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• W2070169130 abstract "The goal of the Dialysis Outcomes in Colombia (DOC) study was to compare the survival of patients on hemodialysis (HD) vs peritoneal dialysis (PD) in a network of renal units in Colombia. The DOC study examined a historical cohort of incident patients starting dialysis therapy between 1 January 2001 and 1 December 2003 and followed until 1 December 2005, measuring demographic, socioeconomic, and clinical variables. Only patients older than 18 years were included. As-treated and intention-to-treat statistical analyses were performed using the Kaplan–Meier method and Cox proportional hazard model. There were 1094 eligible patients in total and 923 were actually enrolled: 47.3% started HD therapy and 52.7% started PD therapy. Of the patients studied, 751 (81.3%) remained in their initial therapy until the end of the follow-up period, death, or censorship. Age, sex, weight, height, body mass index, creatinine, calcium, and Subjective Global Assessment (SGA) variables did not show statistically significant differences between the two treatment groups. Diabetes, socioeconomic level, educational level, phosphorus, Charlson Co-morbidity Index, and cardiovascular history did show a difference, and were less favorable for patients on PD. Residual renal function was greater for PD patients. Also, there were differences in the median survival time between groups: 27.2 months for PD vs 23.1 months for HD (P=0.001) by the intention-to-treat approach; and 24.5 months for PD vs 16.7 months for HD (P<0.001) by the as-treated approach. When performing univariate Cox analyses using the intention-to-treat approach, associations were with age ≥65 years (hazard ratio (HR)=2.21; confidence interval (CI) 95% (1.77–2.755); P<0.001); history of cardiovascular disease (HR=1.96; CI 95% (1.58–2.90); P<0.001); diabetes (HR=2.34; CI 95% (1.88–2.90); P<0.001); and SGA (mild or moderate–severe malnutrition) (HR=1.47; CI 95% (1.17–1.79); P=0.001); but no association was found with gender (HR=1.03, CI 95% 0.83–1.27; P=0.786). Similar results were found with the as-treated approach, with additional associations found with Charlson Index (0-2) (HR=0.29; Cl 95% (0.22-0.38); P<0.001); Charlson Index (3-4) (HR=0.61; Cl 95% (0.48–0.79); P<0.001); and SGA (mild-severe malnutrition) (HR=1.43; Cl 95% (1.15–1.77); P<0.001). Similarly, the multivariate Cox model was run with the variables that had shown association in previous analyses, and it was found that the variables explaining the survival of patients with end-stage renal disease in our study were age, SGA, Charlson Comorbidity Index 5 and above, diabetes, healthcare regimes I and II, and socioeconomic level 2. The results of Cox proportional risk model in both the as-treated and intention-to-treat analyses showed that there were no statistically significant differences in survival of PD and HD patients: intention-to-treat HD/PD (HR 1.127; CI 95%: 0.855–1.484) and as-treated HD/PD (HR 1.231; CI 95%: 0.976–1.553). In this historical cohort of incident patients, there was a trend, although not statistically significant, for a higher (12.7%) adjusted mortality risk associated with HD when compared to PD, even though the PD patients were poorer, were more likely to be diabetic, and had higher co-morbidity scores than the HD patients. The variables that most influenced survival were age, diabetes, comorbidity, healthcare regime, socioeconomic level, nutrition, and education. The goal of the Dialysis Outcomes in Colombia (DOC) study was to compare the survival of patients on hemodialysis (HD) vs peritoneal dialysis (PD) in a network of renal units in Colombia. The DOC study examined a historical cohort of incident patients starting dialysis therapy between 1 January 2001 and 1 December 2003 and followed until 1 December 2005, measuring demographic, socioeconomic, and clinical variables. Only patients older than 18 years were included. As-treated and intention-to-treat statistical analyses were performed using the Kaplan–Meier method and Cox proportional hazard model. There were 1094 eligible patients in total and 923 were actually enrolled: 47.3% started HD therapy and 52.7% started PD therapy. Of the patients studied, 751 (81.3%) remained in their initial therapy until the end of the follow-up period, death, or censorship. Age, sex, weight, height, body mass index, creatinine, calcium, and Subjective Global Assessment (SGA) variables did not show statistically significant differences between the two treatment groups. Diabetes, socioeconomic level, educational level, phosphorus, Charlson Co-morbidity Index, and cardiovascular history did show a difference, and were less favorable for patients on PD. Residual renal function was greater for PD patients. Also, there were differences in the median survival time between groups: 27.2 months for PD vs 23.1 months for HD (P=0.001) by the intention-to-treat approach; and 24.5 months for PD vs 16.7 months for HD (P<0.001) by the as-treated approach. When performing univariate Cox analyses using the intention-to-treat approach, associations were with age ≥65 years (hazard ratio (HR)=2.21; confidence interval (CI) 95% (1.77–2.755); P<0.001); history of cardiovascular disease (HR=1.96; CI 95% (1.58–2.90); P<0.001); diabetes (HR=2.34; CI 95% (1.88–2.90); P<0.001); and SGA (mild or moderate–severe malnutrition) (HR=1.47; CI 95% (1.17–1.79); P=0.001); but no association was found with gender (HR=1.03, CI 95% 0.83–1.27; P=0.786). Similar results were found with the as-treated approach, with additional associations found with Charlson Index (0-2) (HR=0.29; Cl 95% (0.22-0.38); P<0.001); Charlson Index (3-4) (HR=0.61; Cl 95% (0.48–0.79); P<0.001); and SGA (mild-severe malnutrition) (HR=1.43; Cl 95% (1.15–1.77); P<0.001). Similarly, the multivariate Cox model was run with the variables that had shown association in previous analyses, and it was found that the variables explaining the survival of patients with end-stage renal disease in our study were age, SGA, Charlson Comorbidity Index 5 and above, diabetes, healthcare regimes I and II, and socioeconomic level 2. The results of Cox proportional risk model in both the as-treated and intention-to-treat analyses showed that there were no statistically significant differences in survival of PD and HD patients: intention-to-treat HD/PD (HR 1.127; CI 95%: 0.855–1.484) and as-treated HD/PD (HR 1.231; CI 95%: 0.976–1.553). In this historical cohort of incident patients, there was a trend, although not statistically significant, for a higher (12.7%) adjusted mortality risk associated with HD when compared to PD, even though the PD patients were poorer, were more likely to be diabetic, and had higher co-morbidity scores than the HD patients. The variables that most influenced survival were age, diabetes, comorbidity, healthcare regime, socioeconomic level, nutrition, and education. In the past three decades, a substantial body of evidence has been built around the outcomes of dialysis therapies. Among them, survival is one of the most significant, and in spite of the large number of studies, there is a considerable controversy about which therapy provides a better survival. Survival can be attributed to the therapy itself or to other factors such as age, diabetes, history of cardiovascular disease, residual renal function (RRF), gender, comorbidity at the start of therapy, geographical location, and race.1.Bargman J.M. Is there more to living than not dying? A reflection on survival studies in dialysis.Semin Dial. 2007; 20: 50-52Crossref PubMed Scopus (13) Google Scholar, 2.Bloembergen W. Port F. Mauger E. et al.A comparison of mortality between patients treated with hemodialysis and peritoneal dialysis.J Am Soc Nephrol. 1995; 6: 177-183Crossref PubMed Google Scholar, 3.Collins A. Hao W. Xia H. et al.Mortality risk of peritoneal dialysis and hemodialysis.Am J Kidney Dis. 1999; 6: 1065-1074Abstract Full Text Full Text PDF Scopus (317) Google Scholar, 4.Collins A.J. Impact of congestive heart failure and other cardiac diseases on patient outcomes.Kidney Int. 2002; 62: S3-S7Abstract Full Text Full Text PDF Scopus (14) Google Scholar, 5.Collins A.J. Weinhandl E. Snyder J.J. et al.Comparison and survival of hemodialysis and peritoneal dialysis in the elderly.Semin Dial. 2002; 15: 98-102Crossref PubMed Scopus (43) Google Scholar, 6.Fenton S. Schaubel D. Desmeules M. et al.Higher survival with CAPD/CCPD than with HD.Am J Kidney Dis. 1997; 30: 334-342Abstract Full Text PDF PubMed Scopus (538) Google Scholar, 7.Guo A. Mujais S. Patient and technique survival on peritoneal dialysis United States: evaluation in large incident cohorts.Kidney Int. 2003; 64: S3-S12Abstract Full Text Full Text PDF Scopus (168) Google Scholar, 8.Heaf J.G. Lokkegaard H. Madsen M. Initial survival advantage of peritoneal dialysis relative to haemodialysis.Nephrol Dial Transplant. 2002; 17: 112-117Crossref PubMed Scopus (301) Google Scholar, 9.Jaar B.G. Coresh J. Plantinga L.C. et al.Comparing the risk for death with peritoneal dialysis and hemodialysis in a national cohort of patients with chronic kidney disease.Ann Intern Med. 2005; 143: 174-183Crossref PubMed Scopus (269) Google Scholar, 10.Korevaar J.C. Feith G.W. Dekker F.W. et al.Effect of starting with hemodialysis compared with peritoneal dialysis in patients new on dialysis treatment: a randomized controlled trial.Kidney Int. 2003; 64: 2222-2228Abstract Full Text Full Text PDF PubMed Scopus (323) Google Scholar, 11.Liem Y.S. Wong J.B. Hunink M.G.M. et al.Comparison of hemodialysis and peritoneal dialysis survival in The Netherlands.Kidney Int. 2007; 71: 153-158Abstract Full Text Full Text PDF PubMed Scopus (173) Google Scholar, 12.Lynn K.L. McGregor D.O. Moesbergen T. et al.Hypertension as a determinant of survival for patients treated with home dialysis.Kidney Int. 2002; 62: 2281-2287Abstract Full Text Full Text PDF PubMed Scopus (42) Google Scholar, 13.Murphy S.W. Foley R.N. Barrett B.J. et al.Comparative mortality of hemodialysis and peritoneal dialysis in Canada.Kidney Int. 2000; 57: 1720-1726Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, 14.Pei Y.P. Greenwood C.M. Chery A.L. et al.Racial differences in survival of patients on dialysis.Kidney Int. 2000; 58: 1293-1299Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar, 15.Rayner H.C. Pisoni R.L. Bommer J. et al.Mortality and hospitalization in haemodialysis patients five European countries: results from the Dialysis Outcomes and Practice Patterns Study (DOPPS).Nephrol Dial Transplant. 2004; 19: 108-120Crossref PubMed Scopus (283) Google Scholar, 16.Maiorca R. Vonesh E. Cancarini G.C. et al.A six-year comparison of patient and technique survivals in CAPD and HD.Kidney Int. 1988; 34: 518-524Abstract Full Text PDF PubMed Scopus (112) Google Scholar, 17.Rubin J. Barnes T. Burns P. et al.Comparison of home hemodialysis to continuous ambulatory peritoneal dialysis.Kidney Int. 1983; 23: 51-56Abstract Full Text PDF PubMed Scopus (21) Google Scholar, 18.Selgas R. Cirugeda A. Fernandez-Perpen A. et al.Comparisons of hemodialysis and CAPD in patients over 65 years of age: A meta-analysis.Int Urol Nephrol. 2001; 33: 259-264Crossref PubMed Scopus (22) Google Scholar, 19.Schulman G. Mortality and Treatment modality of end-stage renal disease.Ann Intern Med. 2005; 143: 229-231Crossref PubMed Scopus (8) Google Scholar, 20.Termorshuizen F. Korevaar J.C. Dekker F.W. et al.Hemodialysis and peritoneal dialysis: comparison of adjusted mortality rates according to the duration of dialysis: analysis of the Netherlands cooperative study on the adequacy of dialysis 2.J Am Soc Nephrol. 2003; 14: 2851-2860Crossref PubMed Scopus (235) Google Scholar, 21.Vonesh E.F. Snyder J.J. Foley R.N. et al.The differential impact of risk factors on mortality in hemodialysis and peritoneal dialysis.Kidney Int. 2004; 66: 2389-2401Abstract Full Text Full Text PDF PubMed Scopus (285) Google Scholar Assignment of the patients to different treatments varies by country and the type of dialysis center. There are some factors that increase the likelihood that peritoneal dialysis (PD) will be used for renal replacement therapy (RRT). Among these are white race, employed, low comorbidity score, good RRF, and normal albumin levels at the start of the therapy.9.Jaar B.G. Coresh J. Plantinga L.C. et al.Comparing the risk for death with peritoneal dialysis and hemodialysis in a national cohort of patients with chronic kidney disease.Ann Intern Med. 2005; 143: 174-183Crossref PubMed Scopus (269) Google Scholar,11.Liem Y.S. Wong J.B. Hunink M.G.M. et al.Comparison of hemodialysis and peritoneal dialysis survival in The Netherlands.Kidney Int. 2007; 71: 153-158Abstract Full Text Full Text PDF PubMed Scopus (173) Google Scholar Among the different racial groups, there are differences in dialysis survival, which are demonstrated after adjusting for comorbidity risk factors, possibly associated with genetic and environmental factors,14.Pei Y.P. Greenwood C.M. Chery A.L. et al.Racial differences in survival of patients on dialysis.Kidney Int. 2000; 58: 1293-1299Abstract Full Text Full Text PDF PubMed Scopus (94) Google Scholar justifying further research in different countries and ethnic groups. Colombia is a country of 42.1 million inhabitants,22.Departamento Administrativo Nacional de Estadística DANECenso General Colombia 2005. 2008Google Scholar with an unemployment rate of 11%, a monthly minimum wage of 223 USD,23.Departamento Administrativo Nacional de Estadística DANEIndicadores Económicos Colombia. 2007Google Scholar a projected gross domestic product per capita of 2.574 USD, with 52.4% of the population under the poverty line and health expenses equivalent to 7.7% of the GDP.24.Pan American Health Organization, Ministerio de Protección Social Boletín Epidemiológico. PAHO, Bogotá DC2006: 1-24Google Scholar In 2005, the estimated dialysis prevalence was 355 patients per million (p.p.m.) population, of which 40% were on PD and 60% on HD.25.Asociación Colombiana de Nefrología e Hipertensión Arterial Datos Colombianos de Diálisis y Transplantes para el Registro Latinoamericano de Diálisis In: Gómez R, Bogotá DC (eds) Asociación Colombiana de Nefrología e Hipertensión Arterial 2005 data from Asociation Colombiana de Nefrologia for the register of Sociedad Latinoamericana de Nefrologia e Hipertension (SLANH) athttp://www.slanh.org.Google Scholar Approximately 2% of the national health expenses is allocated to the management of the renal disease.26.Ministerio de la Protección Social República de Colombia, Fundación para la Investigación y Desarrollo de Salud y la Seguridad SocialGuia para el manejo de la enfermedad renal crónica -ERC- basada en la evidencia Colombia. 1st edn. Editorial Scripto Ltda, Bogotá, DC2007Google Scholar The Colombian General Social Security and Health System has defined three basic regimes with different financing frameworks that guarantee patients with end-stage renal disease (ESRD) access to the different types of RRT with dialysis. Regime I, also known as the ‘contributive regime,’ which covered 36.3% of the population in 2006, guarantees overall health insurance. Regime II, called the ‘subsidized regime,’ is financed by both state resources and crossover subsidies, and is intended for people who do not have formal employment and are classified as part of the poor population (43%). Regime III, ‘under a subsidized regime,’ provides coverage to a poor population group that is not favored with regime II and gets medical assistance through a structure of public welfare financed with state resources (20.7%). The remaining 4.8% of the population is covered by special regimes with greater accessibility and a larger number of benefits.27.Pan American Health OrganizationPAHO Basic Health Indicator Data Base – Colombia. 2007Google Scholar The goal of the Dialysis Outcomes in Colombia (DOC) study is to compare the survival of hemodialysis (HD) patients and PD patients in a cohort of incident patients getting dialysis in Colombia, taking into account all the aforementioned demographic and socioeconomic factors and assessing variables of interest in the patients studied. Of 1094 patients eligible to enter the DOC study, data from 923 patients who started RRT with dialysis between 1 January 2001 and 1 December 2003 were recorded retrospectively. For the remaining 171 (15.6%) eligible patients, complete baseline and outcome data were not available; these patients were therefore excluded from the study. Of the 923 patients enrolled, 437 (47.3%) were started on HD and 486 (52.7%) on PD, defining the intention-to-treat group. The as-treated group was defined as the sum of the patients who remained on the initial therapy modality until the end of the follow-up period, those who died or were censored (751 patients, 81.3%), and those who switched from HD to PD (85 patients) from PD to HD (87 patients) censored 60 days after the switch (Figure 1). Statistically significant differences in the continuous variables were not found between PD and HD patients upon entering the cohort, except for RRF (higher in PD when compared to HD, P=0.006) and phosphorus level (higher in PD when compared to HD, P=0.01) (Table 1). It should be stressed that only 55.1% (509) of the records actually recorded RRF, the reason why this variable was not included in the multivariate analyses.Table 1Summary for quantitative variablesHDPDP-valueN437486Age (years) Mean (range)54.5 (18–87)52.6 (18–95) s.d.15.815.6NS Median5754Weight (kg) Mean (range)59.5 (33–107)69.4 (34–104) s.d.11.111.3NS Median5860Height (m) Mean (range)1.60 (1.35–1.82)1.60 (1.36–1.82) s.d.0.090.09NS Median1.611.61BMI (kg m−2) Mean (range)23.1 (14.1–44.1)23.5 (15–39.2) s.d.3.93.8NS Median22.823.1RRFaN=509.(ml min−1) Mean (range)2.03 (0–14.7)2.67 (0–26) s.d.2.713.50.006 Median0.7901.61Creatinine (mg%) Mean (range)7.21 (2.0–18.6)7.15 (1.7–29) s.d.33.5NS Median6.96.5Calcium (mg%) Mean (range)8.8 (3.3–14.4)8.7 (3.4–15) s.d.1.61.9NS Median9.08.9Phosphorus (mg%) Mean (range)4.35 (1.0–12)4.6 (1.6–13.8) s.d.1.41.40.01 Median4.14.4BMI, body mass index; HD, hemodialysis; N, number of patients; NS, not significant; PD, peritoneal dialysis; RRF, residual renal function; s.d., standard deviation.a N=509. Open table in a new tab BMI, body mass index; HD, hemodialysis; N, number of patients; NS, not significant; PD, peritoneal dialysis; RRF, residual renal function; s.d., standard deviation. PD and HD patients were compared for gender, social security regime, education, socioeconomic level, ESRD etiology, Subjective Global Assessment (SGA), history of cardiovascular disease, and Charlson Comorbidity Index. A larger proportion of PD patients was found for the following variables: socioeconomic level 1 (P=0.03), healthcare regime II (P<0.001) and III (P<0.001), diabetes mellitus (DM) (P=0.0049), history of cardiovascular disease (P<0.001), and Charlson Comorbidity Index ≥5 (P=0.0037) (Table 2).Table 2Summary for qualitative variablesHDPDN%N%P-valueGender Male2585926754.9NS Female1794121945.1Regime of health coverage I27462.730061.7NS II14533.211122.80.0000 III184.17515.40.0000Education Illiterate317.1357.2NS Elementary26660.928258NS High school9521.712826.3NS University378.5275.6NS Postgraduate81.8142.9NSSocioeconomic level 17817.811623.90.0308 218241.620341.8NS 313029.711924.5NS 4388.7336.8NS 571.661.2NS 620.591.9NSCause of ESRD Diabetes15735.922045.30.0049 Hypertension14032.012826.3NS Glomerulonephritis439.85010.3NS Polycystic kidney disease71.6102.1NS Obstructive uropathy296.6153.1NS Others337.6214.3NS Unknown cause286.4428.6NSSGA Well nourished25357.923949.2NS Mild or moderate malnutrition13831.619339.7NS Severe malnutrition388.7408.2NS No data81.8142.9Cardiovascular history Yes11225.614930.70.0003 No32574.433368.5Charlson Comorbidity Index 0–218041.218738.5NS 3–414332.715030.9NS 5–109221.114429.60.0037ESRD, end-stage renal disease; HD, hemodialysis; NS, not significant; PD, peritoneal dialysis; SGA, Subjective Global Assessment. Open table in a new tab ESRD, end-stage renal disease; HD, hemodialysis; NS, not significant; PD, peritoneal dialysis; SGA, Subjective Global Assessment. By the Kaplan–Meier method with the log-rank test, statistically significant differences were found in patient survival by therapy, with a better survival for PD patients compared to HD patients (P<0.001; Figure 2a). The median survival time was 27.2 months for patients on PD and 23.1 months for patients on HD, with a statistically significant difference (Mann–Whitney test P=0.001). Survival curves of PD vs HD with the Cox proportional hazard model adjusting by covariates did not show statistical differences (HD/PD HR=1.12, CI 95% (0.855–1.484) P=0.396; Figure 2b). Survival adjusted for age and DM did not show statistically significant differences for PD vs HD patients (Figure 3), except for the group of nondiabetic patients younger than 65 years, in whom survival was better on PD (P=0.03). In the univariate Cox model, non-survival risk was associated with age ≥65 years (hazard ratio (HR)=2.21, confidence interval (CI) 95% (1.77–2.755); P<0.001); history of cardiovascular disease (HR=1.96, CI 95% (1.58–2.90); P<0.001); diabetes (HR=2.34, CI 95% (1.88–2.90); P<0.001); and SGA (mild or moderate–severe malnutrition) (HR=1.47, CI 95% (1.17–1.79); P<0.001), whereas there was no association with gender (HR=1.03, CI 95%, 0.83–1.27; P=0.786). In the multivariate Cox proportional risks model, age, SGA, Charlson Comorbidity Index 5 and above, diabetes, regimes I and II, and socioeconomic level 2 showed statistical significance in explaining survival of ESRD patients. There was no difference in survival between HD and PD patients when adjustments were made for other confounding risk factors (Table 3 and Table 4).Table 3Cox proportional hazard model (intention-to-treat)CI 95% for HRβHRLowerUpperP-valueAge (≥65 years)0.6881.9891.5002.6370.000SGA (mild–severe malnutrition)0.2821.3251.0051.7480.046Charlson Comorbidity Index (0–2): (≥5)-1.0160.3620.2430.5380.000Charlson Comorbidity Index (3–4): (≥5)-0.5340.5860.4300.7990.001Diabetes mellitus0.5701.7681.3012.4020.000Regime (I): (III)-0.5260.5910.3870.9010.015Regime (II): (III)-0.5050.6030.3770.9660.036Socioeconomic level (1): (6)0.9362.5500.9396.9280.066Socioeconomic level (2): (6)1.0222.7791.0367.4540.042Cardiovascular history0.2561.2920.9801.7040.069Therapy HD/PD0.1191.1270.8551.4840.396CI, confidence interval; HD, hemodialysis; HR, hazard ratio; PD, peritoneal dialysis; SGA, Subjective Global Assessment. Open table in a new tab Table 4Cox proportional hazard model (as-treated)CI 95 % for HRβHRLowerUpperP-valueAge (≥65 years)0.6261.8711.4702.3800.000SGA (mild–severe malnutrition)0.2831.3271.0571.6650.015Charlson Comorbidity Index (0–2): (≥5)-0.8520.4260.2890.6100.000Charlson Comorbidity Index (3–4): (≥5)-0.3850.6800.5210.8880.005DM0.3281.3891.0661.8090.015Regime (I): (III)-0.5410.5820.3940.8590.006Regime (II): (III)-0.4140.6610.4331.0080.055Socioeconomic level (1): (6)0.8412.3180.8796.1140.089Socioeconomic level (2): (6)0.8252.2820.8755.9510.092Cardiovascular history0.3491.4181.1181.7980.004Therapy HD/PD0.2081.2310.9761.5530.079CI, confidence interval; DM, diabetes mellitus; HD, hemodialysis; HR, hazard ratio; PD, peritoneal dialysis; SGA, Subjective Global Assessment. Open table in a new tab CI, confidence interval; HD, hemodialysis; HR, hazard ratio; PD, peritoneal dialysis; SGA, Subjective Global Assessment. CI, confidence interval; DM, diabetes mellitus; HD, hemodialysis; HR, hazard ratio; PD, peritoneal dialysis; SGA, Subjective Global Assessment. With the Kaplan–Meier method, survival in PD patients was better when compared to HD patients (log-rank test, P=0.0237) (Figure 4a). When comparing the median survival times using this approach (Mann–Whitney test), there was a difference in the median survival time of 7.8 months (P<0.001) in favor of PD. Survival curves for PD vs HD with the Cox proportional hazard model adjusting by covariates did not show statistical differences (HD/PD HR=1.23, CI 95% (0.976–1.553); P=0.079; Figure 4b). In univariate Cox model, non-survival risk was associated with age ≥65 years (HR=2.22, CI 95% (1.79–2.77); P<0.001); history of cardiovascular disease (HR=1.97, CI 95% (1.59–2.45); P<0.001); diabetes (HR=2.19, CI 95% (1.77–2.73); P<0.001); regime I (HR=0.75, CI 95% (0.52–1.06); P=0.107); regime II (HR=0.67, CI 95% (0.45–1.00); P=0.054), Charlson Index (0–2) (HR=0.29, CI 95% (0.22–0.38); P<0.001); Charlson Index (3–4) (HR=0.61, CI 95% (0.48–0.79); P<0.001); SGA (mild or moderate–severe malnutrition) (HR=1.43, CI 95% (1.15–1.77); P<0.001), whereas there was no association with gender (HR=0.92, CI 95% (0.74–1.14); P=0.46). The multivariate Cox proportional risks model showed that the variables that were significant in the intention-to-treat analysis also influenced survival under the as-treated approach, except for the regime II (HR=0.66, CI 95% (0.433–1.00); P=0.055); and socioeconomic level 2 (HR=2.28, CI 95% (0.87–5.95); P=0.092). When conducting the analysis adjusted for age and DM, statistically significant differences were obtained only for patients younger than 65 years and nondiabetic, favoring PD (P=0.021; Figure 5a). The current study constitutes the first large initiative in Colombia to compare survival results of HD and PD patients. Socioeconomic status of patients who were included in the study was similar to that of the Colombian population with ESRD on dialysis therapy.25.Asociación Colombiana de Nefrología e Hipertensión Arterial Datos Colombianos de Diálisis y Transplantes para el Registro Latinoamericano de Diálisis In: Gómez R, Bogotá DC (eds) Asociación Colombiana de Nefrología e Hipertensión Arterial 2005 data from Asociation Colombiana de Nefrologia for the register of Sociedad Latinoamericana de Nefrologia e Hipertension (SLANH) athttp://www.slanh.org.Google Scholar In contrast with studies from other regions,5.Collins A.J. Weinhandl E. Snyder J.J. et al.Comparison and survival of hemodialysis and peritoneal dialysis in the elderly.Semin Dial. 2002; 15: 98-102Crossref PubMed Scopus (43) Google Scholar, 9.Jaar B.G. Coresh J. Plantinga L.C. et al.Comparing the risk for death with peritoneal dialysis and hemodialysis in a national cohort of patients with chronic kidney disease.Ann Intern Med. 2005; 143: 174-183Crossref PubMed Scopus (269) Google Scholar, 13.Murphy S.W. Foley R.N. Barrett B.J. et al.Comparative mortality of hemodialysis and peritoneal dialysis in Canada.Kidney Int. 2000; 57: 1720-1726Abstract Full Text Full Text PDF PubMed Scopus (133) Google Scholar, 16.Maiorca R. Vonesh E. Cancarini G.C. et al.A six-year comparison of patient and technique survivals in CAPD and HD.Kidney Int. 1988; 34: 518-524Abstract Full Text PDF PubMed Scopus (112) Google Scholar, 21.Vonesh E.F. Snyder J.J. Foley R.N. et al.The differential impact of risk factors on mortality in hemodialysis and peritoneal dialysis.Kidney Int. 2004; 66: 2389-2401Abstract Full Text Full Text PDF PubMed Scopus (285) Google Scholar 53% of the patients included in the DOC study were being treated with PD, a higher proportion than reported for Colombia by the Asociación Colombiana de Nefrología in the year 200525.Asociación Colombiana de Nefrología e Hipertensión Arterial Datos Colombianos de Diálisis y Transplantes para el Registro Latinoamericano de Diálisis In: Gómez R, Bogotá DC (eds) Asociación Colombiana de Nefrología e Hipertensión Arterial 2005 data from Asociation Colombiana de Nefrologia for the register of Sociedad Latinoamericana de Nefrologia e Hipertension (SLANH) athttp://www.slanh.org.Google Scholar and for the rest of Latin America. PD utilization is reported to be about 30% in such countries as Brazil, Argentina, Uruguay, Salvador, and Guatemala.28.Pecoits-Filho R. Peritoneal dialysis in Latin America.Perit Dial Int. 2007; 27: 314-315Google Scholar This may possibly be due to a larger acceptance of PD therapy in those units that contributed patients for this study. In addition, dialysis therapy trends have historically shown a preference for PD in Colombia. Gender, age, and comorbidity distribution is similar to the ones in other comparative studies found in the literature. However, regarding the demographic variables (regime, education, and socioeconomic level), there are clear differences specific to a developing country like Colombia.9.Jaar B.G. Coresh J. Plantinga L.C. et al.Comparing the risk for death with peritoneal dialysis and hemodialysis in a national cohort of patients with chronic kidney disease.Ann Intern Med. 2005; 143: 174-183Crossref PubMed Scopus (269) Google Scholar, 11.Liem Y.S. Wong J.B. Hunink M.G.M. et al.Comparison of hemodialysis and peritoneal dialysis survival in The Netherlands.Kidney Int. 2007; 71: 153-158Abstract Full Text Full Text PDF PubMed Scopus (173) Google Scholar, 18.Selgas R. Cirugeda A. Fernandez-Perpen A. et al.Comparisons of hemodialysis and CAPD in patients over 65 years of age: A meta-analysis.Int Urol Nephrol. 2001; 33: 259-264Crossref PubMed Scopus (22) Google Scholar, 29.Vonesh E. Moran J. Mortality in End-stage renal disease: a reassessment of differences between patients treated with hemodialysis and peritoneal dialysis.J Am Soc Nephrol. 1999; 10: 354-365PubMed Google Scholar Health system insurance modality is an important variable with regard to access to dialysis therapy, and equally could be associated with poverty and with final outcomes.24.Pan American Health Organization, Ministerio de Protección Social Boletín Epidemiológico. PAHO, Bogotá DC2006: 1-24Google Scholar In the DOC study the proportion o" @default.
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