Stopping the Hemorrhage
A New Baseline Bleeding Score Brings Us a Step Closer for Patients With Non–ST-Elevation Myocardial Infarction
Aggressive management of high-risk non–ST-elevation acute coronary syndrome patients has focused on reducing ischemic complications with potent medications and mechanical interventions1,2 but at the cost of increased rates of major bleeding and associated adverse outcomes.3,4 The American College of Cardiology/American Heart Association 2007 guidelines for management of patients with unstable angina/non–ST-elevation myocardial infarction (NSTEMI)1 stress the importance of balancing antithrombotic and interventional therapies with therapeutic risk, and they urge special attention in groups at high bleeding risk, including women, the elderly, and those with renal insufficiency. For risk-prone groups, careful selection and dose adjustment of antithrombotics is encouraged, but no specific instruction for calculating bleeding risk or modifying treatment is provided.
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The European Society of Cardiology’s 2007 guidelines for the diagnosis and treatment of non–ST-segment elevation acute coronary syndromes2 also recognize and devote a special section to bleeding complications, covering predictors of bleeding risk, the impact of bleeding on prognosis, the management of bleeding complications, and the impact of blood transfusions on outcomes. Major bleeding has been reported in 2% to 8% of non–ST-elevation acute coronary syndrome patients, with higher rates noted in broad-based registries (as in CRUSADE: Can Rapid risk stratification of Unstable angina patients Suppress Adverse outcomes with Early implementation of the ACC/AHA guidelines) than in controlled clinical trials. Complicating therapeutic decision making is the observation that baseline predictors of bleeding, ie, old age, female sex, renal dysfunction, and baseline anemia, also predict the risk of death due to ischemic complications.
The impact of bleeding on prognosis is increasingly recognized. Major bleeding in the Global Registry of Acute Coronary Events (GRACE) was significantly associated with in-hospital death (adjusted OR 1.645). In registries and trials of more than 30 000 patients, major bleeding was associated with a 4-fold increase in the risk of death, a 5-fold increase in recurrent myocardial infarction, and a 3-fold increase in stroke within 1 month.2 Pooled data from 4 multicenter, randomized clinical trials showed hazard ratios of 2.7 and 10.6 for moderate and severe bleeds at 1 month and hazard ratios of 2.1 and 7.5, respectively, at 6 months, with a similar impact from procedure-related and non–procedure-related bleeds.6
The mechanisms by which bleeding impacts prognosis are poorly understood and likely multifactorial. These undoubtedly include the deleterious hemodynamic effects of anemia and the need to discontinue antithrombotic drugs, with rebound prothrombotic effects and precipitation of recurrent ischemic events in an already frail population. The unique profiles of a growing list of new antithrombotic agents and interventions present an opportunity for benefit-risk refinement in therapeutic decision making. Although significant emphasis has been placed on ischemic complications, and previously developed risk tools have focused on these,7–9 quantitative approaches to bleeding risk assessment have lagged. Into this important gap in risk assessment, the CRUSADE group now has interjected a new quantitative tool for baseline bleeding risk assessment.10
The CRUSADE Quality Improvement Initiative is a large, prospective, observational database enrolling high-risk non–ST-elevation acute coronary syndrome patients admitted to participating US hospitals.11 The aim of the CRUSADE initiative was to develop and validate a scoring system for estimating on admission the in-hospital risk of major bleeding in NSTEMI patients. Data on hematocrit, transfusions, and clinical bleeding events, captured from February 15, 2003, through December 31, 2006, form the basis of this report. The large size (89 134 patients), broad representation (485 US sites), and prospective design allowed for a uniquely powerful assessment of bleeding risk factors. A random 80% sample was selected for model derivation, with the remaining 20% used for model validation. Major bleeding was defined as intracranial hemorrhage or retroperitoneal bleed, a hematocrit drop ≥12%, any red cell transfusion when baseline hematocrit was ≥28%, or a transfusion when baseline hematocrit was <28% and was associated with a clinically apparent bleed (the objective being to exclude transfusions given for baseline anemia). Plots of bleeding rates versus continuous variables were constructed, and clinically useful cut points were selected when appropriate (eg, for blood pressure, hematocrit, creatinine clearance, and heart rate). Promising univariable relationships were tested in multivariable modeling. The CRUSADE bleeding score was then developed by assigning weighted-integer values to independently contributing variables on the basis of their multivariable coefficients. Integer scores were distributed so that their summed total scores could range to a maximum of 100. The bleeding score was then tested in derivation and validation cohorts and in postadmission treatment subgroups of interest.
Characteristics of CRUSADE registry patients were generally similar to other registries of NSTEMI patients, with age averaging 67 years, a modest male preponderance (60%), and a high prevalence of coronary risk factors and prior cardiovascular disease. A high rate of major bleeding of 9.5% was observed. As anticipated, patients with a major bleed were at much higher risk for in-hospital heart failure, cardiogenic shock, and mortality. Significant univariable relationships with major bleeding were found for 6 continuous variables and 9 dichotomous variables. Of these, 8 were selected for the final multivariable model: (Lower) baseline hematocrit, (lower) creatinine clearance, (higher) heart rate, female sex, heart failure at presentation, prior vascular disease, and extreme (low or high) systolic blood pressure. The final regression model discriminated major bleeding risk modestly and equally well in derivation and validation cohorts (c statistics 0.72 and 0.71). The integer-based CRUSADE bleeding score also performed well (c statistics 0.71 and 0.70), demonstrating a curvilinear relationship between increasing score and increasing risk. Low creatinine clearance contributed especially heavily to the integer scores. Bleeding risk increased 10-fold (3% to 30%) from lowest to highest scores and from 3.1% to 19.5% across quintiles of risk score. The model discriminated bleeding risk both in those receiving ≥2 and <2 antithrombotic drugs and in those treated invasively and (less well) conservatively (c statistic 0.68). Within each risk group, bleeding events were associated with greater mortality rates.
Although impressive, the study is subject to limitations, as noted by the authors. The study cohort was not all inclusive. Unstable angina patients, CABG patients at the time of surgery, those dying within 48 hours, and transfers out were excluded. Patients given warfarin also were excluded, so its additive risk cannot be determined. Early outpatient bleeding events were not captured. Also, a past history of bleeding, a strong predictor in other models,5 was not collected. Finally, CRUSADE adds yet another to the several already proposed definitions of major bleeding. To their credit, the investigators did successfully test (c index 0.71) their bleeding model against the well-known and prognostically validated GUSTO (Global Utilization of Streptokinase and t-PA for Occluded coronary arteries) definition.12
Clinical Interpretation, Integration, and Implication
The CRUSADE bleeding score represents an incremental advance in our ability to assess the risk of major bleeding on admission for the large number of patients (≈550 000) presenting annually to hospitals with NSTEMI. In recent years, quantitative tools have been developed and validated to assess the risk of ischemic complications on admission (ie, TIMI [Thrombolysis In Myocardial Infarction],8 GRACE,9 and PURSUIT [Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using InTegrilin]7) but not the baseline (pretreatment) risk of major bleeding. Increasingly, net clinical outcomes (ischemic plus bleeding) have been recognized as worthy of formal assessment.3,4,13 Improvements in baseline bleeding risk determination improve the net risk assessment necessary for optimal therapeutic decision making.
Most of the individual variables selected in the bleeding risk model are well known from previous observations1,2,5 or are intuitive. Surprising, however, are the variables that fell out in the final model: Age, weight, and diabetes. This suggests that bleeding risk associated with each of these is largely contained in others. Although not reported, it is likely that renal dysfunction might account for a major part of age-, diabetes-, and weight-related bleeding risk. The retention of female sex is of interest. Women with high-risk NSTEMI are often older and share reduced creatinine clearance and lower weight, but sex remained an independent predictor when these and other variables were accounted for simultaneously. Overall, the observations in CRUSADE nevertheless are consistent with the unstable angina/NSTEMI guidelines,1 which recommend that therapeutic interventions in the acute phase of unstable angina/NSTEMI for diabetics, women, and the elderly generally be similar to those for nondiabetics, men, and younger patients, respectively. At the same time, the guidelines emphasize attention to appropriate dosing (ie, adjusted for weight and estimated creatinine clearance) for these special groups who are at generally higher bleeding risk.
Beyond the CRUSADE bleeding score, much remains to be done in integrating ischemic and bleeding risk estimates into overall risk assessment and therapeutic algorithms. Many patients are at high risk for both ischemic and bleeding complications. Which consideration should dominate therapeutic decision making? The past assumption that higher-benefit interventions are invariably associated with higher risk has been challenged by recent trials. For example, the anticoagulants bivalirudin4,13 (with an invasive strategy) and fondaparinux3 (especially with a conservative strategy) are reported to achieve similar antiischemic efficacy as standard therapy (ie, unfractionated or low-molecular-weight heparin) but with lower bleeding rates. In contrast, the new agent prasugrel demonstrated higher rates of major bleeding but had superior antiischemic efficacy.14 A further assumption that patients at higher ischemic risk necessarily show greater benefits with aggressive therapies also is under review, including in women, the elderly, and those with renal impairment.1 Current opinion suggests that when appropriately dosed and monitored, cardiovascular medications and interventional strategies can be applied safely in these subgroups; however, not all recent evidence is consistent with this premise, and much more about benefit-risk remains to be learned.
To meet the challenge of a knowledge gap in benefit-risk of the increasing number of therapeutic options in cardiovascular diseases, a much larger commitment to clinical effectiveness research, still in its infancy, is needed.15 Such a commitment should enable more accurate determinations of cost-effectiveness and clinical value among the various diagnostic, pharmaceutical, and device/interventional options in disease management. Clinical effectiveness research could provide the additional incremental information needed to optimize therapeutic decision making in the face of differing baseline risk assessments.
While further progress is occurring in the integration of bleeding and ischemic risk assessment and clinical effectiveness research to improve therapeutic decision making, what is the clinician to do to improve net clinical outcomes and specifically to reduce bleeding risk? Bleeding risk models that incorporate postadmission therapies may be helpful and complementary in indicating the impact of various therapies on risk. The GRACE bleeding risk model is shown in Table 1.5 (It should be noted that variables such as diuretics, intravenous inotropic agents, and right-heart catheterization may be markers for heart failure rather than causal factors, however.)
Furthermore, it has been recognized that excessive dosing of anticoagulant and antiplatelet agents frequently occurs in clinical practice and is a common cause of bleeding. In previous CRUSADE Registry reports, at least 1 dosing error for unfractionated or low-molecular-weight heparin or a glycoprotein IIb/IIIa inhibitor, used to treat non–ST-elevation acute coronary syndrome, was discovered in 42% of patients, and 15% of bleeding events could be attributed to dosing errors.16 High-risk groups for dosing errors included the elderly, women, and those with chronic kidney disease. Recognizing this as an opportunity for quality improvement, the writing committee for the American College of Cardiology/American Heart Association 2008 Performance Measures for Adults With ST-Elevation and Non–ST-Elevation Myocardial Infarction introduced 7 new test measures to address this concern (Table 2).17 These include 5 test measures to document excessive initial doses of heparin, enoxaparin, abciximab, eptifibatide, and tirofiban. A sixth measure assesses evidence of the presence of a dosing protocol in the hospital record of acute myocardial infarction patients that addresses dosing of anticoagulant and parenteral antiplatelet therapy. A seventh test measure assesses the presence of an anticoagulant error-tracking system for identifying dosing errors in antithrombotic therapy.
Aggressive medical management of NSTEMI patients is associated with an increased risk of major bleeding. Tools for assessing bleeding risk on admission have lagged behind those used to assess ischemic risk. The CRUSADE Investigators here report the successful development and validation of a multivariable baseline bleeding risk model and integer bleeding risk score. Beyond this, much remains to be done, including the integration of ischemic and bleeding risk determinations into a net risk assessment tool and the testing of a growing number of new therapeutic options against standard approaches in clinical effectiveness trials. Meanwhile, measures to ensure appropriate dosing of anticoagulant and parenteral antiplatelet agents could represent another important step forward.
The opinions expressed in this article are not necessarily those of the editors or of the American Heart Association.
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