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Detection of cardiac pathology: time intervals and spectral analysis.

El-Segaier, Milad LU ; Pesonen, Erkki LU ; Lukkarinen, Sakari; Peters, Kristoffer LU ; Sörnmo, Leif LU and Sepponen, Raimo (2007) In Acta Pædiatrica 96(7). p.1036-1042
Abstract
AIM: To develop an objective diagnostic method that facilitates detection of noncyanotic congenital heart diseases. METHODS: Heart sounds and murmurs were recorded from 60 healthy children and 173 children with noncyanotic congenital heart disease. Time intervals were measured and spectrum of the systolic murmurs analyzed. Stepwise logistic regression analysis was used to distinguish physiological from pathological signals. The receiver operating characteristic (ROC) curve was plotted to show the classification performance of the model and the area under the curve (AUC) was calculated. The probability cut-off points for calculation of sensitivities and specificities were estimated. RESULTS: The distinguishing variables were the interval... (More)
AIM: To develop an objective diagnostic method that facilitates detection of noncyanotic congenital heart diseases. METHODS: Heart sounds and murmurs were recorded from 60 healthy children and 173 children with noncyanotic congenital heart disease. Time intervals were measured and spectrum of the systolic murmurs analyzed. Stepwise logistic regression analysis was used to distinguish physiological from pathological signals. The receiver operating characteristic (ROC) curve was plotted to show the classification performance of the model and the area under the curve (AUC) was calculated. The probability cut-off points for calculation of sensitivities and specificities were estimated. RESULTS: The distinguishing variables were the interval from the end of the first heart sound (S(1)) and the beginning of the systolic murmur, respiratory variation of the splitting of the second heart sound, intensity of the systolic murmur, and standard deviation of the interval from the end of the S(1) to the maximum intensity of the murmur. The AUC was 0.95, indicating an excellent classification performance of the model. The sensitivity of 95% and specificity of 72% was achieved at a probability cut-off point of 0.45. Significant cardiac defects were correctly classified. CONCLUSION: Interval measurements and spectral analysis can be used to confirm significant noncyanotic congenital heart diseases. Further development of the method is necessary to detect also insignificant heart defects. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
receiver operating characteristic curve, murmur classification, heart sounds, stepwise logistic, signal analysis, regression analysis
in
Acta Pædiatrica
volume
96
issue
7
pages
1036 - 1042
publisher
Wiley-Blackwell Publishing Ltd
external identifiers
  • wos:000247681600022
  • scopus:34250670684
ISSN
1651-2227
DOI
10.1111/j.1651-2227.2007.00318.x
language
English
LU publication?
yes
id
9f884296-d5ea-4ce9-92da-dda18d73fa95 (old id 168090)
alternative location
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=17524025&dopt=Abstract
date added to LUP
2007-07-23 08:48:15
date last changed
2017-08-13 04:19:27
@article{9f884296-d5ea-4ce9-92da-dda18d73fa95,
  abstract     = {AIM: To develop an objective diagnostic method that facilitates detection of noncyanotic congenital heart diseases. METHODS: Heart sounds and murmurs were recorded from 60 healthy children and 173 children with noncyanotic congenital heart disease. Time intervals were measured and spectrum of the systolic murmurs analyzed. Stepwise logistic regression analysis was used to distinguish physiological from pathological signals. The receiver operating characteristic (ROC) curve was plotted to show the classification performance of the model and the area under the curve (AUC) was calculated. The probability cut-off points for calculation of sensitivities and specificities were estimated. RESULTS: The distinguishing variables were the interval from the end of the first heart sound (S(1)) and the beginning of the systolic murmur, respiratory variation of the splitting of the second heart sound, intensity of the systolic murmur, and standard deviation of the interval from the end of the S(1) to the maximum intensity of the murmur. The AUC was 0.95, indicating an excellent classification performance of the model. The sensitivity of 95% and specificity of 72% was achieved at a probability cut-off point of 0.45. Significant cardiac defects were correctly classified. CONCLUSION: Interval measurements and spectral analysis can be used to confirm significant noncyanotic congenital heart diseases. Further development of the method is necessary to detect also insignificant heart defects.},
  author       = {El-Segaier, Milad and Pesonen, Erkki and Lukkarinen, Sakari and Peters, Kristoffer and Sörnmo, Leif and Sepponen, Raimo},
  issn         = {1651-2227},
  keyword      = {receiver operating characteristic curve,murmur classification,heart sounds,stepwise logistic,signal analysis,regression analysis},
  language     = {eng},
  number       = {7},
  pages        = {1036--1042},
  publisher    = {Wiley-Blackwell Publishing Ltd},
  series       = {Acta Pædiatrica},
  title        = {Detection of cardiac pathology: time intervals and spectral analysis.},
  url          = {http://dx.doi.org/10.1111/j.1651-2227.2007.00318.x},
  volume       = {96},
  year         = {2007},
}