Long-term Monitoring of Respiratory Rate in Patients with Heart Failure: the Multiparametric Heart Failure Evaluation in Implantable Cardioverter-Defibrillator Patients (MULTITUDE-HF) Study
Overview
Authors
Affiliations
Background: Monitoring respiratory rate (RR) is recommended at the time of hospital presentation for acute decompensation in heart failure (HF). Device-based continuous monitoring of RR may be helpful for diagnostic and prognostic stratification after implantable cardioverter-defibrillator (ICD) implantation. This study was undertaken to analyze short- and long-term changes in ICD-measured RR and to relate RR with the patient's clinical status and the occurrence of HF events.
Methods: One hundred twenty-four consecutive HF patients who received ICD endowed with this diagnostic capability (Boston Scientific Inc., Natick, MA, USA) were prospectively enrolled. Patients were followed up for 12 months.
Results: At the baseline, the proportion of New York Heart Association (NYHA) class III-IV was higher among patients with daily maximum RR >27 breaths/min (third tertile) than those with <24 breaths/min (first tertile) (43 vs. 23%, p < 0.05). Moreover, the ejection fraction was lower (27 ± 7 vs. 34 ± 8%, p < 0.05). In patients with HF hospitalizations (33 events) and urgent visits for HF (15 events), the weekly average of RR calculated over the 7 days preceding hospital accesses did not differ from values recorded at the baseline and before scheduled follow-up visits. However, the weekly variation in RR (i.e., the difference between maximum and minimum values collected over the week) was significantly higher prior to hospitalization (p < 0.05). A weekly variation >3 breaths/min in maximum RR predicted an impending hospital admission for HF with sensitivity of 73 % and specificity of 57%.
Conclusions: In this study, elevated values of ICD-monitored RR identified patients with worse functional status and lower systolic function. The weekly variation in RR increased before HF exacerbation. This monitoring technology may represent a useful tool in the clinical management of patients with HF.
Santini L, Calo L, DOnofrio A, Manzo M, Dello Russo A, Savarese G Cardiovasc Digit Health J. 2024; 5(3):164-172.
PMID: 38989039 PMC: 11232427. DOI: 10.1016/j.cvdhj.2024.02.005.
Validation of the Sleepiz One + as a radar-based sensor for contactless diagnosis of sleep apnea.
Gross-Isselmann J, Eggert T, Wildenauer A, Dietz-Terjung S, Grosse Sundrup M, Schoebel C Sleep Breath. 2024; 28(4):1691-1699.
PMID: 38744804 PMC: 11303430. DOI: 10.1007/s11325-024-03057-6.
Rivas E, Lopez-Baamonde M, Sanahuja J, Del Rio E, Ramis T, Recasens A Front Med (Lausanne). 2023; 10:1243050.
PMID: 38020176 PMC: 10645134. DOI: 10.3389/fmed.2023.1243050.
Thermal Image Processing for Respiratory Estimation from Cubical Data with Expandable Depth.
Szankin M, Kwasniewska A, Ruminski J J Imaging. 2023; 9(9).
PMID: 37754948 PMC: 10532126. DOI: 10.3390/jimaging9090184.
Boriani G, Bertini M, Manzo M, Calo L, Santini L, Savarese G Europace. 2023; 25(9).
PMID: 37656991 PMC: 10498140. DOI: 10.1093/europace/euad261.