NDT Advance Access originally published online on September 8, 2006
Nephrology Dialysis Transplantation 2006 21(11):3223-3230; doi:10.1093/ndt/gfl392
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Mental health at the third month of haemodialysis as a predictor of short-term survival
1Nephrology Unit, Hospital Universitario Central de Asturias and 2BAP HEALTH OUTCOMES, Asturias, Spain
Correspondence and offprint requests to: Covadonga Valdés, Departamento Técnico Instituto Nacional de Silicosis, C/Manuel Bellmunt sn 33006 Oviedo, Asturias, Spain. Email: cvaldes{at}hca.es
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Abstract |
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Background. The aim of this study was to evaluate the survival of patients initiating haemodialysis (HD), and to analyse whether low health-related quality of life (HRQoL) levels are predictors of mortality in the short-term, controlling certain variables that had been shown in other studies to have a bearing on survival, and using scores, standardized for age and sex, of the HRQoL measurement tool employed.
Methods. This is a multicentric prospective study of all patients on HD in all the dialysis units in Asturias, a region with a little over one million inhabitants, from 1 January 2001 to 30 September 2002. A total of 199 patients initiated HD in our region and survived the first 3 months. Of these, 137 patients who remained on HD for at least 3 months had complete responses on HRQoL measures.
Results. It was observed that adjusted relative risk (RR) of death increased by 5% for each year of age increase (RR = 1.05, 95% CI 1.01–1.09: P = 0.006); in the same way, for each increase in the Mental Component Summary (MCS) score, the adjusted RR of death diminished by 4% (RR = 0.96, 95% CI 0.94–0.99; P = 0.006).
Conclusion. Mental health has been shown to be a factor independently associated with mortality; as the MCS score worsens the adjusted RR of death of a patient on HD increases.
Keywords: elderly; end-stage renal disease; health-related quality of life, mortality; survival
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Introduction |
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In recent years, as well as the parameters habitually used, health-related quality of life (HRQoL) as expressed by the patients has been increasingly employed to evaluate the effectiveness of the various therapies available for a disease. By HRQoL, the subjective evaluation of the influence of state of health, treatments and health promotion on the capacity of the individual to maintain a functional level that enables him to proceed with those activities that are important for him and that affect his well-being, is understood. It is a multidimensional construct that incorporates at least three domains: physical functioning, psychological functioning and social functioning, all of which may be affected by the disease and/or its treatment. Clinicians and researchers from all areas are coming to accept the importance of measuring HRQoL to complete clinical and biomedical results and to integrate these measurements in the traditional biomedical health model. There is an ever-growing awareness of the importance of the patients’ perception of their state of health, of the limitations that a specific treatment implies for them and how they evaluate possible changes during the course of the disease. Moreover, the results of these studies help identify groups of patients more likely to obtain poor results from treatment.
This vision is especially important in the case of patients with chronic disorders such as end-stage renal disease (ESRD). The guide drawn up by the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (K/DOQI) points out the importance of evaluating and controlling the physical and mental functioning of patients with ESRD [1].
Furthermore, the survival of patients with chronic malfunctions is one of the most widely used indicators in the evaluation of the various possible treatments for a particular illness. In the case of ESRD, there is much data available regarding the survival of patients on haemodialysis (HD). In our region for example, according to data published in the report on HD in Asturias regarding the follow-up period 1995–99, survival for these patients was 86% after the first year and 55% after 5 years. Survival among these patients is greatly influenced by type of treatment. According to the European Register, survival at 2, 5 and 10 years was 65, 35 and 11%, respectively, for patients on dialysis and 90, 81 and 64% for those on renal transplant [2]. Among other factors involved are age, sex, comorbidity, diabetes, haematocrit, educational level, functional status measured on the Karnofsky scale and the HRQoL, which is the predictor for hospitalization and mortality [3–7].
All the studies that have related HRQoL with survival in patients receiving HD have used gross scores or scores normalized to the general population and have not compared each patient with the general population of the same age and sex. This is of great importance, as it is well-known HRQoL worsens with age, especially in the physical aspects, which means that the most elderly patients have to be compared with those of their own age to correct this bias. Furthermore, all these studies have analysed the relationship between HRQoL and survival with prevalent patients, and only one has been found, also carried out in our country, in which HRQoL was analysed in the first month of HD. This, however, concentrated principally on diabetic patients in 29 hospitals in Spain and HRQoL measurements were normalized to the general population [4]. No prospective study has been carried out of the survival in relation to HRQoL of all incident patients in a single region, with follow-up from the time the treatment was stabilized (estimated at 3 months). It should be borne in mind that, due to the rise in the average age of patients initiating HD, the analysis of the effect of age on survival, when adjusted for other variables, is of great interest.
The aim of this study was to evaluate survival of patients initiating HD by investigating the differences between elderly patients (age 
65 years) and those under 65, and to analyse whether low HRQoL levels are predictors of mortality in the short-term, controlling certain variables that had been shown in other studies to have a bearing on survival, and using scores, standardized for age and sex, of the HRQoL measurement tool employed.
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Methods |
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A multicentric prospective study of all patients starting HD in all the dialysis units (10 facilities) in Asturias, a region with a little over one million inhabitants, from the 1 January 2001 to 30 September 2002, who remained in HD for at least 3 months. During the year 2001, the incidence of patients on renal replacement therapy (RRT) in Asturias was 135.1 per million of the population (pmp) and during the year 2002, the incidence was 133.6 pmp. The annual incidence of patients with ESRD who started RRT in Spain in 2002 was 131 pmp, which is an intermediate position in the number of patients who started RRT in the European countries. With regard to the prevalence of RRT patients in Asturias in 2002, this was 822 pmp, and in Spain 895 pmp which is one of the highest levels in Europe, but still far from the prevalence observed in the US (1446 pmp) and Japan (1726 pmp). The study was approved by the local Ethics Committee. The patients were followed up until March 2004 or death. Before they were included in the study, Folstein's cognitive mini–mental test was applied. It consists of a brief dementia detection test through the evaluation of cognitive performance of the patient with a few questions, adapted to Spanish by Lobo et al. [8], to objectively exclude those who, due to significant cognitive deterioration (score below 17 points), were not suitable for the personal interview in which the HRQoL measurement questionnaires were administered. A total of 199 patients initiated HD in our region and survived the first 3 months on HD. Of those, 137 patients had complete responses on HRQoL measures at 3 months. Patients with cognitive deterioration or with difficulty in understanding the questionnaire, inpatients, those who had been transplanted in the 3 months prior to the interview were censored, and those who did not wish, or were not able, to respond to the questionnaires when the time came, were excluded from the HRQoL analysis, but follow-up continued until the end of the study to evaluate their survival.
The HRQoL questionnaires were administered through structured interview performed, in all cases, by one of the two appropriately trained interviewers. Data collection was carried out by a medical doctor in the research team responsible for the study. Clinical and HRQoL data were collected at 3 months (the moment at which it was considered that patients had adapted to the therapy), 1 year and 2 years from the initiation of HD.
Health-related quality of life data
The HRQoL measurement questionnaires employed were the following:
Short-form 36 (SF-36) health questionnaire, a generic HRQoL measurement tool translated and validated in our country and applicable to any population group. This questionnaire allows us to establish comparisons between the age groups considered in the study and those of the general healthy population, regarding which there exists complete data in the published population norms [9]. It consists of eight dimensions, whose score may be standardized for age and sex using the published norms aforementioned [10]. The score obtained for each patient is then compared with that normal for the same age and sex. The scores of these dimensions are grouped into a Physical Component Summary (PCS) and a Mental Component Summary (MCS) score. The mean and standard PCS and MCS deviation for the general Spanish population is 50 [10], a value between 45 and 55 being considered ‘normal’, between 40 and 45 ‘rather worse’ and <40 ‘worse’ than 70% of the general population. The MCS cut-off point used in the study was 
42, which is a method of screening as a depression marker with a sensitivity of 74% and a specificity of 81% already employed for patients with ESRD [5].
The physical symptoms scale of the Kidney Disease Questionnaire (KDQ) [11], for patients on dialysis, consists of a list of symptoms related with HD and its treatment, from which the patient has to choose the six items most important for him (symptoms not included on the list but perceived as important by the patient may also be included). Subsequently, the patient responds regarding the problems or difficulties that each symptom has caused him in the last 2 weeks, using a 7-point likert scale. These scales allow us to evaluate in more detail the effects of treatment in each case (dialysis and treatment) and to study the evolution in time of the patients included in the study.
General data
Data were collected corresponding to the dialysis centre, date of entry into the study, date of birth, age at initiation of HD and at present, sex, date of renal transplant and date of death in case of death.
Sociodemographic data
Data were collected on: educational level divided into five groups groups (0, does not read or write; 1, has not completed elementary school, but can read and write; 2, completed elementary school; 3, completed secondary school and 4, degree or higher degree); socioeconomic level, deduced from the net income of the family unit was divided into four groups (1, <300 euros/month; 2, between 301 and 900 euros/month; 3, between 901 and 1800 euros/month and 4, >1800 euros/month); present employment situation was divided into five categories (1, temporary incapacity; 2, permanent incapacity/retirement; 3, part-time work; 4, full-time work and 5, out of work) and social situation was divided into three groups (1, lives alone; 2, lives with family or friend and 3, lives in an institution).
Clinical data
Data relevant to ESRD were collected: principal diagnosis, certain or presumed, grouped into five categories (vascular nephropathy, diabetes mellitus, glomerulonephritis, interstitial nephropathies, and others—including those of unknown aetiology); number of hospital admissions; haemoglobin; haematocrit; serum figures for urea, creatinine, total proteins and albumin; adequate dialysis control parameters; protein catabolic rate (PCR) and Kt/v; Karnofsky scale, for the functional evolution of the patient, evaluated by the physician in charge of the patient; and comorbidity index already employed in other ESRD studies, which includes 24 conditions grouped into: cardiac pathology, vascular pathology, pulmonary pathology, neurological pathology, endocrine pathology, hepatic pathology, gastro-intestinal pathology, miscellaneous and other pathologies. Each disease is defined by specific criteria detailed in the index instructions. For each pathology it is indicated whether it is present or absent, and if present, the severity of functional repercussion: none, slight, moderate or severe. Each pathology is scored thus: 0, if it is not present in the patient; 1, if it is present but does not affect the functional activity; 2, if it is present and limits functional activity slightly; 3, if it is present and limits functional activity moderately; and 4, if it is present and limits functional activity severely. Addition of the scores for each pathology gives a theoretical total score ranging between 0 and 96 [10].
Data analysis
Patients were classified into two groups according to age: <65 and 65 years. While it is not the purpose of the study to analyse the HRQoL of patients in function of the type of replacement therapy, those that had received a transplant during the follow-up were censored to HRQoL analysis. Previous studies [2] have found that receipt of a renal transplant considerably increases HRQoL and so this variable was controlled. To analyse the differences in HRQoL attributable to the receipt of a transplant, we would have to compare those who have received a transplant with those who have not yet, but are on the waiting list, as these would be two clinically similar groups [12].
With the data collected from the personal interview with the patient, three result variables of the HRQoL measurement were created: (i) two aggregate scores were calculated from the correction of the SF-36 health questionnaire and from the elaboration and standardization according to age and sex of the scores resulting from the scales comprising it: (a) 1, physical aggregate score (e.g. PCS)—which evaluates the physical area of the HRQoL expressed by the patient and (b) 2, mental aggregate score (e.g. MCS)—which evaluates the mental aspect; and (ii) on the basis of the correction of the physical symptoms scale of the renal disease questionnaire, (c) a score of 1 (greatest effect) to 7 (least effect), an expression of the degree to which the HRQoL of the patient is affected by the physical symptoms of the renal disease and/or its treatment. The Student's t-test for paired samples was used to stabilize changes in HRQoL over time.
Subsequently, a survival analysis was performed for the whole sample. The survival curves were analysed using the Kaplan–Meier method, and the log rank test was employed to compare all the factors, divided into two values by the clinical criteria already established, on which a hypothesis was made of an association with survival: age, sex, comorbidity, diabetes, haematocrit, albumin, educational level, economic level and functional state measured on the Karnofsky scale. To correct the natural effect of age on patient mortality, the relative risk (RR) of death of patients was calculated by decades with respect to the risk of death by decades of the population of Asturias. This index was calculated using mortality rates in Spain in 2000 by age group and with the formula of Standardized Mortality Index (SMI). SMI = observed deaths/(annual mortality rate x years of monitoring). Finally, the factors independently associated with higher risk of death were analysed with Cox's proportional risk model, with the enter strategy, permitting the analysis of the risk rate of the variables that in univariate analysis had shown different survivals and which were hypothesized in this study. For the statistical analysis, the SPSS 12.0 statistical program was employed.
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Results |
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During the inclusion period (January 2001 to September 2002), 199 patients initiated HD and were followed up until March 2004. Of these, 10 patients were excluded for cognitive problems, five for poor comprehension of the questionnaires, four moved to other communities, six were hospitalized at the moment of interview, six did not wish to participate in the HRQoL questionnaire, 11 were transplanted before 3 months on HD and 20 were not contacted in time for the first interview. Minimum follow-up time was 4 months and the maximum 38 months. Due to the difficulty in coinciding with day 90 for each patient, and since either the patients were indisposed on that date or had been admitted to the hospital in the month prior to the interview, the questionnaire, was postponed until an appropriate moment; the window for the 3 months varied between 82 and 110 days. For the 12-month period, the window varied between 370 and 403 days and for the 2-year period, the window varied between 758 and 797 days.
The average age of the whole sample (n = 199) was 63.5 years (14.31), 60.5% being over 65 years of age. The average age of the patients with HRQoL measurements at 3 months (n = 137) was 63.5 years (14.4) and 62% were elderly.
During follow-up, 65 were transplanted, 49 in the younger group and 16 in the elderly group. Of the patients transplanted, four died and one lost the implant.
During the follow-up period, 57 of the 199 patients died, which means that the overall survival of the sample was 71.36%. In the sample with HRQoL measurements, 36 out of 137 patients died, meaning a survival of 73.7%. Of the total of 120 elderly patients, 47 died, with a survival, therefore, of 61% for this group, while among the elderly with HRQoL measurements, 30 of 85 patients died, a survival of 64.7%. Of the total of the younger group, 10 out of 79 died with a survival of 87.3%. Survival for younger patients with HRQoL measurements was 88.5%, as six of 52 died. There are, therefore, no significant differences in survival between the two population samples: the total and that which had compiled complete HRQoL measurements.
Table 1 shows the sociodemographic data, the functional state and the principal diagnosis of kidney disease at 3 months from the initiation of HD comparing the two age groups. No differences were found between the two groups in sociodemographic data, except for the monthly income, where the proportion of patients with incomes >900 euros was greater in the group of younger patients (P = 0.005). As regards the principal diagnosis, there was a greater number of elderly patients with vascular nephropathy and of younger ones with glomerulonephritis and interstitial nephropathy (P = 0.001). Mean score on the Karnofsky scale, which measures functional state, of the younger patients was 81.86 (16.97) as compared with 71.65 (15.22) for the elderly patients, (P = 0.001).
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Table 2 shows the clinical variables at 3 months from the initiation of HD. Patients over 65 years are compared with those younger. No statistically significant differences were found between the two groups.
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Mean survival for the whole sample was 30.95 months (95% CI 29.47–32.43) and for patients with HRQoL measurements, mean survival was 30.08 months (95% CI 28.25–31.91). In elderly patients, survival was 28.52 months (95% CI 26.59–30.48) for the whole sample and 28.70 (95% CI 26.42–30.97) for patients with HRQoL measurements. Median survival for elderly patients was 35.21 months (95% CI 29.79–40.63) for the whole sample and the same number of months for patients with HRQoL measurements, 35.21 months (95% CI 27.12–43.3). In the younger patients, the mean for the whole sample was 34.45 months (95% CI 32.60–36.31) and 32.22 months (95% CI 30.59–35.86) for patients with HRQoL measurements.
The survival curves of the two age groups were studied for the whole of the sample, and by means of the log rank test it was seen that the differences were statistically significant: P = 0.001. The same was found for patients with HRQoL measurements: P = 0.003 (Figure 1). To correct the natural effect of age on patient mortality, the RR of death of patients was calculated, using SMI, by decades with respect to the risk of death by decades of the population of Asturias. It was found that RR of death diminished progressively with age, as is shown in Table 3.
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In patients who remained on HD during the follow-up, at 3 months, 32.1% had a PCS <40, and a year after, 19.4% had PCS <40; (difference between 3 months and 1 year after initiating HD: P = 0.04). Two years after initiating HD, 46.2% had PCS <40 (difference between 1 year and 2 years after initiating HD: P = 0.002); No statistically significant differences were found between PCS on initiating and PCS 2 years after initiating HD. At 3 months, 26.3% had an MCS
42 (cut-off point chosen for being close to 40 and 42, which is a method of screening as a depression marker). A year after and 2 years after initiating HD, 22.4 and 30.8% had an MCS 42. However, at 3 months, a year after and 2 years after initiating HD 46, 37 and 25% of patients declared that the symptoms of their renal disease caused considerable problems or discomfort (difference between at 3 months and 2 years after initiating HD: P = 0.017). Figure 2 shows the mean PCS and MCS scores for the three time points of the study. In the analysis of patients with HRQoL measurements, statistically significant differences in PCS score means were observed. The mean of the PCS of the 137 patients at 3 months was 43.80 (11.65), the mean of the PCS of the 98 patients at 12 months was 46.07 (11.37) and the mean of the PCS of the 52 patients at 24 months was 41.21 (13.96). However, the means that were compared, with Student's t-test for paired samples, for patients with both interviews when comparing PCS at 3 months and PCS at 24 months, (n = 40) were 43.16 (11.76) vs 39.09 (14.59) respectively; P = 0.031, and the means that were compared, with Student's t-test for paired samples, for patients with both interviews, between the PCS at 12 months and the PCS at 24 months (n = 44) were, 46.01 (8.87) vs 40.80 (14.73), respectively; P = 0.005. No significant differences were observed between 6 months and 24 months after initiating HD on PCS, and no statistically significant differences in MCS were found during the study.
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Furthermore, statistically significant differences were found between the survival in months of patients with a score
50 on the Karnofsky scale and that of those with a higher score for patients with HRQoL measurements, where mean survival was 26.07 months (95% CI 20.7–31.44) for those who scored 50 on the Karnofsky scale and 32.03 months (95% CI 30.45–33.62) for those >50 (P = 0.02). No other sociodemographic or clinical variable associated with survival was found in our sample. The Cox proportional risk model was calculated for patients with HRQoL measurements at the start of HD (n = 137), along with age at the start of HD, sex and the HRQoL variables (PCS, MCS). As a correlation with PCS was observed between the HRQoL measurement tools (Table 4), two of these, the Karnofsky scale and the list of KDQ symptoms were excluded from the final model. It was observed that adjusted RR of death increased by 5% for each year of age increased; RR = 1.05 (95% CI 1.01–1.09); P = 0.006, in the same way for each point that MCS increased, the adjusted RR of death diminished by 4%; RR = 0.96 (95% CI 0.94–0.99); P = 0.006 (Table 5). No relation was observed between the RR of death and HRQoL measurements a year after and 2 years after initiating HD, nor between the RR of death and the change in individual scores.
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Discussion |
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As was hypothesized, with relatively small effect, mental health has been shown to be a factor independently associated with mortality; as the MCS score worsens, the adjusted RR of death of a patient on HD increases. However, in our study it was not found, as was the case in others [3,6–7], that a decrease in PCS increased the RR of death. It is, however, true that in these studies samples of 10 030 and 13 952 patients were analysed, far more than in the present one, but obtained cross-sectionally. Furthermore, on analysing the HRQoL data, standardized for age and sex and at 3 months from the start, we found the patients were less physically deteriorated for their age, while in the other studies, as they were transversal, there is a higher percentage of more deteriorated patients due to the time spent on receiving HD, because younger patients who were transplanted early are no longer included and because they are compared with the population mean and not with those of the same age and sex.
Survival for the whole sample was 71.36%; 61% for those patients 65 years of age and 88.3% for those below this age. However, when the RR of death was calculated, comparing the number of patient deaths for each decade of years with the proportion of deaths for this same decade in the general population, it could be seen that it was not those elderly patients who initiated HD that had the RR of dying, but rather those patients between 34 and 43 years old. For these, the RR was 30 times higher than for the general population. And for those between 44 and 53 years old, it was 20.83 times higher. This RR diminished with increasing age until it was little less than double for the oldest patients in the sample. In patients between 24 and 33 years, we could not calculate the RR because there were no deaths.
Apart from this, it was found that those patients with a better functional state (measured on the Karnofsky scale) had a greater survival rate than those with a more deficient one. A simple and rapid working tool can therefore help us to detect at the start of HD those patients with possible low-survival prognosis.
Another interesting fact identified in the present study is that, while it is true that the majority of patients, both the younger and the older, had their analytical parameters, such as haemoglobin, haematocrit, albumin, etc. corrected, there was a high prevalence of patients with a certain deterioration in the mental aspects. Around 26% of the patients suffered depression according to the screening tool at 3 months from the start, and DeOreo [5] using SF-36 in a study of 1000 patients on haemodialysis found the same percentage, 25%, of patients with an MCS 42 [5]. Kimmel et al. [13] also found a depression rate of 25.5% using Beck Depression Inventory (BDI). However, some authors have found in their studies a depression prevalence of 43–44% [14–16]. It must be borne in mind that if there is a greater depressive malfunction, the medical treatment is more complicated and the prognosis less favourable. As has been demonstrated in other studies, the problem of depression increases morbidity and mortality and may lead to significant psychosocial morbidity with poorer functioning in occupational roles.
The PCS of patients improved a year after initiating HD in comparison at 3 months, but sdecreased drastically 2 years after initiating HD in comparison at 3 months and a year after initiating HD. The MCS of patients remained more stable throughout follow-up. Kimmel et al. [17], evaluating depression levels, found that it is not the basal measurement of depression in patients with ESRD that is associated with mortality, but rather when depression is taken as a time-dependent variable. The difference is that this study was made with prevalent patients and when the basal measurement was taken each patient had been at a different period of time on HD, while our study analyses mental health in all incident patients. Analysing HRQoL at the first month after initiating HD, López Revuelta et al. [4], in a study carried out principally with diabetic patients, found that MCS is a predictor of mortality for the whole of the sample, while PCS is only a predictor for the diabetic patients.
Limitations of the study are the unequal follow-up of the patients, as these were included gradually throughout the 21 months, and the short follow-up conducted, which meant it was not possible to calculate the median of survival of the younger group. Another limitation is that there are patients who did not take part in any of the three interviews, and we did not use any other additional test to estimate the prevalence of depression. However, diverse authors found that both BDI scores and health status, measured by SF-36, were important predictors of diagnosis of depression. All SF-36 subscales correlated highly with BDI scores, suggesting that these measurements may lack adequate discriminant validity [18]; the same was found in ESRD patients and specifically patients on HD [19].
On the other hand, there are no HRQoL studies that evaluate HD results with this prospective design where the patients are followed up through time. As all the patients who initiated HD in our region were pre-included, the risk of bias typical of transversal studies was avoided. We would also like to highlight the originality of standardizing patient scores on the HRQoL questionnaires by age and sex by means of the population norms existing for the SF-36 health questionnaire. This standardization was performed in previous studies by Rebollo et al. [10].
The evidence of interaction between emotional and physical symptoms supposes a challenge in the sense of a new paradigm for disease and medical care. Some mechanisms are already known to explain why depressive states, anxiety, situations of prolonged emotional tension and/or stress lead to a reduction in immune defences or become triggers for severe acute illnesses; for instance, vulnerability to infections, loss of weight, emotional overload with intolerance, poorer performance at home and in the workplace, etc., which may clearly influence survival. It is well accepted that these somatic illnesses are frequently preceded by recent emotional traumas, as may be the case with entry into RRT. The present prospective study shows that the mental health of patients who initiate HD is, once the treatment is stabilized, an independent predictor of mortality in the short-term. Its measurement may provide an indicator of survival that helps the clinician to identify patients at special risk, which makes it worth advising clinicians to pay closer attention to the mental health of patients on HD.
Another point that we feel important and which in the future should be studied in large population samples, is an evaluation of the predictive power of the HRQoL at multiple time points throughout the course of the ESRD, including the period before the start of RRT, since, despite the fact that patients have reported an improved HRQoL, as has been shown recently [20], the predictive value of this time point for a short- or long-term survival has not been evaluated. This would better define at which precise points in time the HRQoL expressed by patients has a greater predictive power for the survival of renal transplant patients.
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Acknowledgements |
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The authors are grateful to all the dialysis units participating in the study: HUCA (J. Alvarez- Grande, J.M. Baltar, C. Diaz-Corte, E. Gago, R. Álvarez Navascues, M. Miguel); Cruz Roja Oviedo (P. Ruíz-Alegría, M.L. Céspedes, A. Álvarez); H. Cabueñes (A.R. Pérez); Cruz Roja Gijón (J. Mejido); H.S. Agustín (I Fuente);); H. Valle del Nalón (A. Díaz); H. de Oriente (F. Tejada); H. de Jarrio (M. Gorostidi). This study was supported by a grant from FIS funds and FEDER funds (01/0388) and a grant from FICYT (PB-MED01-04).
Conflict of interest statement. None declared.
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Accepted in revised form: 31. 5.06
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