Literature DB >> 15742720

Computerised analysis of auscultatory sounds associated with vascular patency of haemodialysis access.

H A Mansy1, S J Hoxie, N H Patel, R H Sandler.   

Abstract

Vascular access for renal dialysis is a lifeline for about 120 000 individuals in the United States. Stethoscope auscultation of vascular sounds has some utility in the assessment of access patency, yet can be highly skill-dependent. The objective of the study was to identify acoustic parameters that are related to changes in vascular access patency. The underlying hypothesis is that stenoses of haemodialysis access vessels or grafts cause vascular sound changes that are detectable using computerised data acquisition and analysis. Eleven patients participated in the study. Their vascular sounds were recorded before and after angiography, which was accompanied by angioplasty in most patients. The sounds were acquired using two electronic stethoscopes and then digitised and analysed on a personal computer. Vessel stenosis changes were found to be associated with changes in acoustic amplitude and/or spectral energy distribution. Certain acoustic parameters correlated well (correlation coefficient = 0.98, p < 0.0001) with the change in the degree of stenosis, suggesting that stenosis severity may be predictable from these parameters. Parameters also appeared to be sensitive to modest diameter changes (> 20%), (p < 0.005, Wilcoxon rank sum test). These results suggest that computerised analysis of vascular sounds may be useful in vessel patency surveillance. Further testing using longitudinal studies may be warranted.

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Year:  2005        PMID: 15742720     DOI: 10.1007/bf02345123

Source DB:  PubMed          Journal:  Med Biol Eng Comput        ISSN: 0140-0118            Impact factor:   2.602


  21 in total

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  10 in total

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3.  Hemodialysis vascular access stenosis detection using auditory spectro-temporal features of phonoangiography.

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5.  VASCULAR STENOSIS DETECTION USING TEMPORAL-SPECTRAL DIFFERENCES IN CORRELATED ACOUSTIC MEASUREMENTS.

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Authors:  B Panda; S Chin; S Mandal; S Majerus
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7.  Bruit-enhancing phonoangiogram filter using sub-band autoregressive linear predictive coding.

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8.  Stenosis Characterization and Identification for Dialysis Vascular Access.

Authors:  S Chin; B Panda; M S Damaser; S J A Majerus
Journal:  IEEE Signal Process Med Biol Symp       Date:  2019-01-17

9.  Quantification and Visualization of Reliable Hemodynamics Evaluation Based on Non-Contact Arteriovenous Fistula Measurement.

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Journal:  Sensors (Basel)       Date:  2022-04-02       Impact factor: 3.576

10.  Feasibility of Deep Learning-Based Analysis of Auscultation for Screening Significant Stenosis of Native Arteriovenous Fistula for Hemodialysis Requiring Angioplasty.

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Journal:  Korean J Radiol       Date:  2022-10       Impact factor: 7.109

  10 in total

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