Heart Failure Alert Duration and Time at Risk of Heart Failure as Potential Modifier Factors of the TriageHF Algorithm in Remote Monitoring of Heart Failure: A Cohort Study

<b>Background</b>: The TriageHF algorithm provides remote monitoring for heart failure (HF), but its clinical implementation is limited by a high rate of false positive alerts. <b>Objective</b>: To assess whether incorporating alarm duration and individual time at risk can improve the diagnostic performance of the TriageHF algorithm. <b>Methods</b>: This was a single-center prospective cohort study in which 37 patients with Medtronic ICDs implanted between January 2020 and June 2022 were enrolled. HF events were defined as episodes requiring intravenous diuretics or hospitalization. A total of 609 TriageHF alerts were analyzed. Two strategies were analyzed: a standard approach (high-risk and moderate-risk alerts > 7 days considered positive) and a modified approach (high-risk and moderate-risk alerts > 15 days considered positive). The relationship between time spent in a low-risk state and the algorithm's positive predictive value (PPV) was also assessed. <b>Results</b>: In the standard configuration, sensitivity was 96.7% and specificity was 76.4%, with 81.9% of false positives. The modified approach showed improved specificity (85.6%) and PPV (24.3%), with minimal impact on sensitivity (87%) and negative predictive value (99.1%). There was a significant inverse correlation between time spent at low-risk and individual PPV (R<sup>2</sup> = 0.64, <i>p</i> = 0.018). <b>Conclusions</b>: Using a ≥15-day threshold improved the specificity and PPV of the TriageHF algorithm. Incorporating individual time at risk may further refine risk stratification and enhance cost-effectiveness in HF remote monitoring strategies.

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Journal
Diagnostics
Published
2025-12-01
DOI
https://doi.org/10.3390/diagnostics15233065
Citations
1
Primary Topic
Healthcare Technology and Patient Monitoring
Type
article
Field-Weighted Citation Impact
2.01
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article

Heart Failure Alert Duration and Time at Risk of Heart Failure as Potential Modifier Factors of the TriageHF Algorithm in Remote Monitoring of Heart Failure: A Cohort Study

Daniel García Iglesias, Roberto Massa, Fernando López Iglesias, Álvaro Lorente-Ros et al.
1 citations
Diagnostics
Healthcare Technology and Patient Monitoring
2.01
article

Heart Failure Alert Duration and Time at Risk of Heart Failure as Potential Modifier Factors of the TriageHF Algorithm in Remote Monitoring of Heart Failure: A Cohort Study

Daniel García Iglesias, Roberto Massa, Fernando López Iglesias, Álvaro Lorente-Ros, Vanesa Alonso, José Manuel Rubín López, David Ledesma Oloriz
article en
1 citations

Abstract

<b>Background</b>: The TriageHF algorithm provides remote monitoring for heart failure (HF), but its clinical implementation is limited by a high rate of false positive alerts. <b>Objective</b>: To assess whether incorporating alarm duration and individual time at risk can improve the diagnostic performance of the TriageHF algorithm. <b>Methods</b>: This was a single-center prospective cohort study in which 37 patients with Medtronic ICDs implanted between January 2020 and June 2022 were enrolled. HF events were defined as episodes requiring intravenous diuretics or hospitalization. A total of 609 TriageHF alerts were analyzed. Two strategies were analyzed: a standard approach (high-risk and moderate-risk alerts > 7 days considered positive) and a modified approach (high-risk and moderate-risk alerts > 15 days considered positive). The relationship between time spent in a low-risk state and the algorithm's positive predictive value (PPV) was also assessed. <b>Results</b>: In the standard configuration, sensitivity was 96.7% and specificity was 76.4%, with 81.9% of false positives. The modified approach showed improved specificity (85.6%) and PPV (24.3%), with minimal impact on sensitivity (87%) and negative predictive value (99.1%). There was a significant inverse correlation between time spent at low-risk and individual PPV (R<sup>2</sup> = 0.64, <i>p</i> = 0.018). <b>Conclusions</b>: Using a ≥15-day threshold improved the specificity and PPV of the TriageHF algorithm. Incorporating individual time at risk may further refine risk stratification and enhance cost-effectiveness in HF remote monitoring strategies.

DiagnosticsVol. 15(23)
Hospital Universitario Central de Asturias (ES), Instituto de Investigación Sanitaria del Principado de Asturias (ES)
Openalex Percentile: Top 10%
Healthcare Technology and Patient Monitoring
2.01
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