AI Article Synopsis

  • The integrated diagnostics (ID) algorithm is a device that gathers data on heart rhythm, heart rate, fluid status, and activity to generate a risk score for predicting heart failure (HF) hospitalization within 30 days.
  • The study aimed to validate this algorithm using data from a heart failure trial involving 1224 patients, assessing diagnostic measures and hospitalizations over 37,861 months.
  • Results showed a strong correlation between the ID algorithm's risk assessment and actual HF hospitalizations, highlighting its potential as a tool for early detection and management of HF, which could help minimize healthcare costs and improve patient outcomes.

Article Abstract

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.

Conclusion: 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.

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Source
http://dx.doi.org/10.1016/j.hrthm.2014.05.015DOI Listing

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