Aspirin resistance associated with HbA1c and obesity in diabetic patients

Journal of Diabetes and Its Complications 22 (2008) 224 – 228

Aspirin resistance associated with HbA1c and obesity in diabetic patientsB Hillel W. Cohena,4, Jill P. Crandallb, Susan M. Hailperna, Henny H. Billettc a

Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA Division of Endocrinology, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA c Division of Hematology, Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA

b

Received 27 September 2006; received in revised form 7 May 2007; accepted 7 May 2007

Abstract Introduction: Diabetes is known to be a prothrombotic state. Since serotonin uptake plays a role in both platelet activation and depression, we undertook to examine a hypothesis that aspirin resistance (AR) may be associated with both HbA1c and depressive symptoms and to assess other potential determinants of AR in diabetic patients. Methods: A whole-blood desktop platelet function analyzer (PFA-100) with an epinephrine agonist was used to assess AR among patients with type 2 diabetes. AR was defined as PFA closure times b192 s. Depression symptoms were assessed with the Physicians Health Questionnaire. Patients being treated for type 2 diabetes (N=48) who took aspirin within the past 24 h constituted the study sample. Associations with AR were assessed with the use of the Mann–Whitney test and Fisher’s Exact Test as well as with logistic regression models. Results: AR was observed in 11 patients (23%) and was not significantly associated with age, sex, or race. AR was significantly associated with HbA1cz8% ( P=.002) and obesity (BMIz30 kg/m2; P=.01) and borderline associated with having z1 depressive symptom ( P=.07). Results were similar after multivariable adjustment in logistic regression models. No statistically significant associations of AR with age, sex, race, plasma glucose, blood pressure, cholesterol, or smoking were observed. Conclusion: These data suggest that AR may be of special concern for diabetic patients with poor glucose control and obesity. Whether the PFA-100 or any other practical measure of AR can be used in clinical practice to identify added cardiovascular disease risk and to inform platelet inhibition therapy needs further study. D 2008 Elsevier Inc. All rights reserved. Keywords: Aspirin; Drug resistance; Diabetes; HbA1c; Obesity

1. Introduction Diabetes is known to be a prothrombotic state, and diabetic patients face a substantially increased risk of mortality from macrovascular disease (Vinikd & Flemmer, 2002). Aspirin therapy for platelet inhibition is recommended by the American Diabetes Association for diabetic patients z30 years old as a means to reduce risk for cardiovascular disease (CVD; American Diabetes AssociaB

No author has any financial interest or affiliation related in any way to this study. 4 Corresponding author. Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, USA. Tel.: +1 718 430 3745; fax: +1 718 430 3747. E-mail address: [email protected] (H.W. Cohen). 1056-8727/08/$ – see front matter D 2008 Elsevier Inc. All rights reserved. doi:10.1016/j.jdiacomp.2007.05.002

tion, 2003). However, platelet function is rarely measured in routine clinical practice, and thus, clinicians do not know who among their patients are responding to aspirin therapy. Lack of adequate platelet inhibition from aspirin therapy is known as aspirin resistance (AR), which may affect 5–60% of adults depending on the population observed and how AR is measured (Mason, Jacobs, & Freedman, 2005). Although data are inconsistent regarding whether AR is more prevalent among diabetic patients (Gum et al., 2001; Watala et al., 2004), the clinical consequences of inadequate platelet inhibition could be substantial. Given the increased platelet activity in diabetes, we hypothesized that HbA1c may be associated with AR. Further, since serotonin uptake plays a role in both platelet activation and depression, we hypothesized that AR might also be associated with

H.W. Cohen et al. / Journal of Diabetes and Its Complications 22 (2008) 224 – 228

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Table 1 Patient characteristics by ARa Characteristicsb

Aspirin resistant (n=11)

Nonresistant (n=37)

Total (N=48)

Age (years) Female sex (%) Race (%) Black White Hispanic Other Current smoker (%) Blood pressure (mmHg) Systolic Diastolic Total cholesterol (mg/dl) Ambient plasma glucose z1 Depressive symptoms (%) Body mass index [BMI] (kg/m2) BMIz30 kg/m2 (%) Weight (lb) HbA1c (% units) HbA1cz8% (%) Daily aspirin dose (%) 81 mg 325 mg PFA-100 closure time (s) Insulin therapy (%) SSRI use (%) History of coronary artery disease (%)

62 (58–72) 73

69 (55–78) 54

68 (56–77) 58

27 46 27 0 9

35 30 30 5 11

33 33 29 4 10

127 (117–138) 70 (66–78) 160 (136–183) 128 (96–174) 57 28.3 (25.3–30.9) 27 172 (154–204) 7.2 (6.4–7.8) 19

127 (118–136) 70 (66–78) 160 (139–183) 131 (97–178) 65 33.9 (29.4–35.9) 38 178 (154–227) 7.3 (6.6–8.4) 31

46 54 299 (259–300) 30 11 27

46 54 281 (216–300) 33 10 27

127 70 159 138 91 33.9 73 230 8.4 73

(119–136) (66–71) (149–234) (98–228) (29.4–35.9) (206–253) (7.3–8.9)

46 54 149 (129–179) 46 9 27

P .55 .32 .86

N.99 .99 .38 .29 .54 .07 .04 .01 .004 .02 .002 .98

b.001 .47 N.99 N.99

a

AR is defined as PFA-100 epinephrine cartridge closure time b192 s. Results for continuous variables are reported as median values (interquartile range) with P values calculated using the Mann–Whitney U test between AR categories. Categorical variables are reported as percentages with P values calculated using Fisher’s Exact Test. b

depressive symptoms (Bruce & Musselman, 2005). We undertook a study to look at these associations among patients with type 2 diabetes.

2. Methods 2.1. Participants Patients z40 years old being treated for type 2 diabetes coming for a routine visit at an outpatient endocrinology clinic were invited consecutively to participate. Four potential participants did not give consent, 15 reported not taking aspirin, and 4 reported taking aspirin but not in the previous 24 h. The remaining 48 constituted the study sample.

3. Measures Platelet function was measured with a whole-blood desktop platelet function analyzer (PFA-100) with an epinephrine agonist (Andersen, Hrulen, Arnesen, & Seljelot, 2003). The PFA-100 is one of at least two point-of-service devices to measure platelet function that could be integrated into clinical practice. We chose the PFA-100 based on our previous experience (Cohen, Billettt, & Monrad, 2003) with

this device that simulates in vivo platelet plug formation by aspirating blood at a high shear rate through a small collagen-coated aperture. The PFA-100 records the amount of time up to a maximum of 300 s necessary for a platelet plug to close the aperture. Based on the literature and on our own prior examination of normal controls, we defined AR as PFA closure time b192 s for patients taking aspirin (Cohen et al., 2003; Frossard et al., 2004; Gum et al., 2001). Depressive symptoms were assessed with the Physicians Health Questionnaire (Kroenke & Spitzer, 2002). HbA1c was measured by standard laboratory high-performance liquid chromatography. Other routine care measures at the clinic visit were transcribed from patient charts.

4. Statistical analysis Results for patient characteristics are presented as median (interquartile range) or as a percentage for the AR and nonAR groups and for the whole sample. Bivariate associations with AR were assessed with the use of the Mann–Whitney test and Fisher’s Exact Test for continuous and categorical variables, respectively. Binary logistic regression models were constructed with presence of AR as the dependent variable to estimate both unadjusted and adjusted odds ratios. Goodness of fit for logistic models was assessed using Hosmer and Lemeshow tests (Hosmer & Lemeshow,

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Table 2 Unadjusted and adjusted odds ratios for ARa Characteristics

Unadjusted

Model 1b

Model 2c

HbA1cz8%

11 (2–54) P=.002 7 (2–33) P=.01 8 (0.9–66) P=.07

16 (3–94) P=.002 7 (1–32) P=.02 7 (0.8–64) P=.07

13 (2–99) P=.02 8 (1–50) P=.03 7 (0.5–101) P=.15

BMIz30 kg/m2 Depression symptoms z1 a

AR is defined as PFA-100 epinephrine cartridge closing time b192 s. Results are presented as odds ratio (95% confidence interval) with P value. b Binary logistic regression model adjusted for age and sex. c Binary logistic regression model including age, sex, HbA1z8%, BMIz30 kg/m2, and depression symptoms z1.

2000). All statistical analyses were performed with SPSS version 13. A two-tailed a of .05 was used to denote statistical significance.

5. Results Patients were 58% female, with similar numbers of Blacks, Whites, and Hispanics (Table 1), and median (interquartile range) age was 68 (56–77) years. In this sample, 10% were current smokers, 38% were obese (BMIz30 kg/cm2), and 31% had HbA1cz8%. SSRI antidepressant use was reported by 10%, and 65% had at least one depressive symptom, but none had symptoms indicating major depression. Median PFA-100 closure time was 281 s (interquartile range=216–300 s), and 23% exhibited AR. In bivariate analysis, AR was significantly associated with HbA1c ( P=.02) and obesity ( P=.006) and had a borderline significant association with having z1 depressive symptom ( P=.07). There were no statistically significant associations of AR with sex, age, race, current smoking, ambient plasma glucose, systolic or diastolic blood pressure, total cholesterol, aspirin dose, insulin treatment, SSRI use, or history of coronary artery disease. Patients with HbA1cz8.0% had an odds ratio of 11 (95% confidence interval=2–54, P=.002) of being aspirin resistant compared to patients with HbA1cb8.0% (Table 2). In multivariable logistic regression models with AR as outcome, adjusting for age and sex did not meaningfully change the associations of AR with HbA1cz8%, obesity, or z1 depressive symptoms. With these latter three variables in the same model, both HbA1cz8% and obesity remained statistically significant ( P=.02 and P=.03, respectively). The point estimate for the multivariable adjusted odds ratio for z1 depressive symptom was consistent with the unadjusted and with the age- and sex-adjusted models, but the confidence interval was wider with P=.15. None of the reported logistic models showed evidence of poor fit when assessed by Hosmer and Lemeshow goodness-offit tests. When the sample was stratified by insulin use, among the 16 patients taking insulin, 60% of those with AR had

elevated HbA1c compared to 36.4% for the non-AR patients ( P=.38). For the 32 patients without insulin treatment, the corresponding values were 83.3% vs. 11.5% ( Pb.001).

6. Discussion The principal finding of this study is that a substantial proportion (23%) of these patients being treated for type 2 diabetes who reported taking aspirin within the previous 24 h did not have the platelet inhibition that would be expected for patients on aspirin therapy. This AR was significantly associated with both poor glycemic control (HbA1cz8%) and obesity and showed a nonsignificant trend toward association with having at least one depressive symptom. These data suggest that AR may be of special concern for diabetic patients with these three conditions that have all been linked previously with higher CVD risk (Cohen & Alderman, 2001; Davidson, Rieckmann, & Rapp, 2005; Poirier et al., 2006; Selvin et al., 2005). Since diabetic patients are already at higher CVD risk, the additional risk conveyed by any of these three conditions would be expected to make the need for platelet inhibition even greater. Yet, it was precisely these potentially higher-risk patients who were more likely to exhibit a lower level of platelet inhibition. In this study, all participants had a diagnosis of type 2 diabetes; hence, we were not able to assess whether AR is associated with a diagnosis of diabetes irrespective of glycemic control, but some mechanisms for an association have been put forward, including elevated aspirin esterase activity and elevated levels of the proinflammatory CD40L in platelets of diabetic patients (Gresner et al., 2006; Varo et al., 2005). Others have observed an association of diabetes with AR in humans and in animal models (Watala et al., 2004, 2006). One recent study of 172 patients with type 2 diabetes did not find an association between HbA1c and AR (Fateh-Moghadam et al., 2005), but 90.1% of patients in the Fateh-Moghadam study were treated with insulin, and we observed in our study that the association of AR with elevated HbA1c was strongest among those not taking insulin. Angiolillo et al. (2006) have reported that insulin therapy may be associated with platelet dysfunction, and in our sample, the insulin-treated group had a somewhat but not significantly higher percentage with AR than those treated with oral medication. While this is not at all a reason to avoid insulin therapy (Scheen & Legrand, 2007), it may contribute to the difference between our findings and those of Fateh-Moghadam’s group. Another study that did not observe a significant association of AR with HbA1c (Mehta et al., 2006) had a predominantly (84%) White sample, included patients with type 1 diabetes (comprising 45% of the sample), did not report what percentage of the patients with type 2 diabetes were on insulin, and used a different platelet function methodology, making comparison difficult. On the other hand, Watala et al. (2004) did report a

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statistically significant inverse correlation of PFA-100 closure time with HbA1c values among 31 patients with type 2 diabetes, consistent with our findings. Our study has several limitations. The relatively small sample size provided low statistical power for testing associations, and the possibility of type II errors is substantial, particularly for the association of AR with depressive symptoms. The small sample size may also explain why we did not observe an aspirin dose association that has recently been observed by others (Abaci et al., 2005). We did a post hoc subgroup analysis despite small numbers in order to compare our findings with others; such analyses always have to be interpreted with caution. Also, despite low statistical power, small sample sizes can sometimes lead to type I errors as well. The small number in the AR group resulted in wide 95% confidence intervals, and it is possible that the relatively large hazard ratios may be overestimations based on lack of statistical precision. However, for the association with HbA1c, the lower value (2) of the confidence interval in the fully adjusted model is still a clinically meaningful odds ratio. There is some controversy whether AR is a biological phenomenon of nonresponse or a result of nonadherence to aspirin therapy (Freedman, 2006; Michelson et al., 2005). We could not confirm the patient self-report that they took aspirin in the previous 24 h. Patient self-report of medication adherence has been observed to be a reasonable measure that is significantly associated with electronic monitoring (Schroeder, Fahey, Hay, Montgomery, & Tim, 2006), although others have found self-report to lead to misclassification. We tried to improve the validity of the self-report by only including those who said they took aspirin in the previous 24 h. Furthermore, although the distinction between nonresponse and nonadherence would be germane to what measures might be taken to improve platelet inhibition, from the perspective of risk identification, the value of identifying nonresponse remains, irrespective of the reason. Knowing that platelet inhibition was less than optimum could lead a clinician to increase patient education regarding adherence to aspirin therapy. Whether the measurement of the PFA-100 or some similar point-ofservice platelet function measure can be used in clinical practice as an indication for alternate therapy or changes in dose still remains to be determined. The effectiveness of therapy for controlling glucose, cholesterol, and blood pressure is routinely monitored, but the effectiveness of aspirin therapy is not. Until recently, platelet inhibition measures such as aggregometry and flow cytometry were too labor intensive and otherwise impractical for routine clinical care. The advent of desktop, pointof-service devices such as the PFA-100 leads to the possibility that monitoring of platelet inhibition therapy can also be done routinely. Nonetheless, there is, as yet, no consensus regarding the clinical utility of assessing platelet inhibition measures for CVD prevention, although some data linking such measures to hard clinical outcomes exist

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(Eikelboom et al., 2002; Gum, Kottke-Marchant, Welsh, White, & Topol, 2003). In conclusion, our findings, consistent with some previous studies, suggest that a substantial number of patients with type 2 diabetes who have been prescribed aspirin therapy may not be obtaining the intended platelet inhibition. Although our findings will need confirmation in larger, controlled prospective studies, in this limited sample of treated patients with type 2 diabetes, AR was associated with poor glucose control and obesity, which would mean that their potentially increased risk of CVD may be elevated even further by inadequate platelet inhibition. Whether the PFA-100 or any other practical measure of AR can be used in clinical practice to identify added CVD risk and to inform platelet inhibition therapy needs further study. Acknowledgment We wish to thank the New York City Speaker’s Fund for Public Health Research for funding assistance for this study. References Abaci, A., Yilmaz, Y., Caliskan, M., Bayram, F., Cetin, M., Unal, A., & Cetin, S. (2005). Thrombosis Research, 116, 465 – 470. American Diabetes Association. (2003). Aspirin therapy in diabetes. Diabetes Care, 26, S87 – S88. Andersen, K., Hrulen, M., Arnesen, H., & Seljelot, I. (2003). Aspirin nonresponsiveness as measured by PFA-100 in patients with coronary artery disease. Thrombosis Research, 108, 37 – 42. Angiolillo, D. J., Bernardo, E., Ramirez, C., Costa, M. A., Sabate, M., Jimenez-Quevedo, P., Hernandez, R., Moreno, R., Escaned, J., Alfonso, F., Banuelos, C., Bass, T. A., Macaya, C., & Fernandez-Ortiz, A. (2006). Insulin therapy is associated with platelet dysfunction in patients with type 2 diabetes mellitus on dual oral antiplatelet therapy. Journal of the American College of Cardiology, 48 (2), 298 – 304. Bruce, E. C., & Musselman, D. L. (2005). Depression, alterations in platelet function, and ischemic heart disease. Psychosomatic Medicine, 67 (Suppl 1), S34 – S36. Cohen, H. W., & Alderman, M. H. (2001). The association between depression and cardiovascular disease in patients with hypertension. Primary Psychiatry, 8 (7), 39 – 54. Cohen, H. W., Billett, H. H., & Monrad, E. S. (2003). Is ASA resistance more common in Black patients? (abstract). 2003 Congress International Society on Thrombosis and Haemostasis. Birmingham, UK. Davidson, K. W., Rieckmann, N., & Rapp, M. A. (2005). Definitions and distinctions among depressive syndromes and symptoms: Implications for a better understanding of the depression–cardiovascular disease association. Psychosomatic Medicine, 67 (Suppl 1), S6 – S9. Eikelboom, J. W., Hirsh, J., Weitz, J. I., Johnston, M., Yi, Q., & Yusuf, S. (2002). Aspirin-resistant thromboxane biosynthesis and the risk of myocardial infarction, stroke or cardiovascular death in patients at high risk for cardiovascular events. Circulation, 105, 1650 – 1655. Fateh-Moghadam, S., Plockinger, U., Cabeza, N., Htun, P., Reuter, T., Ersel, S., et al. (2005). Prevalence of aspirin resistance in patients with type 2 diabetes. Acta Diabetologica, 42, 99–103. Freedman, J. E. (2006). The aspirin resistance controversy: Clinical entity or platelet heterogeneity? Circulation, 113, 2865 – 2867. Frossard, M., Fuchs, I., Leitner, J. M., Hsieh, K., et al. (2004). Platelet function predicts myocardial damage in patients with acute myocardial infarction. Circulation, 110, 1392 – 1397.

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