No-reflow phenomenon and comparison to the normal-flow population postprimary percutaneous coronary intervention for ST elevation myocardial infarction: case–control study (NORM PPCI)

Abstract

Introduction

No-reflow (NR) phenomenon is characterised by the failure of myocardial reperfusion despite the absence of mechanical coronary obstruction. NR negatively affects patient outcomes, emphasising the importance of prediction and management. The objective was to evaluate the incidence and independent predictors of NR in patients presenting with ST-elevation myocardial infarction (STEMI).

Methods

This was a single-centre prospective case–control study. Cases were subjects who suffered NR, and the control comparators were those who did not. Clinical outcomes were documented. Salient variables relating to the patients and their presentation, history and angiographical findings were compared using one-way analysis of variance or χ ² test. Multiple regression determined the independent predictors, and a risk score was established based on the β coefficient.

Results

Of 173 consecutive patients, 24 (13.9%) suffered from NR, with 46% occurring post stent implantation. Patients with NR had increased risk of in-hospital death (OR 7.0, 95% CI 1.3 to 36.7, p=0.022). From baseline variables available prior to percutaneous coronary intervention, the independent predictors of NR were increased lesion complexity, admission systolic hypertension, weight of <78 kg and history of hypertension. Continuous data were transformed into best-fit binary variables, and a risk score was defined. Significant difference was demonstrated between the risk score of patients with NR (4.1±1) compared with controls (2.6±1) (p<0.001), and the risk score was considered a good test (area under the curve=0.823). A score of ≥4 had 75% sensitivity and 76.5% specificity.

Conclusion

Patients with NR have a higher rate of mortality following STEMI. Predictors of NR include lesion complexity, systolic hypertension and low weight. Further validation of this risk model is required.