Intelligent use of advanced capabilities of diagnostic ECG algorithms in a monitoring environment.

A large number of ST-elevation notifications are generated by cardiac monitoring systems, but only a fraction of them is related to the critical condition known as ST-segment elevation myocardial infarction (STEMI) in which the blockage of coronary artery causes ST-segment elevation. Confounders suc...

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Publicado en:Journal of Electrocardiology Vol. 50; no. 5; pp. 615 - 620
Autores principales: Firoozabadi, Reza, Gregg, Richard E., Babaeizadeh, Saeed
Formato: Journal Article
Publicado: W B Saunders Sep2017
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Sep2017
      vid: 50
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      pub: W B Saunders
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        NLM28476433
        10.1016/j.jelectrocard.2017.04.013
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        atl: Intelligent use of advanced capabilities of diagnostic ECG algorithms in a monitoring environment.
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        au:
          Firoozabadi, Reza
          Gregg, Richard E.
          Babaeizadeh, Saeed
        affil: Advanced Algorithm Research Center, Philips Healthcare, Andover, MA, USA
      sug:
        subj:
          Algorithms
          Acute Coronary Syndrome Diagnosis
          Electrocardiography, Ambulatory
          Female
          Male
          Diagnosis, Differential
          Ferrans and Powers Quality of Life Index
          Short Portable Mental Status Questionnaire
          Female
          Male
      ab: A large number of ST-elevation notifications are generated by cardiac monitoring systems, but only a fraction of them is related to the critical condition known as ST-segment elevation myocardial infarction (STEMI) in which the blockage of coronary artery causes ST-segment elevation. Confounders such as acute pericarditis and benign early repolarization create electrocardiographic patterns mimicking STEMI but usually do not benefit from a real-time notification. A STEMI screening algorithm able to recognize those confounders utilizing capabilities of diagnostic ECG algorithms in variation analysis of ST segments helps to avoid triggering a non-actionable ST-elevation notification. However, diagnostic algorithms are generally designed to analyze short ECG snapshots collected in low-noise resting position and hence are susceptible to high levels of noise common in a monitoring environment. We developed a STEMI screening algorithm which performs a real-time signal quality evaluation on the ECG waveform to select the segments with quality high enough for subsequent analysis by a diagnostic ECG algorithm. The STEMI notifications generated by this multi-stage STEMI screening algorithm are significantly fewer than ST-elevation notifications generated by a continuous ST monitoring strategy.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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