Impact of periprocedural morphine use on mortality in STEMI patients treated with primary PCI.

BackgroundIntravenous morphine (MO) decreases the effect of all oral platelet P2Y12 receptor inhibitors in vitro and observational reports suggest that its use may be associated with larger infarct size. Yet, there are limited data available about the impact of this interaction on clinical outcomes. We studied the effect of MO on mortality in ST-segment elevation myocardial infarction (STEMI) patients treated with primary PCI using a prospective registry.MethodsOf the 1255 patients who underwent primary PCI, 397 received MO based on physician's judgment. Clopidogrel was used as P2Y12 receptor antagonist in all cases. Median follow-up time was 7.5 years with 457 deaths. To adjust for confounding, two propensity score-based procedures were performed: 1 to 1 matching (PSM, 728 cases), and inverse probability of treatment weighting (IPTW) retaining data from all patients. Primary outcome measure was time to all-cause death, whereas predischarge left ventricular ejection fraction (LVEF) was used as secondary end point.ResultsAn adequate balance on baseline covariates was achieved by both methods. We found no difference in survival as the HR (MO/no MO) was 0.98 (95% confidence interval [CI]: 0.76-1.26), p = 0.86 using PSM and 1.01 (95% CI: 0.84-1.23), p = 0.88 with IPTW. Likewise, distributions of LVEFs were similar using either methods: with PSM, median LVEFs were 50.0% (interquartile range [IQR]: 43.0%-55.3%) vs 50.0% (IQR: 42.0%-55.0%) in the no MO and MO groups, respectively (p = 0.76), whereas using IPTW, they were 50.0% (IQR: 42.5%-55.0%) vs 50.0% (IQR: 41.0%-55.0%), respectively (p = 0.86).ConclusionsOur data suggest that morphine use may have no impact on long-term mortality and on predischarge ejection fraction in STEMI patients treated with primary PCI

ROC curves for lactate as predictor.

Lactate level alone may have good predictive ability for predicting both in-hospital and 30-day mortality. ROC: Receiver Operating Characteristics; AUC: area under curve.</p

Discharge medication.

Discharge medication.</p

Dataset.

(CSV)</p

Internal validation.

Internal validation.</p

Fig 3 -

Exploratory analysis: Scatter / density (left panels) and box-and-whisker (right panels) plots for 30-day (upper panels) and in-hospital (lower panels) mortality. The left panels show combined scatter and density plots of the two models according to survival status. The diagonal line represents identical predictive ability. With the inclusion of lactate, the probability of dying within 30 days / during hospital stay was shifted downwards in most survivors (blue circles), whereas the majority of non-survivors (red dots) were shifted towards higher risk. The change in density plots also suggest an increased discriminatory power of the expanded models.</p

Demographic, clinical, procedural characteristics and baseline laboratory data.

Demographic, clinical, procedural characteristics and baseline laboratory data.</p

Calibration plot of the apparent and optimism-corrected models.

Calibration curves were created using a smoother on the scatter plot of expected versus observed risks. Differences between predicted and observed event rates were smaller in the expanded models in both apparent and optimism-corrected models, as shown by the decreased mean absolute error. The rug plots across the top of the figures show distribution of predicted risk. Also, the le Cessie-van Houwelingen-Copas-Hosmer test for global goodness of fit demonstrated better model fit in all apparent expanded logistic regression models (Table 3).</p