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Association of Level of Kidney Function and Platelet Aggregation inAcute Myocardial Infarction

Fredrik Karlsson, MD,1,2 Angelo Modica, MD,1,2 and Thomas Mooe, MD, PhD1,2

Background: Decreased kidney function has been established as an important risk factor in patientspresenting with acute coronary syndrome. In acute coronary syndrome, increased platelet aggregationis associated with vascular complications. The aim of this study is to examine whether decreased kidneyfunction is associated with altered platelet function in patients presenting with acute myocardialinfarction.

Study Design: Prospective cohort.Setting & Participants: 413 patients presenting with acute myocardial infarction admitted to the

cardiac intensive care unit at Östersund Hospital, Östersund, Sweden.Predictors: Glomerular filtration rate less than 60 mL/min/1.73 m2 estimated from serum cystatin C

level, comorbidity, medications, and markers of inflammation and hemostasis.Outcomes & Measurements: Platelet aggregation was assessed by measuring the formation of

small platelet aggregates (SPAs) by using a laser light scattering method. A greater SPA level indicatesgreater platelet aggregation. Platelet aggregation analysis was performed on days 1, 2, 3, and 5in-hospital.

Results: We observed a significant increase in platelet aggregation during the first 3 days in thehospital regardless of kidney function (P � 0.001). Platelet aggregation was more pronounced inpatients with estimated glomerular filtration rate less than 60 mL/min/1.73 m2 on day 2 (SPA count,65,000 versus 47,000; P � 0.01) and day 3 (SPA count, 77,000 versus 52,000; P � 0.02). In a multiplelinear regression analysis, decreased kidney function was no longer significantly associated withincreased platelet aggregation. Older age, greater plasma fibrinogen level, and diabetes mellitus wereassociated with increased platelet aggregation in the multivariable model.

Limitations: During the study period, 78 patients presenting with acute myocardial infarction were noteligible for inclusion. Differences in treatment with antiplatelet medication between the 2 groups mighthave affected our findings.

Conclusions: Platelet aggregation increases during the first days after acute myocardial infarctionregardless of kidney function. There is no difference in platelet aggregation in patients according to levelof kidney function.Am J Kidney Dis 54:262-269. © 2009 by the National Kidney Foundation, Inc.

INDEX WORDS: Platelet aggregation; myocardial infarction; chronic kidney disease.

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he presence of decreased kidney function isassociated strongly with increased cardio-

ascular morbidity and mortality.1,2 Nationalealth surveys from the United States indicate anncreasing prevalence of all stages of kidneyisease. The number of patients in the US popu-

From the 1Department of Internal Medicine, Section ofardiology, Östersund Hospital, Östersund; and 2Depart-ent of Public Health and Clinical Medicine, Umeå Univer-

ity Hospital, Umeå, Sweden.Received October 10, 2008. Accepted in revised form

pril 3, 2009. Originally published online as doi:10.1053/j.jkd.2009.04.023 on June 29, 2009.Address correspondence to Fredrik Karlsson, MD, Medi-

inkliniken, Östersunds sjukhus, 83131 Östersund, Sweden.-mail: fredrik.karlsson@jll.se© 2009 by the National Kidney Foundation, Inc.0272-6386/09/5402-0010$36.00/0

cdoi:10.1053/j.ajkd.2009.04.023

American Journal of K62

ation with end-stage renal disease increased from09,000 to 472,000 between 1991 and 2004.3 Theoor long-term prognosis of patients with end-tage renal disease receiving treatment with dialy-is has long been recognized. During the lastecade, convincing evidence has been presentedhat identifies moderate kidney disease as a strongndependent risk factor for cardiovascular death,imilar to that of diabetes mellitus.4,5

Kidney disease also has been established as anmportant risk factor in patients presenting withcute coronary syndrome (ACS). Several studiesave consistently shown a relationship betweenecreased kidney function and poor clinical out-ome in the ACS setting, with increased in-hospitalortality and worsened long-term prognosis.6,7 Glo-erular filtration rate (GFR) calculated from cysta-

in C measurement in plasma has been identified asn independent risk factor for poor clinical out-

ome after ACS.8

idney Diseases, Vol 54, No 2 (August), 2009: pp 262-269

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Kidney Disease and Platelet Aggregation 263

Chronic kidney disease (CKD) is defined andlassified by estimation of GFR and ascertain-ent of markers of kidney damage, predomi-

antly proteinuria. Estimated GFR less than 60L/min/1.73 m2 is associated with the onset of

hysiological and laboratory abnormalities char-cteristic of kidney disease. GFR less than 60L/min/1.73 m2 is well established as the cutoff

alue for the presence of CKD in existing guide-ines.9

In the setting of ACS, platelet function is oflinical interest because increasing platelet ag-regation is associated with vascular complica-ions. Previous studies have shown increasinglatelet aggregation during the first few daysfter myocardial infarction.10,11 CKD is accom-anied by traditional risk factors for cardiovas-ular disease, some of which are associatedith increased platelet reactivity, such as dia-etes and older age.2 Studies of platelet func-ion in patients with kidney disease have beenerformed predominantly in patients receivingemodialysis. Knowledge regarding plateletunction in patients with moderate impairmentf kidney function not receiving dialysis isparse, and we have found no specific dataegarding the dynamics of platelet aggregationn patients with kidney disease presenting withCS.The aims of this study were first, to compare

he dynamics of platelet aggregation during theourse of myocardial infarction between patientsith and without CKD; second, to examine the

ssociation between CKD and platelet aggrega-ion; and third, to describe differences in comor-idity and treatment in unselected patients withcute myocardial infarction (AMI) with and with-ut CKD.

METHODS

etting andParticipants

We included unselected patients with AMI admitted tostersund Hospital in 2002 and 2003. Östersund Hospital is

he primary referral hospital for the county of Jamtland inorthern Sweden, and all patients admitted to the hospitalere considered for inclusion. The catchment area has

pproximately 128,000 inhabitants. All patients were in-luded on admission, and a diagnosis of AMI was madeccording to the guidelines of the European Society of

ardiology.12 s

easurements

Blood samples for measurements of platelet aggregationn day 1, cystatin C, and other laboratory markers consid-red of interest were collected simultaneously at the time ofdmission. Blood samples for measurement of platelet aggre-ation also were collected on days 2, 3, and 5 in-hospital.Patients were divided into 2 groups according to kidney

unction: patients with decreased kidney function or CKD,efined as estimated GFR less than 60 mL/min/1.73 m2, andatients with normal kidney function. GFR calculationsere based on measurements of cystatin C for each patient.Cystatin C level in plasma correlates closely with GFR

ecause it is freely filtered in glomeruli without tubulareabsorption. The method is considered sensitive for detect-ng even small decreases in GFR.13 Venous blood samplesor cystatin C measurement were frozen at �20°C untilnalyzed in December 2006.

Plasma cystatin C measurements were performed by meansf a particle-enhanced immunoturbidimetric method (Modu-ar P; Roche Diagnostics Inc, Basel, Switzerland). Reagentsnd calibrator were obtained from DakoCytomation,lostrup, Denmark. The patient sample was incubated with

eaction buffer for 5 minutes; thereafter, cystatin C immuno-articles were added. The change in absorbance at 564 nmroduced by the agglutination reaction then was measuredfter 300 seconds. The application agreed with instructionsrom DakoCytomation for analysis on Modular P.

The coefficients of variation for the procedure were 3.2%t a cystatin C level of 1.09 mg/L and 2.3% at 4.62 mg/Leasured in commercial controls from DakoCytomation. In

ddition to these controls, the laboratory analyzed a serumool with a coefficient of variation of 2.4% at 2.03 mg/L.The cystatin C–based prediction equation for GFR in-

luded factors for sex and prepubertal age: GFR (mL/min/.73 m2) � 87,62 � (cystatin C)�1,693 (� 1,376 if age � 14ears) (� 0,940 if female). The cystatin C assay wasalibrated for use in the estimating equation and has beenalidated in previous studies.13,14

Platelet aggregation was assessed by using the PA-200echnique (Kowa Inc, Tokyo, Japan). This is a particle-ounting technique based on laser light scattering, which haseen described and validated in detail.15,16 The method haseen shown to be useful in several clinical studies.17-19 Aenous blood sample anticoagulated with citrate is obtained,nd platelet-rich plasma is prepared within 15 minutes ofampling by centrifugation at 150g for 10 minutes at roomemperature. The remaining sample is centrifuged at 300gor 10 minutes to obtain platelet-poor plasma, which is useds a reference. A 20-mW diode laser generates a laser beam0 �m in diameter (wave length, 675 nm), which is passedhrough 300 �L of the platelet-rich plasma stirred in aylindrical glass cuvette with an internal diameter of 5 mm.ight scatter generated by single platelets and platelet aggre-ates is measured within a region of approximately 30 � 65 �45 �m by using a photocell array. The signal frequency isecorded at 10-second intervals during 10 minutes. Data areresented as a 2-dimensional graph showing the changesver time in the count/10 seconds of platelet aggregates. Theight scattering intensity increases in proportion to particle

ize in a suspension and thus gives an estimate of platelet

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Karlsson, Modica, and Mooe264

ggregate size. Particles with an intensity of 25 to 400 mVepresent small aggregates (9 to 25 �m) and were used toetect aggregation in the present study. As an agonist, wesed 30 �L of a solution containing 0.1 mg of epinephrine/L.15

onventional antiplatelet and antithrombotic treatments weresed as clinically indicated.This study complies with the Declaration of Helsinki and

as approved by the local ethics committee. Informedonsent was obtained from all participants.

tatistical Analysis

Statistical analyses were performed using SPSS statisticaloftware (SPSS Inc, Chicago, IL). Group data are expresseds mean � SD for continuous variables and rates forariables on a nominal scale. Median value and interquartileange are used when the distribution of data makes itppropriate. Differences between proportions were analyzedy using �2 test. Univariate analysis of differences betweenroups was assessed by using t test or 1-way analysis ofariance for normally distributed data; Mann-Whitney Uest and Kruskal-Wallis test were used when appropriate.

The initial analysis of differences in platelet aggregationetween the 2 groups was performed in a general linearodel for repeated measurements. Paired comparisons be-

ween different times were assessed by using t test. Analysisf the correlation between platelet aggregation and kidneyunction was assessed by using linear regression.

Multivariable analysis was performed by using multipleinear regression. The multivariable model included vari-bles with a statistically significant impact on platelet aggre-ation, as well as variables considered clinically important.he final multivariable model included age, diabetes melli-

us, C-reactive protein level, fibrinogen level, and kidneyunction.

To fulfill the assumption of normal distribution in theultiple linear regression model and parametric testing, the

utcome variable, small platelet aggregates (SPAs), under-ent square root transformation.The null hypothesis was rejected for P � 0.05.

RESULTS

We included 413 patients with acute myocar-ial infarction in the study; 147 were found toave impaired kidney function and were as-igned to the CKD group.

Five patients in the CKD group were undergo-ng treatment with hemodialysis at the time of

Table 1. SPA Counts S

SPA Count (� 103) eGFR � 60 mL/min/1.73 m2

ay 1 39.0 (100.7)ay 2 65.0 (100.5)ay 3 77.0 (103.0)ay 5 47.0 (85.8)

Note: Data expressed as median (interquartile range)L/min/1.73 m2; conversion factor to mL/s/1.73 m2, �0.016

Abbreviations: eGFR, estimated glomerular filtration rate; SPA,

nclusion. Median delay from first symptom untilnclusion was 7.0 hours (interquartile range, 9.3),ith no significant difference between the 2roups.During the period of inclusion, another 78

atients were admitted and AMI was diagnosed,ut they were not included because of logisticalroblems, terminal illness, death, and patientsot willing to participate in the study.The amount of available platelet aggregation

ata decreased from day 1 to day 5 because ofn-hospital death (n � 34), discharge (n � 99),nd incomplete aggregation data (n � 32).omplete data were available for 396 patientst day 2, 352 patients at day 3, and 248 patientst day 5.

In the 245 patients with complete data for alleasurements, a repeated-measurements analy-

is showed a significant change in SPA levelsver time (P �0 .001). There also was a signifi-ant time � CKD interaction (P � 0.004) indicat-ng that the change is different depending onKD.SPA levels increased significantly during the

rst 3 days of admission in both groups. Be-ween days 3 and 5, platelet aggregation de-reased significantly in the CKD group, whereashere was no significant change in the non-CKDroup.Comparing the 2 groups, patients with im-

aired kidney function had significantly greaterevels of platelet aggregates on days 2 and 3 thanatients without CKD (Table 1).There was a significant association between

latelet aggregation and kidney function (cysta-in C–estimated GFR) in univariate analysis onay 2 (� � �0.17; R2 � 0.03; P � 0.001; Fig 1)nd day 3 (� � �0.16; R2 � 0.03; P � 0.002).

In a multivariate analysis including age, pres-nce of diabetes, and plasma fibrinogen and

d By Kidney Function

R � 60 mL/min/1.73 m2 No. of Patients P

24.5 (58.0) 413 0.0847.0 (70.0) 396 0.0152.0 (80.0) 352 0.0259.0 (91.0) 248 0.5

estimations based on cystatin C levels. Unit of eGFR:

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Kidney Disease and Platelet Aggregation 265

-reactive protein levels, the association be-ween CKD and platelet aggregation was noonger significant at any time of measurementTable 2). Multivariate analysis also was per-ormed with kidney function represented as aontinuous variable (estimated GFR and cystatin

level), with the same result of no independentmpact on platelet aggregation.

Baseline characteristics are listed in Table 3.ge, comorbidity, medication, and plasma

evels of inflammatory parameters differed be-ween patients with different kidney funct-on.

There also were significant differences in treat-ent, including differences in the use of antiplate-

et agents, anticoagulants, and treatment withhrombolytics (Table 4).

DISCUSSION

The mechanism behind the association be-ween CKD and cardiovascular disease is not

Figure 1. Relationship between formation of smalllatelet aggregates on day 2 and deciles of estimatedlomerular filtration rate (eGFR).

Table 2. Predictors of Platelet Aggr

Variable B (95% confidence i

ge 2.26 (1.24 to 3-Reactive protein �0.30 (�0.63 toibrinogen 17.62 (8.6 to 26iabetes 48.90 (21.5 to 7GFR � 60 mL/min/1.73 m2 �9.08 (�35.3 to

Note: R2 � 0.15 (multiple regression analysis). GFR est2; conversion factor to mL/s/1.73 m2, �0.01667.Abbreviations: B, unstandardized regression coefficient;

lar filtration rate.

ully understood. As shown in the present studyf patients with AMI, CKD is associated withuch established risk factors for cardiovascularisease as older age, diabetes, hypertension, andnfavorable serum lipid profile. However, thesestablished risk factors do not give the completexplanation. Nontraditional risk factors, such ashysiological alterations associated with CKDnd underuse or toxicity of known beneficialherapies, also may be of importance.20,21 Amonghese possible nontraditional risk factors, low-rade inflammation has been shown in previoustudies of patients with kidney dysfunction, as inur study.22 An association between level ofnflammation and platelet function, as well asetween increased levels of inflammatory mark-rs and the presence of cardiovascular disease,as previously been reported.23-25 The degree oflatelet reactivity is of interest during the coursef myocardial infarction, and pharmacologicalnhibition of platelet reactivity is a mainstay inhe treatment of ACS. Previous studies haveuggested that increased platelet aggregation isssociated with poor clinical outcome afterMI.10,19 To our knowledge, the possibility of

ncreased platelet reactivity as a contributingactor to poor outcome in patients with CKD inhe ACS setting has not been investigated.

Patients with end-stage kidney disease receiv-ng dialysis present both thrombotic complica-ions and bleeding diathesis, and many hemo-tatic disorders in these patients have beenscribed to abnormalities in platelet function.xtensive studies in this group of patients havehown several intracellular platelet alterations,s well as impaired platelet–vessel wall andlatelet-platelet interactions, some of which ap-ear to be partly corrected by dialysis.26

n on Day 2 in Multivariate Analysis

SE (B) � P

0.52 0.25 �0.0010.16 �0.10 0.074.58 0.22 �0.001

13.94 0.17 0.00113.33 �0.04 0.5

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Platelet function in patients with CKD not atnd-stage kidney disease is less well studied.ata from 1 cross-sectional analysis by Landray

t al23 including 334 patients with CKD defineds serum creatinine level greater than 1.47 mg/dL�130 �mol/L) showed a relationship betweenevel of kidney function and increased concentra-ion of P-selectin, a marker of increased plateleteactivity. These findings remained after adjust-ent for age, sex, vascular disease, and diabetesellitus. The mechanisms of platelet function

re complex and not fully understood. However,ubgroups of patients with increased platelet

Table 3. Demographics

�30 (

ge (y) 81omen (%)ody mass index (kg/m2) 24.7revious stroke (%)revious heart failure (%)revious myocardial infarction (%)revious diabetes mellitus (%)revious hypertension (%)moker (%)otal cholesterol (mg/dL) 193ow-density lipoprotein cholesterol (mg/dL) 124igh-sensitivity C-reactive protein, baseline (mg/L) 30ibrinogen, baseline (mg/dL) 204roponin T, peak value (ng/mL) 2.2latelet count (� 103/�L) 235hite blood cell count (� 103/�L) 11.0emoglobin (g/dL) 12.5reatinine (mg/dL) 2.5ystatin C (mg/L) 2.34GFR (mL/min/1.73 m2) 18.8edications, admission�-Blockers (%)Angiotensin-converting enzyme inhibitors (%)Angiotensin receptor blockers (%)Diuretics (%)Statins (%)edications, in-hospital�-Blockers (%)Angiotensin-converting enzyme inhibitors (%)Angiotensin receptor blockers (%)Diuretics (%)Statins (%)

Note: Results expressed as median (interquartile range)n cystatin C levels. Conversion factors for units: creatini0.0259; hemoglobin in g/dL to g/L, �10; fibrinogen in mg/0.01667. No conversion factor is required for platelets orAbbreviation: eGFR, estimated glomerular filtration rate.

eactivity and at high risk of ischemic events, as t

ell as patients at risk of adverse hemorrhagicomplications when treated with antiplateletgents, have been identified.27,28 However,nowledge regarding the safety and optimal treat-ent with antiplatelet agents in patients with

ecreased kidney function is lacking. Major clini-al studies related to ACS frequently excludeatients with significantly increased creatinineevels, and data regarding the subset of patientsith moderate impairment of kidney function

arely are presented.29

Our study shows that patients with CKD havedynamic increase in platelet aggregation during

ed by Kidney Function

eGFR (mL/min/1.73 m2)

30-44 (n � 42) 45-59 (n � 60) �60 (n � 266) P

86 (70-92) 78 (60-91) 69 (27-91) �0.00152 41 34 0.06

25.1 � 4.3 25.2 � 4.6 26.5 � 4.1 0.0138 19 12 �0.00127 21 7 �0.00148 34 19 �0.00129 21 17 0.354 40 34 0.00412 18 23 0.3

205 � 54 189 � 46 209 � 46 0.01128 � 50 120 � 39 131 � 43 0.23.9 (14) 3.6 (23) 2.8 (4.4) �0.001156 (41) 146 (65) 136 (48) �0.0011.2 (3.7) 1.2 (3.2) 1.4 (2.6) 0.2239 � 58 221 � 71 242 � 55 0.1

10.6 � 3.4 9.3 � 3.3 9.7 � 3.3 0.0312.7 (2.9) 13.0 (2.5) 13.9 (1.8) �0.0011.5 (0.4) 1.2 (0.3) 1.1 (0.2) �0.001

1.65 (0.19) 1.34 (0.15) 0.97 (0.21) �0.00137.2 � 4.1 52.4 � 4.7 97.1 � 25 �0.001

50 55 33 0.00126 26 12 0.0022 7 4 0.002

57 40 15 �0.00114 19 18 0.9

76 79 88 0.0542 42 38 0.75 9 6 0.7

63 54 29 �0.00137 37 65 �0.001

an � SD unless noted otherwise. GFR estimations basedg/dL to �mol/L, �88.4; cholesterol in mg/dL to mmol/L,

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Kidney Disease and Platelet Aggregation 267

ore, kidney function is associated with plateletggregation in univariate analysis.

However, this association is explained by olderge, diabetes mellitus, and plasma levels of in-ammatory biomarkers in patients with CKD.he comorbidity of patients with CKD in thistudy is extensive, and treatment with antithrom-otic and thrombolytic agents differed signifi-antly compared with patients without CKD.

The number of patients treated with low-olecular-weight heparins (LMWHs) was higher

n the non-CKD group (Table 4). The effect ofMWH on SPA formation is unknown, and anffect on our results cannot be ruled out. How-ver, this seems unlikely because previous stud-es evaluating platelet function found no evi-ence of a significant effect of LMWH on plateletggregation.30,31

Antiplatelet medication also differed signifi-antly between groups. Aspirin and clopidogrelere used more frequently in the non-CKD group

Table 4). These differences in medications be-ween groups might affect results of our measure-

ents.However, SPA formation is considered the

rst phase of platelet aggregation and is followedy the formation of medium and large plateletggregates. Studies of several platelet inhibitorygents, such as aspirin and ticlopidine, have

Table 4. Antiplatelet, LMWH, and ThrombolyticTreatment Stratified by Kidney Function

Medication InHospital (%)

eGFR � 60mL/min/1.73 m2

eGFR � 60mL/min/1.73 m2 P

spirin, day 1 88 95 0.004spirin, day 2 87 95 0.004spirin, day 3 86 94 0.007spirin, day 5 84 95 0.003lopidogrel, day 1 26 55 �0.001lopidogrel, day 2 26 56 �0.001lopidogrel, day 3 27 54 �0.001loidogrel, day 5 26 54 �0.001MWH, day 1 74 87 0.001MWH, day 2 76 87 0.005MWH, day 3 79 87 0.05MWH, Day 5 76 85 0.09hrombolytictherapy 15 27 0.003

Note: GFR estimations based on cystatin C levels; Con-ersion factor to mL/s/1.73 m2, �0.01667.Abbreviations: eGFR, estimated glomerular filtration rate;

MWH, low-molecular-weight heparin.

hown that antiplatelet treatment predominantly R

ffects the latter phase, generating medium andarge platelet aggregates.

Previous studies of the AG-10 method havehown that SPA formation is not affected signifi-antly by aspirin.32,33 Knowledge regarding theffect of clopidogrel on SPA formation is lessell studied.In our study, treatment with LMWH, aspirin,

r clopidogrel had no significant impact on plate-et aggregation, measured as SPA formation, inultivariable analysis.There are a few limitations to the study. Dur-

ng the study period, 78 patients were not eligibleor inclusion for different reasons. Sixty-twoatients were not included because of logisticalroblems. A bias cannot be ruled out, but anmportant bias seems unlikely because this oc-urred in an unpredictable way.

Also, some patients were excluded becausef terminal illness, death, or dementia. Thereikely is a relatively high prevalence of kidneyisease in these patients; however, it is un-ikely that this would have affected our resultsecause only 9 patients were excluded forhese reasons. Seven patients did not want toarticipate in the study.In conclusion, our data did not verify an inde-

endent association between CKD and plateletggregation. Similar to previous reports, patientsith CKD in our study presenting with AMI are

haracterized by multiple conditions predispos-ng for severe atherosclerotic disease, as well asncreased platelet aggregation.

In this study, there were also significant differ-nces in treatment with antiplatelet agents andnticoagulants, and patients with decreased renalunction were less likely to receive treatment.hese findings suggest there are possible impor-

ant benefits from treating this high-risk group ofatients presenting with AMI with establishedntiplatelet therapy. The need for a more individu-lized approach to antiplatelet treatment in theCS setting is evident, and differences regarding

omorbidity and other risk factors between pa-ients should be taken into consideration whenesigning future studies of new platelet inhibi-ory agents.

ACKNOWLEDGEMENTSSupport: This study was supported by grants from the

esearch and Development Unit at Jamtland County Coun-

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il, the Heart Foundation of Northern Sweden, and the Jointommittee of the Northern Sweden Health Care Region.Financial Disclosure: None.

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14. Kyhse-Andersen J, Schmidt C, Nordin G, et al: Se-um cystatin C, determined by a rapid, automated particle-nhanced turbidimetric method, is a better marker thanerum creatinine for glomerular filtration rate. Clin Chem0:1921-1926, 199415. Ozaki Y, Satoh K, Yatomi Y, Yamamoto T, Shirasawa

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