Diagnostic performance of a new ECG algorithm for reducing false positive cases in patients suspected acute coronary syndrome.

Background: Early and correct diagnosis of ST-segment elevation myocardial infarction (STEMI) is crucial for providing timely reperfusion therapy. Patients with ischemic symptoms presenting with ST-segment elevation on the electrocardiogram (ECG) are preferably transported directly to a catheterizat...

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Publicado en:Journal of Electrocardiology Vol. 69; pp. 60 - 65
Autores principales: Fakhri, Yama, Andersson, Hedvig, Gregg, Richard E., Babaeizadeh, Saeed, Kastrup, Jens, Holmvang, Lene, Clemmensen, Peter
Formato: research Journal Article
Publicado: W B Saunders Nov2021
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: Journal of Electrocardiology
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      dt: Nov2021
      vid: 69
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      pub: W B Saunders
      place: Philadelphia, Pennsylvania
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        153730203
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        153730203
        10.1016/j.jelectrocard.2021.07.005
        NLM34571467
        153730203
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        atl: Diagnostic performance of a new ECG algorithm for reducing false positive cases in patients suspected acute coronary syndrome.
      aug:
        au:
          Fakhri, Yama
          Andersson, Hedvig
          Gregg, Richard E.
          Babaeizadeh, Saeed
          Kastrup, Jens
          Holmvang, Lene
          Clemmensen, Peter
        affil: Department of Cardiology, The Heart Centre, Rigshospitalet, Copenhagen, Denmark
      sug:
        subj:
          Acute Coronary Syndrome Diagnosis
          Emergency Medical Services
          Electrocardiography
          Algorithms
          Middle Age
          Retrospective Design
          Aged
          Male
          Middle Aged: 45-64 years
          Aged: 65+ years
          Male
      ab: Background: Early and correct diagnosis of ST-segment elevation myocardial infarction (STEMI) is crucial for providing timely reperfusion therapy. Patients with ischemic symptoms presenting with ST-segment elevation on the electrocardiogram (ECG) are preferably transported directly to a catheterization laboratory (Cath-lab) for primary percutaneous coronary intervention (PPCI). However, the ECG often contains confounding factors making the STEMI diagnosis challenging leading to false positive Cath-lab activation. The objective of this study was to test the performance of a standard automated algorithm against an additional high specificity setting developed for reducing the false positive STEMI calls.Methods: We included consecutive patients with an available digital prehospital ECG triaged directly to Cath-lab for acute coronary angiography between 2009 and 2012. An adjudicated discharge diagnosis of STEMI or no myocardial infarction (no-MI) was assigned for each patient. The new automatic algorithm contains a feature to reduce false positive STEMI interpretation. The STEMI performance with the standard setting (STD) and the high specificity setting (HiSpec) was tested against the adjudicated discharge diagnosis in a retrospective manner.Results: In total, 2256 patients with an available digital prehospital ECG (mean age 63 ± 13 years, male gender 71%) were included in the analysis. The discharge diagnosis of STEMI was assigned in 1885 (84%) patients. The STD identified 165 true negative and 1457 true positive (206 false positive and 428 false negative) cases (77.3%, 44.5%, 87.6% and 17.3% for sensitivity, specificity, PPV and NPV, respectively). The HiSpec identified 191 true negative and 1316 true positive (180 false positive and 569 false negative) cases (69.8%, 51.5%, 88.0% and 25.1% for sensitivity, specificity, PPV and NPV, respectively). From STD to HiSpec, false positive cases were reduced by 26 (12,6%), but false negative results were increased by 33%.Conclusions: Implementing an automated ECG algorithm with a high specificity setting was able to reduce the number of false positive STEMI cases. However, the predictive values for both positive and negative STEMI identification were moderate in this highly selected STEMI population. Finally, due the reduced sensitivity/increased false negatives, a negative AMI statement should not be solely based on the automated ECG statement.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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