3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      High-performance dialyzers and mortality in maintenance hemodialysis patients

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Few data are available regarding the association of dialyzer type with prognosis. In Japan, dialyzers are classified as types I, II, III, IV, and V based on β 2-microglobulin clearance rates of < 10, < 30, < 50, < 70, and ≥ 70 mL/min, respectively. We investigated the relationship of the 5 dialyzer types with 1-year mortality. This nationwide cohort study used data collected at the end of 2008 and 2009 by the Japanese Society for Dialysis Therapy Renal Data Registry. We enrolled 203,008 patients on maintenance hemodialysis who underwent hemodialysis for at least 1 year and were managed with any of the 5 dialyzer types. To evaluate the association of dialyzer type with 1-year all-cause mortality, Cox proportional hazards models and propensity score-matched analyses were performed. After adjustment of the data with clinicodemographic factors, the type I, II, and III groups showed significantly higher hazard ratios (HRs) than the type IV dialyzers (reference). After adjustment for Kt/V and β 2-microglobulin levels, the HRs were significantly higher in the type I and II groups. After further adjustment for nutrition- and inflammation-related factors, the HRs were not significantly different between the type IV and type I and II groups. However, type V dialyzers consistently showed a significantly lower HR. With propensity score matching, the HR for the type V dialyzer group was significantly lower than that for the type IV dialyzer group. Additional long-term trials are required to determine whether type V dialyzers, which are high-performance dialyzers, can improve prognosis.

          Related collections

          Most cited references33

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016–40 for 195 countries and territories

          Summary Background Understanding potential trajectories in health and drivers of health is crucial to guiding long-term investments and policy implementation. Past work on forecasting has provided an incomplete landscape of future health scenarios, highlighting a need for a more robust modelling platform from which policy options and potential health trajectories can be assessed. This study provides a novel approach to modelling life expectancy, all-cause mortality and cause of death forecasts —and alternative future scenarios—for 250 causes of death from 2016 to 2040 in 195 countries and territories. Methods We modelled 250 causes and cause groups organised by the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) hierarchical cause structure, using GBD 2016 estimates from 1990–2016, to generate predictions for 2017–40. Our modelling framework used data from the GBD 2016 study to systematically account for the relationships between risk factors and health outcomes for 79 independent drivers of health. We developed a three-component model of cause-specific mortality: a component due to changes in risk factors and select interventions; the underlying mortality rate for each cause that is a function of income per capita, educational attainment, and total fertility rate under 25 years and time; and an autoregressive integrated moving average model for unexplained changes correlated with time. We assessed the performance by fitting models with data from 1990–2006 and using these to forecast for 2007–16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990–2016. We used this model for 195 countries and territories to generate a reference scenario or forecast through 2040 for each measure by location. Additionally, we generated better health and worse health scenarios based on the 85th and 15th percentiles, respectively, of annualised rates of change across location-years for all the GBD risk factors, income per person, educational attainment, select intervention coverage, and total fertility rate under 25 years in the past. We used the model to generate all-cause age-sex specific mortality, life expectancy, and years of life lost (YLLs) for 250 causes. Scenarios for fertility were also generated and used in a cohort component model to generate population scenarios. For each reference forecast, better health, and worse health scenarios, we generated estimates of mortality and YLLs attributable to each risk factor in the future. Findings Globally, most independent drivers of health were forecast to improve by 2040, but 36 were forecast to worsen. As shown by the better health scenarios, greater progress might be possible, yet for some drivers such as high body-mass index (BMI), their toll will rise in the absence of intervention. We forecasted global life expectancy to increase by 4·4 years (95% UI 2·2 to 6·4) for men and 4·4 years (2·1 to 6·4) for women by 2040, but based on better and worse health scenarios, trajectories could range from a gain of 7·8 years (5·9 to 9·8) to a non-significant loss of 0·4 years (–2·8 to 2·2) for men, and an increase of 7·2 years (5·3 to 9·1) to essentially no change (0·1 years [–2·7 to 2·5]) for women. In 2040, Japan, Singapore, Spain, and Switzerland had a forecasted life expectancy exceeding 85 years for both sexes, and 59 countries including China were projected to surpass a life expectancy of 80 years by 2040. At the same time, Central African Republic, Lesotho, Somalia, and Zimbabwe had projected life expectancies below 65 years in 2040, indicating global disparities in survival are likely to persist if current trends hold. Forecasted YLLs showed a rising toll from several non-communicable diseases (NCDs), partly driven by population growth and ageing. Differences between the reference forecast and alternative scenarios were most striking for HIV/AIDS, for which a potential increase of 120·2% (95% UI 67·2–190·3) in YLLs (nearly 118 million) was projected globally from 2016–40 under the worse health scenario. Compared with 2016, NCDs were forecast to account for a greater proportion of YLLs in all GBD regions by 2040 (67·3% of YLLs [95% UI 61·9–72·3] globally); nonetheless, in many lower-income countries, communicable, maternal, neonatal, and nutritional (CMNN) diseases still accounted for a large share of YLLs in 2040 (eg, 53·5% of YLLs [95% UI 48·3–58·5] in Sub-Saharan Africa). There were large gaps for many health risks between the reference forecast and better health scenario for attributable YLLs. In most countries, metabolic risks amenable to health care (eg, high blood pressure and high plasma fasting glucose) and risks best targeted by population-level or intersectoral interventions (eg, tobacco, high BMI, and ambient particulate matter pollution) had some of the largest differences between reference and better health scenarios. The main exception was sub-Saharan Africa, where many risks associated with poverty and lower levels of development (eg, unsafe water and sanitation, household air pollution, and child malnutrition) were projected to still account for substantive disparities between reference and better health scenarios in 2040. Interpretation With the present study, we provide a robust, flexible forecasting platform from which reference forecasts and alternative health scenarios can be explored in relation to a wide range of independent drivers of health. Our reference forecast points to overall improvements through 2040 in most countries, yet the range found across better and worse health scenarios renders a precarious vision of the future—a world with accelerating progress from technical innovation but with the potential for worsening health outcomes in the absence of deliberate policy action. For some causes of YLLs, large differences between the reference forecast and alternative scenarios reflect the opportunity to accelerate gains if countries move their trajectories toward better health scenarios—or alarming challenges if countries fall behind their reference forecasts. Generally, decision makers should plan for the likely continued shift toward NCDs and target resources toward the modifiable risks that drive substantial premature mortality. If such modifiable risks are prioritised today, there is opportunity to reduce avoidable mortality in the future. However, CMNN causes and related risks will remain the predominant health priority among lower-income countries. Based on our 2040 worse health scenario, there is a real risk of HIV mortality rebounding if countries lose momentum against the HIV epidemic, jeopardising decades of progress against the disease. Continued technical innovation and increased health spending, including development assistance for health targeted to the world's poorest people, are likely to remain vital components to charting a future where all populations can live full, healthy lives. Funding Bill & Melinda Gates Foundation.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Clinical practice guidelines for hemodialysis adequacy, update 2006.

            (2006)
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Effect of dialysis dose and membrane flux in maintenance hemodialysis.

              The effects of the dose of dialysis and the level of flux of the dialyzer membrane on mortality and morbidity among patients undergoing maintenance hemodialysis are uncertain. We undertook a randomized clinical trial in 1846 patients undergoing thrice-weekly dialysis, using a two-by-two factorial design to assign patients randomly to a standard or high dose of dialysis and to a low-flux or high-flux dialyzer. In the standard-dose group, the mean (+/-SD) urea-reduction ratio was 66.3+/-2.5 percent, the single-pool Kt/V was 1.32+/-0.09, and the equilibrated Kt/V was 1.16+/-0.08; in the high-dose group, the values were 75.2+/-2.5 percent, 1.71+/-0.11, and 1.53+/-0.09, respectively. Flux, estimated on the basis of beta2-microglobulin clearance, was 3+/-7 ml per minute in the low-flux group and 34+/-11 ml per minute in the high-flux group. The primary outcome, death from any cause, was not significantly influenced by the dose or flux assignment: the relative risk of death in the high-dose group as compared with the standard-dose group was 0.96 (95 percent confidence interval, 0.84 to 1.10; P=0.53), and the relative risk of death in the high-flux group as compared with the low-flux group was 0.92 (95 percent confidence interval, 0.81 to 1.05; P=0.23). The main secondary outcomes (first hospitalization for cardiac causes or death from any cause, first hospitalization for infection or death from any cause, first 15 percent decrease in the serum albumin level or death from any cause, and all hospitalizations not related to vascular access) also did not differ significantly between either the dose groups or the flux groups. Possible benefits of the dose or flux interventions were suggested in two of seven prespecified subgroups of patients. Patients undergoing hemodialysis thrice weekly appear to have no major benefit from a higher dialysis dose than that recommended by current U.S. guidelines or from the use of a high-flux membrane. Copyright 2002 Massachusetts Medical Society
                Bookmark

                Author and article information

                Contributors
                abe.masanori@nihon-u.ac.jp
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                10 June 2021
                10 June 2021
                2021
                : 11
                : 12272
                Affiliations
                [1 ]GRID grid.458411.d, ISNI 0000 0004 5897 9178, The Committee of Renal Data Registry, The Japanese Society for Dialysis Therapy, ; Tokyo, Japan
                [2 ]GRID grid.260969.2, ISNI 0000 0001 2149 8846, Division of Nephrology, Hypertension and Endocrinology, Department of Internal Medicine, , Nihon University School of Medicine, ; Tokyo, Japan
                [3 ]Yabuki Hospital, Yamagata, Japan
                [4 ]Department of Nephrology, Kitasaito Hospital, Asahikawa, Japan
                [5 ]GRID grid.256115.4, ISNI 0000 0004 1761 798X, Department of Clinical Engineering, , Fujita Health University, ; Aichi, Japan
                [6 ]GRID grid.415086.e, ISNI 0000 0001 1014 2000, Medical Science, , Kawasaki Medical School, ; Okayama, Japan
                [7 ]GRID grid.410818.4, ISNI 0000 0001 0720 6587, Department of Nephrology, , Tokyo Women’s Medical University, ; Tokyo, Japan
                [8 ]GRID grid.410802.f, ISNI 0000 0001 2216 2631, Department of General Internal Medicine, , Saitama Medical University, ; Saitama, Japan
                Article
                91751
                10.1038/s41598-021-91751-w
                8192518
                34112908
                612a20d1-9899-4c91-860a-7d709f4b6fd0
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 March 2021
                : 31 May 2021
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                nephrology,renal replacement therapy,haemodialysis
                Uncategorized
                nephrology, renal replacement therapy, haemodialysis

                Comments

                Comment on this article