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      Therapeutics and Clinical Risk Management (submit here)

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      Benefits of Incremental Hemodialysis Seen in a Historical Cohort Study


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          Previous research on incremental hemodialysis transition has mainly focused on one or two benefits or prognoses. We aimed to conduct a comprehensive analysis by investigating whether incremental hemodialysis was simultaneously associated with adequate dialysis therapy, stable complication indicators, long-lasting arteriovenous vascular access, and long-lasting preservation of residual kidney function (RKF) without increasing mortality or hospitalization.

          Patients and Methods

          Incident hemodialysis patients from Huashan Hospital in Shanghai, China, over the period of 2012 to 2019, were enrolled and followed every three months until death or the time of censoring. Changes in complication indicators from baseline to all post-baseline visits were analyzed by mixed-effects models. The outcomes of RKF loss, arteriovenous vascular access complications, and the composite of all-cause mortality and cardiovascular events were compared between incremental and conventional hemodialysis by Cox proportional hazards model.


          Of the 113 patients enrolled in the study, 45 underwent incremental and 68 conventional hemodialysis. There were no significant differences in the changes from baseline to post-baseline visits in complication indicators between the two groups. Incremental hemodialysis reduced the risks of RKF loss (HR, 0.33; 95% CI, 0.14–0.82), de novo arteriovenous access complication (HR, 0.26; 95% CI, 0.08–0.82), and recurrent arteriovenous access complications under the Andersen–Gill (AG) model (HR, 0.27; 95% CI, 0.10–0.74) and the Prentice, Williams and Peterson Total Time (PWP-TT) model (HR, 0.31; 95% CI, 0.12–0.80). There were no significant differences in all-cause hospitalization or the composite outcome between groups.


          Incremental hemodialysis is an effective dialysis transition strategy that preserves RKF and arteriovenous access without affecting dialysis adequacy, patient stability, hospitalization risk and mortality risk. Randomized controlled trials are warranted.

          Most cited references35

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          Modelling recurrent events: a tutorial for analysis in epidemiology.

          In many biomedical studies, the event of interest can occur more than once in a participant. These events are termed recurrent events. However, the majority of analyses focus only on time to the first event, ignoring the subsequent events. Several statistical models have been proposed for analysing multiple events. In this paper we explore and illustrate several modelling techniques for analysis of recurrent time-to-event data, including conditional models for multivariate survival data (AG, PWP-TT and PWP-GT), marginal means/rates models, frailty and multi-state models. We also provide a tutorial for analysing such type of data, with three widely used statistical software programmes. Different approaches and software are illustrated using data from a bladder cancer project and from a study on lower respiratory tract infection in children in Brazil. Finally, we make recommendations for modelling strategy selection for analysis of recurrent event data.
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            Chronic inflammation in end-stage renal disease and dialysis

            Abstract Under normal conditions, inflammation is a protective and physiological response to various harmful stimuli. However, in several chronic debilitating disorders, such as chronic kidney disease, inflammation becomes maladaptive, uncontrolled and persistent. Systemic persistent inflammation has, for almost 20 years, been recognized as a major contributor to the uraemic phenotype (such as cardiovascular disease, protein energy wasting, depression, osteoporosis and frailty), and a predictor of cardiovascular and total mortality. Since inflammation is mechanistically related to several ageing processes (inflammageing), it may be a major driver of a progeric phenotype in the uraemic milieu. Inflammation is likely the consequence of a multifactorial aetiology and interacts with a number of factors that emerge when uraemic toxins accumulate. Beside interventions aiming to decrease the production of inflammatory molecules in the uraemic milieu, novel strategies to increase the removal of large middle molecules, such as expanded haemodialysis, may be an opportunity to decrease the inflammatory allostatic load associated with retention of middle molecular weight uraemic toxins.
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              Second generation logarithmic estimates of single-pool variable volume Kt/V: an analysis of error.

              The original formula proposed to estimate variable-volume single-pool (VVSP) Kt/V was Kt/V = -In(R - 0.008 * t - f * UF/W), where in the Kt/V range of 0.7 to 1.3, f = 1.0 (* denotes multiplication). This formula tends to overestimate Kt/V as the Kt/V increases above 1.3. Because higher Kt/V values are now commonly delivered, the validity of both the urea generation term (0.008 * f) and correction for UF/W were explored by solving VVSP equations for simulated hemodialysis situations, with Kt/V ranging from 0.6 to 2.6. The analysis led to the development of a second-generation formula, namely: Kt/V = -In(R - 0.008 * t) + (4-3.5 * R) * UF/W. The first and second generation formulas were then used to estimate the modeled VVSP Kt/V in 500 modeling sessions in which the Kt/V ranged widely from 0.7 to 2.1. An analysis of error showed that this second-generation formula eliminated the overestimation of Kt/V in the high ranges found with the first-generation formula. Also, total error (absolute value percent error + 2 SD) was reduced with the second-generation formula. These results led to the proposal of a new formula that can be used for a very wide range of delivered Kt/V.

                Author and article information

                Ther Clin Risk Manag
                Ther Clin Risk Manag
                Therapeutics and Clinical Risk Management
                13 November 2021
                : 17
                : 1177-1186
                [1 ]Division of Nephrology, Huashan Hospital, Fudan University , Shanghai, People’s Republic of China
                [2 ]National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University , Shanghai, People’s Republic of China
                [3 ]Harold Simmons Center for Kidney Disease Research and Epidemiology, Division of Nephrology and Hypertension, University of California Irvine Medical Center , Orange, CA, USA
                [4 ]Fielding School of Public Health at UCLA , Los Angeles, CA, USA
                [5 ]Los Angeles Biomedical Research Institute at Harbor-UCLA , Torrance, CA, USA
                Author notes
                Correspondence: Mengjing Wang; Jing Chen Division of Nephrology, Huashan Hospital, Fudan University , 12 Middle Wulumuqi Road, Shanghai, People’s Republic of China Tel +86 21 52889393; +86 21 52889387 Fax +86 21 52889325; +86 21 52888304 Email fiyona27@126.com; chenjing1998@fudan.edu.cn
                Author information
                © 2021 Chen et al.

                This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms ( https://www.dovepress.com/terms.php).

                : 06 August 2021
                : 25 October 2021
                Page count
                Figures: 1, Tables: 17, References: 35, Pages: 10
                Funded by: National Key Research and Development program;
                Funded by: Shanghai Shenkang Hospital Development Center;
                Funded by: Shanghai Program for Outstanding Medical Academic Leader;
                Funded by: National Natural Science Foundation of China, open-funder-registry 10.13039/501100001809;
                Funded by: Natural Science Foundation of Shanghai, open-funder-registry 10.13039/100007219;
                This research was supported, in part, by grants from National Key Research and Development program (2020YFC2005003, and 2018YFC2000204), Shanghai Shenkang Hospital Development Center (SHDC2020CR4014), Shanghai Program for Outstanding Medical Academic Leader (2019LJ03), National Natural Science Foundation of China (81570665, 81730017, and 81600577), Natural Science Foundation of Shanghai (16ZR1449400), and Shanghai Engineering Research Center of AI Assisted Clinical Service forAging-Associated Diseases (19DZ2251700).
                Original Research

                incremental hemodialysis,arteriovenous vascular access,residual kidney function,hospitalization,mortality


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