights into the patient experience.
    • Genotyping analysis aims to identify genetic markers predictive of treatment response and patient prognosis.

    Conclusions:

    • The INVEST substudies provide a rich dataset for understanding hypertension from multiple perspectives.
    • Investigating factors like ABPM, depression, and genetics can lead to personalized treatment approaches.
    • This research has the potential to improve patient outcomes and inform future hypertension management guidelines.