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CIED-based remote monitoring in heart failure using the HeartLogic™ algorithm: Which patients benefit most?

International Journal of Cardiology, vol. 415, pp. 132421

Abstract

BACKGROUND & AIMS: Early identification of worsening HF enables timely adjustments to prevent hospitalization. Recent studies show the HeartLogic™ algorithm detects congestion and reduces HF events. However, it is unclear which patients benefit most. Therefore, this study aims to identify and characterize HF patients who benefit most from CIED-based remote monitoring with HeartLogic™. METHODS: In this multicenter retrospective study, patients with a CIED and HeartLogic™ algorithm under structured follow-up were included. Patients were classified as having "substantial benefit" or "no benefit" from monitoring. RESULTS: In total, 242 patients were included (male n = 190, 79%, median age 61 years [IQR 61-77]). Median follow-up was 1.2 years [IQR 1.1-2.7]. Among 378 alerts, 266 were true positive (70%) and 112 false positive (30%). Of the 242 patients, 69 (29%) were classified as having "substantial benefit", while 173 (71%) had "no benefit" from HeartLogic™ monitoring. Univariate and multivariate analysis showed that patients with "substantial benefit" had higher NYHA functional class (OR 2.64, P = 0.004), higher NT-ProBNP (OR 1.02, P = 0.003), higher serum creatinine (OR 1.10, P < 0.001), lower LVEF (OR 1.19, P = 0.004), more severe mitral regurgitation (OR 2.16, P = 0.006), higher right ventricular end diastolic volume (OR 1.05, P = 0.040), higher pulmonary artery pressures (OR 1.19, P = 0.003), and were more likely to use loop diuretics (OR 2.79, P = 0.001). Among patients with "substantial benefit," the positive predictive value (PPV) of HeartLogic™ to detect congestion was 92%. CONCLUSION: The utilization of CIED-based HeartLogic™ driven HF care demonstrated pronounced efficacy, predominantly in patients exhibiting characteristics of HF at a more advanced disease stage.

Authors 9

  1. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Executive Board, Leiden University Medical Centre, Leiden, the Netherlands

  2. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

  3. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

  4. Onze Lieve Vrouwziekenhuis Hospital

    Affiliation as printed

    Cardiovascular Research Centre Aalst, Department of Cardiology, OLV Clinic, Aalst, Belgium

  5. Onze Lieve Vrouwziekenhuis Hospital

    Affiliation as printed

    Cardiovascular Research Centre Aalst, Department of Cardiology, OLV Clinic, Aalst, Belgium

  6. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

  7. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Executive Board, Leiden University Medical Centre, Leiden, the Netherlands; Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

    Executive Board, Leiden University Medical Centre, Leiden, the Netherlands

  8. Onze Lieve Vrouwziekenhuis Hospital

    Affiliation as printed

    Cardiovascular Research Centre Aalst, Department of Cardiology, OLV Clinic, Aalst, Belgium

  9. Leiden University · Leiden University Medical Center

    Affiliation as printed

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands. Electronic address: s.l.m.a.beeres@lumc.nl

    Department of Cardiology, Leiden University Medical Centre, Leiden, the Netherlands

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References 24