Early referral and planned initiation of dialysis: what impact on quality of life?

Fergus J. Caskey1,, Sarah Wordsworth2, Thomas Ben3, Frank T. de Charro4, Catherine Delcroix5, Vladimir Dobronravov6, Henk van Hamersvelt7, Iain Henderson8, Elizabeth Kokolina9, Izhar H. Khan10, Anne Ludbrook2, Merike Luman11, Gordon J. Prescott12, Dimitri Tsakiris13, Myftar Barbullushi14 and Alison M. MacLeod1 for the EURODICE group

1 Medicine and Therapeutics, University of Aberdeen, 2 Health Economics Research Unit, University of Aberdeen, UK, 3 Medical University of Debrecen, Hungary, 4 Erasmus University, Rotterdam, The Netherlands, 5 Centre Hospitalier Universitaire de Nantes, France, 6 St Petersburg Medical Institute, Russia, 7 University Medical Centre, Nijmegen, The Netherlands, 8 Ninewells Hospital, Dundee, UK, 9 Hippokration General Hospital, Thessaloniki, Greece, 10 Aberdeen Royal Infirmary, UK, 11 Tallinn Pelgulinna Hospital, Estonia, 12 Department of Public Health, University of Aberdeen, UK, 13 Veria General Hospital, Greece and 14 University Medical Centre, Tirana, Albania



   Abstract
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
Background. Early patient referral correlates with improved patient survival on dialysis. We examine whether early referral and a planned first dialysis affect quality of life (QoL).

Methods. All patients commencing dialysis in nine centres in seven European countries between 1 July 1998 and 31 October 1999 were recruited. Definitions: early referral=followed by a nephrologist >1 month before first dialysis (<1 month=late referral); planned=early referral and previous serum creatinine >300 µmol/l and non-urgent first dialysis (early referral and no creatinine >300 µmol/l or urgent first dialysis=unplanned). QoL was measured at 8 weeks using a visual analogue scale (VAS) and Short Form 36 (SF-36).

Results. VAS was significantly higher in early referral patients [mean (SD) 58.4 (20) vs 50.4 (19), P=0.005], particularly if the first dialysis was planned [60.7 (20) vs 54.2 (20), P=0.03]. Planned patients also had higher SF-36 mental summary scores [45.4 (12) vs 39.7 (11), P=0.003], role emotional scores [58.0 (43) vs 30.9 (38), P=0.003], and mental health scores [63.7 (24) vs 54.6 (22), P=0.01] than unplanned patients. Adjusting for centre and other confounding variables showed that having a planned first dialysis had an independent effect on QoL (VAS, and the SF-36's mental summary score, physical functioning, role physical, general health, role emotional and mental health). Early referral had no independent effect on QoL. Socio-economic status had an important positive effect on physical QoL.

Conclusions. While the effect of early referral to a nephrologist on QoL appeared centre dependent, a smooth transition onto dialysis was associated with significantly better early QoL, independent of other variables.

Keywords: dialysis; early referral; Europe; international; quality of life; socio-economic



   Introduction
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
The referral of patients at an early stage of renal failure to a nephrologist has been associated with improved survival [1,2] and lower hospitalization rates [13]. It is therefore not surprising that recommendations on the timing of referral to a nephrologist have been incorporated into renal guidelines [4,5].

Quality of life (QoL) has been recognized as an important outcome measure in dialysis therapy; however, few investigators have studied the effect of early referral on patients' QoL in the first few months of treatment. Sesso and Yoshihiro [6] in Brazil have demonstrated that patients presenting late for dialysis (<1 month) have in several respects significantly worse QoL than those referred to a nephrologist early (>6 months prior to first dialysis). This study, however, examined only haemodialysis patients and did not look at the influence of confounding variables such as co-morbidity. Furthermore, it did not examine the effect of patients with chronic renal failure having a smooth transition onto dialysis and a well-planned first dialysis.

An increasing number of QoL instruments have been translated, culturally adapted and validated for use in international clinical trials and health outcomes research in recent years. One practical problem has been that rigorous quality control requirements in the translation and validation process of questionnaires have limited the number of countries in which each instrument is available. Differences in national wealth must also be taken into account when choosing how to measure socio-economic status—a factor that greatly influences QoL [7]. To our knowledge, this is the first time that the QoL of dialysis patients in different countries has been combined to address a particular research question.

This paper reports the results of a study examining QoL amongst patients with ESRD in nine dialysis units across Europe. Specifically it examines whether baseline QoL differs significantly among: (i) ESRD patients referred to a nephrologist >1 month and <1 month prior to their first dialysis (respectively early vs late referral), and (ii) within the early referral group, dialysis patients having a planned rather than an unplanned first dialysis (planned vs unplanned). The terms early/late referral and planned/unplanned first dialysis are defined below. The paper also highlights some practical difficulties associated with measuring QoL simultaneously in several countries across Eastern and Western Europe.



   Subjects and methods
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
All patients commencing dialysis for chronic renal failure in nine centres (see acknowledgements) in seven countries in Europe between 1 July 1998 and 31 October 1999 were recruited. Data co-ordinators were trained in each centre to collect patient data by a combination of chart review and informal interviews using a standardized form. Basic demographic, co-morbidity and socio-economic data were recorded. Two methods were used to quantify co-morbidity, one classifying patients as low-, medium- or high-risk [8], the other weighting co-morbid illnesses to produce a single score [9]. According to the latter system, patients with moderate or severe renal failure automatically score a minimum of 2, and hence a score of 2 in patients with ESRD indicates no co-morbid illnesses. Annual household income was assessed as a categorical variable. To account for the differences in national wealth between nations, country-specific income bands were calculated from estimates of Gross National Product per capita (Table 1Go) using a previously validated banding system [10]. By this method, the patient's income is assessed relative to the income of others in the same country, in an attempt to overcome variations in absolute wealth between nations. Creatinine clearance at the time of first dialysis was estimated using the equation of Cockcroft and Gault [11] and used as an indicator of residual renal function. Primary renal diagnosis (PRD) was coded using the EDTA codes and grouped using the method developed by the Scottish Renal Registry [12].


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Table 1.  Annual household income bands as % of GNP per capita [10]

 
Patients' pathways onto dialysis were categorized according to the duration of their follow-up by a nephrologist, the level of their serum creatinine in the months preceding initiation of renal replacement therapy (RRT) and the urgency with which their first dialysis treatment is undertaken. To address our hypotheses the main cohort was divided into early and late referral groups and the early referral group further subdivided into planned and unplanned groups (Figure 1Go), as follows.



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Fig. 1.  Division of the cohorts into early vs late referral and planned vs unplanned.

 
Early vs late referral: patients were considered ‘early referral’ if they had been followed by a nephrologist for >1 month before their first dialysis (regardless of how well planned their first dialysis had been), and as ‘late referral’ if they had not been followed by a nephrologist for >1 month before their first dialysis.

Planned vs unplanned (early referral patients only): patients referred to a nephrologist >1 month before their first dialysis were considered ‘planned’ if they had had a previously documented serum creatinine >300 µmol/l and their first dialysis had been arranged in advance and had not been performed urgently for life-threatening renal insufficiency. All other early referral patients (including all those without a previously documented serum creatinine above 300 µmol/l) were considered ‘unplanned’.

QoL was measured 8 weeks after the initiation of dialysis using, where available, two generic instruments: a visual analogue scale (VAS) and a Short Form 36 (SF-36) (not available in Estonia). The VAS produces a score from 0 to 100 representing the patient's assessment of their general health on that particular day (0 indicates the worst imaginable health state and 100 the best). The SF-36 measures eight concepts of QoL (Table 2Go) with initial scores being transformed to produce scores from 0 to 100. Scores summarizing the physical and mental domains [13] were also studied. These summary scores have been standardized so that a UK general population would have mean physical (PCS) or mental component summary (MCS) score of 50 with a standard deviation of 10.


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Table 2.  Interpreting SF-36 scores [13]

 
Data were analysed using the statistical package SPSS (v. 10). Comparisons between groups were made using the Student's t-test and the Mann–Whitney U-test for continuous variables and the Chi-square and Fisher's exact tests for categorical variables. The independence of each variable's effect on QoL was tested using multiple linear regression. Given the diversity of the dialysis units taking part in the study, centre variables were created and centre-effect adjusted for in the multiple linear regression. A forward selection procedure was initially used with variables included at the P<0.05 and excluded at the P>0.20 threshold. The effect of early referral and planned first dialysis were then examined by entering these variables into separate models, including the previously identified significant variables.



   Results
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
Comparing responders and non-responders
262 out of 324 (80.9%) patients completed the VAS and 226 out of 280 (80.7%) completed the SF-36. Table 3Go shows the distribution of responders by centre. In centres where both the VAS and SF-36 were available, no responder completed one without completing the other.


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Table 3.  Number of patients responding per centre

 
Responders had significantly higher household income compared to non-responders [median income bands (%GNP per capita) 90–133 and 53–89%, respectively, P=0.01] but were similar in terms of age, co-morbidity and other socio-economic factors. Responders, therefore, had a median age of 61.6 years [inter-quartile range (IQR) 46–71], 59/262 (23%) had diabetes and 81/262 (31%) had cardiac disease.

196 of the 262 responders (75%) had been followed by a nephrologist for >1 month prior to their first dialysis (early referral), the majority of these (84%) having been referred >3 months prior to their first dialysis. The remaining responders (66) had been referred late (<1 month), with 64% referred within 2 weeks of their first dialysis. 126/196 (64%) of the early referral patients had had a planned first dialysis (planned) and 70/196 (36%) had not (unplanned).

Comparison of patient characteristics according to mode of presentation
Early referral patients had significantly higher haemoglobin levels [mean (SD) (g/l) 95.1 (17) vs 88.4 (17), P=0.008] and were more likely to be employed at the time of initiation of dialysis [35/196 (18%) vs 5/66 (8%), P=0.04] than patients presenting in the month before their first treatment. Early referral patients were also more likely to begin treatment on peritoneal dialysis [57/196 (29%) vs 7/66 (11%), P=0.002]. This difference in initial modality between early and late referral patients was found to be independent of co-morbidity, albumin and distance from the dialysis centre in binary logistic regression. Although a difference persisted, it was no longer significant by 90 days [63/196 (32%) vs 13/66 (20%), P=0.06]. Early referral patients commencing treatment on haemodialysis were markedly more likely than late referral patients to have permanent vascular access [71/139 (51%) vs 3/59 (5%), P<0.001]. There were no other significant differences between early and late referral patients (Table 4Go) and, in particular, no difference between the groups in residual renal function (Cockcroft and Gault) at time of initiation of dialysis.


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Table 4.  Descriptive statistics: all patients responding to the QoL questionnaires

 
Within the early referral cohort, planned haemodialysis patients were markedly more likely to have permanent vascular access than unplanned patients [65/89 (73%) vs 6/50 (12%), P<0.001]. Planned patients also tended to have higher baseline haemoglobin levels, but this difference did not quite reach statistical significance [96.9 (16) vs 91.9 (20), P=0.054]. There were no other significant differences between planned and unplanned patients and, again, no difference between the groups in residual renal function at time of initiation of dialysis.

Correlation between QoL instruments
Although no two instruments measure the same aspects of QoL, we found significant positive correlation between the VAS and the SF-36 PCS score (Spearman's correlation coefficient 0.72, P<0.01) and the MCS score (0.34, P<0.01).

QoL: the effect of early referral to a nephrologist
Univariate analysis. Although early referral patients had significantly higher mean VAS scores than those referred late [58.4 (20) vs 50.4 (19), P=0.005] (Table 5Go), this difference was non-significant when Tallinn, which was unable to contribute to the SF-36 data, was excluded from the VAS analysis (58.8 vs 53.4, P=0.09). Furthermore, we found no significant difference between early and late referral patients in any of the SF-36 summary scores or domain scores (Table 5Go).


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Table 5.  QoL results: all patients, early vs late referral patients and planned vs unplanned patients

 
Multiple linear regression. When all centres were included, patients referred early to a nephrologist had significantly higher VAS scores in multiple linear regression analysis than those referred late. However, exclusion of Estonian patients from the analysis resulted in the effect of early referral becoming non-significant.

QoL: the effect of having a planned first dialysis
Univariate analysis. Within the early referral cohort, planned patients had significantly higher VAS scores than their unplanned counterparts [60.7 (20) vs 54.2 (20), P=0.03] (Table 5Go). Planned patients also had significantly higher MCS scores [45.4 (12) vs 39.7 (11), P=0.003], role emotional scores [58.0 (43) vs 30.9 (38), P=0.003] and mental health scores [63.7 (24) vs 54.6 (22), P=0.01] (Table 5Go).

Multiple linear regression. The multiple linear regression model found two variables, co-morbidity (Charlson index) and centre, as well as planned status, to independently affect VAS scores (Table 6Go). After adjusting for other confounding variables, haemoglobin proved not to be independently associated with VAS score. Therefore, according to the model for VAS, the reference patient is one with no co-morbidity, dialysing in the reference centre (Aberdeen) and presenting to a nephrologist within 1 month of their first dialysis (late referral). Such a patient (represented in the Constant column, Table 6Go) would be expected to have a VAS of 60.8. An identical patient referred to a nephrologist >1 month before their first dialysis, would be predicted to have a VAS 7.8 points higher (95% CI +2.2 to +13.5, P=0.007) (Table 6Go). Following the same approach, the reference patient and the effect of having a planned first dialysis can be estimated for each dimension of QoL from the data provided in Table 6Go.


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Table 6.  Multiple linear regression: the effect of having a planned first dialysis on QoL

 
Patients whose first dialysis was planned had significantly higher MCS, physical functioning, role physical, general health, role emotional and mental health scores than those having an unplanned first dialysis (Table 6Go). Taking MCS as an example, the linear regression models suggest that the reference patient in Aberdeen with no co-morbidity and having an unplanned first dialysis would be expected to have a MCS score of 46.2. The same patient, had they had a planned first dialysis, would be expected to have a MCS score 4.3 points higher [constant 46.2, coefficient (95% CI) +4.3 (+0.6 to +8.0), P=0.02] (Table 6Go). Centre and co-morbidity accounted for much of the explainable variation (adjusted R2) in QoL—centre was found to be an independent explanatory variable for both the SF-36 summary scores and seven of the eight dimensions of the SF-36 (social functioning being the only exception) and the Charlson index had an independent effect on the two SF-36 summary scores and six of the individual QoL dimensions (not social functioning or bodily pain). Socio-economic indicators such as living arrangements and employment status were influential factors and independently explained part of the variation in role physical, bodily pain and the PCS scores, but none of the variation in mental aspects of QoL (Table 6Go).



   Discussion
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
This study has demonstrated that, among patients referred early to a nephrologist, those having a smooth transition onto dialysis have significantly better QoL than those having an unplanned first dialysis. The QoL benefits of early referral to a nephrologist are less strong and appear to come predominantly from one centre, Tallinn in Estonia.

One question that is often raised in relation to QoL research is the clinical relevance of the results. Conventionally a 5–10% change in a health outcome is considered clinically significant, so a 10-point rise in QoL for data that has been transformed to produce scales from 0 to 100 should be considered of clinical importance. It is also possible to measure Cohen's effect size [the difference between the means divided by the standard deviation of the control group (unplanned patients)] [14]. First described 40 years ago, this method has been applied to all aspects of health outcomes research including QoL research. An effect size of 0.2–0.5 is considered small, 0.5–0.8 moderate and >0.8 large. The difference in role emotional scores between planned and unplanned patients according to the linear regression can therefore be considered moderate (effect size 0.6). Although the difference between planned and unplanned patients in VAS scores and four of the SF-36 scales (MCS, physical functioning, role physical and general health) was lower, it was only just below the moderate effect range (0.4). An alternative approach is to consider the increase in QoL relative to the increase that would be required to return ESRD patients' QoL to that of the general population. The mean VAS of a Scottish general population is 85 [15] and the VAS of our reference patient (in Aberdeen with no co-morbidity and whose first dialysis was unplanned) was 60.8, a difference of 24 points. The linear regression model suggests that having a planned first dialysis would result in such a patient having a VAS 7.8 points higher, thus reducing the difference between the ESRD and general population by 33%. A similar approach can be taken to look at the effect of having a planned first dialysis on PCS and MCS, which should both have general population means of 50 and SD of 10. To consider the problem instead at the patient level, concurrent data within the SF-36 can help understand the clinical relevance of the scales. For example, data from the SF-36 manual [13] suggests that the rise in general health score of 6.0 points in our reference patient from a baseline of 53.9 (Table 6Go) would, at a group level, result in a 50% increase in the percentage of patients who describe their health as excellent (3.3–4.9%) and a 60% reduction in the percentage of patients describing their health as fair or poor (21.1–8.3%) (Table 9.2 in Ware et al. [13]). Similar exercises can be carried out for most of the other dimensions of the SF-36.

Although QoL (by VAS) was significantly better in the early referral patients independent of other confounding variables, the difference was not significant when patients in Estonia, where the SF-36 was not available, were excluded. This suggests that the beneficial effect of being followed by a nephrologist on VAS scores came predominantly from this centre. The reduced effect of early referral on VAS scores when this centre is excluded may partly explain why early referral seemed to have no effect on any aspect of the SF-36. No such effect was seen on the effect of having a planned first dialysis on QoL (by VAS) when the Tallinn centre was excluded, so the effect should not simply be due to the reduction in the number of patients being studied.

The better QoL observed in planned patients was found to be independent of co-morbidity and other factors, suggesting that the benefits of a smooth, planned transition onto dialysis does not just represent the selection of patients with fewer co-morbid illnesses. During the design of the study we hypothesized that, within the cohort of patients referred early to a nephrologist, patients having an unplanned first dialysis may be a group whose care could be improved by better preparation for, and more opportune timing of, the initiation of dialysis. Acute factors causing the first dialysis to be unplanned may not necessarily be beyond the control of the nephrologist. For example, if the initiation of dialysis is delayed until a patient becomes fluid overloaded or uraemic and develops pulmonary oedema or a chest infection, were these factors really beyond the control of the nephrologist? As with all observational studies, however, demonstrating an association between planned status and QoL does not necessarily indicate causality. Differences in the physical or mental state of patients may have already existed in the pre-dialysis phase, and indeed these may in some way have influenced whether or not patients had a planned first dialysis.

The positive relationship found in this study between socio-economic factors such as living arrangements, employment status and income and certain aspects of QoL, has been documented previously [7]. In our study, differences in the value of money between countries had to be overcome and patient's income measured relative to the income of others in the same country rather than in absolute terms. Using this approach, socio-economic characteristics explained part of the variation in physical QoL among patients in the early referral cohort, but had no significant effect on mental QoL. This may be partly explained by the larger reduction in physical QoL compared with the mental QoL seen in patients with renal failure (Table 5Go) making differences in physical QoL easier to detect. Alternatively, the significant effect of a patient's socio-economic status on physical QoL may reflect their higher physical functioning improving their employment opportunity rather than the employment improving their physical functioning—cause rather than effect. Longitudinal analysis of the QoL data on these patients will be required before we can comment on the effect of socio-economic factors on the recovery or otherwise of patients' QoL over time as a result of the dialysis treatment they receive. Furthermore, because responders generally had higher annual household incomes than non-responders, we are perhaps overestimating the QoL of our ESRD patients and underestimating the effect of socio-economic factors on ESRD patients' QoL. This is a useful reminder of the important influence of socio-economic status on QoL, not only in responders, but also in non-responders in QoL studies.

It is also possible that our results have underestimated the size of the effect of having a planned first dialysis on early QoL for another reason. Although it is easy to identify and assess patients who have been followed for years in the nephrology clinic and who have a smooth transition onto dialysis, assessing those patients presenting with acute renal failure that does not recover is more difficult. We chose to measure QoL in all patients at the same point in time after the first dialysis, i.e. 8 weeks, thus allowing all patients an equal opportunity to adapt to their new treatment. One inevitable consequence of delaying assessment of QoL is that it introduces an element of selection bias, and this may affect some groups (e.g. those referred late and those with poorer QoL) to differing extents. However, the direction of this bias is probably towards the null, so that the true benefit of being referred to a nephrologist early and having a planned first dialysis might actually be larger than we have observed.

The risk stratification systems used in this study to quantify co-morbidity [8,9] had originally been developed to predict mortality and we could not therefore assume that they would accurately predict QoL. For this reason the effect of co-morbidity on QoL was examined in all analyses both by keeping individual co-morbidities separate and by combining them in one of the two risk stratification systems [8,9]. The results of linear regression models using the individual co-morbidities and Wright's combined age co-morbidity scoring system [8] were less powerful at predicting QoL than those using the Charlson score [9] and have therefore not been presented. This finding suggests that, although originally developed to predict survival in breast cancer patients in North America, the Charlson score is as able, if not more able, to predict baseline QoL in ESRD patients as to present co-morbidity data individually or in association with age. Whichever method was used to adjust for co-morbidity and despite the detailed patient data available, the variance explained by the linear regression models (adjusted R2) remained fairly low (17, 27 and 18% for the VAS, PCS and MCS, respectively) (Table 6Go). This finding, however, is consistent with the results of other QoL investigators [7]. There are also theoretical reasons why multiple linear regression may not be ideal for data that do not have interval scale properties, but its application in QoL research, including SF-36 data, has become accepted practice [7] and it has proven fairly robust to departures from its assumptions.

A recent analysis by the NECOSAD group has suggested that the apparent benefits of early initiation of dialysis may be largely explained, if not negated, by the lead time effect [16]. Using the Cockcroft and Gault formula [11] to estimate residual renal function, our study found no evidence that either patients followed by a nephrologist for >1 month (early referral) or the sub-group of those having a planned first dialysis (planned) started dialysis earlier (or later) than those in the late referral or unplanned groups. We also found no suggestion that older patients were more likely to present late for dialysis or have an unplanned first dialysis. Moreover, there was no significant difference in age demonstrable between patients in the early and late referral groups or between those in the planned and unplanned groups.

This study highlights some of the practical difficulties and complexities that arise in international health outcomes research when QoL instruments are not universally available. The use of more than one instrument when assessing QoL is generally recommended [17], and as this work is part of a larger study of cost-effectiveness we chose generic rather than disease-specific QoL tools. We found only one instrument, the VAS, that was available for all countries, and indeed this quick, simple tool proved able to detect differences between the cohorts. We also required, however, an instrument that would provide more detail about where the differences in QoL lay, the SF-36, but this had not yet been translated and validated for one of the seven countries. Although evidence of measurement equivalence among the different language versions of QoL instruments in different countries has been slow to accumulate [18], general population comparisons have now been carried out for, amongst others, the VAS [19] and the SF-36 [20]. Some small but significant differences in general population results have been demonstrated [19,20] which are likely to inform the interpretation of international clinical trials, but not to negate them. There are not yet sufficient data available on general population QoL to move on and understand the role that variation in general population QoL has had on the QoL of the dialysis patients studied in this work. Furthermore, although we have been able to adjust for centre variation in the multiple linear regression models and increase the validity of our conclusions, the number of centres and patients recruited in each country were insufficient to examine robustly the effect of nationality on QoL in dialysis patients.

We believe our study to be one of the first to examine QoL prospectively in ESRD patients in several different countries and as such it creates new possibilities for studying health outcomes achieved by our patients. We view this as a first step towards not only combining QoL data across international boundaries to make the results of studies more generalizable, but it may also ultimately allow us to compare QoL outcomes between dialysis patients in different countries. To this end, the next step should be to compare these outcomes in patients from renal units serving areas with a defined population base in different countries.



   Conclusions
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 
International collaborative studies examining QoL are complicated by a lack of universally available QoL instruments. Our study has shown that until QoL tools become ubiquitous, a process that is held up by the laborious and expensive nature of the translation and validation process, a simple, easy-to-produce VAS can be used to generate a score for QoL. Such an instrument could be used alongside other validated, more detailed instruments where these are available, but has shown itself to be sensitive to treatment effects.

Socio-economic status has a pivotal role in determining patients' physical QoL in the early months of dialysis, and making allowances for it, although not always straightforward, is of vital importance.

Although early referral of patients with chronic renal failure to a nephrologist may be associated with improved QoL, the effect of having a planned, smooth transition onto dialysis appears more important, and in this study seemed to occur without evidence of dialysis being commenced at an earlier stage of the disease. Our findings suggest that the QoL of our ESRD patients could be significantly improved by reducing the proportion of patients followed by a nephrologist with chronic renal failure who require an urgent first dialysis.



   Acknowledgments
 
We would like to thank all those involved in the collection of the health outcomes data in each of the centres: Medical University of Debrecen, Hungary; Ninewells Hospital, Dundee, UK; Centre Hospitalier Universitaire de Nantes, France; University Medical Centre, Nijmegen, The Netherlands; St Petersburg Medical Institute, Russia; Tallinn Pelgulinna Hospital, Estonia; Hippokration General Hospital, Thessaloniki, Greece; Veria General Hospital, Greece; and the Aberdeen Royal Infirmary, UK. In particular, we would like to thank Ms Carol A. Ritchie for her invaluable assistance with the data collection and data management in the co-ordinating centre, the University of Aberdeen. This study was funded as part of Framework IV, the Biomedical research programme of the European Commission (contract no. BMH4-98-3237). HERU receives core funding from the Chief Scientist Office Scottish Executive Health Department.

Conflict of interest statement. None declared.



   Notes
 
Correspondence and offprint requests to: Dr Fergus J. Caskey, Renal Research Group, Medicine and Therapeutics, Polwarth Building, Foresterhill, Aberdeen AB25 2ZD, UK. Email: f.caskey{at}abdn.ac.uk Back



   References
 Top
 Abstract
 Introduction
 Subjects and methods
 Results
 Discussion
 Conclusions
 References
 

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Received for publication: 13. 8.02
Accepted in revised form: 31. 1.03