Advances in antithrombotic therapy for ST elevation myocardial infarction (STEMI) enhance the risk of bleeding. Therefore, the incidence, determinants, and prognostic implications of in-hospital major bleeding after primary percutaneous coronary intervention for STEMI were investigated. In 963 consecutive patients, the incidence of bleeding was evaluated according to commonly used classifications including Can Rapid risk stratification of Unstable angina patients Suppress Adverse outcomes with Early implementation of the ACC/AHA guidelines, Thrombolysis In Myocardial Infarction, Global Use of Strategies To Open coronary arteries, and Bleeding Academic Research Consortium. Multivariate regression analyses investigated determinants of bleeding and the relation between bleeding and 1-year all-cause mortality. Large variability in incidence existed depending on classification (1.3% to 21%). Female gender, heart rate, creatinine, multivessel disease, cardiogenic shock, and procedural failure were independently associated with bleeding. One-year mortality reached 10.2% in bleeders versus 2.0% in nonbleeders (p <0.001). Bleeding was independently associated with an increased risk of 1-year mortality (hazard ratio [HR] 2.41, p <0.017). Assessment of individual classifications confirmed the increased risk of mortality for Bleeding Academic Research Consortium (HR 2.27, p = 0.048), but not for Can Rapid risk stratification of Unstable angina patients Suppress Adverse outcomes with Early implementation of the ACC/AHA guidelines, Thrombolysis In Myocardial Infarction, and Global Use of Strategies To Open coronary arteries bleeding. Thrombotic events occurred more frequently in bleeders (5.8% vs 1.5%, p <0.001); however, bleeding remained independently related to mortality with a negligible reduction in HR (2.25, p = 0.028) after adjustment. In conclusion, in-hospital major bleeding was frequently observed after STEMI, but a widespread variation in incidence existed depending on the applied definition. Patient and procedural characteristics were related to bleeding, allowing identification of high-risk patients. In-hospital major bleeding was independently associated with 1-year all-cause mortality; however, not all bleeding classifications proved equally relevant to prognosis. The relation between bleeding and mortality was shown not to be driven by the higher rate of thrombotic events among bleeders.
In recent years, advances in mechanical revascularization and antithrombotic therapy led to a considerable progress in the prevention of thrombotic events after acute myocardial infarction (AMI). However, the increasingly aggressive treatment strategies enhance the risk of bleeding. Although previously reported incidences strongly depend on the classification used, bleeding is undoubtedly a frequent complication, in particular after primary percutaneous coronary intervention (PCI), leading to high costs and worse prognosis. Therefore, identifying patients at highest risk for bleeding might improve outcomes by individualized treatment. Although several baseline characteristics have been consistently related to bleeding after acute coronary syndrome, other factors may play a role in case of ST elevation myocardial infarction (STEMI). In addition to an increase in morbidity and costs, previous published works reported an increased risk for death late after discharge in patients who suffered from in-hospital major bleeding, including access site bleeding, which traditionally has been considered relatively benign. However, late mortality conferred by bleeding and the mechanism behind this supposed phenomenon are subject of debate. The purpose of the present study was first to investigate the incidence of in-hospital major bleeding after primary PCI for STEMI and its determinants by evaluating both the Can Rapid risk stratification of Unstable angina patients Suppress Adverse outcomes with Early implementation of the ACC/AHA guidelines (CRUSADE) bleeding risk score and individual potential risk factors. Second, the prognostic implications of bleeding according to commonly used bleeding classifications were studied.
This was a single-center analysis of prospectively collected data from consecutive patients with STEMI enrolled in an ongoing clinical registry from January 2007 to January 2011. All patients were treated according to the institutional STEMI protocol (MISSION!) during 1 year after the index event. This protocol is based on the international guidelines and standard of STEMI care in the district of Hollands-Midden, The Netherlands. Diagnosis of STEMI was made based on typical electrocardiographic ST segment changes in combination with clinical symptoms of AMI and an increase and/or decrease of cardiac biomarkers. All patients underwent primary PCI using the femoral approach. Antithrombotic therapy included upfront abciximab (bolus of 25 μg/kg in-ambulance followed by 10 μg/kg/min for 12 hours), loading doses of aspirin (300 mg) and clopidogrel (600 mg), and periprocedural heparin (5,000 IU) and enoxaparin (1 mg/kg twice daily for 48 hours). Patients transferred to another hospital during hospitalization for geographical reasons were excluded, as well as nonresidents of The Netherlands and those without data on the CRUSADE risk score. Patients without return of spontaneous circulation after out-of-hospital cardiac arrest are not enrolled in the MISSION! Registry.
Data on patient characteristics and adverse events were prospectively entered in the departmental electronic patient dossier (EPD-Vision 10.3.3.0, LUMC, Leiden, The Netherlands) by the attending cardiologists not involved in the present study and were retrospectively analyzed. Vital status of the entire cohort was retrieved retrospectively from municipal civil registries. Patients in whom ≥2 months of clinical follow-up data (other than vital status) were lacking were considered lost to clinical follow-up. Data were included until the last date of follow-up. The primary end points of the present study were major bleeding during the index hospitalization and all-cause mortality during 1 year follow-up. Bleeding was categorized according to several predefined classifications using its criteria for major bleeding not related to coronary artery bypass grafting, including CRUSADE, Thrombolysis In Myocardial Infarction (TIMI), Global Use of Strategies To Open coronary arteries (GUSTO), and Bleeding Academic Research Consortium (BARC). Criteria for each of the classifications are listed in Table 1 . Any bleeding was defined as bleeding according to at least one of the aforementioned bleeding classifications. Spontaneous recurrent AMI during 1-year follow-up was regarded as the secondary end point for thrombotic risk and defined as a troponin-T concentration above the upper limit or a reincrease of >25% after recent AMI, both in the presence of ischemic complaints.
|BARC (class ≥3)|
Categorical data are presented as counts and percentages and continuous data as mean ± SD or median and interquartile range. Data between groups were compared with a Pearson chi-square test, a Fisher’s exact test (as appropriate), or a Student t test. Receiver operating characteristic curves evaluated the discriminative capacity of the CRUSADE risk score for bleeding by means of the area under the curve. Multivariate logistic regression analysis was performed to identify factors associated with in-hospital major bleeding, incorporating baseline variables with p <0.10 in univariate analysis: age, gender, out-of-hospital cardiac arrest, history of hypertension, diabetes mellitus, current smoking, admission creatinine, hematocrit, weight, heart rate, systolic blood pressure and Killip class, multivessel disease (≥50% stenosis in >1 major epicardial coronary vessel), periprocedural cardiogenic shock (requiring therapy), proximity of the culprit lesion, and procedural failure (final thrombolysis in myocardial infarction flow <3). The Kaplan-Meier method was used to estimate cumulative incidences of events during follow-up, which were compared with the log-rank test. To adjust for potential confounders, multivariate Cox proportional hazard regression analysis was performed in a stepwise forward fashion, entering baseline variables based on clinical judgment and p <0.10 in univariate analysis: age, diabetes mellitus, admission heart rate, admission creatinine, periprocedural cardiogenic shock, and peak creatine phosphokinase level during hospitalization. Bleeding status was forced to remain in the model. To assess the prognostic role of thrombotic events in bleeders, it was added as a dichotomous variable to the aforementioned multivariate Cox regression model. All p values were 2-sided, and p <0.05 was considered to be statistically significant. Analyses were conducted with IBM SPSS Statistics 20 (SPSS Inc., Chicago, Illinois).
In total, 1,212 patients were screened for eligibility, of whom 249 were excluded because of a transfer (219), nonresidency (11), or missing data on the CRUSADE risk score (19). The final study population comprised 963 patients. Baseline characteristics are listed in Table 2 .
|Variable||n = 963|
|Age (yrs)||61 ± 12|
|Hypertension ∗||366 (38)|
|Hyperlipidemia †||199 (21)|
|Diabetes mellitus||111 (12)|
|Current smoker||446 (47)|
|Positive family history||416 (44)|
|Previous AMI||100 (10.4)|
|Previous PCI||73 (7.6)|
|Previous coronary artery bypass grafting||27 (2.8)|
|Symptoms-to-balloon time (minutes)||165 (122–256)|
|Diagnosis-to-balloon time (minutes)||79 (68–95)|
|Abciximab-balloon time (minutes)||57 (45–70)|
|Out-of-hospital cardiac arrest||44 (4.6)|
|CRUSADE bleeding risk score||21 (14–29)|
|Admission systolic blood pressure (mm Hg)||130 (116–150)|
|Admission heart rate (beats/min)||70 (60–83)|
|Admission Killip class ≥II||20 (2.1)|
|Admission hemoglobin (mmol/L)||8.8 (8.2–9.3)|
|Admission hematocrit (%)||41 (39–44)|
|Admission creatinine (μmol/L)||77 (67–89)|
|Renal insufficiency ‡||108 (11)|
|Proximal lesion||424 (44)|
|Culprit vessel left anterior descending||400 (42)|
|Periprocedural cardiogenic shock||29 (3.0)|
|Intra-aortic balloon pump use||16 (1.7)|
|Multivessel coronary artery disease||556 (58)|
|Stent implantation||934 (97)|
|Drug-eluting stent||831 (86)|
|Initial TIMI flow ≥2||233 (24)|
|Postprocedural TIMI flow 3||887 (93)|
|Peak creatine phosphokinase (U/L)||1,240 (567–2,552)|
In 216 patients (22%), any in-hospital major bleeding event was observed as defined by at least one of the examined bleeding classifications. In 73 patients (34%), bleeding was attributed to the vascular access site. The incidence of bleeding showed a large variability depending on classification ( Table 3 ). In all classifications, the event rate increased gradually with increasing CRUSADE bleeding risk category. However, this risk score was shown to have a modest capacity to discriminate bleeders from nonbleeders in all classifications ( Table 4 ). Female gender (hazard ratio [HR] 2.58, 95% confidence interval [CI] 1.70 to 3.92, p <0.001), admission heart rate (HR 1.16, 95% CI 1.06 to 1.27 [per 10 beats/min], p = 0.001), admission creatinine (HR 1.08, 95% CI 1.00 to 1.16 [per 10 mmol/L], p = 0.044), multivessel disease (HR 1.54, 95% CI 1.07 to 2.22, p = 0.021), periprocedural cardiogenic shock (HR 3.68, 95% CI 1.45 to 9.34, p = 0.006), and procedural failure (HR 3.22, 95% CI 1.86 to 5.57, p <0.001) were individual parameters found to be independently associated with an increased risk of in-hospital major bleeding (any), whereas age (HR 1.09, 95% CI 0.93 to 1.28, p = 0.31), weight (HR 1.00, 95% CI 0.94 to 1.07, p = 0.94), and baseline hematocrit (HR 0.98, 95% CI 0.93 to 1.02, p = 0.33) were not. Of all patients alive at the time of discharge, the hospitalization duration was significantly longer in any bleeders versus nonbleeders (5 ± 5 days vs 3 ± 2 days, p <0.001).
|CRUSADE Risk Score Categories||n||Any Bleeders ∗||CRUSADE Bleeders||TIMI Bleeders||GUSTO Bleeders||BARC Bleeders|
|Very low||448||57 (13)||50 (11)||12 (2.7)||4 (0.9)||20 (4.5)|
|Low||303||75 (25)||73 (24)||27 (8.9)||4 (1.3)||29 (9.6)|
|Moderate||136||46 (34)||42 (31)||14 (10.3)||1 (0.7)||16 (12)|
|High||60||26 (43)||21 (35)||7 (12)||3 (5.0)||8 (13)|
|Very high||16||12 (75)||11 (69)||6 (38)||1 (6.2)||6 (38)|
|Total||963||216 (22)||197 (21)||66 (6.9)||13 (1.3)||79 (8.2)|
|Classification||Area Under Curve (Interquartile Range)||p|
|Any ∗||0.688 (0.649–0.728)||<0.001|