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Seasonal Variations in Transition, Mortality, and Kidney - - PowerPoint PPT Presentation

Seasonal Variations in Transition, Mortality, and Kidney Transplantation among Patients with End-Stage Renal Disease in the United States Yoshitsugu Obi, Kamyar Kalantar-Zadeh, Elani Streja, Connie M. Rhee, Uttam G. Reddy, Melissa Soohoo,


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SLIDE 1

Seasonal Variations in Transition, Mortality, and Kidney Transplantation among Patients with End-Stage Renal Disease in the United States

Yoshitsugu Obi, Kamyar Kalantar-Zadeh, Elani Streja, Connie M. Rhee, Uttam G. Reddy, Melissa Soohoo, Yaping Wang, Vanessa Ravel, Amy S. You, Jennie Jing, John J. Sim, Danh V. Nguyen, Daniel L. Gillen, Rajiv Saran, Bruce Robinson, and Csaba P. Kovesdy Nephrol Dial Transpl. 2017 in press

https://www.ncbi.nlm.nih.gov/pubmed/28201764

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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 health care policy implications for better resource

allocation across seasons.

Methods: Using the United States Renal Data System (USRDS)

database from 1/1/2000 to 12/31/2013, we calculated monthly counts

  • f 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.

Obi Y, Kalantar-Zadeh K, Streja E, …, and Kovesdy CP.

Seasonal Variations in Transition, Mortality, and Kidney Transplantation among Patients with End-Stage Renal Disease in the United States.

Nephrol Dial Transplant. 2017 in press.

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SLIDE 3

Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.

Characteristics on January 1st and the annual events of each year among patients with ESRD in the U.S. (2000 – 2013)

KTx, kidney transplantation

Year Patient characteristics on January 1st of each year Event frequencies in each year Total ESRD Total Dialysis Age (year) ≥65 yrs (%) Female (%) Blacks (%) Diabetes (%) Transition Death KTx 2000 373,091 278,897 56.0±16.6 34% 45% 32% 34% 103,958 (28%) 71,122 (19%) 14,625 (4%) 2001 394,136 294,395 56.3±16.5 35% 45% 32% 35% 107,750 (27%) 75,215 (19%) 15,261 (4%) 2002 414,259 308,674 56.5±16.4 35% 45% 32% 36% 110,092 (27%) 77,736 (19%) 15,767 (4%) 2003 433,912 322,108 56.8±16.4 35% 45% 32% 36% 112,073 (26%) 80,630 (19%) 16,090 (4%) 2004 452,357 334,822 57.0±16.3 35% 45% 31% 36% 113,699 (25%) 82,090 (18%) 16,920 (4%) 2005 470,963 346,660 57.3±16.3 35% 44% 31% 36% 116,609 (25%) 83,461 (18%) 17,427 (4%) 2006 490,153 358,858 57.5±16.2 35% 44% 31% 37% 120,300 (25%) 85,123 (17%) 18,031 (4%) 2007 511,143 372,719 57.7±16.1 36% 44% 31% 37% 120,496 (24%) 85,079 (17%) 17,504 (3%) 2008 531,685 386,419 57.9±16.0 36% 44% 31% 37% 121,913 (23%) 85,601 (16%) 17,383 (3%) 2009 553,086 401,124 58.1±15.9 36% 44% 31% 37% 125,571 (23%) 87,108 (16%) 17,671 (3%) 2010 576,003 417,651 58.4±15.8 37% 43% 31% 37% 126,118 (22%) 87,675 (15%) 17,728 (3%) 2011 598,722 434,052 58.6±15.8 37% 43% 31% 37% 123,798 (21%) 88,536 (15%) 17,584 (3%) 2012 618,857 447,908 58.8±15.7 38% 43% 31% 37% 126,264 (20%) 86,722 (14%) 17,250 (3%) 2013 642,020 465,404 59.1±15.6 38% 43% 31% 37% 117,372 (18%) 86,781 (14%) 17,605 (3%)

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Transition to ESRD All-cause death

500 1,000 1,500 2,000 2,500 3,000 2,000 4,000 6,000 8,000 10,000 12,000 Jan-00 Sep-00 May-01 Jan-02 Sep-02 May-03 Jan-04 Sep-04 May-05 Jan-06 Sep-06 May-07 Jan-08 Sep-08 May-09 Jan-10 Sep-10 May-11 Jan-12 Sep-12 May-13 Transition to ESRD (Left axis) All-cause death (Left axis) KTx (Right axis) 0.00 0.15 0.30 0.45 0.60 0.75 0.00 0.50 1.00 1.50 2.00 2.50 Jan-00 Aug-00 Mar-01 Oct-01 May-02 Dec-02 Jul-03 Feb-04 Sep-04 Apr-05 Nov-05 Jun-06 Jan-07 Aug-07 Mar-08 Oct-08 May-09 Dec-09 Jul-10 Feb-11 Sep-11 Apr-12 Nov-12 Jun-13 Transition to ESRD (Left axis) All-cause death (Left axis) KTx (Right axis)

KTx

Consistent seasonal variation in transition to ESRD, all-cause death, and KTx irrespective of secular trends. (Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP. NDT 2017 in press.)

KTx Transition to ESRD All-cause death

Monthly fractions = #Events in the month / #ESRD Pts on the 1st day of the month

Normalized monthly counts Normalized monthly fractions

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SLIDE 5

1.2 1.4 1.6 1.8 2 2.2 2.4 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 1.2 1.4 1.6 1.8 2 2.2 2.4 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

For each year 14-year average

Monthly transition to ESRD was lowest in July and highest in January.

Monthly fractions = #Events in the month / #ESRD Pts on the 1st day of the month

Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 6

5000 6000 7000 8000 9000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Number of new ESRD (HD)

400 600 800 1000 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Number of new ESRD (PD)

The seasonal variation in transition to ESRD was mainly attributed to HD, not PD.

Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 7

For each year 14-year average

All-cause mortalities was lowest in August and highest in January.

Monthly fractions = #Events in the month / #ESRD Pts on the 1st day of the month

0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0.9 1 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 8

The seasonal variation in all-cause death was consistent between HD vs. PD.

Number of all-cause death (HD) Number of all-cause death (PD)

4000 4500 5000 5500 6000 6500 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 250 300 350 400 450 500 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 9

The seasonal variation in mortality was consistent between CV vs. infectious death.

Infectious mortality fraction (Total) Cardiovascular mortality fraction (Total)

0.05 0.15 0.25 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0.4 0.6 0.8 1.0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 10

For each year 14-year average

Kidney transplantation was highest in June and lowest in December.

Monthly fractions = #Events in the month / #KTx recipients on the 1st day of the month

0.2 0.24 0.28 0.32 0.36 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 0.2 0.24 0.28 0.32 0.36 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 11

Number of living KTx Number of cadaveric KTx

The seasonal variation in KTx was mainly attributed to living donors, not cadaveric donors.

400 450 500 550 600 650 700 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 400 600 800 1000 1200 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 12

KTx failure fraction

0.4 0.5 0.6 0.7 0.8 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Kidney transplant failure was highest in January and lowest in September.

Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.
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SLIDE 13

Conclusions

  • The 14-year cumulative data from the USRDS

(2000-2013) showed consistent seasonal

variations in the transition to ESRD, and all-cause, cardiovascular, and infectious deaths, as well as kidney transplantation and transplant failure.

  • We found strikingly robust pattern of seasonal

variation in that adverse events and transitioning to ESRD were more frequent in

winter and less frequent in summer.

  • Understanding these variations may allow for

more efficient and cost-effective allocation of health care resources across seasons of the

years, and have subsequent impact upon clinical practice and health care policy.

Obi Y, Kalantar-Zadeh K, Streja E, …, Kovesdy CP.

  • NDT. 2017 in press.