Key result
Semi-automated visual blood pressure assessment shows an ~8 mmHg systolic error versus classical auscultation.
Why the study?
Large intra-personal variability in Korotkoff signal morphology and operator hearing acuity complicate accurate non-invasive blood pressure measurement by sphygmomanometry.
Does a semi-automated visual and algorithmic method of processing Korotkoff sounds improve the accuracy and reliability of non-invasive blood pressure measurement compared to traditional auscultation?
Observational (n=216)
Does a semi-automated visual and algorithmic method of processing Korotkoff sounds improve the accuracy and reliability of non-invasive blood pressure measurement compared to traditional auscultation?
Mean Difference: 8
Visualizing Korotkoff sound energy and applying algorithms may overcome the significant limitations and operator variability of classical sphygmomanometry, challenging its role as a gold standard for NIBP calibration.
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Questions sphygmomanometry reliability as calibration reference; leaves open whether visual/algorithmic methods improve clinical accuracy.
Celler et al. (2017) conducted an observational in Blood pressure measurement (n=216). Visual inspection and automated signal processing of Korotkoff sounds vs. Classical auscultatory method (sphygmomanometry) was evaluated on Difference in systolic pressure between auscultatory and visual/algorithmic methods (mean error 8.0 ± 5.4 mmHg). A semi-automated visual and algorithmic method for determining blood pressure revealed a mean error of 8.0 ± 5.4 mmHg for systolic pressure compared to classical auscultation.
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