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Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads
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| Zeitschriftentitel: | The Open Biomedical Engineering Journal |
|---|---|
| Personen und Körperschaften: | , , , , |
| In: | The Open Biomedical Engineering Journal, 10, 2016, 1, S. 43-50 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Bentham Science Publishers Ltd.
|
| Schlagwörter: |
| author_facet |
Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. |
|---|---|
| author |
Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. |
| spellingShingle |
Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. The Open Biomedical Engineering Journal Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads Biomedical Engineering Medicine (miscellaneous) Bioengineering |
| author_sort |
giuliani, c. |
| spelling |
Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. 1874-1207 Bentham Science Publishers Ltd. Biomedical Engineering Medicine (miscellaneous) Bioengineering http://dx.doi.org/10.2174/1874120701610010043 <jats:p>Electrocardiographic (ECG) T-wave endpoint (T<jats:sub>end</jats:sub>) identification suffers lack of reliability due to the presence of noise and variability among leads. T<jats:sub>end</jats:sub> identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve T<jats:sub>end</jats:sub> identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable T<jats:sub>end</jats:sub> identification. To this aim T<jats:sub>end</jats:sub> measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that T<jats:sub>end</jats:sub> distributions have not statistically different median values (CHS: 340 ms <jats:italic>vs</jats:italic>. 340 ms, respectively; AMIP: 325 ms <jats:italic>vs</jats:italic>. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10<jats:sup>-27</jats:sup>). Thus, measuring T<jats:sub>end</jats:sub> from the 15-dependent-lead DTWs is statistically equivalent to measuring T<jats:sub>end</jats:sub> from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic T<jats:sub>end</jats:sub> identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the T<jats:sub>end</jats:sub> determination from 15 dependent lead DTWs.</jats:p> Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads The Open Biomedical Engineering Journal |
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| title |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_unstemmed |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_full |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_fullStr |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_full_unstemmed |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_short |
Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_sort |
automatic identification of the repolarization endpoint by computing the dominant t-wave on a reduced number of leads |
| topic |
Biomedical Engineering Medicine (miscellaneous) Bioengineering |
| url |
http://dx.doi.org/10.2174/1874120701610010043 |
| publishDate |
2016 |
| physical |
43-50 |
| description |
<jats:p>Electrocardiographic (ECG) T-wave endpoint (T<jats:sub>end</jats:sub>) identification suffers lack of reliability due to the presence of noise and variability among leads. T<jats:sub>end</jats:sub> identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve T<jats:sub>end</jats:sub> identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable T<jats:sub>end</jats:sub> identification. To this aim T<jats:sub>end</jats:sub> measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that T<jats:sub>end</jats:sub> distributions have not statistically different median values (CHS: 340 ms <jats:italic>vs</jats:italic>. 340 ms, respectively; AMIP: 325 ms <jats:italic>vs</jats:italic>. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10<jats:sup>-27</jats:sup>). Thus, measuring T<jats:sub>end</jats:sub> from the 15-dependent-lead DTWs is statistically equivalent to measuring T<jats:sub>end</jats:sub> from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic T<jats:sub>end</jats:sub> identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the T<jats:sub>end</jats:sub> determination from 15 dependent lead DTWs.</jats:p> |
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| author | Giuliani, C., Agostinelli, A., Di Nardo, F., Fioretti, S., Burattini, L. |
| author_facet | Giuliani, C., Agostinelli, A., Di Nardo, F., Fioretti, S., Burattini, L., Giuliani, C., Agostinelli, A., Di Nardo, F., Fioretti, S., Burattini, L. |
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| description | <jats:p>Electrocardiographic (ECG) T-wave endpoint (T<jats:sub>end</jats:sub>) identification suffers lack of reliability due to the presence of noise and variability among leads. T<jats:sub>end</jats:sub> identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve T<jats:sub>end</jats:sub> identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable T<jats:sub>end</jats:sub> identification. To this aim T<jats:sub>end</jats:sub> measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that T<jats:sub>end</jats:sub> distributions have not statistically different median values (CHS: 340 ms <jats:italic>vs</jats:italic>. 340 ms, respectively; AMIP: 325 ms <jats:italic>vs</jats:italic>. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10<jats:sup>-27</jats:sup>). Thus, measuring T<jats:sub>end</jats:sub> from the 15-dependent-lead DTWs is statistically equivalent to measuring T<jats:sub>end</jats:sub> from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic T<jats:sub>end</jats:sub> identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the T<jats:sub>end</jats:sub> determination from 15 dependent lead DTWs.</jats:p> |
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| spelling | Giuliani, C. Agostinelli, A. Di Nardo, F. Fioretti, S. Burattini, L. 1874-1207 Bentham Science Publishers Ltd. Biomedical Engineering Medicine (miscellaneous) Bioengineering http://dx.doi.org/10.2174/1874120701610010043 <jats:p>Electrocardiographic (ECG) T-wave endpoint (T<jats:sub>end</jats:sub>) identification suffers lack of reliability due to the presence of noise and variability among leads. T<jats:sub>end</jats:sub> identification can be improved by using global repolarization waveforms obtained by combining several leads. The dominant T-wave (DTW) is a global repolarization waveform that proved to improve T<jats:sub>end</jats:sub> identification when computed using the 15 (I to III, aVr, aVl, aVf, V1 to V6, X, Y, Z) leads usually available in clinics, of which only 8 (I, II, V1 to V6) are independent. The aim of the present study was to evaluate if the 8 independent leads are sufficient to obtain a DTW which allows a reliable T<jats:sub>end</jats:sub> identification. To this aim T<jats:sub>end</jats:sub> measures automatically identified from 15-dependent-lead DTWs of 46 control healthy subjects (CHS) and 103 acute myocardial infarction patients (AMIP) were compared with those obtained from 8-independent-lead DTWs. Results indicate that T<jats:sub>end</jats:sub> distributions have not statistically different median values (CHS: 340 ms <jats:italic>vs</jats:italic>. 340 ms, respectively; AMIP: 325 ms <jats:italic>vs</jats:italic>. 320 ms, respectively), besides being strongly correlated (CHS: ρ=0.97, AMIP: 0.88; P<10<jats:sup>-27</jats:sup>). Thus, measuring T<jats:sub>end</jats:sub> from the 15-dependent-lead DTWs is statistically equivalent to measuring T<jats:sub>end</jats:sub> from the 8-independent-lead DTWs. In conclusion, for the clinical purpose of automatic T<jats:sub>end</jats:sub> identification from DTW, the 8 independent leads can be used without a statistically significant loss of accuracy but with a significant decrement of computational effort. The lead dependence of 7 out of 15 leads does not introduce a significant bias in the T<jats:sub>end</jats:sub> determination from 15 dependent lead DTWs.</jats:p> Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads The Open Biomedical Engineering Journal |
| spellingShingle | Giuliani, C., Agostinelli, A., Di Nardo, F., Fioretti, S., Burattini, L., The Open Biomedical Engineering Journal, Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads, Biomedical Engineering, Medicine (miscellaneous), Bioengineering |
| title | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_full | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_fullStr | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_full_unstemmed | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_short | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| title_sort | automatic identification of the repolarization endpoint by computing the dominant t-wave on a reduced number of leads |
| title_unstemmed | Automatic Identification of the Repolarization Endpoint by Computing the Dominant T-wave on a Reduced Number of Leads |
| topic | Biomedical Engineering, Medicine (miscellaneous), Bioengineering |
| url | http://dx.doi.org/10.2174/1874120701610010043 |