Literature DB >> 28201764

Seasonal variations in transition, mortality and kidney transplantation among patients with end-stage renal disease in the USA.

Yoshitsugu Obi1, Kamyar Kalantar-Zadeh1,2,3, Elani Streja1, Connie M Rhee1, Uttam G Reddy1, Melissa Soohoo1, Yaping Wang1, Vanessa Ravel1, Amy S You1, Jennie Jing1, John J Sim4, Danh V Nguyen5, Daniel L Gillen6, Rajiv Saran7,8, Bruce Robinson9, Csaba P Kovesdy10,11.   

Abstract

BACKGROUND: Seasonal variations may exist in transitioning to dialysis, kidney transplantation and related outcomes among end-stage renal disease (ESRD) patients. Elucidating these variations may have major clinical and healthcare policy implications for better resource allocation across seasons.
METHODS: Using the United States Renal Data System database from 1 January 2000 to 31 December 2013, we calculated monthly counts of transitioning to dialysis or first transplantation and deaths. Crude monthly transition fraction was defined as the number of new ESRD patients divided by all ESRD patients on the first day of each month. Similar fractions were calculated for all-cause and cause-specific mortality and transplantation.
RESULTS: The increasing trend of the annual transition to ESRD plateaued during 2009-2012 (n = 126 264), and dropped drastically in 2013 (n = 117 372). Independent of secular trends, monthly transition to ESRD was lowest in July (1.65%) and highest in January (1.97%) of each year. All-cause, cardiovascular and infectious mortalities were lowest in July or August (1.32, 0.58 and 0.15%, respectively) and highest in January (1.56, 0.71 and 0.19%, respectively). Kidney transplantation was highest in June (0.33%), and this peak was mainly attributed to living kidney transplantation in summer months. Transplant failure showed a similar seasonal variation to naïve transition, peaking in January (0.65%) and nadiring in September (0.56%).
CONCLUSIONS: Transitioning to ESRD and adverse events among ESRD people were more frequent in winter and less frequent in summer, whereas kidney transplantation showed the reverse trend. The potential causes and implications of these consistent seasonal variations warrant more investigation.
© The Author 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

Entities:  

Keywords:  ESRD; hemodialysis; kidney transplantation; mortality; peritoneal dialysis

Mesh:

Year:  2017        PMID: 28201764      PMCID: PMC6557195          DOI: 10.1093/ndt/gfw379

Source DB:  PubMed          Journal:  Nephrol Dial Transplant        ISSN: 0931-0509            Impact factor:   5.992


  31 in total

1.  Seasonal variations of blood pressure and overhydration in patients on chronic hemodialysis.

Authors:  M Spósito; F J Nieto; J E Ventura
Journal:  Am J Kidney Dis       Date:  2000-05       Impact factor: 8.860

2.  Seasonal variations in clinical and laboratory variables among chronic hemodialysis patients.

Authors:  Alfred K Cheung; Guofen Yan; Tom Greene; John T Daugirdas; Johanna T Dwyer; Nathan W Levin; Daniel B Ornt; Gerald Schulman; Garabed Eknoyan
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Review 3.  Seasonal variations in coronary heart disease.

Authors:  J P Pell; S M Cobbe
Journal:  QJM       Date:  1999-12

4.  Increased winter mortality from acute myocardial infarction and stroke: the effect of age.

Authors:  T Sheth; C Nair; J Muller; S Yusuf
Journal:  J Am Coll Cardiol       Date:  1999-06       Impact factor: 24.094

5.  Heart failure in a cold climate. Seasonal variation in heart failure-related morbidity and mortality.

Authors:  Simon Stewart; Kate McIntyre; Simon Capewell; John J V McMurray
Journal:  J Am Coll Cardiol       Date:  2002-03-06       Impact factor: 24.094

6.  Seasonal variation in chronic heart failure hospitalizations and mortality in France.

Authors:  F Boulay; F Berthier; O Sisteron; Y Gendreike; P Gibelin
Journal:  Circulation       Date:  1999-07-20       Impact factor: 29.690

7.  When throughout the year is coronary death most likely to occur? A 12-year population-based analysis of more than 220 000 cases.

Authors:  R A Kloner; W K Poole; R L Perritt
Journal:  Circulation       Date:  1999-10-12       Impact factor: 29.690

8.  Seasonal modifications in blood pressure are mainly related to interdialytic body weight gain in dialysis patients.

Authors:  Angel Argilés; Ronan Lorho; Marie-Françoise Servel; Guillaume Chong; Peter G Kerr; Georges Mourad
Journal:  Kidney Int       Date:  2004-05       Impact factor: 10.612

9.  Seasonal variation in host susceptibility and cycles of certain infectious diseases.

Authors:  S F Dowell
Journal:  Emerg Infect Dis       Date:  2001 May-Jun       Impact factor: 6.883

Review 10.  Seasonality of infectious diseases and severe acute respiratory syndrome-what we don't know can hurt us.

Authors:  Scott F Dowell; Mei Shang Ho
Journal:  Lancet Infect Dis       Date:  2004-11       Impact factor: 25.071

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Authors:  David T Gilbertson; Kenneth J Rothman; Glenn M Chertow; Brian D Bradbury; M Alan Brookhart; Jiannong Liu; Wolfgang C Winkelmayer; Til Stürmer; Keri L Monda; Charles A Herzog; Akhtar Ashfaq; Allan J Collins; James B Wetmore
Journal:  J Am Soc Nephrol       Date:  2019-01-24       Impact factor: 10.121

2.  Seasonal pattern in elderly hospitalized with acute kidney injury: a retrospective nationwide study in Italy.

Authors:  Alfredo De Giorgi; Alda Storari; Pedro Manuel Rodríguez-Muñoz; Rosaria Cappadona; Nicola Lamberti; Fabio Manfredini; Pablo Jesús López-Soto; Roberto Manfredini; Fabio Fabbian
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3.  Seasonal Changes in the Prevalence of Hyperkalemia in the Emergency Department: A Single Center Study.

Authors:  Teppei Koyama; Ryuichiro Makinouchi; Shinji Machida; Katsuomi Matsui; Yugo Shibagaki; Naohiko Imai
Journal:  Medicina (Kaunas)       Date:  2022-02-14       Impact factor: 2.430

4.  Medicaid Expansion and Incidence of Kidney Failure among Nonelderly Adults.

Authors:  Rebecca Thorsness; Shailender Swaminathan; Yoojin Lee; Benjamin D Sommers; Rajnish Mehrotra; Kevin H Nguyen; Daeho Kim; Maricruz Rivera-Hernandez; Amal N Trivedi
Journal:  J Am Soc Nephrol       Date:  2021-04-01       Impact factor: 14.978

  4 in total

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