Annals of Emergency Medicine
Volume 52, Issue 4 , Pages 329-336.e1, October 2008

Electrocardiographic Criteria for Detecting Acute Myocardial Infarction in Patients With Left Bundle Branch Block: A Meta-analysis

Presented at the Society for Academic Emergency Medicine, May 2006, San Francisco, CA.

  • Jeffrey A. Tabas, MD

      Affiliations

    • Department of Medicine, Division of Emergency Services, San Francisco General Hospital, University of California−San Francisco, San Francisco, CA
    • Corresponding Author InformationAddress for correspondence: Jeffrey A. Tabas, MD, Room 1E21, Emergency Services, San Francisco General Hospital, San Francisco, CA 94110; 415-206-5759, fax 415-206-5818
  • ,
  • Robert M. Rodriguez, MD

      Affiliations

    • Department of Medicine, Division of Emergency Services, San Francisco General Hospital, University of California−San Francisco, San Francisco, CA
  • ,
  • Hilary K. Seligman, MD

      Affiliations

    • Division of General Internal Medicine, San Francisco General Hospital, University of California−San Francisco, San Francisco, CA
  • ,
  • Nora F. Goldschlager, MD

      Affiliations

    • Division of Cardiology, San Francisco General Hospital, University of California−San Francisco, San Francisco, CA

Received 8 August 2006; received in revised form 5 February 2007, 18 April 2007 and 29 October 2007; accepted 4 December 2007. published online 17 March 2008.

Study objective

Numerous investigators have evaluated the ECG algorithm described by Sgarbossa et al to predict acute myocardial infarction in the presence of left bundle branch block and have arrived at divergent conclusions. To clarify the utility of the Sgarbossa ECG algorithm, we perform a systematic review and meta-analysis of these trials.

Methods

A structured search was applied to MEDLINE and Scopus databases, beginning with the year that the algorithm was derived (1996). Two reviewers independently screened citations, assessed for method quality, and extracted data (individual study characteristics, screening performance, and interobserver agreement) with a standardized extraction tool. We assessed qualifying studies for heterogeneity and generated summary estimates for the sensitivity, specificity, and positive and negative likelihood ratios with fixed-effect models.

Results

We identified 11 studies with 2,100 patients that met criteria for at least 1 component of the analysis. Ten studies with 1,614 patients reported a Sgarbossa ECG algorithm score of greater than or equal to 3. These yielded a summary sensitivity of 20% (95% confidence interval [CI] 18% to 23%), specificity of 98% (95% CI 97% to 99%), a positive likelihood ratio of 7.9 (95% CI 4.5 to 13.8), and a negative likelihood ratio of 0.8 (95% CI 0.8 to 0.9). The summary diagnostic odds ratio revealed homogeneity. Seven studies with 1,213 patients reported a Sgarbossa ECG algorithm score of greater than or equal to 2. These yielded sensitivities ranging from 20% to 79% and specificities ranging from 61% to 100%. Positive likelihood ratios ranged from 0.7 to 6.6 and negative likelihood ratios ranged from 0.2 to 1.1. The summary diagnostic odds ratio revealed heterogeneity. Intra- and interobserver agreement was substantial. Sensitivity analysis using the highest-quality studies yielded similar results.

Conclusion

A Sgarbossa ECG algorithm score of greater than or equal to 3, representing greater than or equal to 1 mm of concordant ST elevation or greater than or equal to 1 mm ST depression in leads V1 to V3, is useful for diagnosing acute myocardial infarction in patients who present with left bundle branch block on ECG. The scoring system demonstrates good to excellent overall interobserver variability. A score of 2, representing 5 mm or more of discordant ST deviation, demonstrated ineffective positive likelihood ratios. A Sgarbossa ECG algorithm score of 0 is not useful in excluding acute myocardial infarction.

To access this article, please choose from the options below

Login to an existing account or Register a new account.

  • Purchase this article for 31.50 USD (You must login/register to purchase this article)

    Online access for 24 hours. The PDF version can be downloaded as your permanent record.

  • Subscribe to this title

    Get unlimited online access to this article and all other articles in this title 24/7 for one year.

  • Claim access now

    For current subscribers with Society Membership or Account Number.

  • Visit SciVerse ScienceDirect to see if you have access via your institution.
 

 Supervising editor: Judd E. Hollander, MD

 Author contributions: JAT, RMR, and NFG conceived of the study. JAT and RMR designed the trial and supervised data collection. JAT, RMR, and HKS analyzed the data. RMR and HKS provided statistical advice. JAT and RMR drafted the article, and all authors contributed substantially to its revision. JAT takes responsibility for the paper as a whole.

 Funding and support: By Annals policy, all authors are required to disclose any and all commercial, financial, and other relationships in any way related to the subject of this article, that might create any potential conflict of interest. The authors have stated that no such relationships exist. See the Manuscript Submission Agreement in this issue for examples of specific conflicts covered by this statement.

 Publication dates: Available online March 17, 2008.

 Reprints not available from the authors.

PII: S0196-0644(07)01857-4

doi:10.1016/j.annemergmed.2007.12.006

Annals of Emergency Medicine
Volume 52, Issue 4 , Pages 329-336.e1, October 2008