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HAS-BLED score predicts risk of in-hospital major bleeding in patients with acute non-ST segment elevation myocardial infarction
Thrombosis Research 136 (2015) 775–780
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HAS-BLED score predicts risk of in-hospital major bleeding in patients with acute non-ST segment elevation myocardial infarction Ming-Jer Hsieh 1, Chun-Chieh Wang 1, Chun-Chi Chen 1, Chun-Li Wang 1, Lung-Sheng Wu 1, I-Chang Hsieh ⁎ Department of Cardiology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 5, Fu-Hsing Street, Kwei-Shan, Taoyuan, Taiwan
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Article history: Received 28 June 2015 Received in revised form 3 August 2015 Accepted 22 August 2015 Available online 29 August 2015 Keywords: HAS-BLED CRUSADE ACUITY-HORIZONS Major bleeding NSTEMI
a b s t r a c t Background: The role of the Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, Drugs or alcohol use (HAS-BLED) score in the prediction of in-hospital bleeding in non-ST segment elevation myocardial infarction (NSTEMI) patients receiving dual antiplatelet therapy plus heparin was unknown. In this study, we compared the HAS-BLED score with the Can Rapid Risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines (CRUSADE) and Acute Catheterization and Urgent Intervention Triage strategY and the Harmonizing Outcomes with RevascularIZatiON and Stents in acute myocardial infarction (ACUITYHORIZONS) bleeding risk scores for in-hospital major bleeding risk stratification in NSTEMI patients. Methods: A real world population of 617 NSTEMI patients receiving dual anti-platelet plus heparin as initial therapy were enrolled. CRUSADE, ACUITY-HORIZONS and HAS-BLED risk scores were calculated for each patient. Results: This cohort had a 6.5% incidence of in-hospital major bleeding. For the prediction of in-hospital major bleeding, the discriminations between CRUSADE, ACUITY-HORIZONS and HAS-BLED were good (C-statistic 0.81, 0.82 and 0.80, respectively). There was no significant difference between these three risk scores (HASBLED vs. CRUSADE: z = −0.08, p = 0.27; HAS-BLED vs. ACUITY-HORIZONS: z = −0.06, p = 0.26; CRUSADE vs. ACUITY-HORIZONS: z = −0.15, p = 0.28). Conclusion: The CRUSADE, ACUITY-HORIZONS and HAS-BLED scores were useful tools for risk stratification of inhospital major bleeding in NSTEMI patients. The HAS-BLED score had a simpler calculation and a similar accuracy for risk assessment as the other two scores evaluated. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction Acute non-ST segment elevation myocardial infarction (NSTEMI) is a disease characterized by atherosclerotic plaque rupture-related acute thrombosis. The use of powerful anti-thrombotic therapy has been reported to reduce the ischemic complications seen in these patients [1–3]. However, this strategy increases the likelihood of bleeding, especially in high-risk patients [4–6]. Bleeding in NSTEMI patients not only increased the duration and cost of in-hospital stay, but has also been demonstrated as a predictor of adverse clinical outcomes [7–10]. A number of scoring systems have been established to predict the risk of bleeding in NSTEMI patients [11–13]. The American College of Cardiology/American Heart Association (ACC/AHA) and European Society of Cardiology (ESC) guidelines recommend the use of Can Rapid Risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines (CRUSADE) and Acute Catheterization and Urgent Intervention Triage strategY and the Harmonizing Outcomes with RevascularIZatiON and
Stents in acute myocardial infarction (ACUITY-HORIZONS) risk scores to assess bleeding risk in acute coronary syndrome [14–16]. However, the algorithms of CRUSADE and ACUITY-HORIZONS scores are based on complex scoring systems when applied in clinical practice. The Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, Drugs or alcohol use (HAS-BLED) risk score is a simpler user-friendly score, which has been shown to predict bleeding, cardiovascular events and long-term outcome in atrial fibrillation patients who received anticoagulation therapy [17,18]. Recently, HAS-BLED has also been used to predict the outcome in atrial fibrillation patients receiving percutaneous coronary intervention [19]. However, the predictive value of the HAS-BLED score in NSTEMI patients without atrial fibrillation receiving anti-thrombotic therapy remains unknown. Therefore, in this study we compared the accuracy of the HAS-BLED risk score with that of the CRUSADE and ACUITY-HORIZONS scores in predicting in-hospital major bleeding in NSTEMI patients. 2. Material and Methods
⁎ Corresponding author. E-mail address: [email protected] (I.-C. Hsieh). 1 Present address for all authors: No. 5, Fu-Hsing Street, Kwei-Shan, Taoyuan, Taiwan.
http://dx.doi.org/10.1016/j.thromres.2015.08.015 0049-3848/© 2015 Elsevier Ltd. All rights reserved.
This study was conducted at an academic teaching hospital that functions as both a secondary referral center and tertiary referral center
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serving a population of approximately two million. A total of 652 patients admitted to our cardiovascular department with a final diagnosis of NSTEMI between January 2006 and December 2009. NSTEMI was defined as elevation of troponin-I level ≥ 0.1 ng/ml, accompanied by either typical chest pain for N30 min and/or electrocardiographic change (ischemic ST-segment depression). NSTEMI patients who did not receive dual anti-platelet plus heparin as initial therapy as well as those who had to receive vitamin K antagonist or bypass surgery were excluded from the study. All enrolled patients received dual antiplatelet therapy (loading dosage: aspirin 100–325 mg & clopidogrel 300 mg; maintenance dosage of aspirin 100 mg & clopidogrel 75 mg per day) through the duration of hospital stay unless they suffered from bleeding. The choice of heparin therapy (either unfractionated or low molecular weight heparin) was based on the recommendation of the primary care physician. Treatment continued until the treating physician recommended no further anticoagulation therapy, and at least through angiography and revascularization, if performed. Intravenous unfractionated heparin was given according to a weight-adjusted nomogram (bolus of 60 U/kg [maximum of 5000 U] and initial infusion of 12 U/kg per hour) with a goal-activated partial thromboplastin time of 1.5 to 2.0 times the institutional upper limit of normal. Enoxaparin was given subcutaneously at a dose of 1 mg/kg every 12 h. None of the patients in this cohort received glycoprotein IIb/IIIa inhibitor. A total of 617 patients were included in the final analysis. All demographic
and clinical characteristics were obtained and recorded on admission. The laboratory data, pharmacological and interventional therapy information were obtained from the hospital's computer database. In-hospital major bleeding (Bleeding Academic Research Consortium type 3) was defined as a composite of intracranial, or intraocular bleeding, cardiac tamponade, bleeding requiring surgical intervention or control, reduction in hemoglobin ≧3 g/dl with an overt bleeding source or any blood transfusion with an overt bleeding source. Validation of clinical outcomes was obtained from records from the patient's primary care physicians, or by telephone contact with the patient or caregivers. This study was a retrospective analysis of prospectively collected data in clinical registry database. Patients signed informed consent for data collection and application. Appropriate permissions to conduct the study were obtained from the local institutional review board. Three bleeding risk scores, CRUSADE, ACUITY-HORIZONS and HASBLED, were calculated for each patient from the corresponding prognostic variables in Table 1. The CRUSADE bleeding risk score identified 8 baseline characteristics associated with risk of major bleeding: heart rate, systolic blood pressure, hematocrit, renal function, gender, diabetes, congestive heart failure, and prior vascular disease [11]. The variables which were calculated and weighted for the ACUITY-HORIZONS score included age, gender, white blood cell count, anemia, renal function, and raised cardiac enzyme on presentation [12]. HAS-BLED is an acronym for hypertension, abnormal liver function [defined as chronic
Table 1 CRUSADE, ACUITY-HORIZONS and HAS-BLED score calculator for bleeding risk in NSTEMI. Points from each category are added to calculate risk. CRUSADE Predictor
ACUITY-HORIZONS Score
Gender Male 0 Female 8 Diabetes No 0 Yes 6 Prior vascular disease No 0 Yes 6 Presentation with heart failure No 0 Yes 7 Baseline hematocrit (%) b31 9 31–33.9 7 34–36.9 3 37–39.9 2 ≥40 0 Creatinine clearance (ml/min) ≤15 39 N15–30 35 N30–60 28 N60–90 17 N90–120 7 N120 0 Heart rate (bpm) ≤70 0 71–80 1 81–90 3 91–100 6 101–110 8 111–120 10 ≥120 11 Systolic blood pressure (mm Hg) ≤90 10 91–100 8 101–120 5 121–180 1 181–200 3 ≥201 5
Predictor Gender Male Female Age (years) b50 50–59 60–69 70–79 ≥80 Serum creatinine (mg/dl) b1.0 1.0– 1.2– 1.4– 1.6– 1.8– ≥2.0 WBC b10 10– 12– 14– 16– 18– 20– Anemia No Yes Cardiac enzymes Normal Raised
HAS-BLED Score 0 8 0 3 6 9 12 0 2 3 5 6 8 10 0 2 3 5 6 8 10 0 6
Predictor
Score
Hypertension No 0 Yes 1 Abnormal renal function (dialysis or serum creatinine N2.6 mg/dl) No 0 Yes 1 Abnormal liver function (ALT N 100 mg/dl) No 0 Yes 1 Prior stroke No 0 Yes 1 Bleeding predisposition (anemia or bleeding history) No 0 Yes 1 High INRs (INRs N 1.3) No 0 Yes 1 Elder (age N 65 years) No 0 Yes 1 Alcohol use No 0 Yes 1 NSAIDs prescribed No 0 Yes 1
0 2
Abbreviations: ALT = alanine aminotransferase; INR = international normalized ratio; NSAID = non-steroidal anti-inflammatory drug.
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hepatic disease or Alanine Aminotransferase (ALT) N 100 mg/dl], renal dysfunction (defined as dialysis or serum creatinine N 2.6 mg/dl), prior history of stroke, anemia or predisposition to bleeding, labile international normalized ratio (defined as international normalized ratio N 1.3), elderly (age N 65), alcohol usage and prescription of nonsteroidal anti-inflammatory drugs (NSAIDs). Patients were classified into risk categories based on a modification of the originally published risk scores. The CRUSADE score distinguished three risk categories of bleeding (low risk: 0 to 25; moderate risk: 26 to 40; high risk: ≥41). Based on the ACUITY-HORIZONS risk score, patients were stratified into four risk categories for bleeding (very low risk: 0 to 11, low risk: 12 to 19, moderate risk: 20 to 27 and high risk: ≥28). HASBLED scores classified patients into three risk categories for bleeding (low risk: 0 to 1; moderate risk: 2; high risk: ≥3). Continuous variables were represented as means ± standard deviations. Categorical variables were expressed as frequencies and group percentages. The statistical normality was assessed using the Kolmogorov–Smirnov test. The χ2 test was used to compare categorical variables. ANOVA and T tests were used for variables with normal distributions, and the Whitney U test for other data. Our data contained few missing values (b1%). Missing values for categorical variables were assigned the most frequent gender-specific value, and continuous variables were assigned the gender-specific median values. Receiver operating characteristic curves were used for each of the three risk scores in order to relate the calculated scores to in-hospital major bleeding. The C-statistic defined by the area under ROC curve in relation to outcome was used as a measure of the predictive accuracy of the risk scores. Based on the cutoff with the best accuracy, the sensitivity and specificity of HAS-BLED score were calculated for the prediction of in-hospital major bleeding. The relative performance of each test was evaluated with the 95% confidence interval for the difference between two Cstatistic indices. The goodness of fit of the risk scores was evaluated
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by calculating the Hosmer–Lemeshow statistic. A p value b 0.05 was considered statistically significant. All statistical analyses were performed using the statistical software package SPSS 17.0 for Windows. 3. Results The demographics and clinical characteristics of study patients are shown in Table 2. Aspirin, clopidogrel and heparin were used as the initial antithrombotic therapy for NSTEMI in all the study patients. A total of 40 patients in this cohort (6.5%) suffered from major in-hospital
Table 2 Baseline characteristics of bleeding and non-bleeding patients.
Past medical history Age (years) Male, n (%) Diabetes mellitus, n (%) Hypertension, n (%) Current smoking, n (%) Alcohol drinking, n (%) Hypercholesterolemia, n (%) Prior stroke, n (%) Prior myocardial infarction, n (%) Prior vascular disease, n (%) Previous PCI, n (%) Previous CABG, n (%) Anemia, n (%) NSAID usage, n (%)
Bleeding (n = 40)
Non-bleeding (n = 577)
p-Value
71.8 ± 10.3 23 (57.5) 14 (35.0) 28 (70.0) 18 (45.0) 6 (15.0) 9 (22.5) 8 (20.0) 3 (7.5) 9 (22.5) 4 (10.0) 1 (2.5) 28 (70.0) 0 (0.0)
62.6 ± 13.7 463 (80.2) 194 (33.6) 332 (57.5) 310 (54.2) 96 (16.6) 189 (32.8) 57 (9.9) 77 (13.5) 127 (22.0) 74 (13.1) 12 (2.1) 109 (18.9) 15 (2.6)
b0.001 0.002 0.864 0.137 0.009 1.000 0.363 0.058 0.342 1.000 0.807 0.594 b0.001 0.615
81.1 ± 22.7 139.4 ± 32.4 44 (7.6) 101 (17.5) 1.5 ± 1.7 27 (4.7) 10.7 ± 5.0 293 (50.8) 11.5 ± 18.2 18 (3.1) 459 (79.5)
0.170 0.211 0.001 0.01 b0.001 0.711 0.901 0.327 0.604 0.377 b0.001
Clinical presentation and data on admission Heart rate (bpm) 86.3 ± 23.7 Systolic blood pressure (mm Hg) 132.7 ± 34.6 Killip 3 or 4, n (%) 10 (25.0) LVEF b 40%, n (%) 14 (35.0) Serum creatinine (mg/dl) 3.3 ± 3.0 ALT N 100 mg/dl, n (%) 2 (5.0) 3 White blood cell count (10 /μl) 10.8 ± 4.5 ST segment depression, n (%) 24 (60.0) Troponin I, ng/ml 13.7 ± 22.9 INR N 1.3, n (%) 2 (5.0) Coronary angiography, n (%) 20 (50.0)
Abbreviations: PCI = percutaneous coronary intervention; CABG = coronary artery bypass graft surgery; NSAID = non-steroidal anti-inflammatory drug; LVEF = left ventricular ejection fraction; ALT = alanine aminotransferase; INR = international normalized ratio.
Fig. 1. Rates of major bleeding in the CRUSADE, ACUITY-HORIZONS and HAS-BLED risk groups.
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Table 3 Predictive accuracy and goodness of fit of the risk scores. Risk scores
C-statistic (95% confidence interval)
p value of Hosmer–Lemeshow test
CRUSADE ACUITY-HORIZONS HAS-BLED
0.81 (0.74–0.88) 0.82 (0.75–0.89) 0.80 (0.72–0.88)
0.687 0.186 0.239
bleeding at mean 4.6 ± 3.5 days (range 1 to 10 days) after receiving antithrombotic therapy. A comparison of baseline characteristics between bleeding and non-bleeding patients showed that patients in the bleeding group were older and there were fewer smokers among these patients compared to the non-bleeding group. The bleeding group also had more females and more patients in this group had a history of anemia, a Killip classification of 3 or 4, impaired heart function and abnormal renal function compared to the non-bleeding group. There was no significant difference in diabetes mellitus, hypertension, alcohol drinking, hypercholesterolemia, prior stroke, prior MI, prior vascular disease, previous history of percutaneous coronary intervention or bypass surgery and NSAID usage between the bleeding and nonbleeding groups. Initial clinical presentation revealed no significant difference in heart rate, systolic blood pressure, abnormal liver function, white blood cell count, ST segment depression, troponin I level, and liable INR between the bleeding and non-bleeding groups. The mean CRUSADE score was 34.2 points (interquartile range 20–46). Based on the CRUSADE risk categories, 36.0% of the patients had a low risk, 31.4% had a moderate risk and 32.6% had a high risk of bleeding. Major bleeding occurred in 1.4%, 3.6% and 14.9% of the low-, moderate-, and high-risk CRUSADE categories, respectively (Fig. 1a). The mean ACUITY-HORIZONS score was 17.8 points (interquartile range 11–24). Based on ACUITY-HORIZONS risk categories, 28.0% of the patients had a very low risk, 33.9% had a low risk, 23.2% had a moderate risk and 14.9% of patients had a high risk of bleeding. Major bleeding occurred in 1.2%, 3.3%, 4.9% and 26.1% of the very low-, low-, moderate-, and high-risk ACUITY-HORIZONS categories, respectively (Fig. 1b). The mean HAS-BLED risk score was 1.53 points (interquartile range 1–2). Based on HAS-BLED risk categories, 52.7% of the patients had a low risk, 28.7% had a moderate risk, and 18.6% of the patients had a high risk of bleeding, according to HAS-BLED risk categories respectively. Major bleeding occurred in 1.8%, 3.4% and 24.3% of the low-, moderate-, and high-risk HAS-BLED categories, respectively (Fig. 1c). The non-significant results from the Hosmer–Lemeshow test (p N 0.05) in this study suggested that the calibrations of CRUSADE, ACUITY-HORIZONS and HAS-BLED risk models for predicting inhospital major bleeding were accurate (Table 3). Furthermore, the discriminations of CRUSADE, ACUITY-HORIZONS and HAS-BLED (C-statistic 0.81, 0.82 and 0.80, respectively) scores were also good (Table 3). Data presented in Table 4 demonstrated that there was no significant difference between these three risk scores (HAS-BLED vs. CRUSADE: z = − 0.08, p = 0.27; HAS-BLED vs. ACUITY-HORIZONS: z = − 0.06, p = 0.26; CRUSADE vs. ACUITY-HORIZONS: z = − 0.15, p = 0.28). According to the ROC curve (Fig. 2), the best cutoff of HAS-BLED score was 3 points, with a sensitivity of 70% and specificity of 83%.
Table 4 Comparison of the predictive accuracy of the three different risk scores. Comparison
Difference
z
p value
HAS-BLED vs. CRUSADE HAS-BLED vs. ACUITY-HORIZONS CRUSADE vs. ACUITY-HORIZONS
−0.004 −0.003 −0.008
−0.08 −0.06 −0.15
0.27 0.26 0.28
Fig. 2. Receiver operating characteristic curves of the CRUSADE, ACUITY-HORIZONS and HAS-BLED models for the prediction of in-hospital major bleeding.
4. Discussion The main result of this study demonstrated that HAS-BLED scores was a useful tool for risk stratification of in-hospital major bleeding in NSTEMI patients. Compared with CRUSADE and ACUITY-HORIZONS scores, HAS-BLED score had a simpler calculation and a similar accuracy for risk assessment as the other two scores evaluated. Some limitations of the study should be taken into account. First, this study was designed as a single center, Chinese patient-based, retrospective analysis with limitations inherent to such study designs. In previous studies, race–ethnic differences in responses to antiplatelet therapy have been reported. Compared with other ethnic patients, Asian patients were more likely to have bleeding complication in response to antiplatelet therapy [20,21]. Therefore, the finding of this study provided a more prominent impact on this ethnic race with high bleeding risk. Since no prospective study has been designed to address the present question, our results provided the first evidence for potential clinical application of using HAS-BLED scores in NSTEMI Chinese patients receiving dual anti-platelet (aspirin and clopidogrel) and heparin therapy during hospitalization. However, it is not immediately clear whether this study can be applied to Non-Chinese patients or not. Second, current contemporary ACC/AHA and ESC guidelines recommend the use of ticagrelor in patients with NSTEMI, as well as prasugrel in select patients. Further studies are necessary to investigate the value of these bleeding risk scores in NSTEMI patients receiving these new antiplatelet and antithrombotic medications. Previous clinical trials have reported that the rate of in-hospital major bleeding in NSTEMI patients was around 1.0–10% [22]. Differences in data interpretation between studies may be due to variations in the definition of major bleeding [23]. In this study, our definition of major bleeding was based on recommendations by the Bleeding Academic Research Consortium and was similar to that reported in the Organization for the Assessment of Strategies for Ischemic Syndromes (OASIS)-5 trial [24], which was a randomized clinical trial comparing the efficacy and safety of fondaparinux and enoxaparin in NSTEMI patients. Our data showed that the rate of in-hospital major bleeding was 6.5% and these events mostly occurred within 1 week (mean 4.6 ± 3.5 days, range 1 to 10 days) after receiving antithrombotic therapy. The design and co-interventions in the enoxaparin group of the
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OASIS-5 trial were similar to those in this study. However, the rate of major bleeding in the enoxaparin group on day 9 was 4.2%, which is lower than that in this cohort. It is important to note that patient populations selected from a real world registry are different from those enrolled in clinical trials. Unlike the OASIS-5 trial, our present study included patients with severe kidney disease or receiving dialysis therapy. In addition, the OASIS-5 trial reported significantly lower rate of dual anti-platelet therapy use, especially clopidogrel, compared to this study. In this study, we found that the rate of use of combination of aspirin–clopidogrel dual anti-platelet therapy was 100% prior to event occurrence, whereas the OASIS-5 trial reported a 98% rate of aspirin use. However, the rate of clopidogrel use in the fondaparinux and enoxaparin groups in the OASIS-5 trial was only around 35%. These reasons may explain the higher rate of major bleeding in this study compared to the OASIS-5 clinical trial. The HAS-BLED risk score was established to predict oral anticoagulation therapy- (warfarin or factor IIa/Xa inhibitors) related bleeding and clinical outcomes in patients with atrial fibrillation [17–19,25]. Recently, HAS-BLED scores were also shown to predict the risk of bleeding in acute coronary syndrome patients with atrial fibrillation who received anti-coagulation therapy [26,27]. There was no significant difference between the incidence of bleeding in patients who received dual anti-platelet therapy and patients who received oral anticoagulation therapy for atrial fibrillation [28]. In this study, although patients with atrial fibrillation and those who received warfarin or factor Xa inhibitors were excluded, all enrolled patients received dual antiplatelet therapy plus heparin for NSTEMI. Our study therefore extended the clinical application of using HAS-BLED scores to predict in-hospital bleeding in patients without atrial fibrillation who received dual antiplatelet therapy plus heparin therapy for NSTEMI. Among the clinical variables used to predict bleeding, all three models included abnormal renal function to calculate scores. The highest score of abnormal renal function is 39 points in CRUSADE scores (full score 97 points), 10 points in ACUITY-HORIZONS (full score 46 points) and 1 point in HAS-BLED scores (full score 9 points). Calculation of the CRUSADE and HAS-BLED scores also includes blood pressure, diabetes mellitus and prior vascular disease (including stroke) history, but the ACUITY-HORIZONS score does not. Calculation of the ACUITYHORIZONS and HAS-BLED scores includes age and anemia, but the CRUSADE score does not. Calculation of the CRUSADE and ACUITYHORIZONS scores includes gender, but the HAS-BLED score does not. The HAS-BLED score, which comprises several factors common to the CRUSADE and ACUITY-HORIZONS scores, is therefore considered as a combination of these two traditional scores, and may explain why HAS-BLED can also be used to predict major bleeding risk in NSTEMI patients. The distribution of patient numbers was different between the three scoring models. The distribution of patients in the low, moderate and high-risk groups was more homogenous in the CRUSADE model. In the ACUITY-HORIZONS model, the distribution of patient numbers was a little skewed to the right. In the HAS-BLED model, the rightskewed distribution was more prominent compared to the other two models. Although the three scoring models differed in the distribution of patient numbers, there was no significant difference in C-statistics between HAS-BLED and the other two models. The distribution of patient numbers indicated that most NSTEMI patients had low or moderate HAS-BLED scores (score b 3 points), and the incidence of in-hospital major bleeding in low- and moderate-risk groups was less than 5%. The risk of bleeding was relatively high (20–30%) in NSTEMI patients with a high HAS-BLED score (≥3 points), as well as patients belonging to the high-risk group in the CRUSADE and ACUITY-HORIZONS models. Patients with a HAS-BLED score ≥3 belonged to the high bleeding risk group which received anti-coagulation therapy for atrial fibrillation. For bleeding prediction in atrial fibrillation patients, the sensitivity of high HAS-BLED score was 41%–53%, while the specificity was 65%–78% [29]. In this study, the sensitivity and specificity of HAS-BLED score
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(≥ 3 points) to predict in-hospital major bleeding in NSTEMI patients were 70% and 83%, respectively. Our data suggested that HAS-BLED score has a good predictive value for in-hospital major bleeding in NSTEMI patients. According to this study finding, HAS-BLED score can guide physician to identify high risk bleeding patients before receiving anti-thrombotic therapy. Dual antiplatelet-based anti-thrombotic therapy is the gold standard treatment for NSTEMI patients [30,31]. It is still unclear how to obtain the balance between anti-thrombotic effects and bleeding risk in these NSTEMI patients with high bleeding risk. A study should be conducted to assess the effect of dosage reduction or withdrawal of one of the antithrombotic agents in the high risk bleeding group as identified by the HAS-BLED score in the future. For these patients with high HAS-BLED score (≥ 3 points), physicians can select some subsequent strategies, for example, using smaller size catheter and transradial rather than transfemoral access for coronary intervention, to reduce bleeding complication [32–34]. Acknowledgments This research was supported by the Chang Gung Medical Research Program (CMRPG) grant number: 370211. References [1] K.P. Alexander, A.Y. Chen, M.T. Roe, L.K. Newby, C.M. Gibson, N.M. Allen-LaPointe, et al., Excess dosing of antiplatelet and antithrombin agents in the treatment of non-ST-segment elevation acute coronary syndromes, J. Am. Med. Assoc. 294 (2005) 3108–3116. [2] J.S. Berger, Aspirin, clopidogrel, and ticagrelor in acute coronary syndromes, Am. J. Cardiol. 112 (2013) 737–745. [3] J.F. Saucedo, Balancing the benefits and risks of antiplatelet agents in patients with non-ST-segment elevated acute coronary syndromes and undergoing percutaneous coronary intervention, J. Thromb. Thrombolysis 30 (2010) 200–209. [4] R.D. Lopes, J.A. White, P. Tricoci, H.D. White, P.W. Armstrong, E. Braunwald, et al., Age, treatment, and outcomes in high-risk non-ST-segment elevation acute coronary syndrome patients: insights from the EARLY ACS trial, Int. J. Cardiol. 167 (2013) 2580–2587. [5] P.M. Mannucci, M. Franchini, Mechanism of hemostasis defects and management of bleeding in patients with acute coronary syndromes, Eur. J. Intern. Med. 21 (2010) 254–259. [6] M.A. Cavender, S.V. Rao, Bleeding associated with current therapies for acute coronary syndrome: what are the mechanisms? J. Thromb. Thrombolysis 30 (2010) 332–339. [7] A. Bufe, F. Emile, L. Drogoul, J. Guindo Soldevila, D.P. Giuseppe, L. Maddalena, et al., Costs of bleeds relating to acute coronary syndrome therapies, J. Med. Econ. 13 (2010) 236–240. [8] S.V. Manoukian, The relationship between bleeding and adverse outcomes in ACS and PCI: pharmacologic and nonpharmacologic modification of risk, J. Invasive Cardiol. 22 (2010) 132–141. [9] S.V. Manoukian, F. Feit, R. Mehran, M.D. Voeltz, R. Ebrahimi, M. Hamon, et al., Impact of major bleeding on 30-day mortality and clinical outcomes in patients with acute coronary syndromes: an analysis from the ACUITY trial, J. Am. Coll. Cardiol. 49 (2007) 1362–1368. [10] R. Mehran, S.J. Pocock, G.W. Stone, T.C. Clayton, G.D. Dangas, F. Feit, et al., Associations of major bleeding and myocardial infarction with the incidence and timing of mortality in patients presenting with non-ST-elevation acute coronary syndromes: a risk model from the ACUITY trial, Eur. Heart J. 30 (2009) 1457–1466. [11] S. Subherwal, R.G. Bach, A.Y. Chen, B.F. Gage, S.V. Rao, L.K. Newby, et al., Baseline risk of major bleeding in non-ST-segment-elevation myocardial infarction: the CRUSADE (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA Guidelines) bleeding score, Circulation 119 (2009) 1873–1882. [12] R. Mehran, S.J. Pocock, E. Nikolsky, T. Clayton, G.D. Dangas, A.J. Kirtane, et al., A risk score to predict bleeding in patients with acute coronary syndromes, J. Am. Coll. Cardiol. 55 (2010) 2556–2566. [13] R. Mathews, E.D. Peterson, A.Y. Chen, T.Y. Wang, C.T. Chin, G.C. Fonarow, 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. 107 (2011) 1136–1143. [14] C.W. Hamm, J.P. Bassand, S. Agewall, J. Bax, E. Boersma, H. Bueno, et al., ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the Task Force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC), Eur. Heart J. 32 (2011) 2999–3054. [15] R.S. Wright, J.L. Anderson, C.D. Adams, C.R. Bridges, D.E. Casey Jr., S.M. Ettinger, et al., ACCF/AHA focused update of the guidelines for the management of patients with unstable angina/non-ST-elevation myocardial infarction (updating the 2007
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Full Length Article
HAS-BLED score predicts risk of in-hospital major bleeding in patients with acute non-ST segment elevation myocardial infarction Ming-Jer Hsieh 1, Chun-Chieh Wang 1, Chun-Chi Chen 1, Chun-Li Wang 1, Lung-Sheng Wu 1, I-Chang Hsieh ⁎ Department of Cardiology, Chang Gung Memorial Hospital, Chang Gung University College of Medicine, No. 5, Fu-Hsing Street, Kwei-Shan, Taoyuan, Taiwan
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Article history: Received 28 June 2015 Received in revised form 3 August 2015 Accepted 22 August 2015 Available online 29 August 2015 Keywords: HAS-BLED CRUSADE ACUITY-HORIZONS Major bleeding NSTEMI
a b s t r a c t Background: The role of the Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, Drugs or alcohol use (HAS-BLED) score in the prediction of in-hospital bleeding in non-ST segment elevation myocardial infarction (NSTEMI) patients receiving dual antiplatelet therapy plus heparin was unknown. In this study, we compared the HAS-BLED score with the Can Rapid Risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines (CRUSADE) and Acute Catheterization and Urgent Intervention Triage strategY and the Harmonizing Outcomes with RevascularIZatiON and Stents in acute myocardial infarction (ACUITYHORIZONS) bleeding risk scores for in-hospital major bleeding risk stratification in NSTEMI patients. Methods: A real world population of 617 NSTEMI patients receiving dual anti-platelet plus heparin as initial therapy were enrolled. CRUSADE, ACUITY-HORIZONS and HAS-BLED risk scores were calculated for each patient. Results: This cohort had a 6.5% incidence of in-hospital major bleeding. For the prediction of in-hospital major bleeding, the discriminations between CRUSADE, ACUITY-HORIZONS and HAS-BLED were good (C-statistic 0.81, 0.82 and 0.80, respectively). There was no significant difference between these three risk scores (HASBLED vs. CRUSADE: z = −0.08, p = 0.27; HAS-BLED vs. ACUITY-HORIZONS: z = −0.06, p = 0.26; CRUSADE vs. ACUITY-HORIZONS: z = −0.15, p = 0.28). Conclusion: The CRUSADE, ACUITY-HORIZONS and HAS-BLED scores were useful tools for risk stratification of inhospital major bleeding in NSTEMI patients. The HAS-BLED score had a simpler calculation and a similar accuracy for risk assessment as the other two scores evaluated. © 2015 Elsevier Ltd. All rights reserved.
1. Introduction Acute non-ST segment elevation myocardial infarction (NSTEMI) is a disease characterized by atherosclerotic plaque rupture-related acute thrombosis. The use of powerful anti-thrombotic therapy has been reported to reduce the ischemic complications seen in these patients [1–3]. However, this strategy increases the likelihood of bleeding, especially in high-risk patients [4–6]. Bleeding in NSTEMI patients not only increased the duration and cost of in-hospital stay, but has also been demonstrated as a predictor of adverse clinical outcomes [7–10]. A number of scoring systems have been established to predict the risk of bleeding in NSTEMI patients [11–13]. The American College of Cardiology/American Heart Association (ACC/AHA) and European Society of Cardiology (ESC) guidelines recommend the use of Can Rapid Risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA guidelines (CRUSADE) and Acute Catheterization and Urgent Intervention Triage strategY and the Harmonizing Outcomes with RevascularIZatiON and
Stents in acute myocardial infarction (ACUITY-HORIZONS) risk scores to assess bleeding risk in acute coronary syndrome [14–16]. However, the algorithms of CRUSADE and ACUITY-HORIZONS scores are based on complex scoring systems when applied in clinical practice. The Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly, Drugs or alcohol use (HAS-BLED) risk score is a simpler user-friendly score, which has been shown to predict bleeding, cardiovascular events and long-term outcome in atrial fibrillation patients who received anticoagulation therapy [17,18]. Recently, HAS-BLED has also been used to predict the outcome in atrial fibrillation patients receiving percutaneous coronary intervention [19]. However, the predictive value of the HAS-BLED score in NSTEMI patients without atrial fibrillation receiving anti-thrombotic therapy remains unknown. Therefore, in this study we compared the accuracy of the HAS-BLED risk score with that of the CRUSADE and ACUITY-HORIZONS scores in predicting in-hospital major bleeding in NSTEMI patients. 2. Material and Methods
⁎ Corresponding author. E-mail address: [email protected] (I.-C. Hsieh). 1 Present address for all authors: No. 5, Fu-Hsing Street, Kwei-Shan, Taoyuan, Taiwan.
http://dx.doi.org/10.1016/j.thromres.2015.08.015 0049-3848/© 2015 Elsevier Ltd. All rights reserved.
This study was conducted at an academic teaching hospital that functions as both a secondary referral center and tertiary referral center
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serving a population of approximately two million. A total of 652 patients admitted to our cardiovascular department with a final diagnosis of NSTEMI between January 2006 and December 2009. NSTEMI was defined as elevation of troponin-I level ≥ 0.1 ng/ml, accompanied by either typical chest pain for N30 min and/or electrocardiographic change (ischemic ST-segment depression). NSTEMI patients who did not receive dual anti-platelet plus heparin as initial therapy as well as those who had to receive vitamin K antagonist or bypass surgery were excluded from the study. All enrolled patients received dual antiplatelet therapy (loading dosage: aspirin 100–325 mg & clopidogrel 300 mg; maintenance dosage of aspirin 100 mg & clopidogrel 75 mg per day) through the duration of hospital stay unless they suffered from bleeding. The choice of heparin therapy (either unfractionated or low molecular weight heparin) was based on the recommendation of the primary care physician. Treatment continued until the treating physician recommended no further anticoagulation therapy, and at least through angiography and revascularization, if performed. Intravenous unfractionated heparin was given according to a weight-adjusted nomogram (bolus of 60 U/kg [maximum of 5000 U] and initial infusion of 12 U/kg per hour) with a goal-activated partial thromboplastin time of 1.5 to 2.0 times the institutional upper limit of normal. Enoxaparin was given subcutaneously at a dose of 1 mg/kg every 12 h. None of the patients in this cohort received glycoprotein IIb/IIIa inhibitor. A total of 617 patients were included in the final analysis. All demographic
and clinical characteristics were obtained and recorded on admission. The laboratory data, pharmacological and interventional therapy information were obtained from the hospital's computer database. In-hospital major bleeding (Bleeding Academic Research Consortium type 3) was defined as a composite of intracranial, or intraocular bleeding, cardiac tamponade, bleeding requiring surgical intervention or control, reduction in hemoglobin ≧3 g/dl with an overt bleeding source or any blood transfusion with an overt bleeding source. Validation of clinical outcomes was obtained from records from the patient's primary care physicians, or by telephone contact with the patient or caregivers. This study was a retrospective analysis of prospectively collected data in clinical registry database. Patients signed informed consent for data collection and application. Appropriate permissions to conduct the study were obtained from the local institutional review board. Three bleeding risk scores, CRUSADE, ACUITY-HORIZONS and HASBLED, were calculated for each patient from the corresponding prognostic variables in Table 1. The CRUSADE bleeding risk score identified 8 baseline characteristics associated with risk of major bleeding: heart rate, systolic blood pressure, hematocrit, renal function, gender, diabetes, congestive heart failure, and prior vascular disease [11]. The variables which were calculated and weighted for the ACUITY-HORIZONS score included age, gender, white blood cell count, anemia, renal function, and raised cardiac enzyme on presentation [12]. HAS-BLED is an acronym for hypertension, abnormal liver function [defined as chronic
Table 1 CRUSADE, ACUITY-HORIZONS and HAS-BLED score calculator for bleeding risk in NSTEMI. Points from each category are added to calculate risk. CRUSADE Predictor
ACUITY-HORIZONS Score
Gender Male 0 Female 8 Diabetes No 0 Yes 6 Prior vascular disease No 0 Yes 6 Presentation with heart failure No 0 Yes 7 Baseline hematocrit (%) b31 9 31–33.9 7 34–36.9 3 37–39.9 2 ≥40 0 Creatinine clearance (ml/min) ≤15 39 N15–30 35 N30–60 28 N60–90 17 N90–120 7 N120 0 Heart rate (bpm) ≤70 0 71–80 1 81–90 3 91–100 6 101–110 8 111–120 10 ≥120 11 Systolic blood pressure (mm Hg) ≤90 10 91–100 8 101–120 5 121–180 1 181–200 3 ≥201 5
Predictor Gender Male Female Age (years) b50 50–59 60–69 70–79 ≥80 Serum creatinine (mg/dl) b1.0 1.0– 1.2– 1.4– 1.6– 1.8– ≥2.0 WBC b10 10– 12– 14– 16– 18– 20– Anemia No Yes Cardiac enzymes Normal Raised
HAS-BLED Score 0 8 0 3 6 9 12 0 2 3 5 6 8 10 0 2 3 5 6 8 10 0 6
Predictor
Score
Hypertension No 0 Yes 1 Abnormal renal function (dialysis or serum creatinine N2.6 mg/dl) No 0 Yes 1 Abnormal liver function (ALT N 100 mg/dl) No 0 Yes 1 Prior stroke No 0 Yes 1 Bleeding predisposition (anemia or bleeding history) No 0 Yes 1 High INRs (INRs N 1.3) No 0 Yes 1 Elder (age N 65 years) No 0 Yes 1 Alcohol use No 0 Yes 1 NSAIDs prescribed No 0 Yes 1
0 2
Abbreviations: ALT = alanine aminotransferase; INR = international normalized ratio; NSAID = non-steroidal anti-inflammatory drug.
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hepatic disease or Alanine Aminotransferase (ALT) N 100 mg/dl], renal dysfunction (defined as dialysis or serum creatinine N 2.6 mg/dl), prior history of stroke, anemia or predisposition to bleeding, labile international normalized ratio (defined as international normalized ratio N 1.3), elderly (age N 65), alcohol usage and prescription of nonsteroidal anti-inflammatory drugs (NSAIDs). Patients were classified into risk categories based on a modification of the originally published risk scores. The CRUSADE score distinguished three risk categories of bleeding (low risk: 0 to 25; moderate risk: 26 to 40; high risk: ≥41). Based on the ACUITY-HORIZONS risk score, patients were stratified into four risk categories for bleeding (very low risk: 0 to 11, low risk: 12 to 19, moderate risk: 20 to 27 and high risk: ≥28). HASBLED scores classified patients into three risk categories for bleeding (low risk: 0 to 1; moderate risk: 2; high risk: ≥3). Continuous variables were represented as means ± standard deviations. Categorical variables were expressed as frequencies and group percentages. The statistical normality was assessed using the Kolmogorov–Smirnov test. The χ2 test was used to compare categorical variables. ANOVA and T tests were used for variables with normal distributions, and the Whitney U test for other data. Our data contained few missing values (b1%). Missing values for categorical variables were assigned the most frequent gender-specific value, and continuous variables were assigned the gender-specific median values. Receiver operating characteristic curves were used for each of the three risk scores in order to relate the calculated scores to in-hospital major bleeding. The C-statistic defined by the area under ROC curve in relation to outcome was used as a measure of the predictive accuracy of the risk scores. Based on the cutoff with the best accuracy, the sensitivity and specificity of HAS-BLED score were calculated for the prediction of in-hospital major bleeding. The relative performance of each test was evaluated with the 95% confidence interval for the difference between two Cstatistic indices. The goodness of fit of the risk scores was evaluated
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by calculating the Hosmer–Lemeshow statistic. A p value b 0.05 was considered statistically significant. All statistical analyses were performed using the statistical software package SPSS 17.0 for Windows. 3. Results The demographics and clinical characteristics of study patients are shown in Table 2. Aspirin, clopidogrel and heparin were used as the initial antithrombotic therapy for NSTEMI in all the study patients. A total of 40 patients in this cohort (6.5%) suffered from major in-hospital
Table 2 Baseline characteristics of bleeding and non-bleeding patients.
Past medical history Age (years) Male, n (%) Diabetes mellitus, n (%) Hypertension, n (%) Current smoking, n (%) Alcohol drinking, n (%) Hypercholesterolemia, n (%) Prior stroke, n (%) Prior myocardial infarction, n (%) Prior vascular disease, n (%) Previous PCI, n (%) Previous CABG, n (%) Anemia, n (%) NSAID usage, n (%)
Bleeding (n = 40)
Non-bleeding (n = 577)
p-Value
71.8 ± 10.3 23 (57.5) 14 (35.0) 28 (70.0) 18 (45.0) 6 (15.0) 9 (22.5) 8 (20.0) 3 (7.5) 9 (22.5) 4 (10.0) 1 (2.5) 28 (70.0) 0 (0.0)
62.6 ± 13.7 463 (80.2) 194 (33.6) 332 (57.5) 310 (54.2) 96 (16.6) 189 (32.8) 57 (9.9) 77 (13.5) 127 (22.0) 74 (13.1) 12 (2.1) 109 (18.9) 15 (2.6)
b0.001 0.002 0.864 0.137 0.009 1.000 0.363 0.058 0.342 1.000 0.807 0.594 b0.001 0.615
81.1 ± 22.7 139.4 ± 32.4 44 (7.6) 101 (17.5) 1.5 ± 1.7 27 (4.7) 10.7 ± 5.0 293 (50.8) 11.5 ± 18.2 18 (3.1) 459 (79.5)
0.170 0.211 0.001 0.01 b0.001 0.711 0.901 0.327 0.604 0.377 b0.001
Clinical presentation and data on admission Heart rate (bpm) 86.3 ± 23.7 Systolic blood pressure (mm Hg) 132.7 ± 34.6 Killip 3 or 4, n (%) 10 (25.0) LVEF b 40%, n (%) 14 (35.0) Serum creatinine (mg/dl) 3.3 ± 3.0 ALT N 100 mg/dl, n (%) 2 (5.0) 3 White blood cell count (10 /μl) 10.8 ± 4.5 ST segment depression, n (%) 24 (60.0) Troponin I, ng/ml 13.7 ± 22.9 INR N 1.3, n (%) 2 (5.0) Coronary angiography, n (%) 20 (50.0)
Abbreviations: PCI = percutaneous coronary intervention; CABG = coronary artery bypass graft surgery; NSAID = non-steroidal anti-inflammatory drug; LVEF = left ventricular ejection fraction; ALT = alanine aminotransferase; INR = international normalized ratio.
Fig. 1. Rates of major bleeding in the CRUSADE, ACUITY-HORIZONS and HAS-BLED risk groups.
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Table 3 Predictive accuracy and goodness of fit of the risk scores. Risk scores
C-statistic (95% confidence interval)
p value of Hosmer–Lemeshow test
CRUSADE ACUITY-HORIZONS HAS-BLED
0.81 (0.74–0.88) 0.82 (0.75–0.89) 0.80 (0.72–0.88)
0.687 0.186 0.239
bleeding at mean 4.6 ± 3.5 days (range 1 to 10 days) after receiving antithrombotic therapy. A comparison of baseline characteristics between bleeding and non-bleeding patients showed that patients in the bleeding group were older and there were fewer smokers among these patients compared to the non-bleeding group. The bleeding group also had more females and more patients in this group had a history of anemia, a Killip classification of 3 or 4, impaired heart function and abnormal renal function compared to the non-bleeding group. There was no significant difference in diabetes mellitus, hypertension, alcohol drinking, hypercholesterolemia, prior stroke, prior MI, prior vascular disease, previous history of percutaneous coronary intervention or bypass surgery and NSAID usage between the bleeding and nonbleeding groups. Initial clinical presentation revealed no significant difference in heart rate, systolic blood pressure, abnormal liver function, white blood cell count, ST segment depression, troponin I level, and liable INR between the bleeding and non-bleeding groups. The mean CRUSADE score was 34.2 points (interquartile range 20–46). Based on the CRUSADE risk categories, 36.0% of the patients had a low risk, 31.4% had a moderate risk and 32.6% had a high risk of bleeding. Major bleeding occurred in 1.4%, 3.6% and 14.9% of the low-, moderate-, and high-risk CRUSADE categories, respectively (Fig. 1a). The mean ACUITY-HORIZONS score was 17.8 points (interquartile range 11–24). Based on ACUITY-HORIZONS risk categories, 28.0% of the patients had a very low risk, 33.9% had a low risk, 23.2% had a moderate risk and 14.9% of patients had a high risk of bleeding. Major bleeding occurred in 1.2%, 3.3%, 4.9% and 26.1% of the very low-, low-, moderate-, and high-risk ACUITY-HORIZONS categories, respectively (Fig. 1b). The mean HAS-BLED risk score was 1.53 points (interquartile range 1–2). Based on HAS-BLED risk categories, 52.7% of the patients had a low risk, 28.7% had a moderate risk, and 18.6% of the patients had a high risk of bleeding, according to HAS-BLED risk categories respectively. Major bleeding occurred in 1.8%, 3.4% and 24.3% of the low-, moderate-, and high-risk HAS-BLED categories, respectively (Fig. 1c). The non-significant results from the Hosmer–Lemeshow test (p N 0.05) in this study suggested that the calibrations of CRUSADE, ACUITY-HORIZONS and HAS-BLED risk models for predicting inhospital major bleeding were accurate (Table 3). Furthermore, the discriminations of CRUSADE, ACUITY-HORIZONS and HAS-BLED (C-statistic 0.81, 0.82 and 0.80, respectively) scores were also good (Table 3). Data presented in Table 4 demonstrated that there was no significant difference between these three risk scores (HAS-BLED vs. CRUSADE: z = − 0.08, p = 0.27; HAS-BLED vs. ACUITY-HORIZONS: z = − 0.06, p = 0.26; CRUSADE vs. ACUITY-HORIZONS: z = − 0.15, p = 0.28). According to the ROC curve (Fig. 2), the best cutoff of HAS-BLED score was 3 points, with a sensitivity of 70% and specificity of 83%.
Table 4 Comparison of the predictive accuracy of the three different risk scores. Comparison
Difference
z
p value
HAS-BLED vs. CRUSADE HAS-BLED vs. ACUITY-HORIZONS CRUSADE vs. ACUITY-HORIZONS
−0.004 −0.003 −0.008
−0.08 −0.06 −0.15
0.27 0.26 0.28
Fig. 2. Receiver operating characteristic curves of the CRUSADE, ACUITY-HORIZONS and HAS-BLED models for the prediction of in-hospital major bleeding.
4. Discussion The main result of this study demonstrated that HAS-BLED scores was a useful tool for risk stratification of in-hospital major bleeding in NSTEMI patients. Compared with CRUSADE and ACUITY-HORIZONS scores, HAS-BLED score had a simpler calculation and a similar accuracy for risk assessment as the other two scores evaluated. Some limitations of the study should be taken into account. First, this study was designed as a single center, Chinese patient-based, retrospective analysis with limitations inherent to such study designs. In previous studies, race–ethnic differences in responses to antiplatelet therapy have been reported. Compared with other ethnic patients, Asian patients were more likely to have bleeding complication in response to antiplatelet therapy [20,21]. Therefore, the finding of this study provided a more prominent impact on this ethnic race with high bleeding risk. Since no prospective study has been designed to address the present question, our results provided the first evidence for potential clinical application of using HAS-BLED scores in NSTEMI Chinese patients receiving dual anti-platelet (aspirin and clopidogrel) and heparin therapy during hospitalization. However, it is not immediately clear whether this study can be applied to Non-Chinese patients or not. Second, current contemporary ACC/AHA and ESC guidelines recommend the use of ticagrelor in patients with NSTEMI, as well as prasugrel in select patients. Further studies are necessary to investigate the value of these bleeding risk scores in NSTEMI patients receiving these new antiplatelet and antithrombotic medications. Previous clinical trials have reported that the rate of in-hospital major bleeding in NSTEMI patients was around 1.0–10% [22]. Differences in data interpretation between studies may be due to variations in the definition of major bleeding [23]. In this study, our definition of major bleeding was based on recommendations by the Bleeding Academic Research Consortium and was similar to that reported in the Organization for the Assessment of Strategies for Ischemic Syndromes (OASIS)-5 trial [24], which was a randomized clinical trial comparing the efficacy and safety of fondaparinux and enoxaparin in NSTEMI patients. Our data showed that the rate of in-hospital major bleeding was 6.5% and these events mostly occurred within 1 week (mean 4.6 ± 3.5 days, range 1 to 10 days) after receiving antithrombotic therapy. The design and co-interventions in the enoxaparin group of the
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OASIS-5 trial were similar to those in this study. However, the rate of major bleeding in the enoxaparin group on day 9 was 4.2%, which is lower than that in this cohort. It is important to note that patient populations selected from a real world registry are different from those enrolled in clinical trials. Unlike the OASIS-5 trial, our present study included patients with severe kidney disease or receiving dialysis therapy. In addition, the OASIS-5 trial reported significantly lower rate of dual anti-platelet therapy use, especially clopidogrel, compared to this study. In this study, we found that the rate of use of combination of aspirin–clopidogrel dual anti-platelet therapy was 100% prior to event occurrence, whereas the OASIS-5 trial reported a 98% rate of aspirin use. However, the rate of clopidogrel use in the fondaparinux and enoxaparin groups in the OASIS-5 trial was only around 35%. These reasons may explain the higher rate of major bleeding in this study compared to the OASIS-5 clinical trial. The HAS-BLED risk score was established to predict oral anticoagulation therapy- (warfarin or factor IIa/Xa inhibitors) related bleeding and clinical outcomes in patients with atrial fibrillation [17–19,25]. Recently, HAS-BLED scores were also shown to predict the risk of bleeding in acute coronary syndrome patients with atrial fibrillation who received anti-coagulation therapy [26,27]. There was no significant difference between the incidence of bleeding in patients who received dual anti-platelet therapy and patients who received oral anticoagulation therapy for atrial fibrillation [28]. In this study, although patients with atrial fibrillation and those who received warfarin or factor Xa inhibitors were excluded, all enrolled patients received dual antiplatelet therapy plus heparin for NSTEMI. Our study therefore extended the clinical application of using HAS-BLED scores to predict in-hospital bleeding in patients without atrial fibrillation who received dual antiplatelet therapy plus heparin therapy for NSTEMI. Among the clinical variables used to predict bleeding, all three models included abnormal renal function to calculate scores. The highest score of abnormal renal function is 39 points in CRUSADE scores (full score 97 points), 10 points in ACUITY-HORIZONS (full score 46 points) and 1 point in HAS-BLED scores (full score 9 points). Calculation of the CRUSADE and HAS-BLED scores also includes blood pressure, diabetes mellitus and prior vascular disease (including stroke) history, but the ACUITY-HORIZONS score does not. Calculation of the ACUITYHORIZONS and HAS-BLED scores includes age and anemia, but the CRUSADE score does not. Calculation of the CRUSADE and ACUITYHORIZONS scores includes gender, but the HAS-BLED score does not. The HAS-BLED score, which comprises several factors common to the CRUSADE and ACUITY-HORIZONS scores, is therefore considered as a combination of these two traditional scores, and may explain why HAS-BLED can also be used to predict major bleeding risk in NSTEMI patients. The distribution of patient numbers was different between the three scoring models. The distribution of patients in the low, moderate and high-risk groups was more homogenous in the CRUSADE model. In the ACUITY-HORIZONS model, the distribution of patient numbers was a little skewed to the right. In the HAS-BLED model, the rightskewed distribution was more prominent compared to the other two models. Although the three scoring models differed in the distribution of patient numbers, there was no significant difference in C-statistics between HAS-BLED and the other two models. The distribution of patient numbers indicated that most NSTEMI patients had low or moderate HAS-BLED scores (score b 3 points), and the incidence of in-hospital major bleeding in low- and moderate-risk groups was less than 5%. The risk of bleeding was relatively high (20–30%) in NSTEMI patients with a high HAS-BLED score (≥3 points), as well as patients belonging to the high-risk group in the CRUSADE and ACUITY-HORIZONS models. Patients with a HAS-BLED score ≥3 belonged to the high bleeding risk group which received anti-coagulation therapy for atrial fibrillation. For bleeding prediction in atrial fibrillation patients, the sensitivity of high HAS-BLED score was 41%–53%, while the specificity was 65%–78% [29]. In this study, the sensitivity and specificity of HAS-BLED score
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(≥ 3 points) to predict in-hospital major bleeding in NSTEMI patients were 70% and 83%, respectively. Our data suggested that HAS-BLED score has a good predictive value for in-hospital major bleeding in NSTEMI patients. According to this study finding, HAS-BLED score can guide physician to identify high risk bleeding patients before receiving anti-thrombotic therapy. Dual antiplatelet-based anti-thrombotic therapy is the gold standard treatment for NSTEMI patients [30,31]. It is still unclear how to obtain the balance between anti-thrombotic effects and bleeding risk in these NSTEMI patients with high bleeding risk. A study should be conducted to assess the effect of dosage reduction or withdrawal of one of the antithrombotic agents in the high risk bleeding group as identified by the HAS-BLED score in the future. For these patients with high HAS-BLED score (≥ 3 points), physicians can select some subsequent strategies, for example, using smaller size catheter and transradial rather than transfemoral access for coronary intervention, to reduce bleeding complication [32–34]. Acknowledgments This research was supported by the Chang Gung Medical Research Program (CMRPG) grant number: 370211. References [1] K.P. Alexander, A.Y. Chen, M.T. Roe, L.K. Newby, C.M. Gibson, N.M. Allen-LaPointe, et al., Excess dosing of antiplatelet and antithrombin agents in the treatment of non-ST-segment elevation acute coronary syndromes, J. Am. Med. Assoc. 294 (2005) 3108–3116. [2] J.S. Berger, Aspirin, clopidogrel, and ticagrelor in acute coronary syndromes, Am. J. Cardiol. 112 (2013) 737–745. [3] J.F. Saucedo, Balancing the benefits and risks of antiplatelet agents in patients with non-ST-segment elevated acute coronary syndromes and undergoing percutaneous coronary intervention, J. Thromb. Thrombolysis 30 (2010) 200–209. [4] R.D. Lopes, J.A. White, P. Tricoci, H.D. White, P.W. Armstrong, E. Braunwald, et al., Age, treatment, and outcomes in high-risk non-ST-segment elevation acute coronary syndrome patients: insights from the EARLY ACS trial, Int. J. Cardiol. 167 (2013) 2580–2587. [5] P.M. Mannucci, M. Franchini, Mechanism of hemostasis defects and management of bleeding in patients with acute coronary syndromes, Eur. J. Intern. Med. 21 (2010) 254–259. [6] M.A. Cavender, S.V. Rao, Bleeding associated with current therapies for acute coronary syndrome: what are the mechanisms? J. Thromb. Thrombolysis 30 (2010) 332–339. [7] A. Bufe, F. Emile, L. Drogoul, J. Guindo Soldevila, D.P. Giuseppe, L. Maddalena, et al., Costs of bleeds relating to acute coronary syndrome therapies, J. Med. Econ. 13 (2010) 236–240. [8] S.V. Manoukian, The relationship between bleeding and adverse outcomes in ACS and PCI: pharmacologic and nonpharmacologic modification of risk, J. Invasive Cardiol. 22 (2010) 132–141. [9] S.V. Manoukian, F. Feit, R. Mehran, M.D. Voeltz, R. Ebrahimi, M. Hamon, et al., Impact of major bleeding on 30-day mortality and clinical outcomes in patients with acute coronary syndromes: an analysis from the ACUITY trial, J. Am. Coll. Cardiol. 49 (2007) 1362–1368. [10] R. Mehran, S.J. Pocock, G.W. Stone, T.C. Clayton, G.D. Dangas, F. Feit, et al., Associations of major bleeding and myocardial infarction with the incidence and timing of mortality in patients presenting with non-ST-elevation acute coronary syndromes: a risk model from the ACUITY trial, Eur. Heart J. 30 (2009) 1457–1466. [11] S. Subherwal, R.G. Bach, A.Y. Chen, B.F. Gage, S.V. Rao, L.K. Newby, et al., Baseline risk of major bleeding in non-ST-segment-elevation myocardial infarction: the CRUSADE (Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the ACC/AHA Guidelines) bleeding score, Circulation 119 (2009) 1873–1882. [12] R. Mehran, S.J. Pocock, E. Nikolsky, T. Clayton, G.D. Dangas, A.J. Kirtane, et al., A risk score to predict bleeding in patients with acute coronary syndromes, J. Am. Coll. Cardiol. 55 (2010) 2556–2566. [13] R. Mathews, E.D. Peterson, A.Y. Chen, T.Y. Wang, C.T. Chin, G.C. Fonarow, 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. 107 (2011) 1136–1143. [14] C.W. Hamm, J.P. Bassand, S. Agewall, J. Bax, E. Boersma, H. Bueno, et al., ESC guidelines for the management of acute coronary syndromes in patients presenting without persistent ST-segment elevation: the Task Force for the management of acute coronary syndromes (ACS) in patients presenting without persistent ST-segment elevation of the European Society of Cardiology (ESC), Eur. Heart J. 32 (2011) 2999–3054. [15] R.S. Wright, J.L. Anderson, C.D. Adams, C.R. Bridges, D.E. Casey Jr., S.M. Ettinger, et al., ACCF/AHA focused update of the guidelines for the management of patients with unstable angina/non-ST-elevation myocardial infarction (updating the 2007
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