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Catheter Ablation in Combination With Left Atrial Appendage Closure for Atrial Fibrillation
Published on: February 26, 2013
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.
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.
Introduction:
Clinical prediction rules have been validated and widely used in patients with atrial fibrillation (AF) to predict stroke and major bleeding. However, these prediction rules were not developed in the same population, and do not provide the key information that patients and prescribers need at the time anticoagulants are being considered-what is the individual patient-specific risk of both benefit (decreased stroke) and harm (increased major bleeding). In this study, our primary objective is to develop and validate a prediction model for patients' individual combined benefit and harm outcomes (stroke, major bleeding and neither event) with and without warfarin therapy. Our secondary outcome is all-cause mortality.
Methods And Analysis:
We will use data from the Kaiser Permanente Colorado (KPCO) anticoagulation management databases and electronic medical records. Patients with a primary or secondary diagnosis during an ambulatory KPCO medical office visit, emergency department visit, or inpatient stay between 1 January 2005 and 31 December 2012 with no AF diagnosis in the previous 180 days will be included. Patients' demographic characteristics, laboratory data, comorbidities, warfarin medication data and concurrent use of medication will be used to construct the prediction model. For primary outcomes (stroke with no major bleeding, and major bleeding with no stroke), we will perform polytomous logistic regression to develop a prediction model for patients' individual combined benefit and harm outcomes, taking neither event group as the reference group. As regards death, we will use Cox proportional hazards regression analysis to build a prediction model for all-cause mortality.
Ethics And Dissemination:
This study has been approved by the KPCO Institutional Review Board and the Hamilton Integrated Research Ethics Board. Results from this study will be published in a peer-reviewed journal electronically and in print. The prediction models may aid in patient-physician shared decision-making when they are considering warfarin therapy.
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