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Novel Acoustic Biomarker of Quality of Life in Left Ventricular Assist Device Recipients

BACKGROUND: Although technological advances to pump design have improved survival, left ventricular assist device (LVAD) recipients experience variable improvements in quality of life. Methods for optimizing LVAD support to improve quality of life are needed. We investigated whether acoustic signatu...

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Detalles Bibliográficos
Autores principales: Mainsah, Boyla O., Patel, Priyesh A., Chen, Xinlin J., Olsen, Cameron, Collins, Leslie M., Karra, Ravi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8174227/
https://www.ncbi.nlm.nih.gov/pubmed/33660516
http://dx.doi.org/10.1161/JAHA.120.018588
Descripción
Sumario:BACKGROUND: Although technological advances to pump design have improved survival, left ventricular assist device (LVAD) recipients experience variable improvements in quality of life. Methods for optimizing LVAD support to improve quality of life are needed. We investigated whether acoustic signatures obtained from digital stethoscopes can predict patient‐centered outcomes in LVAD recipients. METHODS AND RESULTS: We followed precordial sounds over 6 months in 24 LVAD recipients (8 HeartWare HVAD™, 16 HeartMate 3 [HM3]). Subjects recorded their precordial sounds with a digital stethoscope and completed a Kansas City Cardiomyopathy Questionnaire weekly. We developed a novel algorithm to filter LVAD sounds from recordings. Unsupervised clustering of LVAD‐mitigated sounds revealed distinct groups of acoustic features. Of 16 HM3 recipients, 6 (38%) had a unique acoustic feature that we have termed the pulse synchronized sound based on its temporal association with the artificial pulse of the HM3. HM3 recipients with the pulse synchronized sound had significantly better Kansas City Cardiomyopathy Questionnaire scores at baseline (median, 89.1 [interquartile range, 86.2–90.4] versus 66.1 [interquartile range, 31.1–73.7]; P=0.03) and over the 6‐month study period (marginal mean, 77.6 [95% CI, 66.3–88.9] versus 59.9 [95% CI, 47.9–70.0]; P<0.001). Mechanistically, the pulse synchronized sound shares acoustic features with patient‐derived intrinsic sounds. Finally, we developed a machine learning algorithm to automatically detect the pulse synchronized sound within precordial sounds (area under the curve, 0.95, leave‐one‐subject‐out cross‐validation). CONCLUSIONS: We have identified a novel acoustic biomarker associated with better quality of life in HM3 LVAD recipients, which may provide a method for assaying optimized LVAD support.