Detection of cardiac pathology: time intervals and spectral analysis.
OBJECTIVE
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.


CONCLUSIONS
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.
El-Segaier
Milad
M
Department of Paediatrics, Division of Paediatric Cardiology, Lund University Hospital, Lund, Sweden. milad.el-segaier@med.lu.se
Pesonen
Erkki
E
Lukkarinen
Sakari
S
Peters
Kristoffer
K
Sörnmo
Leif
L
Sepponen
Raimo
R
D000293:Adolescent; D002648:Child; D002675:Child, Preschool; D005583:Fourier Analysis; D006326:Heart Auscultation / Q000295:instrumentation*; D006330:Heart Defects, Congenital / Q000175:diagnosis* / Q000503:physiopathology; D006337:Heart Murmurs / Q000145:classification / Q000209:etiology*; D006801:Humans; D007223:Infant; D016015:Logistic Models; D010701:Phonocardiography; D011320:Primary Health Care; D012372:ROC Curve; D012680:Sensitivity and Specificity; D012815:Signal Processing, Computer-Assisted