Accurate Prediction of False ST-Segment Elevation Myocardial Infarction: Ready for Prime Time?

Mark R. Heckle, Nephertiti Efeovbokhan, Fridtjof Thomas, Mary Blumer, Mason Chumpia, Uzoma Ibebuogu, Guy L. Reed, Rami Khouzam

Research output: Contribution to journalArticle

Abstract

The incidence of inappropriate cardiac catheterization lab activation for treatment of a false ST-segment elevation myocardial infarction (STEMI) has been reported to be 2.6%-36%. Excessive inappropriate catheterization lab activation may be associated with risks to patients, provider fatigue and improper resource usage. Hypothesis: To derive and validate a prediction score to more accurately classify patients with STEMI. Methods and results: We conducted a retrospective cohort analysis of 1144 consecutive patients initially diagnosed with STEMI between September 2008 and January 2013. The incidence of catheterization laboratory activation for false STEMI was 21.4%. Multiple logistic regression identified 8 factors as important for prediction of false STEMI. Using a prediction rule derived from these factors, the area under the curve for differentiating false from true STEMI patients was 0.80 (95% CI: 0.75-0.84). Using objective standards, criteria were defined that had 95% specificity for detecting patients with an incorrect diagnosis of STEMI. In conclusion: A prediction rule has been derived and validated in a large, racially diverse group to identify false STEMI patients with an incorrect classification rate of 5%, which is an improvement over current clinical practice. Prediction rules may be particularly useful in patients with atypical presentations in which emergent catheterization cannot be achieved rapidly or carries significant patient risk.

LanguageEnglish (US)
Pages400-412
Number of pages13
JournalCurrent Problems in Cardiology
Volume43
Issue number10
DOIs
StatePublished - Oct 1 2018

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Myocardial Infarction
Catheterization
ST Elevation Myocardial Infarction
Incidence
Cardiac Catheterization
Area Under Curve
Fatigue
Cohort Studies
Logistic Models
Therapeutics

All Science Journal Classification (ASJC) codes

  • Cardiology and Cardiovascular Medicine

Cite this

Accurate Prediction of False ST-Segment Elevation Myocardial Infarction : Ready for Prime Time? / Heckle, Mark R.; Efeovbokhan, Nephertiti; Thomas, Fridtjof; Blumer, Mary; Chumpia, Mason; Ibebuogu, Uzoma; Reed, Guy L.; Khouzam, Rami.

In: Current Problems in Cardiology, Vol. 43, No. 10, 01.10.2018, p. 400-412.

Research output: Contribution to journalArticle

Heckle, Mark R. ; Efeovbokhan, Nephertiti ; Thomas, Fridtjof ; Blumer, Mary ; Chumpia, Mason ; Ibebuogu, Uzoma ; Reed, Guy L. ; Khouzam, Rami. / Accurate Prediction of False ST-Segment Elevation Myocardial Infarction : Ready for Prime Time?. In: Current Problems in Cardiology. 2018 ; Vol. 43, No. 10. pp. 400-412.
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abstract = "The incidence of inappropriate cardiac catheterization lab activation for treatment of a false ST-segment elevation myocardial infarction (STEMI) has been reported to be 2.6{\%}-36{\%}. Excessive inappropriate catheterization lab activation may be associated with risks to patients, provider fatigue and improper resource usage. Hypothesis: To derive and validate a prediction score to more accurately classify patients with STEMI. Methods and results: We conducted a retrospective cohort analysis of 1144 consecutive patients initially diagnosed with STEMI between September 2008 and January 2013. The incidence of catheterization laboratory activation for false STEMI was 21.4{\%}. Multiple logistic regression identified 8 factors as important for prediction of false STEMI. Using a prediction rule derived from these factors, the area under the curve for differentiating false from true STEMI patients was 0.80 (95{\%} CI: 0.75-0.84). Using objective standards, criteria were defined that had 95{\%} specificity for detecting patients with an incorrect diagnosis of STEMI. In conclusion: A prediction rule has been derived and validated in a large, racially diverse group to identify false STEMI patients with an incorrect classification rate of 5{\%}, which is an improvement over current clinical practice. Prediction rules may be particularly useful in patients with atypical presentations in which emergent catheterization cannot be achieved rapidly or carries significant patient risk.",
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