Accuracy of bleeding scores for patients presenting with myocardial infarction: a meta-analysis of 9 studies and 13 759 patients

Introduction

Percutaneous coronary intervention (PCI) has demonstrated a survival benefit over medical therapy in patients presenting with acute coronary syndromes (ACS). Consequently, indications have widened, including those with a relevant burden of comorbidities, from renal failure to advanced age [1–5].
Due to the increasing complexity of clinical presentation and despite continuous improvement in medical therapy and technologies, complications still affect a non-negligible number of patients, from acute kidney injury to peri-procedural myocardial infarction to bleeding [2, 5, 6]. The latter, especially, involves management of patients, in the cath lab, during subsequent hospitalization and also after discharge [7]. Major bleeding events have been clearly shown to negatively impact prognosis [7, 8], while minor bleeding may force patients to discontinue dual anti-platelet therapy, with a direct increased risk of stent thrombosis [9, 10].
A clear assessment of bleeding risk in ACS patients has become crucial to drive selection of stents in the cath lab and of antithrombotic drugs during hospitalization and after discharge. Age, hypertension, renal disease and use of oral anticoagulation therapy (OAT) have been commonly related to bleeding [11–13]. Clinical consideration, although obviously the first step, was demonstrated to be not sufficiently accurate, due to variability in clinician experience and to the different weight related to each factor [14].
At the same time, various clinical scores have been derived and externally validated, to appropriately depict the in-hospital bleeding risk of an ACS patient [11–13]. It remains unclear which of them is the most accurate, both in the overall setting of ACS and for patients presenting with ST segment elevation myocardial infarction (STEMI) or non-ST segment elevation myocardial infarction (NSTEMI).

Aim

Consequently we performed a meta-analysis to evaluate the accuracy of different bleeding risk scores for ACS patients.

Material and methods

The present paper is reported according to the PRISMA statement [15, 16].

Search strategy and inclusion/exclusion criteria

Two independent reviewers searched for pertinent articles in PubMed, Cochrane Collaboration and Google Scholar with the following query “((acute coronary syndrome) OR (ACS) OR (acute myocardial infarction) OR (MI) OR (unstable angina) OR (UA)) AND (risk score) AND (bleeding) NOT (review OR editorial OR letter)”.
The following were the inclusion criteria (all had to be met): a) studies enrolling patients presenting with acute coronary syndromes; b) externally validating scores to predict bleeding after percutaneous coronary intervention. Exclusion criteria were (one was enough): a) not ACS patients; b) duplicate reporting (in this case the larger cohort was reported).

Clinical assessment of included studies

Age, weight, body mass index, cardiovascular risk factors, clinical presentation (unstable angina, NSTEMI and STEMI), and arterial access for PCI were appraised in each study by two blinded authors (Fabrizio D’Ascenzo; Giuseppe Biondi Zoccai). Moreover, rates and definitions of major bleeding, of bleeding related to access and of patients needing transfusions were appraised.

End points

Accuracy (defined as AUC, area under the curve) of risk scores in external validation cohorts to predict major bleeding in patients with ACS was the primary end point. Sensitivity analysis was performed according to clinical presentation (STEMI and NSTEMI).

Quality assessment of included studies

Design of study (prospective/retrospective), number of centers involved and geographical area were evaluated.

Statistical analysis

Continuous variables are reported as mean (standard deviation) or median (range). Categorical variables are expressed as n/N (%). Statistical pooling was performed according to a random-effect model with generic inverse-variance weighting and computing AUC of the validation scores with 95% confidence intervals.
Using rate of events as the dependent variable, a random effect meta-regression was performed to test whether an interaction between baseline clinical features (age, gender, diabetes mellitus, NSTEMI or STEMI diagnosis, radial access) and accuracy was present, appraising major bleeding and stroke as outcomes. Moreover, impact of rates of bleeding on accuracy was tested, in order to understand the impact of reporting diagnosis.
Statistical analyses were performed with Comprehensive Metanalysis and Review Manager Revman 5.2.

Results

Four hundred eleven studies were first evaluated during research at the abstract level. Eleven articles were appraised as pertinent; two were excluded because of not evaluating ACS patients and including only patients on triple thrombotic therapy [17, 18]. Finally nine articles were included in the present review [19–27] (Figure 1).
Five of nine studies were developed in Europe, six were prospective and two were multicenter. CRUSADE, ACUITY, ACTION and GRACE [11–13, 28] were the scores externally validated (Tables I, II).
Mean age of included patients was 63 (59–64) years old, 23% (19–25) being female and 30% (28–34) presenting with diabetes mellitus. Seventy percent with STEMI (29–100), 30% with NSTEMI (0–71). Radial access was used the most 59% (49–81) (Table III).
The rate of in-hospital major bleeding was 7% (5–9.2), 1.03% (0.61–0.5) being related to access and 2.55% (2.01–2.95) needing transfusions (Table IV, Figure 2).
When evaluating all ACS patients, ACTION, CRUSADE and ACUITY performed similarly (AUC = 0.75: 0.72–0.79, I2 = 91%; 0.71: 0.64–0.80, I2 = 99%; and 0.71: 0.63–0.77, I2 = 96% respectively) when compared to GRACE (0.66; 0.64–0.67, I2 = 98%) (Figure 3).
When appraising only STEMI patients, all the scores performed similarly (Figure 4, all I2 > 90%), while CRUSADE was the only one externally validated for NSTEMI.
In meta-regression analysis, age (B = 0.9, 95% CI; p = 0.45), diabetes mellitus (B = 0.21, 95% CI; p = 0.09), gender (B = 0.046, 95% CI; p = 0.21), NSTEMI (B = 0.5, 95% CI; p = 0.001), STEMI (B = 0.01, 95% CI; p = 0.27), and radial access (B = 0.01, 95% CI; p = 0.23) did not modify accuracy of CRUSADE.
Both for ACTION and ACUITY, accuracy increased with radial access (B = 0.5, 95% CI; p = 0.004, B = 0.5, 95% CI; p < 0.001) (Table V, Figure 5).
Rates of bleedings did not modify the accuracy of the tested scores.
Definition of major bleeding, as reported in Table VI, was consistent for all studies, apart from that of Nicolau et al. [17]; after excluding it, the accuracy of ACUITY was 0.70 (0.63–0.77, I2 = 99%) without significant variation.
In funnel plot analysis (Figure 6), all the results were consistent among the studies.

Discussion

The present paper represents a systematic review about the accuracy of three scores to predict risk of bleeding in patients with ACS, demonstrating that: a) age, gender, renal function and diabetes mellitus are the most frequently appraised predictors; b) all the scores offer similar accuracy; c) CRUSADE is the only score that is externally validated for NSTEMI; d) still larger sample sizes treated with a radial access are needed to validate bleeding scores.
Among all the risk scores, age, gender, renal function and diagnosis of diabetes mellitus are the most frequently appraised predictors. Increasing age and female gender have been widely described as related to periprocedural complications, among which bleeding events are the most frequent [1, 29, 30]. Similarly, pre-procedural reduced renal function has been widely related to bleeding, because of its association with several primary hemostatic disorders, in particular to a platelet malfunction due to a decrease of the release of adenosine triphosphate and the content of serotonin [31].
In ACS settings, CRUSADE, ACTION and ACUITY are the most accurate tools, showing an accuracy higher than 0.70, which is very similarly to the GRACE score, the most extensively validated and used score predicting risk of ischemic events in ACS [28]. This similar performance is probably related to evaluation of similar risk factors and clinical predictors of bleeding, although derived from samples of different size. The CRUSADE and the ACTION scores were derived from more than 70 000 patients, compared to about 20000 for ACUITY. ACUITY included patients with unstable angina, NSTEMI and STEMI, while CRUSADE included only NSTEMI patients and ACTION included both STEMI and NSTEMI patients, consequently depicting a different population. Moreover, ACUITY was derived from patients included in two randomized controlled trials [32, 33] with pre-specified inclusion/exclusion criteria, while the other two studies were registries enrolling all consecutive patients.
These scores were derived from patients not treated with some contemporary drugs and strategies commonly used for patients with ACS. Apart from ACUITY, no data about bivalirudin have been reported, the latter being a drug showing a reduction in in-hospital bleeding. With regard to access site, contrasting data are reported. In the present meta-analysis, approach-related bleeding events represented only about 1% when compared to an overall rate of 7%. When compared to large randomized controlled trials comparing radial versus femoral access in STEMI patients [34–36], the lower incidence of access-related bleeding is confirmed, while in the present paper an overall higher rate of hemorrhages is present, probably due to inclusion also of NSTEMI patients, who usually present with higher rates of comorbidity [1, 3, 4]. It is important to note that CRUSADE was the only score externally validated in NSTEMI patients, while the other two were tested for all myocardial infarction or only STEMI.
The accuracy of the present scores increases with radial access. Radial access when compared to femoral access reduces arterial site bleeding. Consequently accuracy of scores is still used for the events not related to the site of access. The latter are more commonly related to clinical features and presentation, while access management is affected by different factors not embedded in the present score, such as experience of the operators [37].
The present work has several limitations. We considered only studies that had at least one analysis performed to assess incremental predictive ability. Many other articles reporting only risk factors without a clear evaluation of prediction were excluded, and it is important to remember that empirical evidence in other fields, for example cancer, suggests that new predictors are almost always significant. Moreover, patients with an indication for oral anticoagulation were excluded from the present study, thus limiting the potential usefulness of these scores in this population [38, 39]. Finally, meta-regression was tested on few studies.

Conclusions

ACTION, CRUSADE and ACUITY perform similarly to predict risk of bleeding in ACS patients. The CRUSADE score is the only one externally validated for NSTEMI, while accuracy of the scores increased with radial access.

Conflict of interest

The authors declare no conflict of interest.

References

1. D’Ascenzo F, Gonella A, Quadri G, e. al. Comparison of mortality rates in women versus men presenting with ST-segment elevation myocardial infarction. Am J Cardiol 2011; 107: 651-4.
2. D’Ascenzo F, Presutti DG, Picardi E, et al. Prevalence and non-invasive predictors of left main or three-vessel coronary disease: evidence from a collaborative international meta-analysis including 22 740 patients. Heart 2012; 98: 914-9.
3. Farooq V, Serruys PW, Zhang Y, et al, Short-term and long-term clinical impact of stent thrombosis and graft occlusion in the SYNTAX trial at 5 years: synergy between percutaneous coronary intervention with taxus and cardiac surgery trial. J Am Coll Cardiol 2013; 62: 2360-9.
4. Lipinski MJ, Martin RE, Cowley MJ, et Al. Effect of statins and white blood cell count on mortality in patients with ischemic left ventricular dysfunction undergoing percutaneous coronary intervention. Clin Cardiol 2006; 29: 36-41.
5. Presutti DG, D’Ascenzo F, Omede P, et al. Percutaneous coronary intervention in nonagenarian: a meta-analysis of observational studies. J Cardiovasc Med (Hagerstown) 2013; 14: 773-9.
6. Kooiman J, Seth M, Dixon S, et al. Risk of acute kidney injury after percutaneous coronary interventions using radial versus femoral vascular access: insights from the Blue Cross Blue Shield of Michigan Cardiovascular Consortium. Circ Cardiovasc Interv 2014; 7: 190-8.
7. Steg PG, Huber K, Andreotti F, et al. Bleeding in acute coronary syndromes and percutaneous coronary interventions: position paper by the Working Group on Thrombosis of the European Society of Cardiology. Eur Heart J 2011; 32: 1854-64.
8. Manoukian SV. Predictors and impact of bleeding complications in percutaneous coronary intervention, acute coronary syndromes, and ST-segment elevation myocardial infarction. Am J Cardiol 2009; 104: 9C-15C.
9. D’Ascenzo F, Bollati M, Clementi F, et al, Incidence and predictors of coronary stent thrombosis: evidence from an international collaborative meta-analysis including 30 studies, 221,066 patients, and 4276 thromboses. Int J Cardiol 2013; 167: 575-84.
10. Pierre-Louis B, Aronow WS, Yoon JH, et al. Risk factors for major bleeding and for minor bleeding after percutaneous coronary intervention in 634 consecutive patients with acute coronary syndromes. Am J Ther 2010; 17: e74-7.
11. Mathews R, Peterson ED, Chen AY, et al. In-hospital major bleeding during ST-elevation and non-ST-elevation myocardial infarction care: derivation and validation of a model from the ACTION Registry(R)-GWTG. Am J Cardiol 2011; 107: 1136-43.
12. Mehran R, Pocock SJ, and Nikolsky E, et al. A risk score to predict bleeding in patients with acute coronary syndromes. J Am Coll Cardiol 2010; 55: 2556-66.
13. Nikolsky E, Mehran R, Dangas G, et al. Development and validation of a prognostic risk score for major bleeding in patients undergoing percutaneous coronary intervention via the femoral approach. Eur Heart J 2007; 28: 1936-45.
14. Stroup DF, Berlin JA, Morton SC, et al. Meta-analysis of observational studies in epidemiology: a proposal for reporting. Meta-analysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 2000; 283: 2008-12.
15. Higgins JPT, Green S. Cochrane Handbook for Systematic Reviews of Interventions Version 5.0.2 [updated September 2009]. The Cochrane Collaboration, 2009. www.cochrane-handbook.org. 2011.
16. Puurunen MK, Kiviniemi T, Schlitt A, et al. CHADS2, CHA2DS2-VASc and HAS-BLED as predictors of outcome in patients with atrial fibrillation undergoing percutaneous coronary intervention. Thromb Res 2014; 133: 560-6.
17. Nicolau JC, Moreira HG, Baracioli LM, et al. The bleeding risk score as a mortality predictor in patients with acute coronary syndrome. Arq Bras Cardiol 2013; 101: 511-8.
18. Smith JG, Wieloch M, Koul S, et al. Triple antithrombotic therapy following an acute coronary syndrome: prevalence, outcomes and prognostic utility of the HAS-BLED score. EuroIntervention 2012; 8: 672-8.
19. Amador P, Santos JF, Goncalves S, et al. Comparison of ischemic and bleeding risk scores in non-ST elevation acute coronary syndromes. Acute Card Care 2011; 13: 68-75.
20. Abu-Assi E, Gracia-Acuna JM, Ferreira-Gonzalez I, et al. Evaluating the performance of the can rapid risk stratification of unstable angina patients suppress adverse outcomes with early implementation of the ACC/AHA Guidelines (CRUSADE) bleeding score in a contemporary Spanish cohort of patients with non-ST-segment elevation acute myocardial infarction. Circulation 2010; 121: 2419-26.
21. Abu-Assi E, Raposeiras-Roubin S, Lear P, et al. Comparing the predictive validity of three contemporary bleeding risk scores in acute coronary syndrome. Eur Heart J Acute Cardiovasc Care 2012; 1: 222-31.
22. Chew DP, Junbo G, Parsonage W, et al. Perceived risk of ischemic and bleeding events in acute coronary syndromes. Circ Cardiovasc Qual Outcomes 2013; 6: 299-308.
23. Flores-Rios X, Couto-Mallon D, Rodriguez-Garrido J, et al. Comparison of the performance of the CRUSADE, ACUITY-HORIZONS, and ACTION bleeding risk scores in STEMI undergoing primary PCI: insights from a cohort of 1391 patients. Eur Heart J Acute Cardiovasc Care 2013; 2: 19-26.
24. Lopez-Cuenca A, Manzano-Fernandez S, Marin F, et al. Beta-trace protein and cystatin c as predictors of major bleeding in non-ST-segment elevation acute coronary syndrome. Circ J 2013; 77: 2088-96.
25. Rao SV, McCoy LA, Spertus JA, et al. An updated bleeding model to predict the risk of post-procedure bleeding among patients undergoing percutaneous coronary intervention: a report using an expanded bleeding definition from the National Cardiovascular Data Registry CathPCI Registry. JACC Cardiovasc Interv 2013; 6: 897-904.
26. Ariza-Sole A, Sanchez-Elvira G, Sanchez-Salado JC, et al. CRUSADE bleeding risk score validation for ST-segment-elevation myocardial infarction undergoing primary percutaneous coronary intervention. Thromb Res 2013; 132: 652-8.
27. Ariza-Sole, Formiga F, Lorente V, et al. Efficacy of bleeding risk scores in elderly patients with acute coronary syndromes. Rev Esp Cardiol (Engl Ed) 2014; 67: 463-70.
28. D’Ascenzo F, Biondi-Zoccai G, Moretti C, et al. TIMI, GRACE and alternative risk scores in acute coronary syndromes: a meta-analysis of 40 derivation studies on 216,552 patients and of 42 validation studies on 31,625 patients. Contemp Clin Trials 2012; 33: 507-14.
29. Ahmed E, Alhabib KF, El-Menyar A, et al. Age and clinical outcomes in patients presenting with acute coronary syndromes. J Cardiovasc Dis Res 2013; 4: 134-9.
30. Chu CY, Su HM, Hsu PC, et al. Impact of chronic kidney disease in early invasive versus early conservative revascularization strategies in non-ST-segment elevation acute coronary syndromes: a population-based study from NHIRD of Taiwan. Nephron Clin Pract 2013; 124: 38-46.
31. Soslau G, Brodsky I, Putatunda B, et al. Selective reduction of serotonin storage and ATP release in chronic renal failure patients platelets. Am J Hematol 1990; 35: 171-8.
32. Stone GW, White HD, Ohman EM, et al. Bivalirudin in patients with acute coronary syndromes undergoing percutaneous coronary intervention: a subgroup analysis from the Acute Catheterization and Urgent Intervention Triage strategy (ACUITY) trial. Lancet 2007; 369: 907-19.
33. Stone GW, Witzenbichler B, Guagliumi G, et al. Bivalirudin during primary PCI in acute myocardial infarction. N Engl J Med 2008; 358: 2218-30.
34. Bernat I, Horak D, Stasek J, et al. ST-segment elevation myocardial infarction treated by radial or femoral approach in a multicenter randomized clinical trial: the STEMI-RADIAL trial. J Am Coll Cardiol 2014; 63: 964-72.
35. Jolly SS, Yusuf S, Cairns J, et al. Radial versus femoral access for coronary angiography and intervention in patients with acute coronary syndromes (RIVAL): a randomised, parallel group, multicentre trial. Lancet 2011; 377: 1409-20.
36. Romagnoli E, Biondi-Zoccai G, Sciahbasi A, et al. Radial versus femoral randomized investigation in ST-segment elevation acute coronary syndrome: the RIFLE-STEACS (Radial Versus Femoral Randomized Investigation in ST-Elevation Acute Coronary Syndrome) study. J Am Coll Cardiol 2012; 60: 2481-9.
37. Hannan EL, Farrell LS, Walford G, et al. Utilization of radial artery access for percutaneous coronary intervention for ST-segment elevation myocardial infarction in New York. JACC Cardiovasc Interv 2014; 7: 276-83.
38. D’Ascenzo F, Taha S, Moretti C, et al. Meta-analysis of randomized controlled trials and adjusted observational results of use of clopidogrel, aspirin, and oral anticoagulants in patients undergoing percutaneous coronary intervention. Am J Cardiol 2015; 115: 1185-93.
39. Kyzas PA, Deaxa-Kyza D, Ioannidis JP. Almost all articles on cancer prognostic markers report statistically significant results. Eur J Cancer 2007; 43: 2559-79.