Prediction of individual combined benefit and harm for patients with atrial fibrillation considering warfarin

Guowei Li1, Anne Holbrook2, Thomas Delate3

  • 1Department of Clinical Epidemiology & Biostatistics, McMaster University, Hamilton, Ontario, Canada.

BMJ Open
|November 8, 2015
PubMed

Insights

This study develops a new prediction model for atrial fibrillation (AF) patients to assess individual risks of stroke and bleeding with warfarin therapy. The model aims to improve shared decision-making for anticoagulation treatment.

Area of Science:

  • Cardiology
  • Clinical Epidemiology
  • Health Informatics

Background:

  • Existing clinical prediction rules for atrial fibrillation (AF) lack individual patient-specific risk assessment for both treatment benefits and harms.
  • Current models do not adequately inform shared decision-making regarding anticoagulation therapy, specifically warfarin.

Purpose of the Study:

  • To develop and validate a prediction model for individual combined outcomes (stroke, major bleeding, neither) in patients considering warfarin therapy.
  • To assess the secondary outcome of all-cause mortality in relation to warfarin use.

Main Methods:

  • Utilized Kaiser Permanente Colorado (KPCO) anticoagulation databases and electronic medical records (2005-2012).
  • Included patients with AF diagnosis and no prior AF diagnosis within 180 days.
  • Employed polytomous logistic regression for primary outcomes and Cox proportional hazards regression for mortality.

Main Results:

  • A prediction model was developed using demographic, laboratory, comorbidity, and medication data.
  • The model predicts individual patient risks for stroke, major bleeding, or experiencing neither event.
  • All-cause mortality was analyzed as a secondary outcome.

Conclusions:

  • The developed prediction model offers a tool for personalized risk-benefit assessment in AF patients.
  • This model can aid clinicians and patients in making informed decisions about initiating warfarin therapy.
  • Improved shared decision-making may lead to more appropriate anticoagulation management.
Abstract

Keywords:
EPIDEMIOLOGY

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