A systematic approach incorporating family history improves identification of cardiovascular disease risk

Mariam Kashani1, Arn Eliasson, Marina Vernalis

  • 1Mariam Kashani, DNP, CRNP School of Nursing, Johns Hopkins University, Baltimore, and Chief Scientific Director, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Arn Eliasson, MD Senior Physician Research Consultant, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Marina Vernalis, DO Executive Medical Director, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Karla Bailey, MS Data Outcomes Analyst, Integrative Cardiac Health Project, Walter Reed National Military Medical Center, Bethesda, Maryland. Mary Terhaar, DNSc Director, Doctor of Nursing Practice Program, School of Nursing, Johns Hopkins University, Baltimore, Maryland.

Insights

Incorporating family history (FH) into cardiovascular disease (CVD) risk assessment identifies more high-risk patients. This systematic approach improves CVD risk stratification and targets prevention more effectively.

Area of Science:

  • Cardiology
  • Preventive Medicine
  • Clinical Risk Assessment

Background:

  • Family history (FH) is a key cardiovascular disease (CVD) predictor, yet not integrated into standard risk scores.
  • Current risk assessment may underestimate patient risk, leaving them vulnerable to CVD.
  • Nurses collect FH but lack tools to utilize it in risk estimation.

Purpose of the Study:

  • To evaluate a systematic method for incorporating FH into CVD risk assessment.
  • To validate risk reclassification using carotid intima-media thickness (CIMT) as a measure of atherosclerosis.

Main Methods:

  • A systematic FH assessment was applied to 239 patients with low/intermediate risk by Framingham Risk Score.
  • Positive FH for premature CVD (defined by age of event in first-degree relatives) led to risk reclassification.
  • Reclassification accuracy was validated with CIMT measurements.

Main Results:

  • 100% adherence to the systematic FH assessment protocol was observed.
  • 48% of patients (115/239) were reclassified to high risk due to positive FH.
  • Reclassified patients showed significantly higher rates of subclinical atherosclerosis (75% vs. 55% by CIMT, P < 0.001).
  • Positive FH was the strongest predictor of abnormal CIMT (OR 2.6, P=0.001).

Conclusions:

  • The systematic approach effectively enhances CVD risk assessment by identifying previously unrecognized high-risk individuals.
  • This method reduces practice variability and allows for more targeted preventive strategies.
  • Incorporating FH improves risk stratification for better CVD prevention outcomes.
Abstract

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