A novel algorithm to assess risk of heart failure exacerbation using ICD diagnostics: validation from RAFT.
BACKGROUND
The integrated diagnostics (ID) algorithm is an implantable device-based tool that collates data pertaining to heart rhythm, heart rate, intrathoracic fluid status, and activity, producing a risk score that correlates with 30-day risk of heart failure (HF) hospitalization.


OBJECTIVE
We sought to validate the ID algorithm using the Resynchronization-Defibrillation for Ambulatory Heart Failure Trial.


METHODS
Diagnostic measures of the algorithm include OptiVol fluid index, nighttime heart rate, minutes of patient activity, heart rate variability, and combined measure of cardiac rhythm and biventricular pacing. Monthly evaluations of ID parameters were assessed for the development of HF symptoms and hospitalization for HF.


RESULTS
A total of 1224 patients were included: 741 (61%) with cardiac resynchronization therapy with defibrillator devices and 483 (39%) with implanted cardioverter-defibrillator only. The mean age was 66 ± 9 years, and 1013 (83%) were men. A total of 37,861 months of follow-up data were available, with 258 HF hospitalizations (event rate 0.68% per month). There were 33 HF hospitalizations during low-risk months (0.21% per month), 123 during medium-risk months (0.66% per month), and 102 during high-risk months (2.61% per month). Compared with low-risk months, and 95% confidence intervals) of HF hospitalizations during medium-risk months was 2.9 (2.0-4.4) and during high-risk months was 10.7 (6.9-16.6). Multivariable analysis demonstrated that each ID variable had independent association with HF hospitalization.


CONCLUSIONS
The risk of HF as determined by the ID algorithm correlated with HF hospitalization and several HF signs and symptoms among patients in the Resynchronization-Defibrillation for Ambulatory Heart Failure Trial. This may present a useful adjunct to detect early signs of HF and adjust therapy to reduce morbidity and costs involved with hospital admission.
Western University, London, Ontario, Canada. Electronic address: lgula@uwo.ca.
Lorne J
LJ
Gula
University of Ottawa Heart Institute, Ottawa, Ontario, Canada.
George A
GA
Wells
Western University, London, Ontario, Canada.
Raymond
R
Yee
Medtronic Inc, Moundsview, Minnesota.
Jodi
J
Koehler
Medtronic Inc, Moundsview, Minnesota.
Shantanu
S
Sarkar
Medtronic Inc, Moundsview, Minnesota.
Vinod
V
Sharma
Western University, London, Ontario, Canada.
Allan C
AC
Skanes
Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia.
John L
JL
Sapp
Queen's University, Kingston, Ontario, Canada.
Damian P
DP
Redfearn
Western University, London, Ontario, Canada.
Jaimie
J
Manlucu
Western University, London, Ontario, Canada; University of Ottawa Heart Institute, Ottawa, Ontario, Canada.
Anthony S L
AS
Tang
D000368:Aged; D000465:Algorithms; D017147:Defibrillators, Implantable; D003935:Diagnostic Techniques, Cardiovascular / Q000295:instrumentation*; D005260:Female; D005500:Follow-Up Studies; D005961:Glucosinolates; D006333:Heart Failure / Q000175:diagnosis* / Q000503:physiopathology / Q000628:therapy; D006339:Heart Rate / Q000502:physiology; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D008297:Male; D012008:Recurrence; D015203:Reproducibility of Results; D013997:Time Factors
D005961:Glucosinolates; C009048:progoitrin
Algorithm; Diagnosis; Heart failure; Hospital admission; ICD