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Keywords:

  • cardiovascular risk factors;
  • C-reactive protein;
  • inflammation;
  • procalcitonin

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

Abstract.  Schiopu A, Hedblad B, Engström G, Struck J, Morgenthaler NG, Melander O (Lund University, Skåne University Hospital Malmö, Malmö, Sweden; BRAHMS GmbH/Thermo Fisher Scientific, Hennigsdorf, Germany). Plasma procalcitonin and the risk of cardiovascular events and death: a prospective population-based study. J Intern Med 2012; 272: 484–491.

Objectives:  A number of inflammatory biomarkers such as C-reactive protein (CRP) are independent predictors of cardiovascular risk. The inflammatory biomarker procalcitonin (PCT) has previously been shown to be associated with coronary atherosclerosis and the metabolic syndrome. We evaluated the ability of PCT to predict future cardiovascular events in a population of apparently healthy individuals.

Design:  We measured plasma PCT levels in 3713 subjects with no previous history of cardiovascular disease, randomly selected from the Malmö Diet and Cancer cohort. The correlation between PCT concentration and the incidence of coronary events, stroke and cardiovascular death over a median follow-up period of 13.7 years was studied using a Cox regression analysis corrected for age, sex, CRP level, traditional risk factors and renal function.

Results:  Age and sex were strong determinants of PCT; the concentration of PCT was significantly higher in men than in women. PCT was associated with several of the established cardiovascular risk factors (CRP, hypertension, diabetes and renal function) as determined by multivariate linear regression. Of note, PCT was inversely correlated with HDL and smoking. We found significant correlations between PCT levels, coronary events and cardiovascular death. However, these relationships lost statistical significance when the analysis was corrected for CRP and the traditional risk factors.

Conclusions:  This is the largest population-based prospective study to demonstrate a positive association between plasma PCT levels and cardiovascular risk in subjects with no previous history of acute cardiovascular events. However, the high degree of covariation between PCT and other cardiovascular risk factors limits the value of PCT as an independent cardiovascular risk predictor.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

Correct stratification of individuals at risk of developing acute cardiovascular events is fundamental for the initiation of efficient preventive therapies. Besides age and sex, currently used risk stratification models are based on individual assessment of smoking, hypertension, diabetes mellitus and dyslipidaemia [1]. Additionally, inflammatory biomarkers such as C-reactive protein (CRP) were shown to be valuable independent predictors of cardiovascular risk in healthy individuals and in patients with known coronary artery disease [2, 3]. However, it is now widely accepted that the current risk assessment protocols need to be improved, as a large number of events occur in individuals considered to belong to the low- and intermediate-risk groups [1].

Procalcitonin (PCT) is the pro-hormone of calcitonin, which is involved in calcium metabolism. Under nonpathological conditions, PCT is mainly produced in the neuroendocrine C cells of the thyroid gland and K cells of the lung [4]. Plasma PCT levels are very low in healthy individuals (<0.1 ng mL−1). Bacterial endotoxin is the strongest stimulus for PCT production, resulting in levels of up to 1000 ng mL−1 in the blood of patients with severe sepsis [5, 6].

Procalcitonin has previously been shown to be elevated in patients with advanced atherosclerosis [2]. Recent studies have demonstrated that human adipose tissue (in particular macrophage-activated adipocytes) is able to secrete PCT [7, 8] and that plasma PCT is associated with components of the metabolic syndrome such as obesity and insulin resistance [9]. These findings point to a possible role of PCT in cardiovascular disease. PCT levels were found to be increased in patients with acute coronary syndrome and to predict future cardiovascular mortality after myocardial infarction [10–13]. However, to our knowledge, the relationship between PCT and incident cardiovascular disease in the general population has not previously been examined.

The purpose of the present study was to assess the ability of PCT to predict cardiovascular morbidity and mortality in subjects with no previous history of cardiovascular disease. We investigated whether PCT can offer additional value in detecting individuals at increased risk of developing a first cardiovascular event, over and above the traditional risk factors for cardiovascular disease and CRP, an established marker of systemic inflammation.

Methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

Study design and population

The study population was part of the cardiovascular cohort of the Malmö Diet and Cancer (MDC) study. The MDC is a population-based prospective cohort of 28 449 individuals enrolled between 1991 and 1996. The cardiovascular arm of the MDC was specifically designed to study the epidemiology of carotid artery disease and consists of 6103 subjects selected randomly from the cohort. In the present study, we included 3713 individuals with no previous history of cardiovascular disease for whom complete data on cardiovascular risk factors (see Table 1) and plasma samples for PCT measurements were available. All participants provided written informed consent, and the study was approved by the ethical committee at Lund University, Sweden.

Table 1. Baseline characteristics of the study population
CharacteristicPopulationPCT quartiles
Q1Q2Q3Q4
  1. CRP, C-reactive protein; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; PCT, procalcitonin.

  2. SI conversion factors: to convert LDL-C and HDL-C values to mg dL−1 divide by 0.0259; to convert CRP values to nmol L−1, multiply by 9.524.

Number of participants37137979311097888
Age, mean (SD), year58 (6)55 (6)57 (6)58 (6)59 (6)
Men, no. (%)1511 (40.7)129 (16.2)304 (32.7)531 (48.4)547 (61.6)
Blood pressure, mean (SD), mm Hg
 Systolic142 (19)136 (18)139 (18)144 (19)146 (19)
 Diastolic87 (9)85 (9)86 (9)88 (9)89 (10)
Antihypertensive treatment, no. (%)597 (16.1)90 (11.3)134 (14.4)178 (16.2)195 (22.0)
Hypertension, no (%)2363 (63.6)424 (53.2)558 (59.9)729 (66.5)652 (73.4)
Lipids, mean (SD), mmol L−1
 LDL-C4.16 (1.00)4.00 (1.01)4.12 (0.97)4.27 (0.99)4.21 (0.96)
 HDL-C1.39 (0.37)1.54 (0.38)1.44 (0.35)1.35 (0.35)1.26 (0.33)
Body mass index, mean (SD), kg m−225.7 (3.9)24.6 (3.7)25.3 (3.8)25.9 (3.7)26.9 (4.2)
Diabetes mellitus, no. (%)298 (8)35 (4.4)35 (3.8)98 (8.9)130 (14.6)
Current smoking, no. (%)989 (26.6)217 (27.2)270 (29.0)294 (26.8)208 (23.4)
Cystatin C, mean (SD), mg L−10.77 (0.15)0.71 (0.11)0.75 (0.12)0.79 (0.13)0.83 (0.19)
CRP, median (IQR), mg L−11.30 (0.60–2.80)0.90 (0.50–2.00)1.10 (0.60–2.40)1.30 (0.70–2.65)2.00 (0.90–4.10)
PCT, median (IQR), ng mL−10.016 (0.013–0.020)0.011 (0.010–0.012)0.014 (0.013–0.015)0.018 (0.017–0.019)0.025 (0.022–0.030)
 Males0.018 (0.015–0.023)0.011 (0.010–0.012)0.014 (0.013–0.015)0.018 (0.017–0.019)0.025 (0.022–0.031)
 Females0.014 (0.012–0.018)0.011 (0.010–0.012)0.014 (0.013–0.015)0.017 (0.016–0.019)0.024 (0.022–0.029)

Data collection

All participants provided a medical history and underwent a physical examination. Cigarette smoking was defined as any smoking within the past year and was assessed by a self-administered questionnaire. Blood pressure was measured with a mercury-column sphygmomanometer after resting for 10 min in the supine position. Hypertension was defined as systolic blood pressure (SBP) above 140 mmHg and diastolic blood pressure as above 90 mmHg or use of antihypertensive medication. Diabetes mellitus was defined as a fasting whole-blood glucose level >6.0 mmol L−1, a self-reported physician diagnosis of diabetes or use of antidiabetic medication. Plasma lipids (total cholesterol, HDL cholesterol and triglycerides) were measured by standard procedures at the Department of Clinical Chemistry, Skane University Hospital. LDL cholesterol was calculated using the Friedewald formula. CRP concentration was determined using a high-sensitivity assay (Tina-Quant CRP, Roche Diagnostics, Basel, Switzerland). Cystatin C was used as a surrogate marker of renal function independent of muscle mass and was measured using a particle-enhanced immunonephelometric assay (N Latex Cystatin C; Dade Behring, Deerfield, IL, USA). Serum PCT concentration was determined by an ultrasensitive immunofluorescence assay (PCT sensitive LIA; BRAHMS GmbH, Hennigsdorf, Germany). The lower detection limit of the assay is 0.006 ng mL−1, and the functional assay sensitivity (the lowest value with an inter-assay coefficient of variation below 20%) is 0.007 ng mL−1 [14, 15].

Study end-points

We studied four different outcomes: coronary events, stroke, cardiovascular events and cardiovascular death. The procedure for ascertaining outcome events has been described previously [16, 17]. Coronary events were defined as fatal or nonfatal myocardial infarction or death owing to ischaemic heart disease. Cardiovascular events were defined as coronary events or fatal or nonfatal stroke. Events were identified through linkage of the 10-digit personal identification number of each Swedish citizen with three registries: the Swedish Hospital Discharge Register, the Swedish Cause of Death Register and the Stroke in Malmö register. Myocardial infarction was defined on the basis of the International Classification of Diseases 9th and 10th revisions (ICD9 and ICD10) codes 410 and I21, respectively. Death owing to ischaemic heart disease was defined on the basis of codes 412 and 414 (ICD9) or I22, I23 and I25 (ICD10). Fatal or nonfatal stroke was defined using codes 430, 431, 434 and 436 (ICD9) and I60, I61, I63 and I64 (ICD10). Cardiovascular death was defined using codes 390–459 (IDC9) and I codes (ICD10) as main cause of death in the cause of death registry. Classification of outcomes using these registries has previously been validated [18], and the sensitivity of the registry for detecting events such as myocardial infarction has been shown to exceed 90% [19]. Follow-up for outcomes continued until 1 January 2008.

Statistical analysis

SPSS software (version 19; SPSS Inc, Chicago, IL, USA) was used for all statistical calculations. The degree of covariation between baseline PCT concentration and other cardiovascular risk factors was studied in a multivariate linear regression analysis including all the factors shown in Table 2. The values for PCT and CRP were logarithmically transformed before being included in the analysis as continuous variables. We performed multivariate Cox regression (time to event) analysis to assess whether increasing quartiles of PCT were related to increased risk of developing acute cardiovascular events or cardiovascular death. We used three different models adjusted for (i) age and sex (Model A); (ii) age, sex and CRP (Model B); and (iii) age, sex, CRP and conventional cardiovascular risk factors (blood pressure, antihypertensive treatment, body mass index, HDL, LDL, diabetes mellitus and smoking) together with cystatin C as a marker of renal function (Model C). Data were expressed as hazard ratio (HR) and 95% confidence interval (CI). A two-sided value of < 0.05 was considered statistically significant. Further, we tested for interactions between PCT and the other risk factors included in the Cox regression analysis (Model C). Subsequent subgroup analyses were performed for the risk factors that significantly influenced the relationship between PCT level and cardiovascular outcomes.

Table 2. Multivariate linear regression analysis including PCT as the dependent variable and the traditional risk factors, CRP and cystatin C as independent variables
Risk factorsBeta coefficient ± SEa95% CI for the beta coefficient P
  1. PCT, procalcitonin; CRP, C-reactive protein; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; SE, standard error; CI, confidence interval.

  2. aMutually controlled for age, sex and all the factors included in the analysis. The values for PCT and CRP were logarithmically transformed before being included in the analysis, owing to skewness. The beta coefficient for the continuous variables is expressed per one standard deviation.

Age (per 10 years)0.060 ± 0.0100.040 to 0.080<0.001
Male sex0.199 ± 0.0130.224 to 0.173<0.001
Blood pressure
 Systolic0.032 ± 0.0090.014 to 0.049<0.001
 Diastolic−0.018 ± 0.008−0.035 to −0.0020.03
Antihypertensive treatment0.005 ± 0.017−0.028 to 0.0380.70
Body mass index0.011 ± 0.007−0.002 to 0.0240.10
Lipids
 LDL-C0.007 ± 0.006−0.005 to 0.0180.24
 HDL-C−0.030 ± 0.007−0.043 to −0.017<0.001
Diabetes mellitus0.071 ± 0.0220.028 to 0.1150.001
Current smoking−0.050 ± 0.013−0.076 to −0.023<0.001
CRP0.064 ± 0.0060.052 to 0.077<0.001
Cystatin C0.075 ± 0.0060.063 to 0.087<0.001

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

Characteristics of the study group

Of the 6103 individuals included in the cardiovascular arm of the MDC cohort, 147 subjects were excluded from the present study because of a history of cardiovascular disease (myocardial infarction or stroke) prior to enrolment. Complete data on cardiovascular risk factors (see Table 1) as well as overnight fasting plasma samples for measurement of levels of PCT, CRP, cystatin C and plasma lipids were available for 3713 of the remaining subjects. None of the participants had clinical signs of infection upon enrolment. The mean age of the participants was 58 years and 40% were men (Table 1). At the time of the inclusion, 8% had diabetes, 63.6% had hypertension and 27% were active smokers. During a median follow-up of 13.7 years (interquartile range, 13.1–14.3), 198 subjects suffered a first coronary event, 162 were diagnosed with a first stroke and a first cardiovascular event occurred in 340 subjects. There were 374 deaths during follow-up; 95 (25%) of these were due to cardiovascular disease.

PCT in relation to established risk factors for cardiovascular disease

Baseline PCT levels were significantly correlated with most of the established cardiovascular risk factors as well as with CRP and cystatin C as assessed by a multivariate linear regression analysis including PCT as the dependent variable and the other factors as independent variables (Table 2). PCT was strongly associated with age and sex; men had significantly higher PCT levels than women (Tables 1 and 2; < 0.001). By contrast, CRP levels did not differ between male and female subjects (= 0.80). Amongst the cardiovascular risk factors included in the analysis, CRP and cystatin C were the strongest independent determinants of PCT variability (Table 2). The presence of diabetes mellitus and increased SBP were also associated with higher PCT levels. Of note, we found a significant negative correlation between PCT and HDL as well as between PCT and smoking (Table 2).

PCT and cardiovascular risk

The study participants were categorized according to quartiles of plasma PCT concentration. The baseline characteristics of the study population according to PCT quartile are presented in Table 1. In a Cox regression model adjusted for age and sex (Table 3, Model A), plasma PCT levels were positively associated with the risk of developing an acute cardiovascular event, although the significance levels were modest. This association was almost exclusively related to coronary events, with no significant relationship with stroke. The risk of cardiovascular death was higher with increasing PCT quartiles; subjects with baseline PCT values within the fourth quartile had a 2-fold increased risk of cardiovascular death compared with the lowest quartile (Table 3, Model A). However, after additional adjustment for CRP (Table 3, Model B), the association between PCT level and cardiovascular disease and death lost significance, suggesting that variations in CRP concentration account to a large extent for the trend observed in Model A. In a multivariate analysis including CRP, conventional risk factors (blood pressure, antihypertensive treatment, body mass index, LDL cholesterol, HDL cholesterol, diabetes mellitus and smoking) and renal function (cystatin C), the level of PCT was not related to any of the considered outcomes (Table 3, Model C). However, CRP independently predicted the incidence of coronary events [HR (95% CI) per SD of CRP: 1.19 (1.02–1.38); < 0.05, data not shown] and cardiovascular death [HR (95% CI) per SD of CRP: 1.14 (1.02–1.28); < 0.05, data not shown).

Table 3. PCT and cardiovascular disease
EventPCT quartile (Q) Hazard ratio (95% CI)Linear trend P
Q2 vs. Q1Q3 vs. Q1Q4 vs. Q1Hazard ratio (95% CI) 
  1. PCT, procalcitonin; CV, cardiovascular; CRP, C-reactive protein.

  2. Number of subjects by PCT quartile: Q1 – 797; Q2 – 931; Q3 – 1097; Q4 – 888.

  3. aModel A: adjusted for age and sex.

  4. bModel B: adjusted for age, sex and CRP.

  5. cModel C: adjusted for age, sex, CRP, systolic and diastolic blood pressure, antihypertensive treatment, body mass index, LDL cholesterol, HDL cholesterol, diabetes mellitus at baseline, smoking and cystatin C.

CV events
 Aa1.57 (1.08–2.29)1.33 (0.91–1.93)1.67 (1.14–2.45)1.12 (1.00–1.25)0.04
 Bb1.52 (1.04–2.21)1.23 (0.85–1.80)1.39 (0.94–2.05)1.05 (0.94–1.18)0.36
 Cc1.45 (1.00–2.13)1.04 (0.71–1.51)1.14 (0.77–1.69)0.98 (0.87–1.1)0.75
Coronary events
 A1.44 (0.86–2.40)1.39 (0.84–2.29)1.71 (1.03–2.84)1.15 (0.97–1.34)0.05
 B1.38 (0.83–2.31)1.28 (0.78–2.12)1.40 (0.83–2.33)1.07 (0.93–1.25)0.34
 C1.34 (0.80–2.25)1.10 (0.66–1.82)1.18 (0.70–2.00)1.01 (0.87–1.18)0.88
Stroke     
 A1.72 (1.02–2.92)1.24 (0.72–2.12)1.43 (0.83–2.49)1.04 (0.88–1.22)0.62
 B1.66 (0.98–2.81)1.16 (0.68–1.99)1.22 (0.70–2.14)0.99 (0.84–1.16)0.86
 C1.61 (0.95–2.74)1.00 (0.58–1.71)1.03 (0.58–1.82)0.93 (0.79–1.09)0.37
CV mortality
 A1.39 (0.65–2.99)1.14 (0.54–2.42)2.07 (1.00–4.29)1.25 (1.01–1.56)0.04
 B1.30 (0.61–2.80)1.02 (0.48–2.17)1.57 (0.75–3.29)1.13 (0.91–1.41)0.26
 C1.29 (0.60–2.79)0.85 (0.40–1.82)1.31 (0.61–2.79)1.05 (0.84–1.33)0.64

We found significant interactions between PCT and diabetes mellitus with regard to the risk of coronary events (= 0.018) and cardiovascular death (P = 0.019) as well as between PCT and age with regard to cardiovascular death (= 0.022) in the multivariate Cox regression analysis adjusted for all the considered risk factors (Model C). Subsequent analysis showed a negative correlation between PCT and coronary events in diabetic subjects (= 0.018) and a positive correlation between PCT and cardiovascular death in study participants younger than the median age of the group (= 0.006). However, these interactions are difficult to interpret owing to the low number of coronary events amongst individuals with diabetes (= 36) and of cardiovascular deaths amongst young subjects (= 19).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

In recent years, inflammatory markers such as high-sensitivity CRP have gained importance as independent predictors of cardiovascular events over and above the traditional cardiovascular risk factors [20, 21]. The purpose of the present study was to investigate the ability of PCT, an inflammatory biomarker previously associated with coronary atherosclerosis and the metabolic syndrome [2, 9], to predict first acute cardiovascular events in the general population. An additional aim was to evaluate the relationship between PCT and the already established cardiovascular risk factors. We measured the levels of plasma PCT using an ultrasensitive assay in a large population-based cohort with no previous history of cardiovascular disease and evaluated the ability of this biomarker to predict coronary events, stroke and cardiovascular death over a median follow-up period of 13.7 years. PCT was strongly correlated with CRP and several of the traditional risk factors. We found significant associations between PCT level and the incidence of coronary events and cardiovascular death. However, PCT did not independently provide additional information for risk stratification of individuals with regard to cardiovascular morbidity and mortality.

The levels of plasma PCT in our population were similar to those found by Abassi et al. [9]. To our knowledge, their study and ours are the only two reported investigations to date of PCT levels in the general population under physiological conditions. Plasma PCT levels increased with age and were significantly higher in men. This gender difference does not seem to be indicative of a higher level of systemic inflammation in men, as we found no differences with regard to CRP distribution between male and female subjects in the present cohort. CRP was one of the strongest independent determinants of PCT variation amongst the cardiovascular risk factors considered, suggesting a partial overlap between CRP and PCT in characterizing a similar underlying systemic inflammatory activity in apparently healthy individuals free from infection. Plasma PCT concentration was also strongly correlated with renal function, as assessed by cystatin C. This is in line with previous studies showing that PCT elimination in urine is significantly reduced in patients with impaired renal function [22].

The role of HDL as an anti-inflammatory mediator in addition to its involvement in reverse cholesterol transfer is well established [23]. We found an inverse correlation between the levels of PCT and HDL in this study population, suggesting an inhibitory role of HDL on the inflammatory processes that stimulate PCT production. PCT was also positively correlated with the presence of diabetes mellitus and with SBP. Diabetes mellitus is associated with increased systemic inflammatory activation, which seems to stimulate PCT production. The finding of a relationship between PCT and SBP extends our previously published results showing significant correlations between a panel of inflammation-sensitive plasma proteins (not including PCT or CRP) and SBP [24]. It is interesting that despite the previously demonstrated pro-inflammatory effects of cigarette smoking [25], plasma PCT concentration was lower in smokers compared with nonsmokers in the present study group. It is possible that PCT does not reflect the particular type of inflammation associated with smoking. Nevertheless, it is difficult to predict which mechanisms might link PCT and smoking, as the metabolism of PCT has not yet been fully elucidated.

In a Cox regression analysis corrected for age and sex, baseline PCT levels were significantly correlated with the risk of acute coronary events and cardiovascular death. We found no correlation between PCT levels and stroke, which is in line with previously published data [26]. Although coronary heart disease and stroke share a similar set of risk factors, the relative importance of these factors differs between the two conditions [27, 28]. When the analysis was corrected for the already established cardiovascular risk factors, the relationship between PCT concentration and cardiovascular disease lost statistical significance. This was mainly owing to the high levels of covariation between PCT and the other factors, particularly CRP. By contrast, consistent with our previous findings [3], CRP remained independently associated with the incidence of cardiovascular events. These data suggest that, whilst PCT and CRP define to a certain extent similar pathways of underlying inflammation, CRP may reflect the activation of additional inflammatory mechanisms that do not influence the levels of PCT and that play more important roles in cardiovascular disease. The strongest stimulus for PCT production is bacterial endotoxin, whereas the synthesis of CRP in the liver is governed by the inflammatory cytokine interleukin (IL)-6. Although IL-6 was shown to be independently associated with coronary atherosclerosis [29], previous data indicate that PCT might be related preferentially to peripheral artery disease [2]. In a cohort of patients with cardiovascular disease, PCT levels were found to be elevated in subjects with acute coronary syndrome, compared with those with stable angina, and predicted subsequent cardiovascular mortality [13]. However, PCT did not provide additional prognostic information compared with CRP [13].

The present study has several limitations that should be taken into account. Blood pressure and plasma glucose levels were only measured once upon initial enrolment of subjects into the study. However, as at least two separate measurements are required for the correct diagnosis of hypertension and diabetes, we cannot exclude the possibility of a certain degree of misclassification of these conditions in this population. Our definition of stroke includes both ischaemic and haemorrhagic events that may be related to a heterogeneous underlying pathology, including but not restricted to atherosclerotic vascular disease, intra-cerebral aneurysms or atrial fibrillation. As these conditions may have different relationships with PCT as a marker of systemic inflammation, the association between PCT and stroke should be interpreted with caution. All individuals included in the present study were free of clinical signs of infection. However, the presence of subclinical infections and inflammatory conditions at the time of enrolment that could stimulate PCT production cannot be excluded with certainty.

In conclusion, this is the first large prospective study to assess the ability of PCT to predict the incidence of first cardiovascular events in a population without a previous history of cardiovascular disease. We found that PCT levels increase with age, are significantly higher in men than in women and correlate well with the level of CRP, renal function, SBP and the presence of diabetes mellitus. We have demonstrated that individuals with PCT values in the highest quartile have a significantly increased risk of coronary events and death owing to cardiovascular disease. However, the high degree of covariation between PCT and the other risk factors included in the analysis, particularly CRP, restricts the value of PCT as an independent predictor of acute cardiovascular events in the general population.

Conflicts of interest

  1. Top of page
  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References

Prof Gunnar Engström is employed as a senior epidemiologist by AstraZeneca R&D, Sweden. Dr. Joachim Struck and Dr. Nils G. Morgenthaler are employed by BRAHMS GmbH/Thermo Fisher Scientific, Germany.

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  2. Abstract
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Conflicts of interest
  8. References
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