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A New Single Chamber Implantable Defibrillator with Atrial Sensing: A Practical Demonstration of Sensing and Ease of Implantation
Published on: February 28, 2012
Predicting early mortality after implantable defibrillator implantation: a clinical risk score for optimal patient
Ratika Parkash1, William G Stevenson, Laurence M Epstein
1Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada. ratika.parkash@cdha.nshealth.ca
Insights
A new risk score helps predict early mortality in patients receiving implantable cardioverter defibrillators (ICDs). Simple clinical factors identify those at higher risk, aiding treatment decisions for advanced heart disease.
Area of Science:
- Cardiology
- Medical Devices
- Predictive Analytics
Background:
- Advanced heart disease poses sudden death risk.
- Early mortality from other causes can limit implantable cardioverter defibrillator (ICD) benefits.
- Predicting 1-year mortality post-ICD implantation is crucial.
Purpose of the Study:
- To develop a predictive model for 1-year mortality after ICD implantation.
- To identify simple clinical criteria for high-risk patients.
Main Methods:
- Retrospective analysis of 469 patients undergoing ICD implantation.
- Development of a risk score using multivariate logistic regression.
- Validation of the risk score in a separate patient cohort.
Main Results:
- A risk score was derived using age > 80, atrial fibrillation, creatinine > 1.8 mg/dL, and NYHA class III/IV.
- One-year mortality significantly increased with higher risk scores.
- A risk score ≥ 2 predicted 21% 1-year mortality versus 4% for scores < 2.
Conclusions:
- A simple clinical risk score can identify patients at high risk of early mortality after ICD implantation.
- This score aids in evaluating the risk/benefit of ICDs for individual patients.
- Prospective studies are warranted to confirm these findings.
Background:
Patients with advanced heart disease are at risk from sudden death; however, benefit from implantable cardioverter defibrillators (ICDs) may be limited as a result of early mortality from other causes. The objective of this study was to develop a model to predict mortality within the first year after ICD implantation.
Methods And Results:
A retrospective analysis was performed of 469 consecutive patients who underwent ICD implantation at a single tertiary-care center from 1999 to 2002. Vital status was determined from the Social Security Death Index. Patients were randomized into prediction and validation cohorts. A risk score was derived from the prediction cohort by multivariate logistic regression and applied to the validation cohort. One point was assigned for each variable in the risk score (age > 80 years, history of atrial fibrillation, creatinine > 1.8 mg/dL, New York Heart Association class III or IV). One-year mortality significantly increased with increasing risk score in both the prediction and validation cohorts. Validation cohort mortality was 3.4% for 0 points, 4.3% for 1 point, 17% for 2 points, and 33% for > or = 3 points (P for trend < .0001). A risk score > or = 2 predicted a 1-year mortality rate of 21%, whereas a risk score < 2 predicted a mortality rate of 4% at 1 year (P < .0001).
Conclusion:
A risk score using simple clinical criteria may identify patients at high risk of early mortality after ICD implantation. This may be helpful in consideration of ICD risk/benefit for individual patients. Further studies conducted in a prospective manner using these clinical criteria are warranted.
