Determinants of the Erythrocyte Sedimentation Rate in the Era of Microinflammation. Excluding Subjects With Elevated C-Reactive Protein Levels

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1 Hematopathology / ESR Determinants Determinants of the Erythrocyte Sedimentation Rate in the Era of Microinflammation Excluding Subjects With Elevated C-Reactive Protein Levels Arie Steinvil, MD, Itzhak Shapira, MD, Yaron Arbel, MD, Dan Justo, MD, Shlomo Berliner, MD, PhD, and Ori Rogowski, MD Key Words: Erythrocyte sedimentation rate; High-sensitivity C-reactive protein; Microinflammation DOI: /U04E2YFJRR6JQQTK Abstract The erythrocyte sedimentation rate (ESR) can be used to identify low-grade inflammation that contributes to future vascular events. ESR determinants, however, have not been explored in the absence of a subclinical or microinflammatory response. The ESR was determined in a large cohort of apparently healthy participants, excluding subjects with high-sensitivity C-reactive protein (hs-crp) concentrations more than 5 mg/l (47.62 nmol/l). Linear regression models were used to identify the determinants of the ESR. The study population comprised 6,237 subjects. The main laboratory variables found to affect ESR were levels of fibrinogen, hemoglobin, globulin, and triglycerides (all P <.001; R 2 = 0.34 and 0.44 for men and women, respectively). Sex was found to affect ESR alone and in combined interactions with most other variables. Age did not affect ESR. The main determinants of ESR in an inflammationfree cohort are sex and levels of fibrinogen, hemoglobin, globulins, and triglycerides. Atherothrombotic disease is a leading cause of morbidity and mortality in the Western world and is associated with lowgrade, subclinical inflammation (so-called microinflammation). In this regard, the Westergren erythrocyte sedimentation rate (ESR) has been shown to be an established inflammationsensitive biomarker with proven prognostic value. 1-3 Yet, previous studies that explored the normal values and determinants of ESR in apparently healthy subjects and subjects with atherothrombotic risk factors did not use accepted biomarkers to exclude the presence of a significant acute phase response in the subjects. 2,4-6 This limitation has been repeatedly noted in the literature. 3,7 We analyzed the determinants of ESR in a cohort of apparently healthy subjects and subjects with atherothrombotic risk factors in whom the eventual presence of a significant acute phase response was excluded by using a high-sensitivity C-reactive protein (hs-crp) assay. Materials and Methods Population We analyzed the data collected as part of the Tel-Aviv Medical Center Inflammation Survey (TAMCIS), a registered data bank of the Israeli Ministry of Justice This is a relatively large survey of apparently healthy subjects attending a center for periodic health examinations. In our study, patients attending the Tel-Aviv Sourasky Medical Center, Tel-Aviv, Israel, for a routine health examination between September 2002 and May 2007 were invited to participate in the TAMCIS. All subjects enrolled were recruited during their routine annual health checkup and 486 Am J Clin Pathol 2008;129: by guest 486 DOI: /U04E2YFJRR6JQQTK

2 Hematopathology / Original Article gave written consent in accordance with the guidelines of the institutional ethics committee. A total of 11,274 subjects gave informed consent (7,095 men and 4,179 women). A systematic examination ruled out enrollment bias owing to sociodemographic and biomedical variables. We initially excluded 2,627 subjects owing to known inflammatory diseases (eg, arthritis, inflammatory bowel disease, or psoriasis), pregnancy, steroidal or nonsteroidal treatment (except for aspirin at a dose of 325 mg/d), acute infection, or invasive procedures (eg, surgery or catheterization) during the last 6 months. We later excluded 584 subjects from the analysis owing to a history of proven atherothrombotic event (myocardial infarction, cerebrovascular disease, or peripheral artery occlusion disease) or known diabetes mellitus. We further excluded 210 subjects with missing ESR measurements or with relatively high ESR values (>50 mm/h), as done in previous similar studies, 1 and an additional 692 with anemia, defined as hemoglobin concentrations below the lower limit of normal in our local laboratory (13.5 g/dl [135 g/l] and 11.7 g/dl [117 g/l] for men and women, respectively). Finally, to exclude hidden inflammation and/or infections, we excluded 924 subjects with hs-crp concentrations of more than 5 mg/l (47.62 nmol/l). Following these exclusions, the study group comprised 6,237 subjects (4,187 men and 2,050 women). Laboratory Methods The ESR was determined by using the method of Westergren. 12,13 In brief, 4.5 ml of venous blood was sampled in a BD Vacutainer (Becton Dickinson, Franklin Lakes, NJ) containing a 0.5-mL, 3.8% solution of sodium citrate. The test tube was mixed gently immediately following blood sampling and again just before measuring, which took place within 2 hours after the blood was drawn. A standard 200- mm, Westergren method glass tube was filled to the zero mark at the top, set in a vertical position, and left for 1 hour. The distance from the bottom of the surface of the meniscus to the top of the column was then measured, and the result was expressed as millimeters in the first hour. Analysis of the CBC count was performed using the Coulter STKS electronic cell analyzer (Beckman Coulter, Nyon, Switzerland). Fibrinogen was quantified by the method of Clauss 14 and using a Sysmex 6000 autoanalyzer (Sysmex, Hyaga, Japan), and the hs-crp was measured by using a Behring BN II Nephelometer (DADE Behring, Marburg, Germany). 15 Definition of Atherothrombotic Risk Factors Results of the routine health checkup were assessed by using certain definitions to recognize atherothrombotic risk factors. These included diabetes mellitus, which was defined as a fasting blood glucose level of 126 mg/dl (7.0 mmol/l) or more or the intake of insulin or oral hypoglycemic medications. Hypertension was defined as a blood pressure of 140/90 mm Hg or more in 2 separate measurements or the intake of antihypertensive medications. Dyslipidemia was defined as low-density lipoprotein or non high-density lipoprotein cholesterol concentrations (for subjects with elevated triglyceride concentrations of 200 mg/dl [2.26 mmol/l] or more) higher than the recommended levels according to the risk profile defined by the updated Adult Treatment Panel III recommendations 16 or the intake of lipid-lowering medications. Smokers were defined as subjects who smoked at least 5 cigarettes per day and past smokers as subjects who had quit smoking for at least 30 days before examination. Statistical Analysis All data were summarized and displayed as mean (SE) for continuous variables and as number (percentage) of patients in each group for categorical variables. For all categorical variables the χ 2 statistic was used for assessing the statistical significance between the 2 sexes, and the independent Student t test was used for continuous variables. The age-adjusted comparison of continuous variables between the 2 sexes was done by using analysis of covariance under a general linear model. To assess which variables contribute to the variability of ESR, we performed linear regression using the stepwise method with ESR as the dependent variable and many known and possible confounding parameters as the independent variables, which included sex; age; waist measurement; body mass index; alcohol consumption and sports activity; use of medication, including aspirin, α-blockers, β-blockers, calcium channel blockers, angiotensin converting enzyme inhibitors, angiotensin II receptor blockers, statins, fibrates, oral contraceptives, and hormone replacement therapy; cardiovascular risk factors, including systolic and diastolic blood pressure measurements, smoking status, family history of coronary heart disease, lipid profile including high-density lipoprotein, low-density lipoprotein, and triglyceride concentrations; and glucose, serum albumin and globulin, hemoglobin, and fibrinogen concentrations. In addition to the linear regression models and to evaluate the importance of age, we divided our cohort into age groups, excluded the small groups of subjects younger than 20 years and older than 70 years, and calculated the mean ESR and fibrinogen concentration in each age group plus the overall significance between the age groups and the linear trend between groups, using 1-way analysis of variance. The comparison of ESR in the age groups following adjustment for the differences in fibrinogen concentration between the groups was done using analysis of covariance under a general linear model. Finally, to test the prediction capability of ESR, we randomly chose approximately 70% of the cohort and calculated the simple linear regression equation with the 3 variables that demonstrated the highest partial correlations by guest Am J Clin Pathol 2008;129: DOI: /U04E2YFJRR6JQQTK 487

3 Hematopathology / ESR Determinants in the previous linear regression models and compared the estimated ESR based on this equation with the measured ESR in the remaining 30% of the cohort by using the paired t test. All of the analyses were considered significant at a 2-tailed P value of less than.05. The SPSS statistical package was used to perform all statistical evaluation (SPSS, Chicago, IL). Results We analyzed the data for 6,237 apparently healthy subjects (4,187 men and 2,050 women) at a mean (SD) age of 44 (11) years. The anthropometric values, blood pressure measurements, relevant laboratory values, inflammationsensitive biomarkers including the ESR, sports activity, and alcohol consumption in the 2 sexes are described in ztable 1z. We noted significant differences between sexes in all parameters. The respective cardiovascular risk factors and frequency of medication used in the 2 sexes are described in ztable 2z. To assess which variables explain best the variability in ESR, we performed linear regressions. In the first regression, we included data for all subjects together and included sex as a factor in the analysis and the interaction between sex and other parameters. The results (not shown) demonstrated that sex has an important effect on the ESR ztable 1z Baseline Population Characteristics by Sex * Men (n = 4,187) Women (n = 2,050) P Age (y) 43 (0.2) 45 (0.2) <.001 BMI (kg/m 2 ) 27 (0.1) 24 (0.1) <.001 Waist measurement (cm) 95 (0.1) 80 (0.2) <.001 Blood pressure (mm Hg) Systolic 124 (0.2) 115 (0.3) <.001 Diastolic 78 (0.1) 73 (0.2) <.001 Glucose (mg/dl) 93 (0.2) 88 (0.2) <.001 (mmol/l) 5.16 (0.01) 4.89 (0.01) Cholesterol LDL (mg/dl) 124 (0.5) 119 (0.7) <.001 (mmol/l) 3.21 (0.01) 3.08 (0.02) HDL (mg/dl) 51 (0.2) 66 (0.3) <.001 (mmol/l) 1.32 (0.01) 1.7 (0.01) Triglycerides (mg/dl) 130 (1.1) 93 (1.6) <.001 (mmol/l) 1.46 (0.01) 1.05 (0.02) Fibrinogen (mg/dl) 272 (0.8) 294 (1.1) <.001 (µmol/l) 7.99 (0.02) 8.64 (0.03) hs-crp (mg/l) 1.13 (1.0) 1.06 (1.0).003 (nmol/l) (9.52) (9.52) ESR (mm/h) 8.9 (0.1) 16.3 (0.1) <.001 Sports activity (h/wk) 2.5 (0.05) 2.1 (0.07) <.001 Alcohol consumption (glasses per wk) 1.4 (0.03) 0.6 (0.05) <.001 BMI, body mass index; ESR, erythrocyte sedimentation rate; HDL, high-density lipoprotein; hs-crp, high-sensitivity C-reactive protein; LDL, low-density lipoprotein. * Data are given as mean (SE). All means (besides age) are adjusted for age. ztable 2z Baseline Frequencies of Medication and Cardiovascular Risk Factors by Sex * Men (n = 4,187) Women (n = 2,050) P Hypertension 866 (20.7) 255 (12.4) <.001 Dyslipidemia 1,250 (29.9) 417 (20.3) <.001 Current smoker 690 (16.5) 407 (19.9) <.001 Past smoker 1,069 (25.5) 414 (20.2) Family history of CHD 601 (14.4) 380 (18.5) <.001 Aspirin 203 (4.8) 43 (2.1) <.001 β-blockers 123 (2.9) 55 (2.7).570 Calcium channel blockers 64 (1.5) 23 (1.1).198 ACE inhibitors 97 (2.3) 36 (1.8).150 ARBs 30 (0.7) 6 (0.3).038 Statins 282 (6.7) 120 (5.9).183 Fibrates 33 (0.8) 10 (0.5).178 Oral contraceptives 221 (10.8) Hormone replacement therapy 201 (9.8) ACE, angiotensin converting enzyme; ARB, angiotensin II receptor blocker; CHD, coronary heart disease. * Data are given as number (percentage). 488 Am J Clin Pathol 2008;129: by guest 488 DOI: /U04E2YFJRR6JQQTK

4 Hematopathology / Original Article with significant interaction between sex and most other variables that influenced the ESR (such as levels of fibrinogen, hemoglobin, globulins, and triglycerides). Owing to this finding and to simplify the results, we decided to analyze the sexes separately. ztable 3z gives the results of the linear regression performed for each sex separately. Fibrinogen, hemoglobin, and serum globulin levels are the most important variables that explain most of the variability in the results of ESR (R 2 = 0.34 and 0.44 for men and women, respectively), without significant differences between the sexes. Surprisingly, age did not enter the model for men and entered the model for women with very low partial correlation. To solve this discrepancy with previous studies that did not include fibrinogen levels in the analyses, we divided our cohort into 5 age groups of 10 years and calculated the mean ESR and fibrinogen concentration ztable 4z. As in previously published data, we found significant increases in ESR and fibrinogen with increasing age (P for linear trend <.001 for both variables in the 2 sexes), which was nonsignificant or marginally significant for ESR when we adjusted for fibrinogen differences (Table 4). Finally, to evaluate the magnitude of ESR prediction error, based on the 3 most important determinants we found, we reanalyzed the linear regression equation based on a randomly selected 70% of the cohort ztable 5z and calculated the estimated ESR for the remaining 30% of the cohort. The mean differences (95% confidence interval) between the measured and estimated ESR in this group were 0.18 ( 0.11 to 0.47; P =.22) and 0.37 ( 0.83 to 0.10; P =.13) for men and women, respectively. ztable 3z Linear Regression Results for Erythrocyte Sedimentation Rate in Men and Women Partial β P Correlation Men (R 2 = 0.34) Fibrinogen.053 < Hemoglobin < Globulins.344 < Triglycerides.008 < BMI Women (R 2 = 0.44) Fibrinogen.074 < Hemoglobin < Globulins.504 < LDL Waist Triglycerides Fibrate use Age Past smoker ztable 5z Concise Linear Regression Results for a Randomly Selected 70% of the Cohort Partial β P Correlation Men (R 2 = 0.33) Fibrinogen.055 < Hemoglobin < Globulins.377 < Women (R 2 = 0.41) Fibrinogen.081 < Hemoglobin < Globulins.545 < BMI, body mass index; LDL, low-density lipoprotein. ztable 4z Mean ESR, Fibrinogen Level, and Fibrinogen-Adjusted ESR According to 10-year Age Groups in Men and Women * Age Group ANOVA P for P Trend Men (n = 609) (n = 1,105) (n = 1,297) (n = 952) (n = 208) ESR 6.9 ( ) 8.4 ( ) 9.1 ( ) 9.6 ( ) 11.3 ( ) <.001 <.001 Fibrinogen 240 ( ) 260 ( ) 278 ( ) 287 ( ) 300 ( ) <.001 <.001 (mg/dl) ESR 8.5 ( ) 8.9 ( ) 8.7 ( ) 8.7 ( ) 9.8 ( ).038 Women (n = 215) (n = 396) (n = 736) (n = 610) (n = 73) ESR 13.6 ( ) 15.3 ( ) 16.5 ( ) 17.8 ( ) 18.0 ( ) <.001 <.001 Fibrinogen 269 ( ) 285 ( ) 296 ( ) 312 ( ) 303 ( ) <.001 <.001 (mg/dl) ESR 15.6 ( ) 16.1 ( ) 16.5 ( ) 16.6 ( ) 17.4 ( ).222 ANOVA, analysis of variance; ESR, erythrocyte sedimentation rate. * Fibrinogen levels are given in conventional units; to convert to Système International units (µmol/l), multiply by Parenthetical values represent the 95% confidence interval for the mean. Fibrinogen-adjusted estimated marginal mean of ESR. by guest Am J Clin Pathol 2008;129: DOI: /U04E2YFJRR6JQQTK 489

5 Hematopathology / ESR Determinants Discussion The present study is the first to document the determinants of ESR in a relatively large group of apparently healthy subjects and subjects with atherothrombotic risk factors in whom significant underlying acute phase response was excluded by using an hs-crp assay and a conservative cutoff level of 5 mg/l (47.62 nmol/l). Our main finding is that the determinants of ESR in these carefully selected subjects are similar to what has been shown in the past and include the levels of fibrinogen, hemoglobin, globulins, and triglycerides. 2,4-6 These findings are relevant for the use of ESR as a cheap and readily available screening tool for the presence of low-grade inflammation in apparently healthy people and people with atherothrombotic risk factors. This low-grade inflammation on the one hand and the ESR on the other have been shown to be of help in the process of singling out people at risk. In addition, the present study helps to define normal values for people who indeed have a relatively low inflammatory burden and atherothrombotic risk. Sex differences were significant for all population characteristics, including acute phase response proteins. Sex has an important role in defining normal values for the ESR. In our analysis, sex had significant statistical interactions with all of the major determinants of the ESR, demonstrating an additive effect on the ESR and on its components. Age did not correlate strongly with ESR. Previous large population studies 2,4,6 demonstrated an age-related increase in the normal values of ESR. This finding was also noted in our primary analysis. However, when we adjusted our results for the fibrinogen concentration, the main laboratory determinant of the ESR, we found that age had no consistent linearity with ESR. Furthermore, when we compared age groups, we first found an age-related difference and trend as noted in previous studies. However, when we again adjusted our results to the mean fibrinogen level in each age group, there was no difference in the ESR between groups. The fibrinogen effect on ESR is well described in the literature, 17,18 which makes it a variable that cannot be ignored in any study investigating the ESR. The limitation of the previous studies that did not consider fibrinogen levels as a possible confounder in their ESR analysis was also noted in the literature. 3,7 The finding that ESR might be age independent is further supported by the previous work of Feher and colleagues 19,20 on hemorheological parameters and aging. Feher and colleagues studied the differences in fibrinogen, hematocrit, RBC aggregation, and plasma and whole blood viscosity in 3 age groups (<45, 45-65, >60 years) in 6,236 cardiovascular and cerebrovascular patients and in a selected smaller group with matching parameters to exclude the effect of risk profile. In the whole population, the correlation of these hemorheological parameters and advancing age was inconsistent, and in the selected population, these parameters did not correlate with advancing age at all. Our results add to these data, suggesting that ESR as well is independent of aging and that increased values are probably associated with higher prevalence of diseases such as atherosclerosis. In that context, ESR may have a potential role in early detection of hyperfibrinogenemia and low-grade inflammation 21 and as a marker of the atherosclerotic burden in apparently healthy people. 22 We finally validated our results by constructing a linear equation 23 based on the main 3 contributors of ESR for each sex in a randomly selected 70% of the study population. When we applied this equation to data for the remaining 30% of the study population, we found no statistically significant difference between the measured and predicted ESR. Such an equation might be useful for an indirect measure of the fibrinogen level. The ESR is an easy-to-use and inexpensive method that can aid in early detection of microinflammation and eventual atherosclerotic burden. Its main determinants are sex and levels of fibrinogen, hemoglobin, globulins, and triglycerides. The ESR is not strongly related to age. From the Department of Internal Medicine D, Tel-Aviv Sourasky Medical Center and Sackler Faculty of Medicine, Tel- Aviv University, Tel-Aviv, Israel. Address reprint requests to Dr Rogowski: Internal Medicine D, Tel-Aviv Sourasky Medical Center, 6 Weizman St, Tel-Aviv, Israel. References 1. Andresdottir MB, Sigfusson N, Sigvaldason H, et al. Erythrocyte sedimentation rate, an independent predictor of coronary heart disease in men and women: the Reykjavik Study. Am J Epidemiol. 2003;158: Erikssen G, Liestol K, Bjornholt JV, et al. Erythrocyte sedimentation rate: a possible marker of atherosclerosis and a strong predictor of coronary heart disease mortality. Eur Heart J. 2000;21: Gillum RF, Mussolino ME, Makuc DM. Erythrocyte sedimentation rate and coronary heart disease: the NHANES I Epidemiologic Follow-up Study. J Clin Epidemiol. 1995;48: Bottiger L, Svedberg C. Normal erythrocyte sedimentation rate and age. Br Med J. 1967;2: Danesh J, Collins R, Peto R, et al. Haematocrit, viscosity, erythrocyte sedimentation rate: meta-analyses of prospective studies of coronary heart disease. Eur Heart J. 2000;21: Wetteland P, Roger M, Solberg HE, et al. Population-based erythrocyte sedimentation rates in 3910 subjectively healthy Norwegian adults: a statistical study based on men and women from the Oslo area. J Intern Med. 1996;240: Rapaport E. Erythrocyte sedimentation rate: is it a useful risk marker for coronary heart disease? Eur Heart J. 2000;21: Am J Clin Pathol 2008;129: by guest 490 DOI: /U04E2YFJRR6JQQTK

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