1Department of Renal Medicine, Birmingham Heartlands Hospital, Birmingham, UK, 2University Renal Research and Education Association, Ann Arbor, Michigan, USA, 3Nephrology Section, University of Heidelberg, Heidelberg, Germany, 4Nephrology Department, Lapeyronie University Hospital, Montpellier, France, 5Clinic for Nephrology, Hypertension and Dialysis, Augusta-Kranken-Anstalt, Ruhr University, Bochum, Germany, 6Department of Nephrology and Dialysis, A. Manzoni Hospital, Lecco, Italy, 7Nephrology Service, Hospital General Vall dHebron, Barcelona, Spain, 8Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA and 9Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
Correspondence and offprint requests to: Dr Friedrich K. Port, MD, MS, University Renal Research and Education Association, 315 W. Huron St, Suite 260, Ann Arbor, MI 48103, USA. Email: fport{at}urrea.org
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Abstract |
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Results. In the UK, 28.1% of haemodialysis patients received prior peritoneal dialysis treatment compared with 4.28.3% in other countries. Kidney transplantation rates ranged from 3.3 (per 100 patient years) in Italy to 11.6 in Spain. The relative risk (RR) of mortality, adjusted for age, sex and diabetes status was significantly higher in the UK (RR = 1.39, P = 0.02) compared with Italy (reference) and increased in association with age (RR = 1.60 for every 10 years older, P <0.001), diabetes as cause of end-stage renal disease (ESRD) (RR = 1.55, P < 0.001), male patients <65 years (RR = 1.29, P = 0.02) and peritoneal dialysis in the 12 months prior to starting haemodialysis (RR = 1.72, P = 0.06). Hospitalization for cardiovascular disease was highest in France and Germany (0.40 and 0.43 hospitalizations per patient year, respectively) and lowest in the UK (0.19), although cardiovascular comorbidity was similar in the UK and France. Hospitalization rates for vascular access-related infection ranged from 0.01 hospitalizations per patient year in Italy to 0.08 in the UK, consistent with the higher dialysis catheter use in the UK (25%) vs Italy (5%). Hospitalization risk was significantly higher in France than in other Euro-DOPPS countries and was significantly (P < 0.05) associated with prior peritoneal dialysis therapy, peripheral vascular disease, gastrointestinal bleeding in the prior 12 months, diabetes, cancer, cardiac disease, psychiatric disease and recent onset of ESRD (within 30 days of study entry).
Conclusions. The large differences in haemodialysis practice and outcomes in the Euro-DOPPS countries suggest opportunities for improvement in patient care.
Keywords: haemodialysis; hospitalization; international comparison; mortality; outcomes; practice patterns
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Introduction |
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Although the primary goal of the DOPPS is to identify haemodialysis practices associated with improved outcomes for patients, interest exists within the nephrological community in identifying geographic variation in outcomes, as well. Thus, this paper reports mortality and hospitalization results for haemodialysis patients treated in the five European countries in Phase 1 of the DOPPS. Two other papers focusing upon specific haemodialysis practices in these same countries appear in this issue [1,2]. Furthermore, more than 20 DOPPS papers have been accepted for publication, covering a variety of haemodialysis practices and outcomes [35; www.dopps.org/publications.php (accessed June 2, 2003)].
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Subjects and methods |
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Facilities participating in Euro-DOPPS were randomly selected from a list of all dialysis units within each country. Only facilities having >24 haemodialysis patients were eligible for study participation. These facilities typically serve >95% of all facility-based haemodialysis patients in each country. Selection was stratified, such that facility samples provide proportional representation of the types of haemodialysis units and geographic regions within each country. Among randomly selected facilities, >90% agreed to participate. Data were collected from Euro-DOPPS dialysis units from May 1998 through November 2000, with 98% of all participating dialysis units entering DOPPS between May 1998 and February 1999. Additional details of the DOPPS data collection protocol and study design have been described previously [7].
Data source: patient samples used for analysis
Census patients (n = 11,422). Limited data were collected at each participating Euro-DOPPS dialysis unit for all patients who were >17 years old and receiving chronic maintenance haemodialysis, haemodiafiltration or haemofiltration. For this group of patients (census patients), the following data were collected: patient age, gender, race, whether diabetes was primary cause of end-stage renal disease (ESRD), date and reason for patient entry and departure from the dialysis unit and date of death (if applicable). Census patients included all haemodialysis patients treated at participating DOPPS units at any time during the study. The mean study observation time was 1.07 years per census patient.
Random sample patients (n = 4591). A sample of patients was selected randomly from the list of census patients at the beginning of the study to achieve an average of 30 patients per facility (range: 2040 patients per facility, dependent on facility size, with an average facility size of 60 haemodialysis patients). For these random sample patients, detailed longitudinal data were collected, including patient demographics, and more than 65 indications: baseline comorbidity, measures of socioeconomic status, baseline and longitudinal laboratory data, vascular access use and procedures, hospitalization and outpatient events, characteristics of haemodialysis treatment, prescribed and delivered haemodialysis dose, medications, measures of anaemia and mineral metabolism management, residual renal function, patient quality of life assessments, primary causes of ESRD, modality history during ESRD and pre-ESRD care.
Informed patient consent was obtained, with consent rates approaching or exceeding 90% in each country. To maintain an approximately constant random-sample patient cohort over time, additional randomly selected patients entering the unit since the time of the previous random selection were chosen routinely to replace random sample patients who left the study for any reason (e.g. death, transfer to a different facility, change in modality and transplant). The total number of random sample patients per country for whom data were collected was: France (n = 981), Germany (n = 908), Italy (n = 869), Spain (n = 936) and the UK (n = 897).
Data were collected using standardized questionnaires translated into the national languages. In addition to patient data, information regarding different facility practices was collected from annual questionnaires completed separately by the dialysis unit medical director and nurse manager.
Statistical methods
These analyses include various subgroups of patients, as delineated below. For each analysis, the largest appropriate group of patients was included.
Descriptive statistics. Descriptive statistics were calculated for a prevalent sample of patients (n = 6109) at time of facility entry into the DOPPS, in order to compare specific baseline characteristics by country. Statistics concerning patient demographics and percentage of patients for whom diabetes was the primary cause of ESRD were calculated from the census patient sample (n = 6109), whereas other baseline characteristics (average number of years on renal replacement therapy, percentage of patients with prior peritoneal dialysis therapy, percentage catheter use and percentage tunnelled catheter use) were only available from data collected from the random sample patient group (n = 2590).
To evaluate the frequencies for different causes of ESRD by country and mean age of ESRD onset, the analysis was based on new (incident) ESRD patients who entered the DOPPS within 30 days of their first treatment as chronic dialysis patients (n = 1192). This incident patient sample was more appropriate than a prevalent patient sample, as it avoided survivor bias resulting from higher death rates for certain ESRD causes.
Country rates for kidney transplantation were calculated using all census patients participating in the study (n = 11 422) and compared for patients 1865 years and 6675 years old.
Outcomes analysis: mortality. The comparison of crude and adjusted mortality rates, by country, was performed using census patients, since this provided a sample size 2-fold larger than would be possible if random sample patients had been used. The census patient data provided adjustments for age, gender and diabetes (as cause of ESRD). Country mortality rates were calculated based on all census patients participating in the DOPPS during the 1 year time period from 1 May 1999 to 30 April 2000 (n = 9050). This particular period was chosen as all dialysis units were participating in the Euro-DOPPS during this timeframe. In sensitivity analyses, mortality rates were calculated for four other 1 year intervals, starting on the first days of January, February, March or April 1999. The mortality rates calculated from 1 May 1999 to 30 April 2000 were representative of those obtained using these other 1 year time intervals.
The following start and censoring dates were used in performing these mortality analyses: the patient start date was 1 May 1999 for patients who entered the study on or before 1 May 1999; this was the study enrolment date for patients entering the DOPPS between 1 May 1999 and 30 April 2000. Observation time was censored at one of three points, whichever was earliest: date of patient departure from the facility, last date of known follow-up or 30 April 2000. This start-date convention assumes an exponential survival distribution, which has been observed in DOPPS data.
Crude mortality rates by country were expressed as deaths per patient year. Confidence intervals (CIs) for unadjusted country mortality rates were obtained using unadjusted Poisson models. Relative risks (RR) of mortality by country were determined using Cox regression modelling for time to death with adjustment for age, gender and diabetes (as cause of ESRD), country and facility clustering effects. Italy is presented as the reference group for the adjusted mortality analyses, since its crude mortality rate was intermediate among the five Euro-DOPPS countries.
Crude mortality rates were also calculated for a cross-sectional (point-prevalent) sample of census patients dialysing in each dialysis unit on 1 May 1999 (n = 6322). For these patients, this date served as the start for the mortality analysis, with observation time censored on the earliest of three possibilities: the date of patient departure from the facility, the last date of known follow-up or 30 April 2000.
To examine the relationship between mortality and prior peritoneal dialysis therapy, random sample patients treated between 1 May 1999 and 30 April 2000 were used, since information regarding prior peritoneal dialysis therapy was collected for random sample patients but not for all census patients. Complete data on 4069 patients in this sample were available to allow adjustments for age, gender, years of ESRD, country and 14 classes of comorbidity, including coronary artery/cardiac disease, congestive heart failure, other cardiac disease, peripheral vascular disease, hypertension, cerebrovascular disease, diabetes mellitus, lung disease, dyspnoea, cancer, gastrointestinal bleed in the 12 months prior to study entry, neurological disease, psychiatric disease and recurrent skin disease (e.g. cellulitis and gangrene).
Outcomes analysis: hospitalization. Hospitalization analyses were performed using random sample patients, since hospitalization information was collected for this sample, but not for all census patients. Country hospitalization rates were calculated based on all random sample patients participating in the DOPPS during the 1 year time period from 1 May 1999 to 30 April 2000 (n = 4124).
Crude hospitalization rates were calculated as the total number of hospitalizations per patient year at risk. Time spent in the hospital was excluded from time at risk.
Adjusted relative risks of hospitalization by country were estimated using Cox regression for modelling time to first hospitalization. For these analyses, a patient's start date was the same as indicated for the mortality analyses. Time was censored at whichever was earliest: the date of patient departure from the facility, the last date of known follow-up or 30 April 2000. These analyses were adjusted for age, gender, initiation of dialysis within 30 days prior to study entry, years of ESRD, country, whether the patient had received peritoneal dialysis prior to entry into the DOPPS as a haemodialysis patient, country of residence, facility clustering effects and the same 14 classes of comorbidity indicated for some of the mortality analyses. Germany is presented as the reference group for the adjusted hospitalization analyses, as its crude hospitalization rate was intermediate among the five Euro-DOPPS countries.
Crude hospitalization rates also were calculated for a cross-sectional (point-prevalent) sample of random sample patients dialysing in each unit on 1 May 1999 (n = 2969).
All statistical analyses were performed using SAS version 8.2 (SAS Institute, Cary, NC, USA). Cox regression analyses employed a robust standard error adjustment, based on the sandwich estimator [8], to account for facility clustering effects.
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Results |
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Further adjustments for 14 classes of comorbidity, incidence to ESRD, time on ESRD for non-incident patients and prior peritoneal dialysis use were performed on a smaller subset of patients for whom these data were available (Table 7). This analysis revealed a high risk of mortality for patients who had been on peritoneal dialysis within the 12 months prior to entering the DOPPS as a haemodialysis patient (RR = 1.72, P = 0.06).
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Discussion |
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The rates of mortality and hospitalization show significant variations among the five Euro-DOPPS countries. The mortality rates from the DOPPS are very similar to the mortality rates reported by the national registries from Germany, Spain and the UK. Registry-report mortality rates were: Germany, 16.9% (year 2000, haemodialysis and peritoneal dialysis patients) [www.quasi-niere.de (accessed December 24, 2002)]; Spain, 13.4% (year 2000, haemodialysis patients) [www.senefro.org/registro.htm (accessed December 24, 2002)]; and the UK, 18.0% (year 1999, haemodialysis and peritoneal dialysis patients) [www.renalreg.com (accessed December 24, 2002)]. Comparable data were not available for France. In Italy, the registry reports a lower mortality rate than observed in the DOPPS sample [www.sin-ridt.org/sin-ridt/sin-ridt.org.htm (accessed December 24, 2002)]. The mortality rate reported by the Italian Registry is for home haemodialysis, peritoneal dialysis and in-centre haemodialysis patients combined and only includes patients who have been on dialysis for 30 days. Similarly, it is difficult to compare causes of ESRD between the DOPPS and some registry reports because of differences in how the causes of ESRD are defined and categorized.
Further analysis and adjustment of the outcomes data have been made in an attempt to adjust for differences in age, gender, comorbidity and the like, which may influence results in different countries. To the extent that adjustment works to make these factors more equal, underlying differences in mortality may be clarified and correlations with haemodialysis practice patterns may be sought. Statistical stratification by country allows evaluation of consistency of patterns across all countries. Analysis of hospitalization is a further means of identifying countries with haemodialysis practices that are associated with better patient outcomes.
Mortality
Increasing age was found to be strongly associated with an increased mortality risk in analyses adjusted for age, gender and diabetes as cause of ESRD. The mortality hazard ratio of 1.60 per 10 year increase in age was higher than the range reported in a meta-analysis [9] of the literature (95% CI: 1.131.45). However, when Euro-DOPPS analyses were adjusted for gender and 14 different classes of comorbidity, the mortality hazard ratio declined to 1.45 per 10 year increase in age. This latter hazard ratio indicates that age captures the effect of comorbidities that are not included in the mortality model.
Mean age in the prevalent sample would be affected by the average age of patients entering the pool on haemodialysis and the age of patients lost from the pool to transplantation, peritoneal dialysis, home haemodialysis or death. Transplantation rates varied 34-fold across the five Euro-DOPPS countries and were almost exclusively confined to patients aged <66 years. Since transplants tend to be given to healthier patients, a country with a high transplantation rate would tend to have older patients and a haemodialysis population with greater comorbidity. The average ages by country for haemodialysis patients starting ESRD (i.e. incident) ranked the same as was observed for prevalent patients. The average age of the prevalent sample was highest in Italy (Table 1). The average age of the prevalent sample was lowest in the UK, even though the UK had a relatively high transplantation rate for patients aged <65 years (Table 4) and a high rate of peritoneal dialysis use (Table 2). The mean age of patients with ESRD commencing peritoneal dialysis in the UK is lower than that for haemodialysis [www.renalreg.com]. The sample populations were >93% of Caucasian origin, except in the UK (83%).
The relationship between gender and mortality was not statistically significant when adjusted for patient characteristics and country. However, mortality was significantly greater in male patients aged <65 years compared with female patients aged <65 years (RR = 1.29, P = 0.02; Table 6). Men had higher death rates in a US dialysis population study [10].
The prevalence of diabetes as the cause of ESRD varied >2-fold among countries (Table 1). The risk of mortality associated with diabetes (RR = 1.55, P < 0.001; Table 6) is similar to that reported previously by Marcelli et al. [11] in comparing adjusted dialysis patient mortality in the US with that of the Lombardy Dialysis and Transplant Registry. In addition, the risk of mortality associated with diabetes also is within the 95% CIs for many of the studies described by Johnson et al. [9] in reviewing the literature in this area.
Adjustment of the mortality analysis for age, gender and diabetes as cause of ESRD was performed on the complete population of haemodialysis patients dialysing in the participating dialysis units in a 12 month period. The adjusted mortality rates did not differ significantly between France, Germany, Italy and Spain (Table 6). However, the RR of mortality was significantly higher in the UK (RR = 1.39, P = 0.02) compared with Italy as the reference country, which had an intermediate mortality rate. This difference was more marked in patients aged <65 years (RR = 1.84, P = 0.002) than those >64 years of age (RR = 1.24, P = 0.18). Countries with higher transplantation rates or having a high proportion of patients with prior peritoneal dialysis showed a marked difference in relative risk of mortality in patients aged <65 years compared with those >65 years old, consistent with a selection bias due to these factors in the younger age group. It is likely that country outcome rates are influenced by the degree to which factors such as rate of transplantation, use of peritoneal dialysis and access to care affect the composition of patients remaining in the haemodialysis population. Consequently, caution should be used in interpreting comparisons of country mortality rates, despite extensive efforts to adjust for differences in patient comorbidities and demographics.
Adjustments for comorbidity and prior peritoneal dialysis therapy were possible on a smaller sample of patients studied in more detail (Table 7). Because of its smaller size, the subsample was not used for comparing adjusted country mortality rates, but was used to describe the relationship of various patient characteristics with mortality in the whole of Euro-DOPPS. Patients who had peritoneal dialysis therapy within the 12 months prior to haemodialysis treatment displayed a substantially greater risk of mortality (RR = 1.72), with this risk bordering on statistical significance (P = 0.06). Conversion from peritoneal dialysis to haemodialysis may occur because the patient is no longer able to manage peritoneal dialysis at home or because of peritoneal dialysis treatment failure. This may exert a biasing effect on the outcomes of the haemodialysis population through a number of mechanisms. First, patients who are at increased risk of converting to haemodialysis may be independently at an increased risk of mortality. For example, patients with cerebrovascular disease who suffer a stroke may have to change to haemodialysis and will independently be at an increased risk of mortality. This effect should be excluded, as the analysis has been adjusted for cerebrovascular disease. Second, the cause of peritoneal dialysis treatment failure, such as inadequate dialysis clearance or peritonitis, may be directly associated with increased mortality during the subsequent period of haemodialysis. There are only limited published data describing the reasons for transfer from peritoneal dialysis to haemodialysis. In a single-centre study from Belgium, of 32 patients, 50% changed to haemodialysis because of peritonitis or exit site infection and 25% because of inadequate dialysis or ultrafiltration problems [12]. Mortality was not increased in this small group of patients transferring to haemodialysis compared with a matched haemodialysis group. Third, starting haemodialysis in patients previously on peritoneal dialysis may be associated with an increased risk of mortality. In particular, many patients on peritoneal dialysis do not have a functioning arteriovenous fistula when starting haemodialysis and so require a temporary dialysis catheter for initiating haemodialysis. Studies in the DOPPS and two other populations have demonstrated a significant association between the use of dialysis catheters and mortality [5,13,14]. Consistent with this association, the use of haemodialysis catheters and peritoneal dialysis was much higher in the UK than in the other four countries. Change of dialysis modality also has been shown to be associated with a significant increased mortality risk, independent of age and comorbidity, in an analysis of the Danish European Dialysis and Transplant Association register [15]. Furthermore, compared with patients receiving only haemodialysis since ESRD onset, Ganesh et al. [16] have recently shown transfer from peritoneal dialysis to haemodialysis to be associated with a higher risk of death (RR = 1.431.68, depending on whether or not the patient had diabetes and/or coronary artery disease, P < 0.001 in each case).
It is important to emphasize that demonstrating an association between prior peritoneal dialysis and an increased risk of mortality likely reflects issues related to failure of peritoneal dialysis leading to haemodialysis therapy. As this study only evaluates haemodialysis patients, it does not imply that peritoneal dialysis treatment overall has a higher risk of mortality compared with haemodialysis. Substantial variability has been observed in other studies regarding mortality risks for patients receiving haemodialysis vs peritoneal dialysis therapy. Some of these differences may be related to patient selection [1719] and preservation of residual renal function [20]. Nonetheless, these results do indicate a need for further studies of patients changing from peritoneal dialysis to haemodialysis in order to identify remediable factors that may reduce the subsequent risk of mortality. In addition, an implication of the higher mortality risk for haemodialysis patients who recently transferred from peritoneal dialysis is that the success of a peritoneal dialysis programme will depend, in part, upon it being backed up by a haemodialysis programme that allows rapid transfer of patients from peritoneal dialysis when clinically necessary.
Previous studies have demonstrated an increased mortality rate in patients starting haemodialysis without prior nephrological care [19]. The effect of late referral is most marked in the first 90 days, as a recent study found that the difference in mortality between early and late referred patients was no longer detectable after 3 months of ESRD [21]. Only moderate differences are found between the Euro-DOPPS countries in the proportion of patients starting haemodialysis without prior nephrological care [3].
Data have not been presented on the cause of death in the study population, as the exact cause of death was often uncertain or unknown, rendering the analysis unreliable. In contrast, the reason for hospitalization appeared to be more reliably determined from patient hospital records.
Hospitalization
In-patient care is one of the costliest elements of haemodialysis treatment [22]. Marked variation in hospital admission rates was found across countries. The differences among countries in the crude rate of hospitalization did not mirror the patterns for crude mortality rates. For example, crude mortality rates in France and Italy were quite similar, whereas the crude hospitalization rate in France was nearly double that in Italy. The mean length of stay varied also between countries, ranging from 8.7 days in the UK to 14.7 days in Germany (median length of stay varied from 4 to 10 days for these countries). Day case treatment was excluded from this analysis.
Factors affecting the rate of hospitalization and the average length of each admission include the clinical reason for admission, the treatment protocols of the medical and nursing teams, the availability of hospital beds and the arrangements surrounding financial reimbursement. In the US, differences in length of stay have been reported to be associated with the specialty and nephrological experience of the admitting physician, being shorter when the in-patient stay is managed by a nephrologist than by an internist or general physician [23]. The wide variations among countries suggest marked differences in the way in-patient care is organized within countries, an observation that deserves more detailed clinical and health economic analysis.
Hospitalization analyses were also adjusted for patient characteristics. These analyses were based on rates of first admission from the start of the study analysis period. Factors associated with a significantly increased risk of first hospitalization were prior peritoneal dialysis treatment, peripheral vascular disease, diabetes, cancer, cardiac disease, psychiatric disease, gastrointestinal bleeding in the prior 12 months and start of ESRD within 30 days of study entry. Peritoneal dialysis treatment within 12 months prior to study entry was strongly associated with an increased risk of hospitalization (RR = 1.73, P < 0.001), particularly in patients 1864 years of age (RR = 2.18, P < 0.001) (Table 11). Patients with an increased risk of converting to haemodialysis may be independently at an increased risk of hospitalization. Adjustment for comorbidity should exclude most of this effect. Furthermore, the cause of peritoneal dialysis treatment failure, such as inadequate dialysis clearance or peritonitis, may carry over to hospitalization during the subsequent period of haemodialysis. Finally, starting haemodialysis in patients previously on peritoneal dialysis may require admission for vascular access reasons.
In interpreting the reasons for hospitalization, one can distinguish between admissions resulting from complications of haemodialysis treatment and admissions for the treatment of comorbid conditions unrelated to haemodialysis. Differences in the rate of admissions for vascular access between countries were closely related to the prevalence of catheter use, which was significantly greater in the UK. Differences among countries regarding the pathway of care leading to arteriovenous fistula use have been previously reported [3]. The significantly greater relative risk of hospitalization of patients aged <65 in the UK, after adjustment for demographics, comorbidity and prior peritoneal dialysis treatment, may be related to the much higher prevalence of catheters in this age group compared with the other countries (Table 10).
Rates of admission for cardiovascular disease varied >2-fold between the UK (0.19 per patient year) and Germany (0.43 per patient year). The relatively high rates of cardiovascular admission in Germany correspond to the relatively high prevalence of moderate or severe coronary artery disease (44%) and congestive heart failure (23%). These differences in the prevalence of cardiovascular comorbidity are consistent with a previous EDTA report [24]. In contrast, the low rate of admission for cardiovascular disease in the UK was disproportionate to the high prevalence in the UK of moderate or severe coronary artery disease (30.4%) and congestive heart failure (32.9%) [2]. Greater use of in-patient care for cardiovascular disease has been associated with lower mortality [25]. This suggests there may be an underutilization of in-patient treatment for cardiovascular disease in haemodialysis patients in the UK.
Conclusions
Differences in patient mix and causes of ESRD were observed for haemodialysis patients treated in the five Euro-DOPPS countries. Adjustment for differences in age, gender and diabetes as cause of ESRD has provided a comparison of mortality risks across these countries. Older age, diabetes as cause of ESRD, male gender for patients 1864 years of age and peritoneal dialysis therapy within the 12 months prior to study participation were associated with significantly higher mortality risk. A 34-fold difference in kidney transplantation rates was seen across the Euro-DOPPS countries and a 7-fold difference was seen in the percentage of patients having had peritoneal dialysis therapy prior to study entry. Furthermore, crude hospitalization rates and mean length of hospital stay varied nearly 2-fold across the Euro-DOPPS. Differences in hospitalization rates across countries did not match differences in mortality rates. Causes of hospitalization differed substantially by country and risk of hospitalization was significantly increased for patients who had peripheral vascular disease, gastrointestinal bleeding in the prior 12 months, recent onset of ESRD, diabetes, cancer, cardiac disease and psychiatric disease. The disproportionality between cause-specific hospitalization rates by country and level of comorbidity suggests a need for further examination of whether hospital services are underutilized in some settings for certain types of patient comorbidity.
These results regarding mortality and hospitalization in the Euro-DOPPS provide an important framework for future investigations to explore facility practices leading to improvements in haemodialysis patient outcomes. The DOPPS design of focused representative samples serves as a tool for analysis of outcomes in a timely and powerful fashion.
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Acknowledgments |
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Conflict of interest statement. D. A. Goodkin is a former employee of Amgen Inc. and holds stock in Amgen, the makers of Epogen and Aranesp, although these products are not directly relevant to this manuscript. The remaining authors declare no conflicts of interest.
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Notes |
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Professor E. Hecking died 18 September 2002
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References |
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