Literature DB >> 30475736

Non-Invasive Detection of Mechanical Alternans Utilizing Photoplethysmography.

Tudor Besleaga, Sveeta Badiani, Guy Lloyd, Nicola Toschi, Antonio Canichella, Andreas Demosthenous, Pier David Lambiase, Michele Orini.   

Abstract

BACKGROUND AND SIGNIFICANCE: Mechanical alternans (MA) is a biomarker associated with mortality and life-threatening arrhythmias in heart failure patients. Despite showing prognostic value, its use is limited by the requirement of measuring the continuous blood pressure (BP), which is costly and impractical.
OBJECTIVE: To develop and test, for the first time, non-invasive MA surrogates based on photoplethysmography (PPG).
METHODS: Continuous BP and PPG were recorded during clinical procedures and tests in 35 patients. MA was induced either by ventricular pacing (Group A, N = 19) or exercise (Group B, N = 16). MA was categorized as sustained or intermittent if MA episodes were observed in at least 20 or between 12 and 20 consecutive beats, respectively. Eight features characterizing the pulse morphology were derived from the PPG, and MA surrogates were evaluated.
RESULTS: Sustained alternans was observed in 9 patients (47%) from Group A, whereas intermittent alternans was observed in 13 patients (68%) from Group A and in 10 patients (63%) from Group B. The PPG-based MA surrogate showing the highest accuracy, V'M, was based on the maximum of the first derivative of the PPG pulse. It detected both sustained and intermittent MA with 100% sensitivity and 100% specificity in Group A and intermittent MA with 100% sensitivity and 83% specificity in Group B. Furthermore, the magnitudes of MA and its PPG-based surrogate were linearly correlated (R2 = 0.83, p < 0.001).
CONCLUSION: MA can be accurately identified non-invasively through PPG analysis. This may have important clinical implications for risk stratification and remote monitoring.

Entities:  

Year:  2018        PMID: 30475736     DOI: 10.1109/JBHI.2018.2882550

Source DB:  PubMed          Journal:  IEEE J Biomed Health Inform        ISSN: 2168-2194            Impact factor:   5.772


  1 in total

Review 1.  A review of wearable and unobtrusive sensing technologies for chronic disease management.

Authors:  Yao Guo; Xiangyu Liu; Shun Peng; Xinyu Jiang; Ke Xu; Chen Chen; Zeyu Wang; Chenyun Dai; Wei Chen
Journal:  Comput Biol Med       Date:  2020-12-13       Impact factor: 4.589

  1 in total

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