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Factors explaining the under-use of reperfusion therapy among ideal patients with ST-segment elevation myocardial infarction

Alter DA, Ko DT, Newman A, Tu JV. Eur Heart J. 2006; 27(13):1539-49. Epub 2006 Jun 7.


Aims — To determine the relative impact of time to hospital arrival, baseline cardiovascular risk (i.e.TIMI mortality risk index), intracerebral haemorrhage risk, and comorbid disease burden on the likelihood of not receiving reperfusion therapy among ST-segment elevation myocardial infarction (STEMI) patients without contraindications to treatment.

Methods and Results — Retrospective population-based cohort of 3994 patients admitted to 103 acute care hospitals with chest pain and STEMI within 12 h of symptom onset in Ontario, Canada, between 1999 and 2001. Patients with one or more documented absolute or relative contraindication (n=909) were excluded from the analyses. Reperfusion therapy was defined as the receipt of either fibrinolysis or primary percutaneous coronary intervention. Multivariable analysis and likelihood χ2 was used to quantify the importance of each factor in predicting the non-utilization of therapy. In total, 23.1% of patients received no reperfusion therapy. Listed in order from greatest to least importance, predictors of non-utilization of reperfusion therapy included increasing time to hospital presentation (likelihood χ2 31.6, P<0.001), higher intracerebral haemorrhage risk (likelihood χ2 27.1, P<0.001), higher baseline cardiovascular risk (likelihood χ2 25.4, P<0.001), and greater number of chronic comorbid conditions (likelihood χ2 15.4, P<0.001). The importance of each factor on non-utilization was independent, additive, not explained by age effects alone, or driven by subgroups traditionally under-represented in clinical trials.

Conclusion — Care gaps in the use of reperfusion therapy widen with both increasing baseline cardiovascular risk and increasing intracerebral haemorrhage risk. Future studies should examine whether the implementation of clinical decision tools which allow for more accurate risk–benefit tradeoff predictions improve the treatment gaps when using life-saving therapies in this patient population.

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Keywords: Coronary disease/Myocardial infarction Therapy and rehabilitation

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