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The cause is that age and comorbidity of these patients is increasing. On the other hand, there are notable differences in morbidity and mortality among countries. Thus, even when adjusted for age and comorbidity, mortality is higher in the U.S. than in Europe; in Japan it is still lower. Therefore, it should be interesting to compare the epidemiology of this population and the treatment methods among the different countries.<span class="elsevierStyleSup"> </span>Great prospective observational studies, like the Dialysis Outcomes and Practice Patterns Study (DOPPS)<span class="elsevierStyleSup">3</span> and the United States Renal Data System Dialysis Morbidity and Mortality Wave II<span class="elsevierStyleSup">4,5</span> have provided numerous data and valuable information about which clinical HD practices show the best results. In Europe, there are also many epidemiological prospective studies that describe the incident HD population.<span class="elsevierStyleSup">6-12</span> In Spain, we have the ANSWER study, carried out in 2341 HD incident patients during 2003 and 2004.13-15</p><p class="elsevierStylePara">The methodology used in the studies is fundamental when it comes to evaluating the validity of the findings and extrapolating the results to other populations. Records that require data to be collected online and that are mandatory are of great value. In general, prospective studies in incident patients are easier to interpret than those carried out with prevalent cohorts of patients. The sample population is another important factor. Studies that collect data from all the population, as opposed to a sample, avoid the inherent disadvantages of the sampling technique. The EuCliD<span class="elsevierStyleSup">®</span> database, implemented in the Fresenius Medical Care in Spain (FME) fulfils all of these requirements: mandatory online registry and includes all the HD population on their clinics. The EuCliD<span class="elsevierStyleSup">®</span> database has given rise to many publications with these characteristics.<span class="elsevierStyleSup">16-21</span></p><p class="elsevierStylePara">The main objective of this observational study of dialysed patients on the FME clinics is to understand the clinic's characteristics and treatment methods, comparing them with other studies from the literature and in order to improve patients’ prognosis and quality of life.</p><p class="elsevierStylePara"><span class="elsevierStyleBold"> </span></p><p class="elsevierStylePara"><span class="elsevierStyleBold">METHOD</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Observational descriptive study on HD patients in FME clinics in 2009 and 2010. Among the epidemiological data described are: demographic characteristics, personal and comorbidity history, dialysis and vascular access characteristics, laboratory data, medication received and data on patients' evolution during follow up (see list of variables of interest).</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Patient selection</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">We included all patients with chronic kidney disease on a HD programme from all FME clinics. We put together all incident and prevalent patients during 2009 and 2010 that were registered on the EuCliD<span class="elsevierStyleSup">®</span> database. Prevalent patients have been defined as the ones registered as of 1 January, 2009 who had been on HD more than three months. Incident patients are defined as patients that started HD in a FME clinic since October 2008 and that have been followed up for at least 3 months. We have accounted for all causes of loss of follow up, including functioning kidney transplant, transfer to another technique (peritoneal dialysis [PD]), transfer to another facility, death (both patients who died while under the responsibility of the dialysis centre, those who died during hospitalisation or those who were transferred and died in three months) and other losses of follow up</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">EuCliD<span class="elsevierStyleSup">®</span> database</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Our database was created from the data of patients included in EuClid<span class="elsevierStyleSup">®</span> (<span class="elsevierStyleBold">Eu</span>ropean <span class="elsevierStyleBold">Cli</span>nical <span class="elsevierStyleBold">D</span>atabase of Fresenius Medical Care). EuCliD<span class="elsevierStyleSup">®</span> is an information tool developed to monitor the treatment of patients in Fresenius clinics in Europe, the Middle East, Africa and Latin-America.<span class="elsevierStyleSup">22,23</span> All patients whose data are included on EuCliD<span class="elsevierStyleSup">®</span> sign the appropriate consent form. The database complies with the regulations for information protection. Data on dialysis treatment (HD and PD) including medication during treatment and at home, as well as incident and comorbidities, are registered prospectively. EuCliD<span class="elsevierStyleSup">®</span> is based on two main databases: the EuCliD<span class="elsevierStyleSup">®</span> tables and the database itself. The tables contain extensive information that includes, for example, the codification of diseases ICD 10 (International Classification of Diseases) from the World Health Organisation, the ATC code (Anatomical Therapeutic Chemical Classification System) for treatment with medication, its own codes for diagnostic trials, laboratory trials and consumables used. The tables are similar in all the centres that use EuCliD<span class="elsevierStyleSup">®</span> regardless of the country. Besides the tables, EuCliD<span class="elsevierStyleSup">®</span> includes the database itself, which gives it great value. It contains patients' demographics, history, physical examination, comorbidities, laboratory data and tests, treatment medication and dialysis, treatment follow up, inputs and outputs for different reasons (hospitalisation, transplantation, recovery of renal function, death, etc.) and their causes. EuCliD<span class="elsevierStyleSup">®</span> is based on a Lotus Domino server and Notes Client Platform, a computer program recognised worldwide for its ability to store great volumes of information. Access to EuCliD<span class="elsevierStyleSup">®</span>, properly protected, takes place online and allows us to design different levels of access to information according to the user’s profile. This database has been used for previous epidemiological studies.<span class="elsevierStyleSup">16-23</span></p><p class="elsevierStylePara">All patients included in the EuClid<span class="elsevierStyleSup">®</span> registry are required to sign a consent form for the utilisation of their information in compliance with the Agency for Data Protection regulations.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Variables of interest</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Number of centres with patients included, total number of studied patients, incident patients and prevalent patients. Epidemiological characteristics (incident and prevalent patients): start date of dialysis in FME centre, age at the start of dialysis, sex, aetiology of renal disease according to ICD 10, accompanying diseases according to ICD 10, body mass index (BMI)(first available during this time), weight and height (first available during this time) and time on dialysis. With respect to dialysis (incident and prevalent patients): type of vascular access (%), native arteriovenous fistula (AVF), arteriovenous fistula prosthesis (graft), permanent catheter (tunnelled) and temporary catheter (not tunnelled). Dialysis characteristics (6 months average): blood flow (ml/min), session duration (minutes), session frequency, dialysis technique: HD or post dilution on-line haemodialfiltration (OL-HDF), dialysis dose calculated according to eKt/V (applying Daugirdas 2nd generation formula and applying his correction for the urea rebound). Analytical data (incident and prevalent patients, average of 6 months): haemoglobin (Hb), transferrin saturation index, ferritin, total calcium, phosphorus (P), parathyroid hormone, C-reactive protein, albumin and total cholesterol. Treatments: incident and prevalent patients (at some point in evolution): erythropoiesis-stimulating agents (ESAs), insulin, oral antidiabetics, antihypertensive drugs, angiotensin-converting enzyme inhibitors (ACEIs), statins, phosphate binders, oral vitamin D (calcitriol, paricalcitol, vitamin D native), cinacalcet. Progression data: incident and prevalent patients.</p><p class="elsevierStylePara">We recorded the following as date of patient termination in the study: death, transplant, transfer, treatment interruption, other losses of follow up or study closing failing. Follow-up time: the time from the start of tracking prevalence or incidence to date of termination. We considered as death all patients who died while under the responsibility of the dialysis centre, or during hospitalisation or those who were transferred and died within three months. Causes of death: cardiovascular (CV), sudden death or at home, infectious, and tumours among others. Hospitalisation: inpatient percentage per year, duration of hospitalisation.</p><p class="elsevierStylePara">Method for calculating mortality rate: the mortality rate was calculated for the years 2009 and 2010 by means of a proportion, as used in the records of Andalusia, Asturias, Catalonia and the Basque Country (Figure 1). We have also calculated it using a ratio, as in the records of Castilla y León and Valencia (Figure 1). Finally, it was also calculated as a density index of mortality, just as it is done in the Canary Islands (Figure 1). In the latter case, the periods were 2009 and 2010. This methodology is used by the Spanish Registry of Dialysis and Transplantation (GRER) for data processing of the Annual mortality registry, although the methodology is different, the results are comparable.<span class="elsevierStyleSup">24</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Statistics</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Qualitative variables are shown as percentages and quantitative variables as mean (and standard deviation). For comparison of qualitative variables, χ2 test was used. Values of <span class="elsevierStyleItalic">P</span> <.05 were considered to be statistically significant. The analysis was performed using SPSS software version 19 (SPSS Inc. Chicago IL).</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">RESULTS</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Population Characteristics</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Population is composed of 2637 incident patients and 4679 prevalent patients; which makes a total of 7316 patients included in this study. 62.7% are male and 37.3% female. This male dominance is greater in the incident patients, 64.4%, than in the prevalent population, 61.7%. The mean age is 64 (15.1) years. It is slightly higher in incident patients (65 [15.4] years) than in prevalent patients (63.5 [14.9] years). Women were slightly older than men in both the incident and the prevalent patients (<span class="elsevierStyleItalic">P</span>=.021).</p><p class="elsevierStylePara">In incident patients (2637) the cause of chronic renal disease was: diabetes 22.9%, vascular nephropathy 13.9%, glomerulonephritis 11%, chronic interstitial nephropathy 9.8%, hereditary nephropathy 8.4% and 4% other causes. In 30% of cases, the cause was not specified or known. In prevalent patients (4679), the cause of chronic kidney disease was: diabetes 17.2%, vascular nephropathy 12.5%, glomerulonephritis 11%, chronic interstitial nephropathy 11%, hereditary nephropathy 8% and 4.5% other causes. In 35.8 % of cases, the cause was not specified or known.</p><p class="elsevierStylePara">Incident patients' (2637) BMI was 26.8 (6.4) kg/m<span class="elsevierStyleSup">2</span> and in prevalent patients (4679) it was 26.3 (5.3) kg/m<span class="elsevierStyleSup">2</span>. Among prevalent patients (4679), 24.4% had diabetes, 76.3% had a history of cardiovascular disease (CVD) and 13.4% cancer. At any point during the study, 33.5% of incident patients had diabetes; 80.6% had presented CVD and 12.6% cancer.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Characteristics of dialysis and vascular access</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">59.2% of incident patients had an AVF, 1.8% graft, 32.1% had a permanent catheter and 6.9% a temporary catheter. Among prevalent patients, the percentages were: 68.5% AVF, graft 5.6%, 23.7% permanent catheter and temporary catheter 2.3%. Differences between both groups were statistically significant with a <span class="elsevierStyleItalic">P</span>-value <.001. Table 1 lists some features of HD. 23.2% of prevalent patients and 9.6% of incident patients are treated with OL-HDF. The average value of calcium in dialysate was 1.39 (0.13) mmol/l.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Analytical controls and treatments received</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Table 2 displays the distribution of patients according to their Hb level, bone mineral metabolism parameters and other biochemical data. Table 3 registers the percentage of patients on treatment with: ESA, statins, ACE inhibitors, other antihypertensives, insulin, oral antidiabetics, oral vitamin D, phosphorus binders and cinacalcet. The difference in the use of treatment whether it was incident or prevalent patients were statistically significant (<span class="elsevierStyleItalic">P</span>=.001 in the case of statins and <span class="elsevierStyleItalic">P</span><.001in the rest of cases).</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Mortality and morbidity</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">On 2009, 523 incident patients were admitted to hospital at least once, and in 2010, 690 patients were admitted. In total, during both years, 46% of incident patients were admitted to the hospital; among prevalent patients, 2403 were admitted during the two-year studied period (52.2% [<span class="elsevierStyleItalic">P</span><.001]. The average number of hospitalisation days was 10.7 for incident patients and 11.5 for prevalent patients. Together, the average (7316) was 11.2 hospitalisation days.</p><p class="elsevierStylePara">During the two years studied, 990 prevalent patients and 248 incident patient passed away; in total, 1238 out of 7316 patients died. Among incident patients, the causes of death were: 29.6% CV, sudden death or unknown cause 19.3%, 9.4% infectious, 7.6% cancer. Among prevalent patients, causes of death were: 30.5% CV, sudden death or unknown cause 24.9%, 6.1% infectious, 5.2% cancer. An annual 4.2% of patients discontinued treatment: 14 patients in 2009 and 26 in 2010 changed to PD technique.</p><p class="elsevierStylePara">The mortality rates obtained through the formulae used by the GRER<span class="elsevierStyleSup">24</span> give the following results: F1, F2, F3 2009 (10.8 %, 12.2 %, 11.9 %) respectively; F1, F2, F3 2010 (11.6 %, 13.1 %, 11.9 %) respectively (Table 4). Moreover, these differences are maintained in the stratification by age group for both periods (Figure 2).</p><p class="elsevierStylePara">During the controlled period, 179 incident patients (6.8%) and 478 prevalent patients (10.2%) received a transplant. The annual average of transplants was 4.5%. 4.2% of patients per year were transferred, 22 patients were lost for follow up due to unknown reasons and treatment was discontinued in 20 patients.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">DISCUSSION</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">In 2009, the 4679 prevalent patients on HD who were recruited in this study represent 20.2% of prevalent patients on HD in Spain. That year, Spain had 1039.4 prevalent patients on renal replacement therapy per million population, 47.67% of which were on HD.<span class="elsevierStyleSup">25</span> In 2010, the prevalent patients included in this study accounted for 22.8% of the population on HD in Spain.<span class="elsevierStyleSup">26</span> They represent, therefore, a large sample of the total population. At the same time, it is a peculiar sample because they belong to outpatient HD centres, while the general population includes both hospital and outpatient units. HD patients treated on HD hospital centres would represent 41.67% (source: Annual Market&Competitor Survey FME 2011).</p><p class="elsevierStylePara">With respect to HD incident patients, those recruited during 2009 in this study represent 25.8% of the total population and 21% of it during 2010. These percentages are similar to those of the prevalent patient population.</p><p class="elsevierStylePara">How are the patients in our study similar or different to the rest of patients in Spain? How are they with respect to age, gender, and comorbidity?</p><p class="elsevierStylePara">We can suppose that, since they belong to outpatient services, they would be younger and with less comorbidity. However, their mean age is 64 years old in the prevalent patients and 65 in the incident patients in this study, which is similar to that of other studies in Spain: 65.2 years in the ANSWER study, 62 years in the study referred by the Nephrology Department of the Hospital Gregorio Marañón in Madrid<span class="elsevierStyleSup">27</span>, 61.5 years for incident patients and 66.1 for prevalent patients in the SEN Quality Group Revision.<span class="elsevierStyleSup">28</span> These studies include in-patient and outpatient HD patients. In the ARO study<span class="elsevierStyleSup">21</span>, which includes several European countries, including Spain, the mean age is 65, though it varies by country. It is a shame that the GRER does not provide this data with a concrete number.</p><p class="elsevierStylePara">The relation between men and women is 1.7 among prevalent patients and 1.8 among the incident patients. This ratio is equal to the ANSWER<span class="elsevierStyleSup">13</span> study (1.7) which included hospitalised patients, and GRER's 2006 ratio of 1.74.<span class="elsevierStyleSup">29</span> This predominance of men appears also, though less marked, in France (1.43), Italy (1.45) and Portugal (1.48), while not in countries like the Czech Republic (0.98) or Hungary (0.97).<span class="elsevierStyleSup">21</span> Male dominance may contribute to increased cardiovascular risk and mortality, although in some studies females have been associated with increased risk of cardiovascular death in HD.<span class="elsevierStyleSup">15,30</span></p><p class="elsevierStylePara">The two leading causes of renal failure and starting of dialysis of this study patients are diabetes, 22.9%, and vascular causes, 13.9%. In the GRER data from 2009,<span class="elsevierStyleSup">25</span> these percentages are 21.5% and 13.9%, respectively. In 2010 they accounted for 24.7% and 14.2%.<span class="elsevierStyleSup">26</span></p><p class="elsevierStylePara">If, among prevalent patients, those with diabetes in the GRER represent 14.3% in 2009 and 14.8% in 2010,<span class="elsevierStyleSup">25,26 </span>then this group accounted for 25.13%. As in the ANSWER study, the frequency of diabetes as a concomitant disease was 10% higher than diabetic nephropathy as the cause for renal failure.<span class="elsevierStyleSup">13</span> Among the incident patients of our study, this percentage increases to 33.45%; this number represents the gradual increase of diabetics within the HD population in Spain. We must not forget that diabetes is a factor that increases the risk of death in the dialysis population.<span class="elsevierStyleSup">11,31,32</span></p><p class="elsevierStylePara">CV history is a fact of poor prognosis.<span class="elsevierStyleSup">15</span> Approximately, a third of patients who start HD in Spain suffer a CV event during the first two years.<span class="elsevierStyleSup">15</span> These events are more frequent and more lethal among patients with a previous history of CV events. In the ANSWER study, 44.9% of patients had a history of cardiovascular events, while in our study 76.3% had it. The difference is probably due in part to differences in definition and CVD event and in the EuCliD<span class="elsevierStyleSup">®</span> documentation method. In the ARO study, with its definition of "disease", this same percentage was 73%. On the other hand, certain vascular pathologies are underestimated in the clinics, for example peripheral vascular disease. In studies designed to value this pathology, it reaches 39.5%.<span class="elsevierStyleSup">27</span></p><p class="elsevierStylePara">The previous history of tumour of 13.4% is higher that the 10% in the ANSWER<span class="elsevierStyleSup">13</span> and the ARO study (5%-11%); it seems, again, that the EuCliD<span class="elsevierStyleSup">®</span> documentation criteria may be one of the reasons for these differences.</p><p class="elsevierStylePara">BMI in HD patients is inversely related to mortality, opposite to the general population.<span class="elsevierStyleSup">15</span> It is an example of "inverse epidemiology" which comes from the existence of other death risk factors that act as confounding factors at the statistical level.<span class="elsevierStyleSup">15,33</span> In this study, BMI, which is 26.8-26.3 is in the high range of the ARO's study in which BMI varies between 24.8 and 26.5 in European countries.</p><p class="elsevierStylePara">On our study the population follows a classic pattern with respect to vascular access. A high percentage of incident patients start HD with a catheter (39%) and some of them have a native AVF performed later. Among prevalent patients, the native FAV percentage reaches 68.5%, a significantly lower number than the 78.4% mean for European countries.<span class="elsevierStyleSup">21</span> This percentage is similar to a recent study in the Canary Islands, with 67%,<span class="elsevierStyleSup">34</span> and higher than a study in Madrid with 47% of patients with catheters. These patients had a risk of death of 1.86 times compared to a native AVF carriers.<span class="elsevierStyleSup">35</span> The presence of a catheter for vascular access is an independent risk factor for mortality, even adjusted for age, BMI, Karnofsky and Charlson index, duration of HD sessions, weight gain between dialysis sessions and various biochemical parameters in the ANSWER study.<span class="elsevierStyleSup">15</span> The percentage of native AVF in this study is low. In Spain, as in other countries, an effort is being made to improve vascular accesses for HD.<span class="elsevierStyleSup">28</span></p><p class="elsevierStylePara">There are factors of HD that may be related to a higher HD survival rate, such as: high-flux polysulfone membranes in diabetic patients with low albumin; OL-HDF, with more than 20l of infusion per session; HD length greater than 4 hours, less interdialytic weight gain and higher eKt/V. <span class="elsevierStyleSup">15,32,36,37</span> In a multicentre study conducted in 2007 with 2526 HD patients in Spain, both in hospital and outpatient units, 89% of patients were on conventional HD, 56.7% with high-flux membranes and medium blood flow 348.4ml/min.<span class="elsevierStyleSup">28</span> In our series, the proportion of patients with high-flux polysulfone membranes (99.9%), OL-HDF patients (23.2%) and other parameters listed is higher than in many HD units. Blood flow (386.48ml/min) and eKt/V (1.47) obtained are above the mean in Spain and the mean for the ARO study.<span class="elsevierStyleSup">21</span> In the Madrid region, the proportion of patients in OL-HDF is 8.5%, associating this technique to better results in dialysis.<span class="elsevierStyleSup">37</span> The high prevalence of OL-HDF in FME clinics is due to the belief by many Spanish nephrologists that this is a more complete dialysis technique than conventional HD.</p><p class="elsevierStylePara">The mean duration of the HD (t) in Spain has always been low compared to other countries<span class="elsevierStyleSup">36</span>, although is increasing. In DOPPS I, t was 215 minutes, 220 minutes in DOPPS II and 228 minutes in DOPPS III. The duration of the session is a factor associated with improved survival even independently from Kt/V.<span class="elsevierStyleSup">36,38.</span>The mean duration of the HD in this study is 230 minutes and, although half of patients do not reach the 240 minutes mark, it is higher than that observed in DOPPS for Spain.</p><p class="elsevierStylePara">Biochemical parameters, some as albumin, in relation to mortality are worse in incident patients than in prevalent patients, possibly showing that even patients with advanced chronic kidney disease (ACKD) or predialysis come into dialysis precariously, without good medical control. We must take into account that rated analytical determinations are the average of six months, so that this difference between incident and prevalent is attenuated.</p><p class="elsevierStylePara">This study highlights the high percentage of patients receiving various types of drugs during its time period. This percentage increases from incident to prevalent patients for certain drugs, such as insulin, vitamin D, P binders and cinacalcet, and decreases with others, such as oral antidiabetics, antihypertensive drugs, including ACE inhibitors. With other drugs, such as statins and ESA it remains the same. One of the possible reasons for this observation may be, once again, EuCliD<span class="elsevierStyleSup">®</span> methodology, which includes the use of encryption ATC (Anatomical Therapeutic Chemical Classification System), which would facilitate the evaluation of the medication used from the statistical point of view. While the use of classic oral antidiabetics is contraindicated in the case of HD patients, they are still used in a small percentage. Although in recent years concern for the diagnosis and treatment of bone mineral disease increased in patients with ACKD, it is performed more completely during the HD stage, as evidenced by the increased use of calcimimetics and vitamin D in prevalent patients in comparison with incident patients, as occurs with phosphate binders, higher in prevalent patients than in incident patients.</p><p class="elsevierStylePara">Hospitalisation rates for these patients are low: 0.46 hospitalisations per incident patient/year and 0.52 per prevalent patient/year, lower than the average for Spain (0.75) and Europe (0.99) in the Dopps study.<span class="elsevierStyleSup">39</span> Mean hospital stay is similar to that of most studies.<span class="elsevierStyleSup">39,40.</span></p><p class="elsevierStylePara">HD patient mortality in this study is considerably lower than GRER's.<span class="elsevierStyleSup">25,26</span> According to the formulae used, it ranges from 10.8% in 2009 and 13.1% in 2010. GRER mortality was of 14.79% for 2009 and 17.3% for 2010. 2009 Mortality in GRER is in line with the figure for previous years, between 14% and 15%. On the other hand, given the fact that the population of this study is part of the registry's population and represents 20% of it, implies that the difference is even greater between patients studied here and the rest of patients, including hospital patients. These differences are maintained in the stratification by age group for both periods (Figure 2).</p><p class="elsevierStylePara">The formulae used to calculate mortality are the same ones used by records of different Spanish regions. Regarding the criteria used to define patients who died, this study was more demanding, and it counted patients deceased in other centres during the three months after their transfer. It attempts to avoid cases of patients transferred and who passed away soon after. One possible explanation for the discrepancy is in how GRER assesses deceased patients. Transplant patients in critical condition who lose kidney function, are transferred to HD and die shortly after are recorded as HD patients. The same can be applied to patients who are transferred from PD to HD for loss of peritoneal function, such as peritoneal sclerosis sufferers, who have very poor prognosis.</p><p class="elsevierStylePara">Mortality in other studies, such as ANSWER, is 13.8%, 13.8% also in the ARO study and 22% in DOPPS USA.<span class="elsevierStyleSup">39</span></p><p class="elsevierStylePara">The mortality of HD patients in this study is still very high. It has to be situated between the mortality of patients with leukaemia and myeloma,<span class="elsevierStyleSup">41</span> which gives an idea of the magnitude of the problem. Another way to reference it is comparing it with the mortality rate in Spain in 2010, which was 0.79%, or that of people of 65 years old (0.90%), which means 13 times more mortality (INE-base, the National Statistics Institute).</p><p class="elsevierStylePara">The main cause of death in this study is CV death by 50% among incident patients and 55% among prevalent. Note that sudden deaths occurred in 19% of incident and 25% of prevalent patients. These percentages are similar to those of the ANSWER study<span class="elsevierStyleSup">15</span> (23.5% sudden deaths), the 22% in the HEMO study<span class="elsevierStyleSup">42</span> and the ARO study (42% of CV). In GRER<span class="elsevierStyleSup">25,26</span> the percentages for sudden deaths are 4% in 2009 and 6% in 2010. Probably much of unknown origin causes correspond to sudden deaths, 14% and 15% respectively. We see great improvement on this type of death.</p><p class="elsevierStylePara">The percentages of deaths caused by infection in the GRER, 18% and 19%, are higher than those of this study (between 6% and 10%).</p><p class="elsevierStylePara">Interruption of treatment in this series is very low, both in incident and prevalent patients, as it is usual in Spain.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">CONCLUSION</span></p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">Patients treated in FME clinics seem to have comorbidity and epidemiological characteristics similar to those of GRER and other series of HD patients, including hospital HD patients. The result of morbidity and mortality in FME clinics can therefore be considered good as compared to the GRER and other international series. This does not mean that there are no areas for improvement, such as increasing the dialysis time, convective techniques and the percentage of native AVF.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara"><span class="elsevierStyleBold">Conflicts of interest</span></p><p class="elsevierStylePara">The authors are members of the ORD scientific group, promoted by Fresenius Medical Care in Spain.</p><p class="elsevierStylePara"> </p><p class="elsevierStylePara">ACKNOWLEDGEMENTS<br></br>We wish to thank all the physicians of Fresenius Medical Care clinics in Spain for their participation, the inclusion and collecting of the data essential for the realisation of this report: <br></br>Aguilera Jover, Josep; Ajenjo Mas, Enrique; Al Massri, Mohamad; Alcalá Rueda, María Luisa; Almoguera González, Ana María; Álvarez Francos, Marta; Amoedo Rivera, María Luisa; Ampuero Mencia, Jara; Aramburu Hostench, Javier; Araque Juan, Alicia; Ariza Fuentes, Francisco Javier; Arruche Herrero, M. Mercedes; Bar, Andrzej Witold; Barbacid Santos, Ignacio Alberto; Barbetta, Massimo; Barbosa Puig, Francisco; Barrera Padilla, Rosario; Berdud Godoy, Isabel; Berlanga Alvarado, José Ramón; Blanco Santos, Ana; Calvar García, Carlos Alberto; Cantón Guerrero, Petra; Carazo Calvo, María Eugenia; Cardoso Represa, Alejandro; Carretero Dios, Diana; Castellano Gasch, Sandra; Cid Parra, María Cruz; Civex Muiño, Alejandro Daniel; Contreras Ríos, Juan José; Corredera Romero, M. Teresa; Crespo Navarro, Antonio; De Miguel Anasagasti, Teresa; Devesa Such, Ramón; Durán Sánchez, Victorino; El Rifai El Sayed, Abdallah; Espada Guerrero, Rosa María; Estadella Llobet, Concepció; Estrada Patricia, N; Faez Herrera, Yamile; Faiña Rodríguez-Vila, Beatriz; Feliz Díaz, Tamara Carmelina; Fernández Robres, M. Amparo; Fernández Carbonero, Enrique; Fernández de Diego, Álvaro; Fernández Marchena, Dolores; Fernández Chávez, Abelardo Claudio; Fernández Solís, María Antonia; Gad, Noura; Galán González, Josefa; Galano Quiala, Marilee; Gallego García, María José; García Guijosa, M. Ángeles; García Lacomba, Juan José; García Crespo, María del Mar; García de Vinuesa Calvo, Elena; García-Izquierdo Otero, Ambrosio; Giner Segui, Rafael; Giráldez Casasnovas, José Diego; Gómez Couñago, Inmaculada; González Olmedo, Petronila; Gorostiza Rodríguez, Guillermo; Grisales Arroyave, Juan Carlos; Gurpegui Prieto, María Luz; Hernández Moreno, María Teresa; Herrera Denis, Imara; Hidalgo García, Patricia; Hurtado Muñoz, Sara; Ibrik Ibrik, Omar; Insense Pons, Alberta; Izaguirre Martín, Ana Isabel; Jordan Pérez, Joel; Juan Pérez, M. Ángeles; Loras Amorós, Laura; Macías Galán, Rosa María; Márquez Ramón, Juan Antonio; Martín Gil, Alfredo Javier; Martín Pérez, María Belén; Martínez Rubio, M. Pilar; Matas Serra, Margarita; Merin Serra, Ana; Mestres Capdevila, Rosa; Mora Macia, Josep; Moreno Vega, Darío Manuel; Moreno Muñoz, María Victoria; Morente Esquivel, Jorge Camilo; Moreso Mateos, Francesc; Munteanu,  Oana Mihaela; Nin Zulueta, Jordi; Olivares Ortiz, Álvaro Mauricio; Olivas Ferrandis, Juan Luis; Ortuño Celdran, Tomás Antonio; Pascual Domínguez, Francisco Javier; Paz Martín, Rodrigo; Pérez Velasco, Cristina; Pons Aguilar, Mercedes; Ruiz Carrero, María Asunción; Puyuelo Lanao, Trinidad; Quintana Rozadilla, Elena; Quintanilla Valles, Nuria; Quiroz Morales, Manuel Augusto; Ramos Sánchez, Rosa; Redondo García, Concepción; Requena Soriano, Juan Francisco; Riaño Castañedo, María Jesús; Ribera Tello, Laura; Rico Salvador, Inmaculada; Ríos Moreno, Francisco; Rivera Pérez, Mariana; Rodríguez de Oña, María del Mar; Romero Nieves, M. del Carmen; Romero Jiménez, Rafaela; Romero Mallorca, Alonso; Rubia García, Francisco Manuel; Rueda Lombillo, María Emma; Ruiz Caro, María Caridad; Ruiz Roda, Jesús; Ruiz Alaminos, Jesús Daniel; Ruiz Losada, Ana María; Sánchez Enríquez, Carlos Alberto; Sánchez García, Olga María; Sánchez Sancho, Mercedes; Sánchez Torres, Dolores; Santos Herrera, Marta; Sastre Romaniega, M. Lourdes; Sese Torres, Josep; Setién Conde, María Ángeles; Silgado Rodríguez, Gema; Simonyan Hamazasp; Soler García, Jordi; Soto Montañez, Carlos Antonio; Sujan Sujan, Seema; Suria Arenes, Miguel Carlos; Uribe Echeverri, Juan Diego; Valdés Chiong, Evaristo; Valentín González, Félix; Vázquez Cruzado, Juan; Vidiella Martorell, Juan; Villaverde Ares, M. Teresa; Virguez Pedreros, Leonardo.<br></br><br></br><br></br><br></br></p><p class="elsevierStylePara"><a href="11549_19157_38898_en_table3.doc" class="elsevierStyleCrossRefs">11549_19157_38898_en_table3.doc</a></p><p class="elsevierStylePara">Table 3. Medication </p><p class="elsevierStylePara"><a href="11549_19157_38899_en_table4.doc" class="elsevierStyleCrossRefs">11549_19157_38899_en_table4.doc</a></p><p class="elsevierStylePara">Table 4. Mortality index</p><p class="elsevierStylePara"><a href="11549_19157_38900_en_figure1.doc" class="elsevierStyleCrossRefs">11549_19157_38900_en_figure1.doc</a></p><p class="elsevierStylePara">Figure 1. Method of calculating mortality index</p><p class="elsevierStylePara"><a href="11549_19157_38901_en_figure2.doc" class="elsevierStyleCrossRefs">11549_19157_38901_en_figure2.doc</a></p><p class="elsevierStylePara">Figure 2. Mortality by ages, between 2009 and 2010</p><p class="elsevierStylePara"><a href="11549_19157_38912_en_table1.doc" class="elsevierStyleCrossRefs">11549_19157_38912_en_table1.doc</a></p><p class="elsevierStylePara">Table 1. Characteristics of haemodialysis treatment (at 6 months)</p><p class="elsevierStylePara"><a href="11549_19157_38913_en_table2.doc" class="elsevierStyleCrossRefs">11549_19157_38913_en_table2.doc</a></p><p class="elsevierStylePara">Table 2. Analytical controls (At 6 months)</p>" "pdfFichero" => "P1-E544-S3760-A11549-EN.pdf" "tienePdf" => true "PalabrasClave" => array:2 [ "es" => array:5 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec437041" "palabras" => array:1 [ 0 => "Morbilidad" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec437043" "palabras" => array:1 [ 0 => "Hemodiálisis" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec437045" "palabras" => array:1 [ 0 => "Diabetes" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec437047" "palabras" => array:1 [ 0 => "Epidemiología" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Palabras clave" "identificador" => "xpalclavsec437049" "palabras" => array:1 [ 0 => "Mortalidad" ] ] ] "en" => array:5 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec437042" "palabras" => array:1 [ 0 => "Morbidity" ] ] 1 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec437044" "palabras" => array:1 [ 0 => "Haemodialysis" ] ] 2 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec437046" "palabras" => array:1 [ 0 => "Diabetes" ] ] 3 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec437048" "palabras" => array:1 [ 0 => "Epidemiology" ] ] 4 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec437050" "palabras" => array:1 [ 0 => "Mortality" ] ] ] ] "tieneResumen" => true "resumen" => array:2 [ "es" => array:1 [ "resumen" => "<p class="elsevierStylePara">Estudio observacional de los pacientes dializados en las clínicas de Fresenius Medical Care en España (FME) durante los años 2009 y 2010. Los datos se recogen de la base de datos EuCliD<span class="elsevierStyleSup">®</span>, implementada en las clínicas FME, que cumple con las siguientes características: registro en línea, obligatorio, realizado en pacientes incidentes y que abarca a toda la población en hemodiálisis (HD) atendidos en esas clínicas. Su objetivo es comprender las características de los pacientes y los patrones de tratamiento, comparándolos con otros estudios descritos en la literatura y con el fin de mejorar su pronóstico y calidad de vida. Se incluyen 2637 pacientes incidentes y 4679 prevalentes, lo que hace un total de 7316 pacientes. Un 24,4 % de los pacientes prevalentes eran diabéticos, un 76,3 tenían antecedentes de enfermedad cardiovascular (ECV) y un 13,4 % de cáncer. Entre los incidentes estos porcentajes eran: 33,5 % diabéticos; 80,6 % habían presentado ECV y el 12,6 % cáncer. Los pacientes prevalentes tenían como acceso vascular: fístula arteriovenosa (FAV) 68,5 %, prótesis 5,6 %, catéter permanente 23,7 % y catéter temporal 2,3 %. El promedio de la duración de las sesiones de HD era de 230 minutos. Un 23,2 % de los pacientes prevalentes estaban en técnica de hemodiafiltración en línea. Los índices de hospitalización de estos pacientes son bajos: 0,46 hospitalizaciones por paciente incidente y año y 0,52 por paciente prevalente y año. La tasa de mortalidad bruta anual es de un 12 %. La mortalidad de los pacientes en HD de este estudio es menor que la del Registro Español (GRER). El resultado de morbilidad y mortalidad de las clínicas FME se puede, por tanto, considerar como bueno en comparación con el del Registro Español de Diálisis y Trasplante y de otras series internacionales. Eso no quiere decir que no haya áreas de mejora, como el aumento del tiempo de diálisis, de las técnicas convectivas y del porcentaje de FAV.</p>" ] "en" => array:1 [ "resumen" => "<p class="elsevierStylePara">Observational study of patients on haemodialysis (HD) in FMC<span class="elsevierStyleSup">®</span> Spain clinics over the years 2009 and 2010. Data was collected from the EuClid<span class="elsevierStyleSup">®</span> database, implemented in the FMC<span class="elsevierStyleSup">® </span>clinics, which complies with the following features: online record, mandatory, conducted in incident patients and covering the entire population on HD in these clinics. It aims to understand the characteristics of patients and treatment patterns, comparing them with other studies described in the literature and in order to improve their prognosis and quality of life. It includes 2637 incident and 4679 prevalent patients, which makes a total of 7316 patients. In prevalent patients: 24.4% were diabetic; 76.3% had cardiovascular disease (CVD) and 13.4% cancer. Among the incident patients these percentages were: 33.5% diabetic; 80.6% had CVD and 12.6% cancer. The prevalent patients had vascular access such as: AVF 68.5%, prosthesis 5.6%, permanent catheter 23.7% and 2.3% temporary catheter. The average duration of the sessions of HD was 230 minutes. 23.2% of prevalent patients were on on-line haemodiafiltration. These patients’ hospitalisation rates were 0.46 hospitalisations per incident patient per year and 0.52 per prevalent patient per year. The annual gross mortality rate was 12%. The mortality of HD patients in this study is smaller than those of the Spanish Registry of Dialysis and Transplant (GRER). The result of morbidity and mortality of the FMC clinics of Spain can, therefore, be considered good when compared with those of the GRER and other international series. This does not mean that there are no areas of improvement as the increase in the dialysis time, the percentage of patients on on-line haemodiafiltration, convective techniques and the percentage of FAV.</p>" ] ] "multimedia" => array:6 [ 0 => array:8 [ "identificador" => "mmc1" "etiqueta" => "Tab. 3" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38898_en_table3.doc" "ficheroTamanyo" => 29696 ] "descripcion" => array:1 [ "en" => "Medication " ] ] 1 => array:8 [ "identificador" => "mmc2" "etiqueta" => "Tab. 4" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38899_en_table4.doc" "ficheroTamanyo" => 25600 ] "descripcion" => array:1 [ "en" => "Mortality index" ] ] 2 => array:8 [ "identificador" => "mmc3" "etiqueta" => "Fig. 1" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38900_en_figure1.doc" "ficheroTamanyo" => 107008 ] "descripcion" => array:1 [ "en" => "Method of calculating mortality index" ] ] 3 => array:8 [ "identificador" => "mmc4" "etiqueta" => "Fig. 2" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38901_en_figure2.doc" "ficheroTamanyo" => 88576 ] "descripcion" => array:1 [ "en" => "Mortality by ages, between 2009 and 2010" ] ] 4 => array:8 [ "identificador" => "mmc5" "etiqueta" => "Tab. 1" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38912_en_table1.doc" "ficheroTamanyo" => 26624 ] "descripcion" => array:1 [ "en" => "Characteristics of haemodialysis treatment (at 6 months)" ] ] 5 => array:8 [ "identificador" => "mmc6" "etiqueta" => "Tab. 2" "tipo" => "MULTIMEDIAECOMPONENTE" "mostrarFloat" => true "mostrarDisplay" => false "copyright" => "Elsevier España" "Ecomponente" => array:2 [ "fichero" => "11549_19157_38913_en_table2.doc" "ficheroTamanyo" => 31744 ] "descripcion" => array:1 [ "en" => "Analytical controls (At 6 months)" ] ] ] "bibliografia" => array:2 [ "titulo" => "Bibliography" "seccion" => array:1 [ 0 => array:1 [ "bibliografiaReferencia" => array:42 [ 0 => array:3 [ "identificador" => "bib1" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:3 [ "referenciaCompleta" => "Pozzoni P, Del Vecchio L, Pontoriero G, Di Filippo S, Locatelli F. 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Year/Month | Html | Total | |
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2024 November | 5 | 4 | 9 |
2024 October | 64 | 338 | 402 |
2024 September | 70 | 58 | 128 |
2024 August | 45 | 47 | 92 |
2024 July | 53 | 29 | 82 |
2024 June | 71 | 62 | 133 |
2024 May | 74 | 53 | 127 |
2024 April | 60 | 62 | 122 |
2024 March | 42 | 30 | 72 |
2024 February | 56 | 50 | 106 |
2024 January | 38 | 38 | 76 |
2023 December | 27 | 58 | 85 |
2023 November | 41 | 74 | 115 |
2023 October | 35 | 55 | 90 |
2023 September | 41 | 47 | 88 |
2023 August | 56 | 56 | 112 |
2023 July | 43 | 52 | 95 |
2023 June | 50 | 49 | 99 |
2023 May | 57 | 31 | 88 |
2023 April | 45 | 13 | 58 |
2023 March | 87 | 32 | 119 |
2023 February | 82 | 29 | 111 |
2023 January | 112 | 44 | 156 |
2022 December | 139 | 28 | 167 |
2022 November | 71 | 31 | 102 |
2022 October | 64 | 55 | 119 |
2022 September | 50 | 30 | 80 |
2022 August | 48 | 47 | 95 |
2022 July | 27 | 81 | 108 |
2022 June | 48 | 30 | 78 |
2022 May | 32 | 30 | 62 |
2022 April | 33 | 31 | 64 |
2022 March | 49 | 51 | 100 |
2022 February | 46 | 37 | 83 |
2022 January | 44 | 36 | 80 |
2021 December | 45 | 53 | 98 |
2021 November | 30 | 50 | 80 |
2021 October | 41 | 66 | 107 |
2021 September | 44 | 52 | 96 |
2021 August | 29 | 36 | 65 |
2021 July | 49 | 40 | 89 |
2021 June | 50 | 31 | 81 |
2021 May | 29 | 38 | 67 |
2021 April | 58 | 33 | 91 |
2021 March | 54 | 27 | 81 |
2021 February | 48 | 12 | 60 |
2021 January | 42 | 17 | 59 |
2020 December | 36 | 22 | 58 |
2020 November | 37 | 14 | 51 |
2020 October | 35 | 22 | 57 |
2020 September | 33 | 8 | 41 |
2020 August | 39 | 13 | 52 |
2020 July | 35 | 13 | 48 |
2020 June | 36 | 17 | 53 |
2020 May | 34 | 15 | 49 |
2020 April | 40 | 21 | 61 |
2020 March | 40 | 14 | 54 |
2020 February | 37 | 16 | 53 |
2020 January | 54 | 21 | 75 |
2019 December | 41 | 26 | 67 |
2019 November | 46 | 22 | 68 |
2019 October | 18 | 13 | 31 |
2019 September | 33 | 19 | 52 |
2019 August | 14 | 18 | 32 |
2019 July | 34 | 23 | 57 |
2019 June | 38 | 21 | 59 |
2019 May | 29 | 23 | 52 |
2019 April | 70 | 50 | 120 |
2019 March | 43 | 19 | 62 |
2019 February | 40 | 22 | 62 |
2019 January | 38 | 32 | 70 |
2018 December | 108 | 43 | 151 |
2018 November | 117 | 39 | 156 |
2018 October | 98 | 33 | 131 |
2018 September | 67 | 23 | 90 |
2018 August | 71 | 19 | 90 |
2018 July | 46 | 20 | 66 |
2018 June | 45 | 26 | 71 |
2018 May | 48 | 26 | 74 |
2018 April | 45 | 14 | 59 |
2018 March | 36 | 12 | 48 |
2018 February | 43 | 15 | 58 |
2018 January | 32 | 9 | 41 |
2017 December | 44 | 10 | 54 |
2017 November | 53 | 8 | 61 |
2017 October | 43 | 6 | 49 |
2017 September | 52 | 13 | 65 |
2017 August | 36 | 13 | 49 |
2017 July | 52 | 13 | 65 |
2017 June | 36 | 14 | 50 |
2017 May | 35 | 18 | 53 |
2017 April | 34 | 13 | 47 |
2017 March | 40 | 9 | 49 |
2017 February | 33 | 15 | 48 |
2017 January | 23 | 20 | 43 |
2016 December | 104 | 10 | 114 |
2016 November | 102 | 12 | 114 |
2016 October | 117 | 18 | 135 |
2016 September | 174 | 11 | 185 |
2016 August | 253 | 7 | 260 |
2016 July | 249 | 13 | 262 |
2016 June | 158 | 0 | 158 |
2016 May | 179 | 0 | 179 |
2016 April | 138 | 0 | 138 |
2016 March | 125 | 0 | 125 |
2016 February | 154 | 0 | 154 |
2016 January | 133 | 0 | 133 |
2015 December | 163 | 0 | 163 |
2015 November | 116 | 0 | 116 |
2015 October | 118 | 0 | 118 |
2015 September | 151 | 0 | 151 |
2015 August | 622 | 0 | 622 |
2015 July | 91 | 0 | 91 |
2015 June | 46 | 0 | 46 |
2015 May | 65 | 0 | 65 |
2015 April | 15 | 0 | 15 |