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NDT Advance Access originally published online on March 30, 2006
Nephrology Dialysis Transplantation 2006 21(7):1809-1815; doi:10.1093/ndt/gfl117
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© The Author [2006]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org


Original Articles: Clinical Nephrology

Coeliac disease and risk of renal disease—a general population cohort study

Jonas F. Ludvigsson1,3, Scott M. Montgomery2,3, Ola Olén3,4, Anders Ekbom3,5, Johnny Ludvigsson6 and Michael Fored3

1 Department of Paediatrics, 2 Clinical Research Centre, Örebro University Hospital, 3 Clinical Epidemiology Unit, Department of Medicine, Karolinska University Hospital/Institute and4 Department of Paediatrics, Stockholm Söder Hospital, Sweden, 5 Harvard Medical School, Boston, Massachusetts, USA and 6 Division of Paediatrics and Diabetes Mellitus Research Centre, Department of Molecular and Clinical Medicine, Faculty of Health Sciences, Linköping University, Sweden

Correspondence and offprint requests to: Jonas F Ludvigsson, Department of Paediatrics, Örebro University Hospital, Sweden. Email: jonasludvigsson{at}yahoo.com



   Abstract
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 
Background. Coeliac disease (CD) may be a risk factor for renal disease.

Methods. We investigated the risk of any form of glomerulonephritis (GN) (acute, chronic and non-specified), chronic glomerulonephritis (CGN) and renal replacement therapy including dialysis treatment and kidney transplantation (KT) in patients with CD in a general population-based cohort study. We used Cox regression to assess the risk of renal disease in 14 336 patients who had received a diagnosis of CD (1964–2003) and 69 875 reference individuals matched for age, calendar year, sex and county. Patients were identified using the Swedish Hospital Discharge Registry. Follow-up began 1 year after study entry.

Results. CD was associated with an increased risk of any form of GN (hazard ratio (HR) = 1.64; 95% confidence intervals (CI) = 1.01–2.66; P = 0.046; 89 events), CGN (HR = 2.65; 95% CI = 1.34–5.24; P = 0.005; 39 events), dialysis (HR = 3.48; 95% CI = 2.26–5.37; P<0.001; 102 positive events) and KT (HR = 3.15; 95% CI = 1.29–7.71; P = 0.012; 22 events).

Conclusion. We suggest that immune characteristics associated with CD increase the risk of chronic renal disease. Individuals with CD may also be at a moderately increased risk of any form of GN.

Keywords: auto-immune; coeliac; cohort study; diabetes mellitus; kidney; renal disease



   Introduction
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 
Coeliac disease (CD) affects up to 1% of the population in the Western world [1–3]. CD mostly occurs in individuals with human leucocyte antigen (HLA) DR3, DQ2 and results in a characteristic T-cell-mediated inflammation in the small bowel [4]. It is associated with a large number of autoimmune diseases [5]; among them type 1 diabetes mellitus (DM) [6]. A gluten-free diet in patients with both CD and type 1 DM is not only associated with an improvement in gastrointestinal symptoms but sometimes also with lower levels of haemoglobin (Hb)A1c [7].

The incidence of end-stage renal disease with a need for renal replacement therapy such as dialysis or kidney transplantation (KT) is increasing internationally [8]. The underlying cause of this increase is largely unknown [8].

In 2002, Collin et al. [9] showed an increased prevalence of CD in patients with IgA nephropathy. Patients with primary glomerulonephritis (GN) often have an activated mucosal immune system [10] with increased numbers of intra-epithelial T-cells in the mucosa [11] and increased gut permeability [11]. Several studies have demonstrated increased levels of CD auto-antibodies in patients with renal disease [12,13]; and certain renal disease will improve on a low-antigenic diet lacking in gluten [14]. Little is known, however, about the risk of severe renal disease such as renal failure in individuals with CD.

In this study, we used data from a general population-based register, the Swedish Hospital Discharge Registry, to study the risk of renal disease in individuals with CD. We examined associations of CD with GN, chronic glomerulonephritis (CGN) and renal failure assessed by the occurrence of renal dialysis or KT.



   Materials and methods
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 
Individuals with a hospital-based discharge diagnosis of CD between 1964–2003 were identified through the Swedish Hospital Discharge Registry (HDR). The HDR was initially established in some regions of Sweden in 1964, and since 1987 it has covered all of Sweden. It contains individual data and is maintained by the Swedish National Board of Health and Welfare.

The HDR was also used to identify individuals with GN, CGN, renal dialysis treatment, KT or type 1 or type 2 DM in study participants.

For each individual in the CD-patient cohort, Statistics Sweden (the government agency for population statistics), identified up to five reference individuals (matched for age, calendar year, sex and county) through the Swedish total population registry. Where more reference individuals were available, five were chosen at random. The total population registry [15] includes information on area of residence, vital status and dates of immigration or emigration.

All the individuals in the HDR and the population registry are identified through their personal identity number. The personal identity number is a unique number assigned to over 99.9% of all Swedish residents at birth or immigration [16].

Definition of CD, renal disease and DM
Every person who had been hospitalized from 1964–2003 under any of the following International Classification of Disease (ICD) codes was defined as having CD: ICD-7: 286.00; ICD-8: 269.00, 269.98; ICD-9: 579A; ICD-10: K90.0.

We defined any form of GN, which in Sweden includes IgA nephropathy, as follows (ICD codes signifying chronic GN have been italicized): ICD-7: 590, 592, 593.00; ICD-8: 580, 582; ICD-9: 580, 582; ICD-10: N00, N01, N03, N05.

Dialysis was defined according to the following surgical codes: 9200, 9206, 9207, 9211, 9212, 9213, 9214, 9223 or any of the following ICD codes: ICD-9: V45B, V56; ICD-10: Z49.1, Z49.2, Z99.2. Temporary dialysis (e.g. during cardiopulmonary surgery) was not used in the definition of dialysis in this study.

We defined KT according to the following surgical codes: 6070, KAS00, KAS10 and KAS20.

Finally, we defined DM as follows: ICD-7: 260; ICD-8: 250; ICD-9: 250; ICD-10: E10-E14. The HDR does not allow any distinction between type 1 or type 2 DM.

Inclusion criteria
The Swedish National Board of Health and Welfare identified 15 533 individuals with CD diagnosed before the end of follow-up. We excluded individuals with a shorter follow-up than 1 year in order to minimize the risk of detection bias. We also excluded individuals with any of the four renal outcome measures occurring before study entry or less than 1 year after study entry (n = 1103). Hence, both the CD-patient cohort and the reference cohort consisted of individuals without renal disease at the start of follow-up. Another 94 individuals with CD were excluded due to data irregularities, such as date of death preceding that of the first recorded CD diagnosis. The analyses of the current study were therefore based on 14 336 individuals with CD and 69 875 reference individuals who had never had a diagnosis of CD. Their characteristics are given in Table 1. It is important to note, that an individual free of renal disease at, for example, 15 years of age and entering the study at that time may later have had diagnoses of all four renal disorders studied in this article, e.g. GN (aged 25 years with a follow-up of 10 years), CGN (aged 27 years; follow-up P = 12 years), dialysis (aged 35; follow-up P = 20 years) and KT (aged 42 years; follow-up P = 27 years).


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Table 1. Characteristics of participants (n (%))a

 
Socio-economic status
In a subset of individuals (n = 45 367), we were able to obtain data on socio-economic status (SES) from Statistics Sweden (Table 1). The SES was based on a three-category occupational classification from 1968 [17]. Among individuals with data on SES, some 6500 children born after 1990 were assigned a socio-economic code on the basis of the occupation of the mother.

Statistical methods and analyses
We used Cox regression to calculate hazard ratios (HRs) for renal disease in individuals with CD.

Follow-up time began 1 year after study entry and ended on the date of first discharge diagnosis of renal disease, date of emigration, death or the end of the study period (31 December 2003), whichever happened first. The Cox model was internally stratified. This means that the analysis was divided by risk-set and then a summarized risk estimate was produced. Each risk-set consisted of one individual with CD and his/her age- and sex-matched reference individuals. All individuals in one risk-set originated from the same county and entered the study in the same calendar year.

In sub-analyses, we stratified for sex and age at study entry (≤15 vs ≥16 years). In order to test the statistical significance of seemingly different HRs for renal dialysis in males and females, we carried out an additional regression analysis with regards to renal dialysis in which we included CD and sex but also a multiplicative term (interaction term) consisting of sex and CD.

In separate analyses, we adjusted for DM and excluded individuals with a diagnosis of DM. We tested one model in which DM was dichotomized (no DM vs DM) and a second model in which individuals with DM diagnosed at an age of ≤30 years were assumed to have predominantly type 1 DM and those with a later diagnosis were assumed to have a higher proportion of type 2 DM. Both models yielded the same risk estimates for the association of renal disease with CD. In this article, we have consistently presented the data from the statistical model where DM was coded as a dichotomous variable, not taking age into consideration at the first recorded diagnosis of DM.

In order to increase the specificity of GN, CGN and dialysis treatment, we calculated the risk of having at least two hospital discharge diagnoses of these outcome measures (e.g. a diagnosis of CGN during hospitalization both in 1987 and in 1989). The occurrence of repeated diagnoses minimizes the risk of findings being based on misclassifications of outcome measures. We also calculated the risk of having received a hospital discharge diagnosis of GN, CGN or dialysis in a department of renal disease, internal medicine or paediatrics in order to increase the specificity of renal disease. Misclassification is less likely in departments where a majority of individuals with renal disorders are cared for. We did not carry out the corresponding analyses for KT as this procedure only takes place in specialized settings.

We also tested the relationship between CD and renal disease including events in the first year after study entry.

In a separate analysis, we included the ICD-10 code N02 (recurrent or persistent haematuria) when calculating the risk of any GNF. Earlier ICD versions do not distinguish between recurrent/persistent haematuria and other haematuria.

The 95% confidence intervals (CI) for HRs not including 1.00 were considered statistically significant.

Statistics were calculated using SPSS 11.0 (2002. Chicago, Illinois).

Ethics
This study was approved by the Research Ethics Committee of the Karolinska Institute. None of the participants were contacted. Patient information was anonymized prior to the analyses.

Results
The median age at study entry (corresponds to date of CD diagnosis in individuals with CD) was 3 years (range: 0–94).

The median age at first recorded diagnosis of GN in individuals with CD was 28 years (range: 4–86). Corresponding age at diagnosis of CGN was 47.5 years (4–86); dialysis = 61.5 (28–87) and KT = 34 (25–58). The median duration between diagnosis of CD and first recorded diagnosis of GN was 6 years (range: 1–22)(CGN = 4 (1–22); dialysis = 6.5 (1–27) and KT = 12 (4–25)).

Any form of glomerulonephritis
A diagnosis of GN was more often recorded among patients with CD than among reference individuals and this association was statistically significant (Table 2). This risk increase was only seen in CD diagnosed in adulthood (HR = 2.62; 95% CI = 1.24–5.52; P = 0.011), with the risk estimate in children not attaining statistical significance (HR = 1.20; 95% CI = 0.62–2.32; P = 0.585). There was no notable difference between the risk estimates in males and females (data not shown).


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Table 2. CD and risk of later renal disease

 
In the subset of individuals with data on SES, the crude HR for the association of CD with GN was 1.74 (95% CI = 0.91–3.32; P = 0.095) and the adjusted HR was 1.62 (95% CI = 0.84–3.12; P = 0.151). The risk estimate for any form of GN did not change when individuals with a diagnosis of DM were excluded (Table 2) or when our outcome measure was restricted to at least two discharge diagnoses of GN (HR = 1.81; 95% CI = 0.80–4.09; P = 0.154) (based on nine positive events in 14 336 individuals with CD and 22 positive events in 69 875 reference individuals). The risk estimate for having received a diagnosis of GN in departments of paediatrics, internal medicine or renal medicine was 1.53 (95% CI = 0.85–2.73; P = 0.155). The risk estimate for GN was similar when we included the first year after study entry in the follow-up time (HR = 1.69; 95% CI = 1.07–2.66; P = 0.025).

When we included the ICD-10 code N02 (recurrent or persistent haematuria) among outcome measures the HR did not attain statistical significance [HR of 1.48 (95% CI = 0.89–2.55; P = 0.130)].

Chronic glomerulonephritis
CD was associated with a more than 2-fold increased risk of CGN; this association was statistically significant (Table 2). This risk increase was most pronounced in individuals with CD diagnosed in adulthood (HR = 3.96; 95% CI = 1.52–10.30; P = 0.005) than those with CD diagnosed in childhood (HR = 1.76; 95% CI = 0.64–4.90; P = 0.276). There was no notable difference between the risk estimates in males and females (data not shown).

In a subset of individuals with socio-economic data, adjustment for SES did not affect the risk estimate (crude HR = 2.93; 95% CI = 1.04–8.30; P = 0.043) (adjusted HR = 2.77; 95% CI = 0.93–8.23; P = 0.067); the reduction in statistical significance compared with the main analysis is due in part to the smaller number of individuals with SES data available for analysis. The risk estimates for CGN remained statistically significant also when we excluded individuals with DM (Table 2); restricted our outcome measure to at least two discharge diagnoses (HR = 2.74; 95% CI = 1.08–6.96; P = 0.035) or restricted our outcome measure to patients diagnosed in departments of paediatrics, internal medicine or renal medicine (HR = 2.48; 95% CI = 1.15–5.34; P = 0.021). Inclusion of the first year after study entry, did not affect the risk estimate for CGN (HR = 2.71; 95% CI = 1.46–5.02; P = 0.001).

Dialysis
CD was associated with a statistically significant 3-fold increased risk of dialysis (Table 2). Due to lack of positive events in individuals with CD diagnosed in childhood we were not able to calculate a meaningful risk estimate in this age group (HR = 0.00; 95% CI = 0 to above 100). In individuals with CD diagnosed in adulthood, the risk estimate was close to four (HR = 3.71; 95% CI = 2.40–5.76; P<0.001). The HR for subsequent dialysis in females with CD was 5.40 compared with 2.43 in males. A formal interaction test found that this difference (between the sexes) was not statistically significant (P = 0.156).

In a subset of individuals with socio-economic data, adjustment for SES had only a marginal effect on the risk estimate (crude HR = 4.39; 95% CI = 2.48–7.77; P<0.001) (adjusted HR = 4.19; 95% CI = 2.35–7.48; P<0.001). The CD remained statistically, significantly associated with dialysis after adjustment for DM or exclusion of individuals who had ever had a diagnosis of DM (Table 2). There was also a risk increase also when we restricted our outcome measure to at least two discharge diagnoses of dialysis (HR = 3.97; 95% CI = 2.26–6.96; P<0.001) (24 and 34 positive events), or to a diagnosis of dialysis in the departments of paediatrics, internal medicine or renal medicine (HR = 3.42; 95% CI = 2.18–5.35; P<0.001). Including the first year after study entry, the HR for dialysis was 3.56 (95% CI = 2.41–5.27; P<0.001).

Kidney transplantation
KT was more common in individuals with CD than among reference individuals (Table 2). The risk increase for KT was restricted to individuals diagnosed with CD in adulthood (HR = 5.45; 95% CI = 1.83–16.24; P = 0.002) (CD diagnosed in childhood: HR = 0.80; 95% CI = 0.10–6.70; P = 0.841). There was no notable difference between the risk estimates in males and females (data not shown).

Adjustment for SES in a subset of individuals with data on SES did not affect our risk estimates (crude HR = 7.73; 95% CI = 2.26–26.50; P = 0.001) (adjusted HR = 8.67; 95% CI = 2.77–27.10; P<0.001). Excluding individuals with DM before the end of follow-up, the HR for KT was 1.71 and failed to reach statistical significance (Table 2). Including the first year after study entry in the follow-up time, the risk of KT increased slightly (HR = 3.84; 95% CI = 1.79–8.20; P = 0.001).

The underlying diagnoses of patients with dialysis or KT are given in Table 3.


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Table 3. Medical diagnoses of individuals with CD and renal replacement therapy

 


   Discussion
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 
The current study showed an association between CD and GN, CGN and dialysis. The CD was also associated with KT, although, unlike for the other diseases, the risk increase was not statistically significant when a diagnosis of DM was taken into account.

Most previous reports on renal disease and CD have concerned nephritis and IgA nephropathy [9,12,13,18–20] although other renal or urinary diseases [21–25] may also be increased in individuals with CD. Collin et al. [9] reported a CD prevalence of 3–4% among patients with IgA nephropathy; Fornasieri et al. [18] found evidence of CD in 2/121 patients with IgA nephropathy. In contrast, the purpose of our cohort study was to look at the risk of renal disease in individuals with CD and we cannot therefore estimate the risk of CD in patients with renal disease. Our study results are in line with those of Peters et al. [24]. That study did, however, focus on mortality in individuals with CD and was based on death certificates and not incident disease. Peters et al. [24] reported increased standardized mortality rates (SMR) for urinary diseases (SMR = 2.7) and nephritis (SMR = 5.4) in patients with CD.

In contrast with previous research [9,12,13,18–20,24] we have tried to minimize the impact of DM, potentially a confounding factor [6,26]. The CD and type 1 DM share HLA DR3, DQ2 and DR4, DQ8 [27–29]. In addition, both type 1 DM [30,31] and type 2 DM [32,33] are major risk factors for renal failure. Type 1 DM may also be linked to IgA nephropathy [34]. The HDR does not distinguish between type 1 and type 2 DM. In this study, adjustment for DM and exclusion of individuals with type 1 or type 2 DM resulted in similar HRs. We also carried out analyses assigning different proxy values for individuals aged ≤30 with first recorded DM diagnosis and for those receiving a DM diagnosis at ≥31 years of age, strongly indicating probable DM type. This approach produced identical risk estimates to the model where we adjusted for DM. This suggests that the increase in renal disease in individuals with CD is not solely mediated through DM.

After excluding individuals with type 1 or type 2 DM, CD was statistically, significantly associated with a raised risk for any form of GN, CGN and dialysis, but not with KT.

As the associations with glomerulonephritis are independent of DM, presence of DM may be another marker of auto-immunity that is intermediate in the casual pathway, so that adjustment or exclusion for DM may have produced conservative estimates of the true association in our analyses. Therefore, our exclusion of patients with DM may have masked an association between CD and KT as those with the more severe autoimmunity could have been excluded from the analyses of relatively few events.

In contrast with other outcome measures of this study, KT constitutes an active decision by health professionals. It may be that Swedish doctors are more inclined to transplant a non-functioning kidney in individuals with type 1 or type 2 DM, due to such factors as patient age and prognosis, than in individuals with other reasons for renal failure. This could explain the lower HR for KT in CD individuals when taking DM into account. The risk of KT when excluding individuals with type 1 or type 2 DM was instead similar to that of GN, although events were fewer and the confidence intervals therefore wider. When the number of events is small the risk estimates are inherently less stable; for instance, so were both crude and adjusted HRs for KT in a restricted sample of CD individuals with available data on SES above seven, as compared with 3–4 when estimating the risk including individuals with missing data on SES. In this study, the risk increase for renal disease was seen in individuals with an adult diagnosis of CD. This is most likely due to insufficient follow-up time in individuals with a diagnosis of CD in childhood. A child with CD diagnosed in 1982 at the age of 3 years, would only have been 24-years old at the end of follow-up.

None of the previous studies on CD and renal disease [9,12,13,18–2024,35] were adjusted for SES. In our study, we had data on SES in a subset of individuals. Although adjustment for SES did not affect our risk estimates, the smaller number of participants diminishes our study power. Adjustment for SES is nevertheless important since SES is associated with use of health services [36] and lower status is linked with an increased risk of some renal diagnoses [37]. It is also closely linked to smoking pattern in Sweden [38] and as the HDR contains no information on smoking, adjustment for SES provides some adjustment for such behavioural factors. Smoking may be negatively associated with CD [39,40], but seems to be a positive risk factor for chronic renal failure [41]. Neither SES nor smoking is therefore likely to explain our results. Given these associations, it is likely that inclusion of smoking could have resulted in higher rather than lower risk estimates for the association of CD with renal disease.

Due to the high CD prevalence in the Nordic countries [1,42], most Swedish doctors are well aware of the necessity to confirm CD with a small-bowel biopsy [43]. The diagnostic use of small-bowel biopsy is likely to have increased the sensitivity of our study. Especially in the earlier part of our study period hospitalization (and as a consequence of this inclusion in the HDR) was often a prerequisite for small-bowel biopsy.

This is important since positive serology does not always correspond with true CD [44]. In a recent study, Smedby et al. [45] validated the diagnosis of CD in the HDR and found a specificity of above 85% in patients with lymphoma. The specificity of chronic diseases in the HDR is generally regarded as high. We chose diagnoses for dialysis or KT as proxies for renal failure since the specificity for such procedures are likely to be high. Although, the proportion of individuals with CD and subsequent dialysis/KT was small, the large study size resulted in sufficient events for stratifications. We also believe that the specificity for GN and CGN is high even though we are aware that CGN in patients with long-standing type 1 DM may be diagnosed as DM nephropathy. We cannot exclude that some individuals have been misclassified. This should, however, only affect our risk estimates marginally; otherwise the risk of misclassification differs between individuals with CD and their reference individuals. We find such differential misclassification unlikely. Instead there is a risk that misclassification may attenuate true relationships between CD and renal disease.

Also the sensitivity with regards to dialysis/KT ought to be high. We do not expect any patient with end-stage renal disease and dialysis/KT to lack a hospital discharge diagnosis of dialysis/KT. However, there is a risk that not all patients with CD or CGN/GN are identified through a hospital-based registry. Despite this, our study had considerable power to detect associations, as there were 89 patients with a diagnosis of GN among our 14 000 patients with CD and some 70 000 reference individuals.

This study also has some potential weaknesses.

We cannot exclude the possibility that there may be false-negative reference individuals with CD. These are, however, unlikely to affect our risk estimates since individuals without CD dominate the reference population. There is also a risk that individuals with CD will receive a diagnosis of renal disease due to regular check-ups for their CD. Control visits and medical investigations are usually most common just after diagnosis. In this study, the risk estimates for renal diseases were independent of events in the initial year after the first recorded CD diagnosis. For that reason, we do not think that the surveillance bias has had a large impact on the association between CD and renal disease. Furthermore, we cannot rule out that individuals with CD identified through hospitalization suffer from more severe CD than the average individual with CD, although risk estimates for CGN and dialysis both remained above 2.6 and were statistically significant when we adjusted for one marker of CD severity (DM).

Patients with IgA nephropathy seem to have the same prevalence of HLA-DQ2 or DQ8 as individuals without IgA nephropathy [9]. So HLA is unlikely to explain the association between CD and GN, since IgA nephropathy is the most common form of CGN in the Western world. Instead, we speculate that many patients with an initial CD diagnosis in adulthood had active, yet undiagnosed, CD earlier in life and in some individuals there was also other auto-immune disease activity. An adverse effect on renal function in CD could be mediated through several mechanisms such as exposure to nephrotoxic substances [9,46–48], and high nitric oxide production (nitric oxide is also a pro-inflammatory mediator in renal disease [49] and nitric oxide synthase inhibitors may improve renal function [50]). Also greater activation of auto-reactive peripheral T-cells [51,52] could contribute to the increased risk of renal disease in individuals with CD. CD has a negative effect on blood glucose regulation in individuals with type 1 DM [7]. In parallel, it may worsen the prognosis of a number of renal diseases, thereby increasing the need for renal replacement therapy.



   Conclusion
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 
In conclusion, our study suggests that CD is associated with an increased risk of CGN and renal failure.



   Acknowledgments
 
J.F.L. was supported by grants from the Swedish Research Council and the Örebro University Hospital while writing this article. This project was supported by The Swedish Society of Medicine, the Karolinska Institute Funds, the Swedish Research Council, the Majblomman Foundation and the Swedish Coeliac society.

Conflict of interest statement. None declared.



   References
 Top
 Abstract
 Introduction
 Materials and methods
 Discussion
 Conclusion
 References
 

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Received for publication: 15. 2.06
Accepted in revised form: 23. 2.06


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