David E Haines1, Yongfei Wang, Jeptha Curtis. 1. Department of Cardiovascular Medicine, Oakland University William Beaumont School of Medicine, Beaumont Hospital, Royal Oak, MI, USA. dhaines@beaumont.edu
Abstract
BACKGROUND: Patients undergoing implantable cardioverter-defibrillator (ICD) implantation are at risk of postprocedural complications. However, we do not have a risk stratification schema to identify patients at high and low risk of adverse events. METHODS AND RESULTS: We analyzed data from 268 701 ICD implants submitted to the ICD Registry and developed logistic regression models to identify variables most strongly associated with the risk of acute complications and/or in-hospital death. Overall, 3.2% of the population experienced an adverse event. A simple risk score consisting of 10 readily available variables successfully identified patients at high and low risk of complications. The variables included in the score and assigned points included: age ≥ 70 years (1 point), female (2 points), New York Heart Association class III (1 point) or IV (3 points), atrial fibrillation (1 point), prior valve surgery (3 points), chronic lung disease (2 points), blood urea nitrogen >30 (2 points), reimplantation for reasons other than battery change (6 points), ICD type dual chamber (2 points) or biventricular (4 points), and nonelective ICD implant (3 points). The risk of any in-hospital complication increased from 0.6% among patients with a score of ≤ 5 (8.4% of the population) to 8.4% among patients with ≥ 19 risk points (3.9% of the population). CONCLUSIONS: A simple risk score consisting of readily available clinical variables can identify high- and low-risk subsets of patients undergoing ICD implantation. This information can guide the physician in patient selection and determining the intensity of care required post procedure.
BACKGROUND:Patients undergoing implantable cardioverter-defibrillator (ICD) implantation are at risk of postprocedural complications. However, we do not have a risk stratification schema to identify patients at high and low risk of adverse events. METHODS AND RESULTS: We analyzed data from 268 701 ICD implants submitted to the ICD Registry and developed logistic regression models to identify variables most strongly associated with the risk of acute complications and/or in-hospital death. Overall, 3.2% of the population experienced an adverse event. A simple risk score consisting of 10 readily available variables successfully identified patients at high and low risk of complications. The variables included in the score and assigned points included: age ≥ 70 years (1 point), female (2 points), New York Heart Association class III (1 point) or IV (3 points), atrial fibrillation (1 point), prior valve surgery (3 points), chronic lung disease (2 points), blood urea nitrogen >30 (2 points), reimplantation for reasons other than battery change (6 points), ICD type dual chamber (2 points) or biventricular (4 points), and nonelective ICD implant (3 points). The risk of any in-hospital complication increased from 0.6% among patients with a score of ≤ 5 (8.4% of the population) to 8.4% among patients with ≥ 19 risk points (3.9% of the population). CONCLUSIONS: A simple risk score consisting of readily available clinical variables can identify high- and low-risk subsets of patients undergoing ICD implantation. This information can guide the physician in patient selection and determining the intensity of care required post procedure.
Authors: John A Dodson; Matthew R Reynolds; Haikun Bao; Sana M Al-Khatib; Eric D Peterson; Mark S Kremers; Michael J Mirro; Jeptha P Curtis Journal: J Am Coll Cardiol Date: 2013-12-11 Impact factor: 24.094
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Authors: John A Dodson; Rachel Lampert; Yongfei Wang; Stephen C Hammill; Paul Varosy; Jeptha P Curtis Journal: Circulation Date: 2013-11-05 Impact factor: 29.690
Authors: Daniel B Kramer; Kevin F Kennedy; Peter A Noseworthy; Alfred E Buxton; Mark E Josephson; Sharon-Lise Normand; John A Spertus; Peter J Zimetbaum; Matthew R Reynolds; Susan L Mitchell Journal: Circ Cardiovasc Qual Outcomes Date: 2013-06-11
Authors: Marat Fudim; Fatima Ali-Ahmed; Craig S Parzynski; Andrew P Ambrosy; Daniel J Friedman; Sean D Pokorney; Jeptha P Curtis; Gregg C Fonarow; Frederick A Masoudi; Adrian F Hernandez; Sana M Al-Khatib Journal: JAMA Cardiol Date: 2020-06-01 Impact factor: 14.676
Authors: Alan Cheng; Darshan Dalal; Barbara Butcher; Sanaz Norgard; Yiyi Zhang; Timm Dickfeld; Zayd A Eldadah; Kenneth A Ellenbogen; Eliseo Guallar; Gordon F Tomaselli Journal: J Am Heart Assoc Date: 2013-02-22 Impact factor: 5.501