A new method to detect erratic sinus rhythm in RR-interval files generated from Holter recordings

Peter P. Domitrovich; P. K. Stein

A new method to detect erratic sinus rhythm in RR-interval files generated from Holter recordings

Peter P. Domitrovich
, P. K. Stein

Research output: Contribution to journal › Conference article › peer-review

Abstract

Episodes of erratic sinus rhythm (ESR), assumed to be as a high-degree of non-respiratory sinus arrhythmia with normal p-waves, are seen on Holter recordings in the elderly and cardiac patients. ESR increases heart rate variability (HRV) and may confound its predictive value. We hypothesized that a triplet of normal-to-normal (NN) intervals represented by (N₁N₂N₃N₄) is ESR if N₁N₂/N₂N₃ and N₂N₃/N₃N₄ are both outliers in the distribution of NN-interval ratios. The time spent in ESR in each ten-minute segment was visually estimated using a heart-rate tachogram of NN intervals (HRTACH) and compared with the calculated values. A total of 858 ten-minute segments in six randomly selected 24-Hour recordings of older adults were examined. A qualitative test of the algorithm yielded a positive predictive value of 0.83 and a negative predictive value of 0.87 for 552 positive tests. Results suggest that the method can identify subjects with and without ESR in RR-interval files.

Original language	English
Pages (from-to)	665-668
Number of pages	4
Journal	Computers in Cardiology
Volume	29
State	Published - Dec 1 2002
Event	Computers in Cardiology 2002 - Memphis, TN, United States Duration: Sep 22 2002 → Sep 25 2002

Cite this

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title = "A new method to detect erratic sinus rhythm in RR-interval files generated from Holter recordings",

abstract = "Episodes of erratic sinus rhythm (ESR), assumed to be as a high-degree of non-respiratory sinus arrhythmia with normal p-waves, are seen on Holter recordings in the elderly and cardiac patients. ESR increases heart rate variability (HRV) and may confound its predictive value. We hypothesized that a triplet of normal-to-normal (NN) intervals represented by (N1N2N3N4) is ESR if N1N2/N2N3 and N2N3/N3N4 are both outliers in the distribution of NN-interval ratios. The time spent in ESR in each ten-minute segment was visually estimated using a heart-rate tachogram of NN intervals (HRTACH) and compared with the calculated values. A total of 858 ten-minute segments in six randomly selected 24-Hour recordings of older adults were examined. A qualitative test of the algorithm yielded a positive predictive value of 0.83 and a negative predictive value of 0.87 for 552 positive tests. Results suggest that the method can identify subjects with and without ESR in RR-interval files.",

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TY - JOUR

T1 - A new method to detect erratic sinus rhythm in RR-interval files generated from Holter recordings

AU - Domitrovich, Peter P.

AU - Stein, P. K.

PY - 2002/12/1

Y1 - 2002/12/1

N2 - Episodes of erratic sinus rhythm (ESR), assumed to be as a high-degree of non-respiratory sinus arrhythmia with normal p-waves, are seen on Holter recordings in the elderly and cardiac patients. ESR increases heart rate variability (HRV) and may confound its predictive value. We hypothesized that a triplet of normal-to-normal (NN) intervals represented by (N1N2N3N4) is ESR if N1N2/N2N3 and N2N3/N3N4 are both outliers in the distribution of NN-interval ratios. The time spent in ESR in each ten-minute segment was visually estimated using a heart-rate tachogram of NN intervals (HRTACH) and compared with the calculated values. A total of 858 ten-minute segments in six randomly selected 24-Hour recordings of older adults were examined. A qualitative test of the algorithm yielded a positive predictive value of 0.83 and a negative predictive value of 0.87 for 552 positive tests. Results suggest that the method can identify subjects with and without ESR in RR-interval files.

AB - Episodes of erratic sinus rhythm (ESR), assumed to be as a high-degree of non-respiratory sinus arrhythmia with normal p-waves, are seen on Holter recordings in the elderly and cardiac patients. ESR increases heart rate variability (HRV) and may confound its predictive value. We hypothesized that a triplet of normal-to-normal (NN) intervals represented by (N1N2N3N4) is ESR if N1N2/N2N3 and N2N3/N3N4 are both outliers in the distribution of NN-interval ratios. The time spent in ESR in each ten-minute segment was visually estimated using a heart-rate tachogram of NN intervals (HRTACH) and compared with the calculated values. A total of 858 ten-minute segments in six randomly selected 24-Hour recordings of older adults were examined. A qualitative test of the algorithm yielded a positive predictive value of 0.83 and a negative predictive value of 0.87 for 552 positive tests. Results suggest that the method can identify subjects with and without ESR in RR-interval files.

UR - https://www.scopus.com/pages/publications/0036945632

M3 - Conference article

AN - SCOPUS:0036945632

SN - 0276-6574

VL - 29

SP - 665

EP - 668

JO - Computers in Cardiology

JF - Computers in Cardiology

T2 - Computers in Cardiology 2002

Y2 - 22 September 2002 through 25 September 2002

ER -

A new method to detect erratic sinus rhythm in RR-interval files generated from Holter recordings

Abstract

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