Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

The modality of dialysis does not influence atheromatous vascular disease progression or cardiovascular outcomes in dialysis patients without previous cardiovascular disease

  • Mercè Borràs Sans ,

    Roles Conceptualization, Formal analysis, Investigation, Methodology, Project administration, Supervision, Visualization, Writing – original draft, Writing – review & editing

    mmborras.lleida.ics@gencat.cat

    Affiliations Department of Nephrology, University Hospital Arnau de Vilanova de Lleida, Lleida,Spain, UDETMA Unitat de Detecció de Malalties Aterotrombòtiques, Lleida, Spain, Vascular and Renal Translational Research Group, UDETMA, REDinREN del ISCIII, IRBLleida, Lleida, Spain

  • Miguel Pérez-Fontán,

    Roles Formal analysis, Methodology, Supervision, Visualization

    Affiliation Department of Nephrology, University Hospital A Coruña, A Coruña, Spain

  • Montserrat Martinez-Alonso,

    Roles Data curation, Formal analysis, Investigation, Software, Writing – review & editing

    Affiliations UDETMA Unitat de Detecció de Malalties Aterotrombòtiques, Lleida, Spain, Vascular and Renal Translational Research Group, UDETMA, REDinREN del ISCIII, IRBLleida, Lleida, Spain

  • Auxiliadora Bajo,

    Roles Data curation, Visualization

    Affiliation Department of Nephrology, University Hospital La Paz, REDinREN del ISCIII, Madrid, Spain

  • Àngels Betriu,

    Roles Data curation, Investigation, Project administration, Resources, Validation

    Affiliations UDETMA Unitat de Detecció de Malalties Aterotrombòtiques, Lleida, Spain, Vascular and Renal Translational Research Group, UDETMA, REDinREN del ISCIII, IRBLleida, Lleida, Spain

  • José M. Valdivielso,

    Roles Data curation, Investigation, Project administration, Supervision, Writing – review & editing

    Affiliations UDETMA Unitat de Detecció de Malalties Aterotrombòtiques, Lleida, Spain, Vascular and Renal Translational Research Group, UDETMA, REDinREN del ISCIII, IRBLleida, Lleida, Spain

  • Elvira Fernández,

    Roles Funding acquisition, Investigation, Methodology, Project administration, Resources, Writing – review & editing

    Affiliations Department of Nephrology, University Hospital Arnau de Vilanova de Lleida, Lleida,Spain, UDETMA Unitat de Detecció de Malalties Aterotrombòtiques, Lleida, Spain, Vascular and Renal Translational Research Group, UDETMA, REDinREN del ISCIII, IRBLleida, Lleida, Spain

  • on behalf of NEFRONA INVESTIGATORS

    Membership of the NEFRONA INVESTIGATORS is provided in the Acknowledgments.

The modality of dialysis does not influence atheromatous vascular disease progression or cardiovascular outcomes in dialysis patients without previous cardiovascular disease

  • Mercè Borràs Sans, 
  • Miguel Pérez-Fontán, 
  • Montserrat Martinez-Alonso, 
  • Auxiliadora Bajo, 
  • Àngels Betriu, 
  • José M. Valdivielso, 
  • Elvira Fernández, 
  • on behalf of NEFRONA INVESTIGATORS
PLOS
x

Correction

28 Jun 2018: Borràs Sans M, Pérez-Fontán M, Martinez-Alonso M, Bajo A, Betriu À, et al. (2018) Correction: The modality of dialysis does not influence atheromatous vascular disease progression or cardiovascular outcomes in dialysis patients without previous cardiovascular disease. PLOS ONE 13(6): e0200226. https://doi.org/10.1371/journal.pone.0200226 View correction

Abstract

Background

There is limited and inconclusive information regarding the influence of the modality of renal replacement therapy on the atherosclerotic burden of patients on dialysis. The aim of this study was to compare the prevalence of asymptomatic atheromatous carotid disease, as also its rate of progression and cardiovascular outcomes, in two matched populations of patients treated with hemodialysis (HD) and peritoneal dialysis (PD).

Methods

Following a prospective, observational and multicenter design, we compared 237 PD and 237 HD patients without previous cardiovascular disease, included in the NEFRONA study, and matched for age, sex, diabetes and time on dialysis. Carotid ultrasound study was performed at baseline and after two years of follow-up in 6 carotid territories. Atheromatous vascular disease (AVD) progression was defined as any increase in the number of territories with plaques after 2 years. Fatal and non fatal cardiovascular events were also recorded during 36-month of follow-up.

Main results

At baseline, PD patients presented a worse general cardiovascular risk profile than HD patients. On the contrary, some markers of prevalent atherosclerotic disease (common carotid intima-media thickness and ankle-brachial index) were more favorable in PD patients. During follow-up, we observed no differences either in the rate of progression of atheromatous vascular disease (OR 1.78, 95% CI 0.80–4.06, p = 0.161) or in the incidence of cardiovascular events (OR 1.51, 95% CI 0.85–2.66, p = 0.159), according to the modality of dialysis.

Conclusion

Dialysis modality did not impact on atherosclerotic carotid disease progression or cardiovascular outcomes, in two groups of patients treated with PD or HD.

Introduction

Cardiovascular disease (CVD) is the leading cause of mortality in patients with end stage renal disease (ESRD) [1,2]. Available evidence suggests that atherosclerosis is a primary contributor to this outcome, although non-atherosclerotic CVD, including volume overload and left ventricular hypertrophy, may also play a significant role in the increased CV mortality observed in these patients. Patients on dialysis present a high burden of traditional risks factors for CVD, including dyslipemia, diabetes mellitus and hypertension, usually present at the initiation of therapy. In addition, many nontraditional risk factors for this condition, including hyperparathyroidism, hyperfibrinogenemia, hyperhomocysteinemia, hypoalbuminemia and others [3,4] are also very prevalent. The modality of dialysis itself–hemodialysis (HD) or peritoneal dialysis (PD)–could also have a differentiated effect on general and specific CV risk factors, and also on the progression of atherosclerotic disease (AD). If this was the case, the effect should be more pronounced as time on dialysis increases.

High-resolution carotid ultrasonography (cUS) is a reliable and relatively simple instrument for the study of atherosclerotic vascular disease. Increased carotid intima media thickness (cIMT) and the presence of calcified and non calcified plaques are strong predictors of CV events in the general population [57], and have been claimed to portend similar outcomes in patients with ESRD treated with HD [810] or PD [10].

There is limited and inconclusive information regarding the compared atherosclerotic burden according to the modality of dialysis, as estimated by cUS [1113]. Cross-sectional studies may provide information on this question, but the risk of selection biases hampers the interpretation of the results. A longitudinal design could provide more reliable information but, to our knowledge, this approach has not been undertaken, so far.

The aim of the present study is to compare the risks of progression of atheromatous arterial disease and to assess risk factors of incident cardiovascular outcomes, in two matched populations of patients treated with HD and PD, respectively.

Material and methods

Study design and participants

The NEFRONA project is a Spanish multicentric, observational, prospective study, designed to investigate the atherosclerotic burden of patients with chronic kidney disease (CKD), including relatively large samples of patients with ESRD treated with HD or PD. The general design and objectives of NEFRONA have been reported in detail [14,15]. In summary, 2445 CKD patients (of whom 688 were prevalent patients on dialysis), 18–75 years of age, were enrolled from 81 Spanish hospitals between October 2010 and June 2012, with a scheduled follow-up visit after 24 months. A main inclusion criterion was the absence of overt atherosclerotic disease at the start of follow-up. Consequently, patients who had stenotic carotid plaques or ankle-brachial index (ABI) <0.7 at baseline evaluation were excluded from the follow-up visit. Patients who suffered a CV event, received a renal allograft or died after the first ultrasound exploration, were also excluded from the second exploration.

The objective of the present study was to compare the progression of carotid artery atherosclerotic disease and assess risk factor of incident cardiovascular events in patients treated with PD and HD. Given the usual mismatches when these two types of patients are compared, we created two groups of patients. The NEFRONA study included a total of 237 PD patients (all of them included in this study) together with 451 HD patients. A selection of 237 HD patients matched by age, sex, diabetes and time on dialysis was performed from the group of HD patients in order to get comparable groups, with the ultimate aim of reducing the bias risk.

The study protocol was approved by the ethics committee of University Hospital Arnau de Vilanova, Lleida, Spain, and written informed consent was requested to all participants. The study complied with the principles of the Declaration of Helsinki.

Clinical and biochemical data

At the time of recruitment, information about current health status, medical history, former cardiovascular risk factors and drug use was obtained. A physical examination was performed, including in anthropometric measures, standard vital tests and ABI measurement as previously described [16]. A pathological ABI was described as ≤0.9 or ≥1.4. Biochemical data were obtained from a routine blood test performed within three months of the vascular study. For HD patients, blood samples were retrieved at the start of the second session of the week. Parathyroid hormone (PTH) level was standardized using a recognized conversion method [17] to overcome inter-method variability between different centers. Determinations of high-sensitivity C reactive protein (hsCRP), 25hydroxy-vitamin D and 1.25hydroxy-vitamin D were performed in a centralized laboratory, to avoid variability among methods.

Carotid ultrasound (cUS)

B-mode ultrasound of the carotid arteries was performed using the Vivid BT09 device (General Electric Instruments, Freiburg, Germany), with the help of 6–13 MHz broadband linear array probes. The measurement of cIMT and the analysis on presence of atheromatous plaques was performed by a single reader in a blinded fashion, using the semi-automatic software EchoPAC Dimension (General Electric Healthcare, Harten, Norway). We previously assessed the quality of the reading and the intraobserver variability, using a sample of 20 individuals in whom estimations were performed 3 to 5 times at different days. A kappa coefficient of 1 was obtained, indicating an optimal intraobserver reliability.

US imaging was performed for both carotid arteries with the subjects in a supine position and the head turned 45° contralateral to the side of the probe. cIMT was measured in the last centimeter of the far wall of the common carotid artery, the bulb section and, finally, the first centimeter of the internal carotid artery. Measurements were made in plaque-free arterial segments. The presence of atheromatous plaques in each of the mentioned points was defined by a cIMT ≥ 1.5 mm protruding to the lumen, following the recommendations of the ASE Consensus Statement [18] and the Mannheim cIMT Consensus report [19].

We created a carotid plaque score, which resulted from the addition of the number of points scrutinized (n = 6), including common, bulb and internal carotid arteries in each side in which at least one plaque was detected. Thus, the range of the score extended between 0 (no plaques) to 6 (all sites examined with plaque). We defined progression of AD over the two-year study span as any increase in the number of territories with plaque, when compared with to the baseline visit, as previously reported in the MESA study [20].

Study variables and data analysis

The main study variable was dialysis modality classified as HD (including hospital, satellite, and home-based HD) or PD (including continuous ambulatory PD and automated PD) according to the dialysis at the study inclusion. First main outcome variable was progression of AVD defined according to cUS results by any increase in the number of territories with plaque at the c-US two-year study when compared with the baseline study, measured by the plaque score. The second main outcome variable was presentation of fatal and non-fatal CV events during a minimum of 36 month follow up. CV events were defined according to the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD9-CM) which includes unstable angina, myocardial infarction, transient ischemic attack, cerebrovascular accident, congestive heart failure, arrhythmia, peripheral artery disease or amputation for vascular disease and aorta aneurisma [14]. Control variables included demographic, clinical, biochemical and prescription factors depicted in Table 1 (all included patients) and Table 2 (patients with 2-years follow-up).

thumbnail
Table 2. Main Baseline characteristics of patients with 2-years follow-up according to dialysis modality.

https://doi.org/10.1371/journal.pone.0186921.t002

Statistical analysis

Summary measures included median and interquartile intervals for quantitative variables. Qualitative variables were summarized with absolute and relative frequencies and we used the chi-squared test (or exact Fisher test when the expected frequencies was less than 5 in some cell) for comparisons between groups. We used Mann-Whitney’s test to compare quantitative variables between two groups, and Kruskal-Wallis’ test to compare three or more groups. A multivariate logistic regression model for atherosclerotic disease progression was fitted, including all significant covariates (according to the likelihood ratio test) and recoding those quantitative variables according to a cutoff value improving discrimination. Interactions were assessed as well as model’s calibration and discrimination. The analysis of risk factors of incident cardiovascular events was based on hazard ratio estimations based on log-rank test for qualitative variables and Cox’s proportional hazards regression for quantitative variables. A final multivariate Cox’s proportional hazards regression model was fitted, including the assessment of interactions and the performance of a test of the proportional hazards assumption.

Results

Baseline characteristics

A total of 237 PD and 237 HD patients were included. Tables 1 and 2 show the main baseline patients' characteristics, according to dialysis modality. Table 1 with all included patients and Table 2 with the patients with 2-years follow-up. No differences were observed in plaque presence and number of carotid territories (plaque score) when baseline atherosclerotic burden was compared between PD and HD patients. However, HD patients had higher cIMT and more pathological ABI: fewer patients had a normal ABI and more individuals showed an increased ABI compared to PD patients.

Outcomes

Of the 474 dialysis patients included in the baseline analysis, 214 (45.1%) received a renal allograft during the ensuing 36 months. PD patients were significantly more likely to be transplanted than HD patients (50.2% vs 40.1%; p = 0.03). Fourteen patients died from non CV diseases; this outcome was less likely in PD patients (1,9%) than in HD patients (8.4%)(p = 0.03). Fifty-one (10.7%) patients either presented a CV event or died from CV disease, without significant differences between PD (11,8%) and HD patients (9,7%)(p = 0.13). Thirty two (6.5%) patients were lost to follow-up (p = 0.28). Finally, 21 (4.4%) patients did not undergo a second cUS, because they had stenotic carotid plaque or ABI <0.7 at baseline (n = 20), or because they had a maximal plaque score at baseline (n = 1), which prevented any possibility of score progression.

Analysis of atheromatous vascular disease progression after two years

Of the 174 patients with a full 24-month evaluation, 80 (34%) were treated with PD, and 94 (40%) with HD. The proportion of patients presenting at least one carotid plaque increased significantly after 24 months of follow-up, from 56.1% to 70.3% (p = 0.0001). Progression of the lesions occurred in 51.1% of the patients, and the mean number of territories affected by plaque increased from 1.30 ±1.50 to 1.98 ±1.78 (p<0.01).

Univariate analysis of baseline potential risk factors for AVD progression is presented in Table 3. Patients with AVD progression were older, with more prevalence of diabetes, higher levels of c-Reactive Protein and lower levels of 25-hydroxy-vitamin D.

thumbnail
Table 3. Baseline factors associated with progression of atheromatous vascular disease (AVD) in all patients.

https://doi.org/10.1371/journal.pone.0186921.t003

Multivariate analysis (Table 4) showed that baseline presence of at least one carotid plaque, older age, and higher uric acid and cholesterol levels associated with an increased risk of plaque progression during follow-up. We detected a significant interaction between baseline presence of plaques and age, indicating that age predicted this outcome only in patients without plaques at baseline. Remarkably, the modality of dialysis did not predict progression of carotid plaques during follow-up.

Analysis of survival to cardiovascular events

A total of 51 patients had a fatal or non fatal CV event (18 acute coronary syndromes, 10 ischaemic strokes, 8 limb ischaemia events, 6 sudden deaths, 4 hemorrhagic strokes, 2 mesenteric ischaemia events, 1 aortic aneurism rupture, 1 heart failure and 1 major arrhythmia) during a median follow-up of 21.36 months (range 0.16–53.91). Univariate analysis showed that factors predicting CV events were age (HR 1.02; p = 0.037); diabetic nephropathy as etiology of renal disease (HR 4.8; p<0.001) longer dialysis vintage (HR 0.98;p = 0.011), higher serum glucose levels (HR 1.01; p<0.001), treatment with antiplatelet drugs (HR 2.15; p = 0.005), baseline presence of carotid plaques (HR 5 p<0.001), baseline number of territories with plaque (HR 1.39; p<0.001), thicker cIMT (HR3.87; p = 0.007) and ischaemic ABI (HR 2.08; p = 0.024)

Multivariate analysis of survival to the first CV event (Table 5) identified smoking status, baseline presence of at least one carotid plaque, diabetic and vascular nephropathy and serum phosphate levels as independent predictors of this outcome. On the contrary, the modality of dialysis did not perform as a significant predictor of the risk of CV events.

Discussion

The results of the present study showed that the modality of dialysis did not bear a differential impact either on the progression of atheromatous carotid or CV outcomes, when two relatively large samples of PD and HD patients, matched by age, gender, diabetes and dialysis vintage were compared, over a follow-up period of two years.

There is general agreement that ESRD patients suffer from accelerated atherosclerosis, as a consequence of the interplay of many traditional, uremia-related and novel risk factors [21]. The modality of dialysis can potentially influence the effects of some of these factors. For instance, both recurrent peritoneal loading with glucose-based dialysis solutions and a continuous peritoneal leak of proteins may result in a more atherogenic profile in PD patients, when compared with their counterparts on HD. The expected consequences include more severe degrees of dyslipidemia and insulin resistance in the former group. On the contrary, PD associates a better preservation of RKF, which may contribute to improve inflammation, endothelial dysfunction and vascular calcification, in these patients. However, the latter effects tend to fade with time on dialysis, as RKF declines. This can help to explain why in our study, which was restricted to prevalent patients, PD patients were more dyslipidemic, and presented worse blood pressure and mineral disease profiles than HD patients (Tables 1 and 2). Remarkably, these compared profiles did not match with the findings of baseline vascular US, which disclosed thinner cIMT and a lower proportion of patients with pathologic ABI values, in the PD group. The explanation for this apparent discrepancy is not clear, and could be a consequence of selection biases, but also of some protective effect of PD during the earlier phases of renal replacement therapy. In any case, atheromatous carotid disease progressed to a similar extent in both populations, and the incidence of CV events was not different. These findings support the current idea that PD and HD are medically equivalent, and that the selection of the modality of dialysis should be made according to the preference of the patient, after structured information and education processes [22].

The compared effect of the modality of dialysis on the progression of atherosclerotic disease has been insufficiently studied. A majority of the previous studies followed a cross-sectional design, and included relatively small samples of patients [1113]. As a consequence the results were largely inconclusive. On the contrary, our study had a longitudinal design, and the study groups were matched for essential variables related to the preexistent atherosclerotic burden of the patients. This type of strategy brings the design of the study close to a randomized clinical trial [23], which is not feasible in practical terms, given the difficulties to randomize patients to the modality of dialysis [24]. This approach should be considered superior to multivariate Cox regression, at the time of correcting for confounding factors, in observational studies [23].

In agreement with the general results of the NEFRONA study [25], the baseline presence of any carotid plaque was a consistent predictor of progression of AD and CV events. Similar observations have been reported by some studies in HD patients [2628]. In our study, AVD progression, including appearance of new plaques and CV events, was the rule in patients with carotid plaques at baseline, and the exception in those without. These findings support the utility of vascular US to detect CV risk subsets among ESRD patients with asymptomatic AD. This notwithstanding, the identification of phenotypic features could help to refine the identification of these subgroups.

Our results confirm the well-known association of some classic risk factors, including age and serum cholesterol, with AVD progression. Interestingly, we observed a statistical interaction between age and the baseline presence of carotid plaques, at the time of predicting the study outcomes. Older age predicted progression only in patients without plaques at baseline. This is in apparent contradiction with the notion that age is one of the most powerful correlates of AVD, and indicates that the presence of plaques in baseline US is more determinant, to predict outcomes. On the other hand, another apparently paradoxical finding was the inverse association between serum cholesterol levels and the progression of AVD. However, serum cholesterol has been claimed to present a U-shaped relationship to survival [2931] and both, low and high levels, seem to have a negative impact. Serum uric acid levels presented a direct correlation with the risk of progression of AVD. Besides the general association with the genetic background, dietary intake and comorbid conditions, serum uric acid levels in ESRD patients are also dependent on increased degradation pathways, RKF, dialysis removal and drug therapies, among other factors. The association between uric acid and progression of AVD in patients with CKD has not been reported previously, other than by other analyses of the NEFRONA project [25]. However, some previous studies have suggested an association between hyperuricemia and the presence of carotid plaques in the general population [32] as well as in diabetic individuals [33] and in patients with an established diagnosis of CV disease [34]. Moreover, some ongoing studies are exploring the role of antihyperuricemic drugs on the progression of carotid atherosclerosis, as evaluated by US [35].

Smoking, diabetic nephropathy and serum phosphate levels showed an independent effect in the prediction of CV events. These findings are essentially confirmatory of current knowledge. For instance, there is evidence that smoking increases the CV risk of patients on dialysis [36,37]. The increased CV risk profile of diabetics all along the spectrum of CKD is also well-known, and was clearly detected in the baseline analysis of the NEFRONA study [38]. Finally, hyperphosphatemia has been clearly linked to the CV outcome of patients on dialysis [39,40].

This study has significant limitations. The conclusions cannot be applied to the overall population of patients on dialysis, because only individuals without known preexistent CV disease were subject of analysis. This potential selection bias is more likely for hemodialysis patients, because group matching restricted inclusion to those with similar characteristics to PD patients. The size of the sample was relatively large, but may still be considered insufficient, given the large amont of covariables as well as the high rate of drop-outs. The period of monitorization could also be considered too short, but the risk of bias linked to the high proportion of study drop-outs, particularly in the PD group, argued against a longer follow-up. Among the strengths of the study, we should mention the multicenter, prospective approach, the matched group design, the quality of the screening tools (including vascular US), and the presentation of clear conclusions, well supported by the results of the study.

In summary, atherosclerotic arterial disease is very prevalent among patients on dialysis, and progresses over time in a significant proportion of cases. The presence of vascular disease at baseline is the best individual predictor of progression. Our study was able to identify some demographic and clinical correlates of progression, including older age, smoking, diabetic nephropathy, and serum levels of cholesterol, uric acid and serum phosphate. Most importantly, the modality of dialysis did not appear to influence the progression of atherosclerotic disease. These results agree to the notion of an essential clinical equivalence of HD and PD for the management of ESRD, and support selection of the modality of dialysis based on informed decision by the patients.

Acknowledgments

The authors would like to thank the NEFRONA team (Eva Castro, Virtudes María, Teresa Molí, Teresa Vidal, Meritxell Soria) and the Biobank of RedInRen for their invaluable support. The NEFRONA study investigator group is composed by the following: Aladrén Regidor, Mª José. Hospital Comarcal Ernest Lluch (Calatayud); Almirall, Jaume; Ponz, Esther. Corporació Parc Taulí (Barcelona); Arteaga Coloma, Jesús. Hospital de Navarra (Pamplona); Díaz, Raquel Hospital La Paz (Madrid); Belart Rodríguez, Montserrat. Sistemes Renals (Lleida); Gascón, Antonio, Hospital Obispo Polanco (Teruel); Bover Sanjuan, Jordi. Fundació Puigvert. IIB Sant Pau (Barcelona); Bronsoms Artero, Josep. Clínica Girona (Girona); Cabezuelo Romero, Juan B; Muray Cases, Salomé. Hospital Reina Sofía (Murcia); Calviño Varela, Jesús. Hospital Universitario Lugus Augusti (Lugo); Caro Acevedo, Pilar. Clínica Ruber (Madrid); Carreras Bassa, Jordi. Diaverum Baix Llobregat (Barcelona); Cases Amenós, Aleix; Massó Jiménez, Elisabet. Hospital Clínic (Barcelona); Moreno López, Rosario. Hospital de la Defensa (Zaragoza); Cigarrán Guldris, Secundino; López Prieto, Saray. Hospital Da Costa (Lugo); Comas Mongay, Lourdes. Hospital General de Vic (Barcelona); Comerma, Isabel. Hospital General de Manresa (Barcelona); Compte Jové, Mª Teresa, Hospital Santa Creu Jesús (Tarragona); Cuberes Izquierdo, Marta. Hospital Reina Sofía (Navarra); de Álvaro, Fernando; Hevia Ojanguren, Covadonga. Hospital Infanta Sofía (Madrid); de Arriba de la Fuente, Gabriel. Hospital Universitario Guadalajara (Guadalajara); del Pino y Pino, Mª Dolores. Complejo Hospitalario Universitario Torrecardenas (Almería); Diaz-Tejeiro Izquierdo, Rafael; Ahijado Hormigos, Francisco Hospital Virgen de la Salud (Toledo); Dotori, Marta. USP Marbella (Málaga); Duarte, Verónica. Hospital de Terrassa (Barcelona); Estupiñan Torres, Sara. Hospital Universitario Canarias (Santa Cruz de Tenerife); Fernández Reyes, Mª José. Hospital de Segovia (Segovia); Fernández Rodríguez, Mª Loreto. Hospital Príncipe de Asturias (Madrid); Fernández, Guillermina. Clínica Santa Isabel (Sevilla); Galán Serrano, Antonio. Hospital General Universitario de Valencia (Valencia); García Cantón, Cesar. Hospital Universitario Insular de Gran Canaria (Las Palmas); García Herrera, Antonio L. Hospital Universitario Puerto Real (Cádiz); García Mena, Mercedes. Hospital San Juan de Dios (Zaragoza); Gil Sacaluga, Luis; Aguilar, Maria. Hospital Virgen del Rocío (Sevilla); Górriz, José Luis. Hospital Universitario Doctor Peset (Valencia); Huarte Loza, Emma. Hospital San Pedro (Logroño); Lerma, José Luis. Hospital Universitario Salamanca (Salamanca); Liebana Cañada, Antonio. Hospital de Jaén (Jaén); Marín Álvarez, Jesús Pedro. Hospital San Pedro de Alcántara (Cáceres); Martín Alemany, Nàdia. Hospital Jose p Trueta (Girona); Martín García, Jesús. Hospital Nuestra Señora de Sonsoles (Ávila); Martínez Castelao, Alberto. Hospital Universitari de Bellvitge (Barcelona); Martínez Villaescusa, María. Complejo Hospitalario Universitario de Albacete (Albacete); Martínez, Isabel. Hospital Galdakao (Bilbao); Moina Eguren, Iñigo. Hospital Basurto (Bilbao); Moreno Los Huertos, Silvia. Hospital Santa Bárbara (Soria); Mouzo Mirco, Ricardo. Hospital El Bierzo, Ponferrada (León); Munar Vila, Antonia. Hospital Universitari Son Espases (Palma de Mallorca); Muñoz Díaz, Ana Beatriz. Hospital Virgen del Consuelo (Valencia); Navarro González, Juan F. Hospital Universitario Nuestra Señora de Candelaria (Santa Cruz de Tenerife); Nieto, Javier; Carreño, Agustín. Hospital General Universitario de Ciudad Real (Ciudad Real); Novoa Fernández, Enrique. Complexo Hospitalario de Ourense (Ourense); Ortiz, Alberto; Fernandez, Beatriz. IIS-Fundación Jiménez Díaz (Madrid); Paraíso, Vicente. Hospital Universitario del Henares (Madrid); Peris Domingo, Ana. Hospital Francesc de Borja (Valencia); Piñera Haces, Celestino. Hospital Universitario Marqués de Valdecilla (Santander); Prados Garrido, Mª Dolores. Hospital Universitario San Cecilio (Granada); Prieto Velasco, Mario. Hospital de León (León); Puig Marí, Carmina. Hospital d'Igualada (Barcelona); Rivera Gorrín, Maite. Hospital Universitario Ramón y Cajal (Madrid); Rubio, Esther. Hospital Puerta del Hierro (Madrid); Ruiz, Pilar. Hospital Sant Joan Despí Moisès Broggi (Barcelona); Salgueira Lazo, Mercedes; Martínez Puerto, Ana Isabel. Hospital Virgen Macarena (Sevilla); Sánchez Tomero, José Antonio. Hospital Universitario de la Princesa (Madrid); Sánchez, José Emilio. Hospital Universitario Central de Asturias (Oviedo); Sans Lorman, Ramon. Hospital de Figueres (Girona); Saracho, Ramon. Hospital de Santiago (Vitoria); Sarrias, Maria; Serón, Daniel. Hospital Universitari Vall d’Hebron (Barcelona); Soler, María José; Barrios, Clara. Hospital del Mar (Barcelona); Sousa, Fernando. Hospital Rio Carrión (Palencia); Toran, Daniel. Hospital General de Jerez (Cadiz); Tornero Molina, Fernando. Hospital de Sureste (Arganda del Rey); Usón Carrasco, José Javier. Hospital Virgen de la Luz (Cuenca); Valera Cortes, Ildefonso. Hospital Virgen de la Victoria (Málaga); Vilaprinyo del Perugia, Mª Merce. Institut Catala d’Urologia i Nefrologia (Barcelona); Virto Ruiz, Rafael C. Hospital San Jorge (Huesca); Vicente Pallarés Carratalá Clinica MEDEFIS (Vila-real. Castellón), Carlos Santos Altozano CS Azuqueca de Henares (Guadalajara); Miguel Artigao Ródenas CS Zona III (Albacete); Inés Gil Gil Área Básica Sanitaria de Arán. CAP Viella (Lleida); Francisco Adan Gil CS Alfaro (La Rioja); Emilio García Criado Centro de Salud del Carpio (Córdoba.); Rafael Durá Belinchón CS Godella (Valencia); Jose Mª Fernández Toro CS Zona Centro (Cáceres); Juan Antonio Divisón Garrote Centro de Salud de Casas Ibáñez. Consultorio de Fuentealbilla (Albacete).

References

  1. 1. Go AS, Chertow GM, Fan D, Mc Culloch CE, Hsy CY. Chronic kidney disease and the risks of death, cardiovascular events and hospitalization. N Engl J Med 2004; 351:1296–1305. pmid:15385656
  2. 2. Foley RN, Murray AM, Li SL, Herzog CA, Mac Bean Am, Eggers PW et al. Chronic kidney disease and the risk for cardiovascular disease, renal replacement, and death in the United States medicare population, 1998 to 1999. J Am Soc Nephrol 2005;16: 489–495. pmid:15590763
  3. 3. Bayés B, Pastor C, Bonal J, Juncà J, Hernández JM, Riutort M et al. Homocysteine, C-reactive protein, lipid, peroxidation and mortality in haemodialysis patients. Nephrol Dial Transplant 2003; 18:106–112. pmid:12480967
  4. 4. Nishizawa Y, Shoji T, Kawagishi T, Morii H. Atherosclerosis in uremia: possible roles of hyperparathyroidism and intermediate density lipoprotein accumulation. Kidney Int Suppl. 1997; 62:S90–92. pmid:9350691
  5. 5. O’Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke Gl, Wolfson SK Jr. Carotid- artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group. N Engl J Med 1999; 340:14–22. pmid:9878640
  6. 6. Johnsen SH, Mathiesen EB, Joakimsen O. Carotid atherosclerosis is a stronger predictor of myocardial infarction in women than in men: a 6-year follow-up study of 6226 persons: the Tromsø Study. Stroke 2007; 38:2873–2880 pmid:17901390
  7. 7. Hollander M, Bots ML, Del Sol AI, Koudstaal PJ, Witterman JC, Grobbee DE et al. Carotid plaques increase the risk of stroke and subtypes of cerebral infarction in asymptomatic elderly: the Rotterdam study. Circulation 2002; 105:2872–2877 pmid:12070116
  8. 8. Nishizawa Y, Shoji T, Maekawa K, Nagasue J, et al. Intima-media thickness predicts cardiovascular mortality in hemodialysis patients. Am J Kidney Dis 2003;41(S1): S76–S79.
  9. 9. Maeda S, Sawayama Y, Furusyo N, Shigematsu M, Hayashi J. The association between fatal vascular events and risk factors for carotid atherosclerosis in patients on maintenance hemodialysis: Plaque number of dialytic atherosclerosis study. Atherosclerosis 2009; 204:549–555. pmid:19281981
  10. 10. Benedetto FA, Mallamaci F, Triperi F, Zoccali C. Prognostic value of ultrasonographic measurement of carotid intima media thickness in dialysis patients. J Am Soc Nephrol 2001; 12:2458–2464. pmid:11675423
  11. 11. Yilmaz FM, Akay H, Duranay M, Yilmaz G, Oztekin PS, Kosar U et al. Carotid atherosclerosis and cardiovascular risk factors in hemodialysis and peritoneal dialysis patients. Clinical Biochemistry 2007; 40:1361–1366. pmid:17936258
  12. 12. Mutluay R, Degertekin CK, Poyraz F, Yilmaz MI, Yücel C, Turfan M et al. Dialysis type may predict carotid intima media thickness and plaque presence in end-stage renal disease. Adv Ther 2012; 29(4):370–382 pmid:22467434
  13. 13. Shi Z, Zhu M, Guan , Shen J, He Q, Zhang X J et al. Dialysis methods may affect carotid intima-media thickness in Chinese end-stage renal disease patients. Renal Failure 2012; 34:1206–1211. pmid:23009226
  14. 14. Junyent M, Martinez M, Borràs M, Coll B, Valdivielso JM, Vidal T et al. Predicting cardiovascular disease morbidity and mortality in chronic kidney disease in Spain. The rationale and design of NEFRONA: a prospective, multicenter, observational cohort study. BMC Nephrol 2010; 11: 14. pmid:20609210
  15. 15. Junyent M, Martinez M, Borràs M, Bertriu A, Coll B, Craver L et al. Usefulness of imaging techniques and novel biomarkers in the prediction of cardiovascular risk in patients with chronic kidney disease in Spain: The NEFRONA project. Nefrologia 2010; 30: 119–26. pmid:20098474
  16. 16. Arroyo D, Betriu A, Martínez-Alonso M, Vidal T, Valdivielso JM, Fernández E. Observational multicenter study to evaluate the prevalence and prognosis of subclinical atheromatosis in a Spanish chronic kidney disease cohort: baseline data from the NEFRONA study. BMC Nephrology 2014; 15: 168. pmid:25326683
  17. 17. La Piedra C, Fernández E, Casaus MLG, Parra EG. Different biological functions in PTH molecules? What are we measuring? Nefrologia 2008; 28: 123–128.
  18. 18. Stein JH, Korcarz CE, Hurst RT, Lonn E, Kendall CB, Mohler ER et al. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: A consensus statement from the American society of echocardiography carotid intima-media thickness task force endorsed by the society for vascular medicine. J Am Soc Echocardiogr 2008; 21: 93–111. pmid:18261694
  19. 19. Touboul PJ, Hennerici MG, Meairs S, Adams H, Amarenco P, Bornstein N et al. Mannheim carotid intima-media thickness and plaque consensus (2004-2006-2011). An update on behalf of the advisory board of the 3rd, 4th and 5th watching the risk symposia, at the 13th, 15th and 20th European Stroke Conferences, Mannheim, Germany, 2004, Brussels, Belgium, 2006, and Hamburg, Germany, 2011. Cerebrovasc Dis 2012; 34:290–296.
  20. 20. Tattersall MC, Gassett A, Korcarz CE, Gepner AD, Kaufman JD, Liu KJ et al. Predictors of Carotid Thickness and Plaque Progression during a decade The Multi-Ethnic Study of Atherosclerosis. Stroke 2014; 45:3257–3262 pmid:25213342
  21. 21. García-López E, Carrero JJ, Suliman ME, Lindholm B, Stenvinkel P. Risk factors for cardiovascular disease in patients undergoing peritoneal dialysis. Perit Dial Int 2007; 27(S2):S205–S209.
  22. 22. Covic A, Barnmens B, Lobbedez T, Segall L, Heimbürger O, van Biesen W et al. Educating end-stage renal disease patients on dialysis modality selection: clinical advice from the European Renal Best practices (ERBP) Advisory Board. Nephrol Dial Transplant 2010; 25:1757–59. pmid:20392704
  23. 23. Austin PC. An introduction to Propensity Score Methods for reducing the effects of confounding in observational studies. Mult Behav Res 2011; 46:399–424.
  24. 24. Korevaar JC, Feith GW, Dekker FW, van Manen JG, Boeschoten EW, Bossuyt PM et al for the Necosad Study Group. Effect of starting with hemodialysis compared with peritoneal dialysis in patients new on dialysis treatment: A randomized controlled trial. Kidney International 2003; 64:2222–2228. pmid:14633146
  25. 25. Gracia M, Betriu À, Martínez-Alonso M, Arroyo D, Abajo M, Fernández E, Valdivielso JM. NEFRONA Investigators. Predictors of Subclinical Atheromatosis Progression over 2 Years in Patients with Different Stages of CKD. Clin J Am Soc Nephrol. 2016 Feb 5;11(2):287–96 pmid:26668022
  26. 26. Sánchez-Alvarez JE, Delgado-Mallén P, González-Rinne A, Hernández-Marrero D, Lorenzo-Sellares V. Carotid ultrasound: prevention of heart disease and mortality on haemodialysis. Nefrologia. 2010; 30: 427–434. pmid:20651884
  27. 27. Schwaiger JP, Lamina C, Neyer U, König P, Katherin H, Sturm W et al. Carotid plaques and their predictive value for cardiovascular disease and all-cause mortality in hemodialysis patients considering renal transplantation: a decade follow-up. Am J Kidney Dis 2006; 47:888–897. pmid:16632029
  28. 28. Collado S, Coll E, Nicolau C, Pons M, Cruzado JM, Pascual J, et al. (2015) Carotid Atherosclerotic Disease Predicts Cardiovascular Events in Hemodialysis Patients: A Prospective Study. PLoS ONE
  29. 29. Iseki K, Yamazato M, Tozawa M, Takishita S. Hypocholesterolemia is a significant predictor of death in a cohort of chronic hemodialysis patients. Kidney Int 2002; 61:1887–1893. pmid:11967041
  30. 30. Kilpatrick RD, McAllister CJ, Kovesdy CP, Derose SF, Kopple JD, Kalantar-Zadeh K. Association between Serum Lipids and Survival in Hemodialysis Patients and Impact of Race. J Am Soc Nephrol 2007;18: 293–303. pmid:17167113
  31. 31. Lowrie EG, Lew NL. Death risk in hemodialysis patients: The predictive value of commonly measured variables and an evaluation of death rate differences between facilities. Am J Kidney Dis 1990; 15:458–482. pmid:2333868
  32. 32. Neogi T, Ellison RC, Hunt S, Terkeltaub R, Felson DT, Zahng Y. Serum uric acid is associated with carotid plaques: the National, Heart, Lung and Blood Institute Family Heart Study. J Rheumatol 2009; 36: 378–384. pmid:19012359
  33. 33. Li Q, Yang Z, Lu B, Wen J, Ye Z, Chen L et al. Serum uric acid level and its association with metabolic syndrome and carothid atherosclerosis in patients with type 2 diabetes. Cardiovascular Diabetology 2011; 10:72. pmid:21816063
  34. 34. Kumral E, Karaman B, Orman M, Kabaroglu C. Association of uric acid and carotid artery disease in patients with ischemic stroke. Acta Neurol Scand 2014; 130:11–17. pmid:24313880
  35. 35. Oyama J, Tanaka A, Sato Y, Tomiyama H, Sata M, Ishizu T et al PRIZE Study Investigators. Rationale and design of a multicenter randomized study for evaluating vascular function under uric acid control using the xanthine oxidase inhibitor, febuxostat: the PRIZE study. Cardiovasc Diabetol 2016; 15:87 pmid:27317093
  36. 36. Foley RN, Herzog CA, Collins AJ. Smoking and cardiovascular outcomes in dialysis patients: The United States Renal Data System Wave 2 study. Kidney Int 2003; 63:1462–1467 pmid:12631362
  37. 37. Zoccali C, Tripepi G, Mallamaci F. Predictors of cardiovascular death in ESRD. Semin Nephrol 2005; 25:358–362 pmid:16298255
  38. 38. Barrios C, Pascual J, Otero S, Soler MJ, Rodriguez E, Collado S et al investigators of the NEFRONA study. Diabetic nephropathy is an independent factor associated to severe subclinical atheromatous disease. Atherosclerosis 2015; 242:37–44. pmid:26177272
  39. 39. Schneider A, Jardine AG, Schneider MP, Holdaas H, Holme I, Fellstroem BC et al AURORA Study Group. Determinants of cardiovascular risk in haemodialysis patients: post hoc analyses of the AURORA study. J Ren Nutr 2013; 23:411–421.
  40. 40. Lertdumrongluk P, Rhee CM, Park J, Lau WL, Moradi H, Jing J et al. Association of serum phosphorus concentration with mortality in elderly and nonelderly hemodialysis patients. Am J Nephrol 2013; 3:144–151.