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Heart failure can be classified in various ways, with the most common classifications based on physical activity limitations, disease progression, severity, and treatment strategies.The Functional Classification of Heart Failure divides patients into four categories based on physical activity limitation due to symptom burden.Class I: Patients in this class have cardiac disease but no physical activity limitations. Ordinary activities like walking, climbing stairs, or routine tasks do not cause...
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Systolic Heart Failure and Compensatory MechanismsSystolic heart failure (also termed HFrEF, Heart Failure with Reduced Ejection Fraction) is the most prevalent type of heart filure. It results in a decreased volume of blood being pumped from the ventricle. The aortic arch and carotid sinuses have baroreceptors that detect reduced blood pressure, triggering the sympathetic nervous system (SNS) to release epinephrine and norepinephrine. Initially, this response aims to boost heart rate and...
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Heart Failure I: Introduction01:27

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Heart failure refers to a clinical syndrome caused by structural or functional cardiac disorders that prevent the heart from pumping an adequate amount of blood to meet the body's metabolic needs. This condition often arises from myocardial infarction or ischemia, leading to decreased cardiac output, reduced tissue perfusion, impaired gas exchange, fluid volume imbalance, and decreased functional ability.Heart failure can result from disruptions in the mechanisms that regulate cardiac output...
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Heart failure (HF) is a progressive syndrome involving ventricles that leads to inadequate cardiac output. It can be classified based on location and output or ejection fraction. Ejection fraction (EF) is an essential measurement in the diagnosis and surveillance of HF. Reduced EF corresponds to systolic heart failure (HFrEF). However, HF with preserved ejection fraction (HFpEF) is becoming increasingly prevalent. Also known as diastolic HF, this form of HF is related to aging. The...
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Heart failure (HF) manifests primarily as dyspnea, fatigue, and fluid retention, resulting in peripheral and pulmonary edema. Symptoms may vary depending on which ventricle is more affected, left or right.Left-Sided Heart FailureAlso known as left ventricular failure, this condition results from the left ventricle's inability to fill or eject sufficient blood into the systemic circulation. It leads to pulmonary congestion, which occurs when the left ventricle fails to eject blood effectively...
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  1. Home
  3. Development And Validation Of A Long-term Incident Heart Failure Risk Model.
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  3. Development And Validation Of A Long-term Incident Heart Failure Risk Model.

Related Experiment Video

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
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Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure

Published on: June 10, 2025

295

Development and Validation of a Long-Term Incident Heart Failure Risk Model.

Sadiya S Khan1,2, Hongyan Ning2, Norrina B Allen2

  • 1Division of Cardiology, Department of Medicine (S.S.K., C.W.Y., S.J.S., J.T.W., D.M.L.-J.), Northwestern University Feinberg School of Medicine, Chicago, IL.

Circulation Research
|December 10, 2021

View abstract on PubMed

Summary
This summary is machine-generated.

New heart failure (HF) risk equations predict 30-year risk, identifying high-risk individuals for earlier interventions. These sex- and race-specific models improve long-term HF risk assessment.

Keywords:
adultfemalehumansmaleyoung adult

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Area of Science:

  • Cardiology
  • Epidemiology
  • Preventive Medicine

Background:

  • Heart failure (HF) poses a high lifetime risk, with significant variations across sex and race.
  • Existing models lack the ability to estimate long-term HF risk, hindering early identification and intervention in high-risk populations.

Purpose of the Study:

  • To derive and validate sex- and race-specific 30-year risk prediction equations for heart failure (HF).
  • To enable earlier identification and targeted interventions for individuals at high risk of developing HF.

Main Methods:

  • Utilized data from 5 population-based cohorts, including 24,938 adults aged 20-59 free of cardiovascular disease at baseline.
  • Derived and validated sex- and race-specific 30-year HF risk equations using 599,951 person-years of follow-up, accounting for competing non-HF mortality.
  • Assessed model performance using 10-fold cross-validation, evaluating discrimination (Harrell C statistics) and calibration (Hosmer-Lemeshow test).

    • Main Results:

    • Incident HF rate was 4.0 per 1000 person-years.
    • Achieved high discrimination with Harrell C statistics ranging from 0.82 to 0.85 across sex-race groups.
    • Demonstrated acceptable calibration across all subgroups, with risk estimations varying significantly by sex and race.

    Conclusions:

    • Developed sex- and race-specific equations for predicting long-term heart failure risk.
    • These models exhibit high discrimination and adequate calibration, offering a valuable tool for risk stratification.
    • The findings support earlier identification and tailored interventions for individuals at elevated risk of HF.