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Framingham Risk Score - Pooled Cohort ASCVD Risk Equations from 2013 American College of Cardiology and American Heart Association (ACC/AHA) Guideline on the Assessment of Cardiovascular Risk (CVD).

Installation

pip install git+https://github.com/zhaojuanwendy/framingham.git

Usage

from framingham import aha_frs_cvd
frs(gender='F', age=55, tchol=213, hdlc=50, sbp=120, smoking=0, diab=0, ht_treat=False, race='W',time=10)
X = ['F', 55, 213, 50, 120, 0, 0, False, 'W', 10]
score = frs(*X)
print(score) #expected  -29.67
risk = estimate_risk(score, mean_frs=-29.18, gender='F',race='W') #expected 0.021, mean_frs is the mean frs score of the race and sex group
print(risk)

mean_frs is the mean frs score of the race and sex group, it can be retrived from your population sample mean. It can also be used with the recommended values from ACC/AHA.

  • White women, 29.18
  • White men, 61.18
  • African American women, 86.61
  • African American mean, 19.54

Lower risk threshold

The lower risk threshold recommended by ACC/AHA is 7.5%. For implementation, the risk score produced by estimate_risk() is less than 7.5% is low risk of CVD.

Reference

  1. Goff DC, Lloyd-Jones DM, Bennett G, Coady S, D’Agostino RB, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):2935–59.https://www.sciencedirect.com/science/article/pii/S0735109713060312?via%3Dihub#tbl5
  2. Zhao, J. et al. Learning from Longitudinal Data in Electronic Health Record and Genetic Data to Improve Cardiovascular Event Prediction. bioRxiv (2018). [doi:10.1101/366682] (https://doi.org/10.1101/366682)

About

Algorithm for ASCVD algorithm published in 2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk based on framingham.

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