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NDT Advance Access published online on May 17, 2007
Nephrology Dialysis Transplantation, doi:10.1093/ndt/gfm247
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© The Author [2007]. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Time-dependent changes in cardiac growth after kidney transplantation: the impact of pre-dialysis ventricular mass

Domingo Hernández1,3, Ana González1, Margarita Rufino1,3, Ignacio Laynez2,3, Alejandro de la Rosa2, Esteban Porrini1, Juan Lacalzada2, Antonio Barragán2, Víctor Lorenzo1 and Armando Torres1,3

1Department of Nephrology, 2Department of Cardiology, Research Unit, Hospital Universitario de Canarias, Instituto Reina Sofía de Investigación, and 3University of La Laguna, 38320 La Laguna, Tenerife, Spain

Correspondence and offprint requests to: Domingo Hernández, Department of Nephrology, Hospital Universitario de Canarias, E-38320, La Laguna. Tenerife, Spain. Email: dhmarrero{at}hotmail.com; domingohernandez{at}gmail.com



   Abstract
Top
 Abstract
Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 
Background. Left ventricular hypertrophy (LVH) is common in chronic kidney disease (CKD), including kidney transplant recipients. However, time-related left ventricular mass changes ({triangleup}LVM) from pre-dialysis stage to beyond the first post-transplant year have not been clearly identified.

Methods. We studied a cohort of 60 stages 4–5 CKD patients without overt cardiac disease, who underwent three echocardiograms during follow-up: at pre-dialysis stage, on dialysis and after kidney transplantation (KT). Multiple linear regression was used to model {triangleup}LVM from baseline study. Cox proportional analysis was used to determine risk factors associated with either de novo LVH or >20% {triangleup}LVMI over time.

Results. Patients with baseline LVH (n = 37; 61%) had a higher body mass index (BMI) than those without LVH (n = 23; 39%) (P = 0.013). BMI, haemoglobin levels (P = 0.047) and non-use of angiotensin-converting enzyme inhibitors (ACEI) (P = 0.057) were associated with baseline left ventricular mass index (LVMI). Twelve out of 23 patients (52%) with normal LVM at baseline, developed either de novo LVH or >20% {triangleup}LVMI at follow-up. On the other hand, 29 (78%) of those with initial LVH maintained this abnormality, and 8 (22%) normalized LVM post-transplantation. Factors associated with {triangleup}LVMI were age (P = 0.01), pre-dialysis LVMI (P < 0.0001), serum creatinine (P = 0.012) and the use of ACEI post-transplantation (P = 0.009). In Cox analysis, pre-dialysis LVMI was associated with de novo LVH or >20% {triangleup}LVMI over time (hazard ratio 1.009; 95% confidence interval 1.004 to 1.015; P = 0.001).

Conclusions. Successful KT may not completely normalize LVM post-transplantation. Pre-dialysis LVMI, traditional risk factors and no use of ACEI may perpetuate cardiac growth following KT.

Keywords: chronic kidney failure; kidney transplantation; left ventricular hypertrophy



   Introduction
Top
 Abstract
 Introduction
Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 
Left ventricular hypertrophy (LVH) is a powerful risk factor for cardiovascular death in the uraemic population, including kidney transplant recipients [1]. This entity is highly prevalent in patients with chronic kidney disease (CKD) before starting dialysis, and cardiac growth appears to progress during dialysis therapy [2]. Several risk factors such as, age, hypertension, anaemia, arteriovenous fistula, hyperparathyroidism or volume overload, have been identified as stimulating LVH in both pre-dialysis and dialysis population [2–5].

Successful kidney transplantation (KT) may improve some cardiovascular risk factors inherent to chronic renal failure, but the beneficial effect of KT on left ventricular mass (LVM) is somewhat controversial. While some prospective studies have demonstrated improvement of LVH after KT [6,7], others have not [8,9]. Cardiac growth is a dynamic process and LV remodelling occurs early in the course of kidney failure [10]. Thus, it is plausible that an increased pre-dialysis LVM may contribute to persistence or worsening of post-transplant LVH, particularly in the presence of emerging risk factors during renal replacement therapy. However, relatively little is known about time-related LVM changes from pre-dialysis stage to KT. In addition, it is unclear whether pre- and post-transplant risk factors, including pre-dialysis LVM, may modulate the magnitude of cardiac growth following KT.

The aim of this historic cohort study is to describe the time-dependent LVM changes from pre-dialysis stage to beyond the first post-transplant year and to identify risk factors for cardiac growth in these patients.



   Subjects and methods
Top
 Abstract
 Introduction
 Subjects and methods
Results
 Discussion
 Acknowledgements
 References
 
Design
This is a retrospective observational cohort study of patients with stages 4–5 CKD [calculated creatinine clearance (ClCr) <30 ml/min/1.73 m2] eligible for KT who underwent three echocardiographic studies to examine the structural changes in LVM from pre-dialysis stage to beyond the first post-transplant year.

Figure 1 summarizes the timing of echocardiograms made during the study. The first echocardiogram was performed at pre-dialysis stage before starting dialysis (median time 8 months, interquartile range 3–18 months). A second echocardiogram was performed after initiation of dialysis therapy according to clinical needs (median duration 3 months, interquartile range 1–12 months). The median time between the first and second echocardiography was 16 months (interquartile range, 7–29 months). Finally, all patients underwent a third echocardiogram after KT (median time 19 months, interquartile range 18–20 months) and the median duration between the second and third echocardiogram was 27 months (interquartile range, 20–40 months).


Figure 1
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  		Fig. 1. Timing of echocardiograms made during the study. Times (t1, t2, t3 and t4) are shown as median and interquartile range. PD, pre-dialysis, KT, kidney transplantation. t1: 8 months (3–18 months); t2: 3 months (1–12 months); t3: 7 months (3–13 months); t4: 19 months (18–20 months). Median time between Echo 1 and Echo 2 was 16 months (interquartile range, 7–29 months). Median time between Echo 2 and Echo 3 was 27 months (interquartile range, 20–40 months).

 
The study was purely descriptive and no attempts were undertaken to modify any aspect of therapy. This study was approved by the Ethics Committee of the Hospital Universitario and was conducted according to the Declaration of Helsinki.

Patients and follow-up study
From a cohort of 256 incident patients of our pre-dialysis clinic between January 1998 and January 2002, a total of 137 patients who had an assessable baseline echocardiogram and followed from 2001 for a median time of 7 months (interquartile range, 3–11 months), were initially eligible for this study. Figure 2 shows the flowchart of patients during the study. The enrolment criteria in the cohort study were the following: ClCr (using the Gault–Cockcroft formula) <30 ml/min/1.73 m2, older age than 18 years and to be eligible patients for a first KT. Exclusion criteria were severe ischaemic heart disease, congestive heart failure, erythropoietin (EPO) resistance criteria, severe chronic respiratory disease, severe to moderate valvulopathies, alcohol abuse, drug-induced cardiotoxicity and inadequate acoustic window for echocardiography study.


Figure 2
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  		Fig. 2. Flowchart of patients during the study.

 
During pre-dialysis care follow-up, three patients died, 14 were excluded from the waiting list or had overt cardiac disease and 21 continued in our pre-dialysis clinic. Thus, at the end pre-dialysis care (median time 19 months, interquartile 10 to 30 months), 99 eligible patients were accepted for maintenance dialysis therapy in our center. Patients on haemodialysis (75%) underwent thrice-weekly standard bicarbonate dialysis, with a prescribed urea reduction rate >65%. Medium-and high-flux membranes were used in all dialysis sessions. Peritoneal dialysis therapy was performed using a 4-exchange/d schedule with standard dialysis bags. During maintenance dialysis, three patients died, 15 were excluded from the waiting list for KT due to several reasons and 12 patients continued on dialysis up to the current time. Thereafter, a total of 69 patients received a deceased KT after initiation of dialysis therapy (median time of 12 months, interquartile range 6 to 24 months). Immunosuppression consisted of prednisone plus antithymocyte globulin for induction followed by calcineurin inhibitors and azathioprine or mycophenolate mofetil. Episodes of acute rejection were initially treated with three boluses of 500 mg of intravenous methylprednisolone. Post-transplant follow-up was performed in our centre by nephrologists participating in the study. Finally, one patient died and eight patients lost their grafts during the first post-transplant year. Thus, the final cohort involves 60 patients who underwent three sequential echocardiographic studies from pre-dialysis stage to beyond of the first year after KT (Figure 2).

The overall median duration of the follow-up was 58 months (interquartile range, 42–76 months).

Data collection
The following data were recorded: age, gender, cause of end-stage renal disease (ESRD), time of pre-dialysis nephrological care, antihypertensive drugs, treatment with recombinant EPO, blood pressure, body mass index (BMI, kilograms per metre square) haemoglobin levels, ClCr, presence or not of definitive vascular access and pre-existing vascular calcifications. Arterial hypertension was defined as blood pressure >130/80 mmHg on at least three consecutive office measurements. Mean blood pressure (MBP) was calculated as diastolic blood pressure + 1/3(systolic blood pressure minus diastolic blood pressure). Pulse pressure (PP) was calculated as systolic blood pressure minus diastolic blood pressure. We used the average MBP and PP determinations recorded 3 months before each echocardiography study.

After initial assessment, the following clinical data were collected during follow-up: modality of dialysis, time on dialysis, post-transplant diabetes, haemoglobin levels, renal function after KT, time of post-transplant follow-up and acute rejection.

Laboratory measurements
Blood sampling for the measurement of routine and other special biochemical measurements were performed before echocardiographic studies. We used mean haemoglobin levels, serum creatinine and Cl Cr measured 3 months before each echocardiogram.

Echocardiography
Using standard methods, M-mode, 2D and colour-flow Doppler echocardiograms were performed by two experienced readers (I.L. and A.R.) without previous knowledge of the subjects’ clinical characteristics. All echocardiographic measurements were undertaken following the recommendations of the American Society of Echocardiography [11]. Left ventricular end-diastolic diameter (LVEDD), posterior wall thickness (PWT) and the interventricular septum thickness (IVS) were measured at the end diastole. LVM was defined according to the method of Devereux and Reichek [12] and indexed to body surface area to yield the LVM index (LVMI). LVH was defined by a LVMI >143 g/m2 in men and LVMI >102 g/m2 in women [13]. LV relative wall thickness was calculated as (IVS + PWT)/EDD. Systolic function was assessed by the ejection fraction, which was calculated by the formula of Teichholz et al. [14]. Pulsed-wave Doppler of transmitral flow was used to assess overall diastolic function. The Doppler indexes measured were peak early velocity (E) and peak atrial velocity (A) in centimetres per second. In addition, E/A ratio was calculated. The mean of measurements from three to five consecutive cycles was determined for each of these indices. In our laboratory, interobserver variability for these measurements was <10%, similar to previous results of our team [15].

Outcome
Primary outcome was determined as percent changes in LVMI ({triangleup}LVMI) after KT from baseline [(final value – baseline value) x 100/baseline value]. Based on previous studies, significant change of LVMI was defined as a relative increase ≥20% from baseline values or absolute values >20 g/m2 [10].

Statistical analyses
Data are presented as mean ± SD or median ± interquartile range. Data of patients with de novo LVH or {triangleup}LVMI ≥ 20% were compared with patients with normal LVMI during follow-up. Comparisons of continuous variables between groups were made by means of Mann–Whitney U-test. Chi-square test and Fisher's exact test, when appropriate, were used for between-group comparisons of categorical variables. Multiple regression analysis with backward selection was performed to determine independent predictors of final {triangleup}LVMI from baseline. All potential predictors of cardiac growth of our database, namely, pre-dialysis, dialysis and post-transplant clinical and echocardiographic parameters were included to obtain the best multivariate model. We screened the following variables: age, gender, primary cause of kidney disease, time of follow-up, use of angiotensin-converting enzyme inhibitors (ACEI) and other antihypertensive drugs, type of dialysis, arteriovenous fistulae, obesity (BMI > 26 kg/m2), blood pressure, vascular calcification prior to KT, EPO therapy, haemoglobin levels, renal function, LVMI and changes from baseline of MBP, BMI and haemoglobin levels. We built two models to identify risk factors associated with post-transplant {triangleup}LVMI. One prediction model included pre-dialysis LVMI, whereas in the second model dialysis LVMI was entered in the regression analysis. Colinearity and the assumption of normality were never violated. Accordingly, only the significant variables were considered in the final model. Finally, we used Cox proportional hazards analysis to determine risk factors associated with either de novo LVH or >20% {triangleup}LVMI over time. We recorded dates of all echocardiograms. Thus, we calculated the time between baseline study and the first time that a significant increase of LVMI (de novo LVH or >20% {triangleup}LVMI) was observed in the subsequent echocardiograms. Because only 28 cases of significantly increased LVMI were seen during follow-up, the model allowed us to introduce no more than three independent variables. Thus, different covariables were added one by one to baseline LVMI to build the final model. A P-value <0.05 was considered significant. All computations were made using the SPSS 12.0 for Windows® statistical package (SPSS Inc., Chicago, IL, USA).



   Results
Top
 Abstract
 Introduction
 Subjects and methods
 Results
Discussion
 Acknowledgements
 References
 
Initial echocardiographic studies revealed that 37 (61%) patients had LVH and 23 (39%) a normal LVM. Figure 3 shows the flowchart of LVMI changes from pre-dialysis period to post-transplantation in patients with normal LVM or LVH at study entry. Twenty-nine (78%) of those with initial LVH maintained elevated LVMI at the end of study, whereas eight (22%) demonstrated normalization of myocardial mass. Likewise, of those with normal initial LVMI, 12 (52%) developed either de novo LVH or >20% increase in LVMI, whereas 11 (48%) maintained normal LVM.


Figure 3
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  		Fig. 3. Changes in left ventricular mass during the study. LVH, left ventricular hypertrophy; LVM, left ventricular mass; KT, kidney transplantation.

 
Pre-dialysis echocardiographic comparisons
Table 1 summarizes initial demographic, clinical and echocardiographic parameters of pre-dialysis patients according to initial presence or not of LVH. At baseline, patients with LVH had a higher BMI and LVM as well as lower E/A ratio. No significant differences, however, were found between the groups for age, gender, presence of diabetes, time of follow-up, use of ACEI, use of antihypertensive agents other than ACEI, serum creatinine, blood pressure levels, haemoglobin concentration, the presence of pre-existing vascular calcifications, definitive vascular access or treatment with EPO.


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  		Table 1. Demographic, clinical and echocardiographic data for patients with and without LVH at study entry

 
By backward linear regression analyses, BMI (ß = 0.339, P = 0.011) was associated with baseline LVMI (pre-dialysis phase) after adjusting for other confounder variables. In addition, mean haemoglobin concentration (ß = –0.259, P = 0.047) and the use of ACEI (ß = –0.246, P = 0.056) correlated negatively with pre-dialysis LVMI.

Post-transplant subgroups analysis
Patients with maintained LVH (n = 29) showed a higher BMI and serum creatinine as compared with patients who had sustained normal LVM (n = 11) at study end. In addition, those with sustained LVH showed a trend toward older age, higher PP and lower proportion of ACEI (Table 2).


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  		Table 2. Comparisons of clinical data and changes in values at the end of follow-up for patients with and without LVH at study entry, according to observed changes in LVM at study end

 
Patients who developed de novo LVH at the end of follow-up (n = 12) differed from those with maintained normal LVMI (n = 11) in that they received a lower proportion of ACEI and had a significant increase in PP and MBP at end of follow-up (Table 2; left panel). Likewise, they showed a trend toward older age, higher BMI and use of more post-transplant antihypertensive drugs, as well as lower post-transplant glomerular filtration rate (GFR). A lower proportion of diabetes was also seen in patients who developed LVH during follow-up. As expected, significant echocardiographic differences between both groups were identified in LVMI and LVEDD at the study end (Table 3).


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  		Table 3. Echocardiographic parameters and change in values at the end of follow-up for patients with and without LVH at study entry, according to observed changes in LVM at study end

 
Comparisons between those who maintained LVH from study entry (n = 29) and those who regressed to normal LVM (n = 8) demonstrated older age and a higher post-transplant PP in the group with maintained LVH. A higher proportion of males was also observed in this group (Table 2; right panel). No significant differences were observed for BMI, haemoglobin concentration, time of follow-up, use of ACEI or post-transplant creatinine. For echocardiographic parameters, significant differences were observed in IVS and {triangleup}LVEDD (Table 3).

Patients with a reduction of LVM to normal levels (n = 8) at the end of follow-up were also compared with those who developed de novo LVH (n = 12). Again, a significant difference in the {triangleup}PP from baseline was observed between groups. Moreover, a trend toward a greater {triangleup}BMI was found in those with de novo LVH. A significant increase in LVEDD and IVS was also observed in patients who developed de novo LVH (Tables 2 and 3).

Predicting post-transplant changes in LVMI
We investigated potential risk factors for LVM changes in both overall population and among patients with and without initial LVH. After KT, the variables that independently predicted the change of LVMI from baseline were age, pre-dialysis LVMI, serum creatinine and the use of post-transplant ACEI according to the first multivariate model that accounted for 52% of the total variation in the change of LVMI (Table 4). In the second model, when replacing baseline LVMI by dialysis LVMI, only age (ß = 0.82; P = 0.019) and the use of post-transplant ACEI (ß = –22.8; P = 0.028) were independently associated with {Delta}LVMI. In addition, other risk factors for cardiac growth inherent to dialysis therapy such as type of dialysis, hypertension, volume overload or time on dialysis were not significantly related to {Delta}LVMI in both prediction models.


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  		Table 4. Predictors of change in LVMI from baseline in kidney transplant recipients, as identified by linear regression analysis

 
Interestingly, in patients with initial LVH (n = 37), age and pre-dialysis LVMI were independent predictors of LVMI change following KT after adjusting for remaining covariables (Table 4). On the other hand, PP change from screening study correlated positively with {triangleup}LVMI from baseline in patients with initial normal LVM.

Finally, pre-dialysis LVMI was an independent risk factor for de novo LVH or >20% {triangleup}LVMI over time [hazard ratio 1.009; 95% confidence interval (CI), 1.004 to 1.015; P = 0.001], adjusting for age, post-transplant BMI and serum creatinine post-transplantation.



   Discussion
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
Acknowledgements
 References
 
This historic cohort study, mainly, demonstrates that pre-dialysis LVM plays a crucial role in the long-term changes of cardiac mass after KT. Further risk factors that may, independently, predispose to an increased post-transplant LVM are age, post-transplant renal function, PP and non-use of ACEIs. To our knowledge, this is the first study to document the evolution of LVM from pre-dialysis stage to beyond the first post-transplant year. For a better understanding of the time-related LVM changes, we included only low-risk patients without overt cardiac disease. Additionally, we developed a significant predictive model for echocardiographic changes from baseline screening.

Pre-dialysis stage
In the present study, 61% of patients were found to have LVH at outset. This prevalence is similar to previous observations in stage 3–5 CKD patients [16], but substantially greater than the one previously reported in subjects with higher GFR levels [2,10]. This suggests that in patients with CKD, LVH takes hold earlier than expected and tends to increase progressively along the GFR decline, achieving the greatest prevalence in patients with ClCr < 30 ml/min/1.73 m2 like in our study.

Anaemia, hypertension and obesity appear to be the risk factors most consistently related to the development of LVH in both early and advanced renal insufficiency [2–5]. Accordingly, haemoglobin concentration and BMI were independent predictors of cardiac growth in our pre-dialysis population. We did not observe an association between blood pressure and LVMI, but patients with and without pre-dialysis LVH received a similar proportion of antihypertensive agents. In addition, the use of ACEIs, which may regress LVH by blocking the renin-angiotensin system (RAS) [17], was marginally associated with baseline LVMI in our prediction model. Thus, these findings could have masked the deleterious effect of hypertension on cardiac growth.

Post-transplantation
A high proportion of our patients showed persistent or de novo LVH following KT. Although successful KT may optimize uraemia-related risk factors, a reduction in LVMI has not been an universal observation in this population [6–9]. The reasons for this are not sufficiently explained by a high prevalence of post-transplant risk factors and it may reflect significant pre-existing cardiac abnormalities. Cardiac growth is a dynamic process that occurs early in the course of chronic renal failure. Thus, an increased pre-dialysis LVM may be a biological limiting factor for regression of cardiac growth, mainly in presence of emerging risk factors for LVH during replacement renal therapy.

In consonance with these arguments, pre-dialysis LVM was one of the most important prognostic predictors for LVH reversal in our KT recipients. Further risk factors for post-transplant cardiac growth were older age, BMI, a lower renal function and blood pressure, as previously reported [7,8,18]. In addition, the presence of pre-dialysis normal LVM did not prevent the development of post-transplant cardiac growth, and {triangleup}PP from baseline was the independent sole factor that seemed to predict the extent of LVM after KT. Synergistic effects of post-transplant volume and pressure overload become more evident under baseline structural cardiac abnormalities and impaired renal function, especially in older KT recipients. Thus, dilatation and growth of cardiac cavities may be expected after long-term follow-up, as seen in this study. We did not assess haemodynamic consequences of persistent arteriovenous fistulas on cardiac structures, but a similar proportion of persistent arteriovenous fistula was observed in patients with and without final LVH (70 vs 66%). Whether LVM growth could be a consequence of uraemia-associated myocardial interstitial fibrosis, which does not regress following KT [19], is undetermined. In any case, these observations reinforce the prognostic importance of serial echocardiographic measurements from the beginning of CKD in order to detect early LVH and, eventually, to perform targeting prophylactic interventions.

Important risk factors for LVH inherent to dialysis therapy such us hypertension, type of dialysis, volume overload, arteriovenous fistulae or time on dialysis were not associated with post-transplant {Delta}LVMI. We did not determine 24-h ambulatory monitoring of blood pressure in this study which may have underestimated the effect of blood pressure on cardiac mass, but patients had an optimal blood pressure control assessed by casual measurements during follow-up, including dialysis therapy. Moreover, dialysis LVM was not related to cardiac changes after KT in the multivariate model. We do not have an easy explanation for these findings. However, we studied a cohort of candidate patients to KT without overt cardiac disease. In addition, a high proportion of these patients received ACEIs. All these factors could have attenuated the negative effect of dialysis on structural cardiac changes at the end of study. The fact that only five of 23 patients with initial normal LVM developed LVH on dialysis, supports this argument.

The use of ACEIs may antagonize angiotensin-mediated cardiac growth, independently of blood pressure. This could well explain the protective effect of ACEI therapy on post-transplant cardiac growth observed in our final multivariate model. In favour of this view, patients with sustained normal LVM received a higher proportion of ACEIs than those with development of post-transplant LVH. Whether a longer period of treatment with ACEIs or dosage reduction of immunosuppressive drugs may regress LVM in patients with maintained LVH is undetermined.

Previous reports have shown that LVH is associated with cardiac failure, ischaemic heart disease and death. In our study, however, no patients had these life-threatening complications. A time lag between abnormalities of the cardiac structure and outcome has been documented in both dialysis patients and general population [20,21]. Thus, it is enticing to speculate that the lack of association between LVH and mortality in this study may be a lag effect.

Some limitations of the present study merit to be commented, the most important being the sample size. However, this is alleviated by homogeneity of the study group and by the fact that all subjects of the final cohort completed the investigation, which increases the precision of the echocardiographic changes. In addition, given the limited number of patients with significantly increased LVMI during follow-up, we added different covariables 1 by 1 to pre-dialysis LVMI in the multivariate Cox analysis and not the complete group of independent variables. Thus, the influence of pre-dialysis LVMI on post-transplant LVMI should be interpreted with caution. Secondly, echocardiograms were not scheduled regularly at each stage, but time of follow-up at each period was not associated with cardiac growth in the prediction models performed of this study. Since echocardiograms were performed based on clinical needs, a selection bias of high-risk patients for LVH could occur. Consequently, this particular population could have less likely to regress cardiac mass. In any case, this observational study may provide useful prognostic information, which may better reflect the everyday clinical practice. Finally, regression of the mean phenomenon may have occurred in this study, but the results were adjusted for baseline LVMI as a predictor variable, which make it unlikely.

In summary, correction of the uraemic state by successful KT may not completely normalize LVM beyond the first post-transplantation year. Pre-dialysis LVMI, traditional risk factors and no prescription of ACEIs may perpetuate cardiac structural abnormalities in KT recipients.



   Acknowledgements
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
References
 
The authors thank the Cardiology Unit team from the Hospital Universitario de Canarias for their collaboration. This study was supported by grant (PI 2003/008) from Consejería de Educación, Cultura y Deportes del Gobierno de Canarias and by grant (FIS 02/1350 and C03/03) from Spanish Ministry of Health.

Conflict of interest statement. None declared.



   References
Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Acknowledgements
 References
 

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Received for publication: 7. 9.06
Accepted in revised form: 30. 3.07


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