1. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 When Using DOPPS Slides We welcome the use of DOPPS slides as we value the distribution of our research for the benefit of patient care and renal research Because the DOPPS data and analyses on the following slides are published in the public domain, we ask that you honor our attached guidelines when using DOPPS slides for your own research purposes

2. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 DOPPS Slide Use Guidelines Modifying DOPPS data, analyses, tables, and graphics in any form is not permitted without prior approval from the DOPPS coordinating center staff at Arbor Research Each DOPPS slide used must include the citation of the associated publication and feature the corresponding DOPPS logo Contact Arbor Research for permission to reproduce slides for publication and obtain a high-quality version suitable for print DOPPS@ArborResearch.org DOPPS@ArborResearch.org

3. Dialysis Outcomes and Practice Patterns Study Modifiable Practices Associated with Sudden Death among Hemodialysis Patients in the Dialysis Outcomes and Practice Patterns Study Michel Jadoul; Jyothi Thumma; Douglas S. Fuller; Francesca Tentori; Yun Li; Hal Morgenstern; David Mendelssohn; Tadashi Tomo; Jean Ethier; Friedrich Port; Bruce M. Robinson Clin J Am Soc Nephrol 2012; (7)5: 765-774

4. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Background Sudden death accounts for 20%–25% of all deaths in hemodialysis (HD) patients Although sudden death is also common among patients on peritoneal dialysis, there are reasons to speculate that practices related to the HD treatment itself may play a specific role: –Well-established risk of arrhythmias associated with electrolyte imbalances, especially potassium shifts –Increased risk of sudden death in the 12-hour period that begins with the start of the HD session or at the end of the long HD-free interval –Several patient characteristics—such as heart failure, left ventricular hypertrophy, and coronary artery disease—have been associated with a high risk of sudden death in hemodialysis patient

5. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Hypothesis We hypothesized that the rapid changes in extracellular fluid and electrolyte concentrations that occur during shorter dialysis sessions, using low dialysate potassium (KD) and at a higher ultrafiltration rate, may trigger arrhythmias and other cardiac events that may lead to higher incidence of sudden death.

6. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 DOPPS Background (1) International, prospective cohort study of hemodialysis patients and HD unit practices Uniform international data collection Goal: Identify HD practice patterns associated with improved patient outcomes (adjusted for patient mix) Major outcomes: mortality, hospitalization, vascular access, quality of life DOPPS is supported by scientific research grants from Amgen (since 1996), Kyowa Hakko Kirin (since 1999, in Japan), Sanofi/Genzyme (since 2009), and Abbott Laboratories (since 2009) without restrictions on publications Coordinated by Arbor Research Collaborative for Health (Ann Arbor, MI USA)

7. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 DOPPS Background (2) YearsCountriesFacilitiesPatients DOPPS 1 1996-2001730817,034 DOPPS 2 2002-20041232212,839 DOPPS 3 2005-20081230011,170 DOPPS 1: France, Germany, Italy, Japan, Spain, UK, US DOPPS 2, 3: DOPPS 1 Countries + Australia/New Zealand, Belgium, Canada, Sweden

8. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Data Sources and Variables (1) 37,765 participants on 3x-weekly HD from 930 dialysis facilities during the first three phases of DOPPS. Baseline patient characteristics including demographics, detailed comorbidities, laboratory values, and dialysis treatment characteristics are obtained at the time of study entry by medical record abstraction. Clinical variables and medical events, including mortality and cause of death, are updated every four months.

9. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Data Sources and Variables (2) Primary exposures –Short duration of dialysis sessions (prescribed treatment time <210 minutes) –Low dialysis dose (single pool Kt/V <1.2) –Large ultrafiltration (UF) volume (>5.7% of the post-dialysis weight) –Dialysate potassium <3 mEq/L –Prescription of beta blockers and QTI prolonging drugs Outcomes –All-cause mortality –Sudden death, defined as primary cause of death reported as death due to cardiac arrhythmia, cardiac arrest, and/or hyperkalemia –Other cardiovascular death, if due to cardiovascular disease –Non-cardiovascular deaths, not classified as “sudden death” or other cardiovascular death

10. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Statistical Methods (1) Cox regression models were used to assess the associations of the four dialysis practices and QT- prolonging medications with all-cause mortality, sudden death, other CV death, and non-CV death. –Time at risk was defined as the period from study enrollment until the earliest of death, transplant, change of treatment modality, withdrawal from dialysis, transfer to another facility, or study end. –Models were adjusted for age, sex, black race, body mass index, years with ESRD, 14 comorbidity classes, catheter use, serum albumin, phosphorus, calcium, PTH, hemoglobin, serum creatinine, ferritin, white blood cell count, single pool Kt/V, and indicators of facility achievement of clinical guidelines. –Models were stratified by DOPPS phase and country; robust variance (sandwich) estimates were used to account for facility-level clustering.

11. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Statistical Methods (2) To partially reduce the impact of unmeasured patient-level confounders, we also applied a two-stage instrumental variable approach, using the dialysis facilities as the instruments. –In the first stage, patient-level predicted treatment was determined using a linear regression model. –In the second stage, Cox regression was used to estimate the hazard of mortality associated with the patient-level predicted treatment. We also used limited information maximum likelihood regression (LIML) –We used one-year mortality as the second stage outcome and modeled it as a dichotomous variable using linear regression as an approximation to logistic regression. IVEware was used to perform multiple imputations of missing data, including cause of death. –Estimates and their variances from the multiple imputation results were combined according to the Rubin method.

12. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Patient Characteristics by Treatment Practice (1) Mean (SD) or % Tx time < 210 minKt/V < 1.2 NoYesNoYes N patients28,8788,53618,8247,273 Age61.0 (14.6)64.6 (15.3) a 62.0 (14.8)61.2 (14.5) c Male6049 a 5372 a Black1315 a 1413 a Vintage4.2 (5.5)2.0 (3.8) a 4.9 (5.7)2.6 (4.3) a Body mass index24.9 (5.8)24.1 (5.2) a 24.2 (5.6)25.4 (5.9) a Catheter2335 a 1828 a Comorbid Conditions: CAD4546 42 Other cardiovascular3532 b 3631 a Cerebrovascular disease1618 a 1716 CHF35373533 Diabetes38403544 a Labs: Hgb (g/dl)10.9 (1.7)10.5 (1.7) a 11.1 (1.6)10.5 (1.8) a Albumin (g/dl)3.7 (0.5)3.6 (0.6) a 3.7 (0.5)3.7 (0.6) a Potassium (mEq/l)5.0 (0.8)4.8 (0.8) a 5.0 (0.8)4.9 (0.8) a Phosphorous (mg/dl)5.6 (1.8)5.6 (1.9) a 5.5 (1.7)5.7 (1.9) a PTH (pg/ml) † 177 (275)187 (282)172 (272)184 (269) b Creatinine (mg/dl)9.2 (3.2)8.0 (3.1) a 9.2 (3.0)9.2 (3.5) a Ferritin (ng/ml) † 285 (431)247 (403) b 314 (456)203 (332) a † Serum PTH and ferritin values summarized as median (interquartile range). a p<0.001, b 0.001≤p<0.05, and c 0.05≤p<0.10 for 'yes' vs. 'no' column.

13. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Patient Characteristics by Treatment Practice (2) Mean (SD) or % UF volume > 5.7%Dialysate K < 3 mEq/l NoYesNoYes N patients26,8803,9706,60629,629 Age62.5 (14.6)57.2 (14.9) a 64.4 (14.5)61.3 (14.8) a Male5855 a 5459 a Black1313 a 1314 a Vintage3.7 (5.2)6.3 (6.2) a 1.8 (3.5)4.1 (5.5) a Body mass index25.0 (5.7)21.5 (4.0) a 25.8 (5.9)24.5 (5.6) b Catheter2311 a 4122 a Comorbid Conditions: CAD46405443 a Other cardiovascular3435 a 3933 a Cerebrovascular disease1714 a 2016 a CHF3433 a 4234 a Diabetes3835 b 4637 a Labs: Hgb (g/dl)10.9 (1.7)10.6 (1.6)10.8 (1.7)10.8 (1.7) a Albumin (g/dl)3.7 (0.5)3.8 (0.5) a 3.5 (0.6)3.7 (0.5) a Potassium (mEq/l)4.9 (0.8)5.2 (0.8) a 4.7 (0.8)5.0 (0.8) a Phosphorous (mg/dl)5.5 (1.8)5.9 (1.9) a 5.4 (1.9)5.6 (1.8) a PTH (pg/ml) † 178 (271)175 (297) a 190 (269)178 (280) Creatinine (mg/dl)8.9 (3.1)10.1 (3.2) a 7.3 (3.0)9.2 (3.2) a Ferritin (ng/ml) † 286 (429)222 (439) c 278 (410)273 (426) a † Serum PTH and ferritin values summarized as median (interquartile range). a p<0.001, b 0.001≤p<0.05, and c 0.05≤p<0.10 for 'yes' vs. 'no' column.

14. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Association of Dialysis Treatment Practices with Mortality Patient levelIV approach HR95% CIpHR95% CIp Treatment time <210 min (vs. ≥210 min): All-cause mortality1.06(1.00, 1.13)0.041.09(0.94, 1.27)0.26 Sudden death1.13(1.00, 1.27)0.041.38(1.04, 1.83)0.03 Other cardiovascular death1.00(0.89, 1.12)0.960.77(0.58, 1.03)0.08 Non-cardiovascular death1.06(0.97, 1.17)0.201.16(0.93, 1.44)0.18 Kt/V <1.2 (vs. ≥1.2): All-cause mortality1.06(1.00, 1.12)0.071.39(1.07, 1.81)0.01 Sudden death1.10(0.97, 1.24)0.151.71(1.02, 2.87)0.04 Other cardiovascular death0.96(0.85, 1.08)0.480.95(0.60, 1.50)0.83 Non-cardiovascular death1.10(1.00, 1.21)0.041.59(1.11, 2.29)0.01 UF volume >5.7% of post-weight (vs. ≤5.7%): All-cause mortality1.09(1.01, 1.19)0.031.32(0.84, 2.08)0.23 Sudden death1.15(1.00, 1.32)0.041.56(0.60, 4.03)0.35 Other cardiovascular death1.17(1.01, 1.36)0.042.36(1.02, 5.46)0.05 Non-cardiovascular death1.00(0.88, 1.14)0.980.78(0.43, 1.43)0.42

15. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Association of Dialysate K * with Mortality (1) Patient-level Dialysate K ≤1.5 (vs. ≥3)Dialysate K 2-2.5 (vs. ≥3) HR95% CIpHR95% CIp All patients (N=37,741) All-cause mortality1.13(1.03, 1.25)0.011.08(1.01, 1.16)0.03 Sudden death1.39(1.12, 1.74)0.0041.17(1.01, 1.37)0.04 Other cardiovascular death1.14(0.95, 1.36)0.161.04(0.91, 1.19)0.54 Non-cardiovascular death0.99(0.84, 1.17)0.931.05(0.94, 1.16)0.38 Among patients with serum K ≥5 (N=17,327) All-cause mortality1.09(0.95, 1.26)0.231.08(0.97, 1.20)0.17 Sudden death1.21(0.91, 1.61)0.181.11(0.90, 1.38)0.33 Other cardiovascular death1.16(0.88, 1.52)0.291.00(0.82, 1.21)0.97 Non-cardiovascular death0.97(0.77, 1.22)0.811.10(0.93, 1.31)0.27 Among patients with serum K <5 (N=20,414) All-cause mortality1.15(1.00, 1.33)0.041.06(0.98, 1.15)0.15 Sudden death1.53(1.10, 2.13)0.011.18(0.98, 1.42)0.08 Other cardiovascular death1.05(0.85, 1.31)0.641.05(0.88, 1.24)0.58 Non-cardiovascular death1.03(0.77, 1.38)0.831.00(0.88, 1.15)0.95 * N KD ≤ 1.5 =5,493; N KD = 2-2.5 =25,552; N KD ≥ 3 =6,696

16. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Association of Dialysate K * with Mortality (2) IV approach Dialysate K ≤1.5 (vs. ≥3)Dialysate K 2-2.5 (vs. ≥3) HR95% CIpHR95% CIp All patients (N=37,741) All-cause mortality1.09(0.88, 1.35)0.431.23(1.04, 1.45)0.01 Sudden death1.67(0.99, 2.81)0.051.61(1.12, 2.30)0.01 Other cardiovascular death1.11(0.75, 1.64)0.621.23(0.90, 1.68)0.19 Non-cardiovascular death0.84(0.61, 1.16)0.291.03(0.83, 1.29)0.76 Among patients with serum K ≥5 (N=17,327) All-cause mortality1.13(0.87, 1.47)0.371.23(0.99, 1.52)0.06 Sudden death1.27(0.73, 2.22)0.401.30(0.81, 2.08)0.28 Other cardiovascular death1.18(0.74, 1.88)0.491.17(0.79, 1.72)0.44 Non-cardiovascular death1.02(0.70, 1.47)0.931.21(0.87, 1.69)0.25 Among patients with serum K <5 (N=20,414) All-cause mortality1.04(0.80, 1.36)0.761.23(1.03, 1.46)0.02 Sudden death2.01(0.96, 4.24)0.061.86(1.31, 2.63)<0.001 Other cardiovascular death0.94(0.56, 1.56)0.801.23(0.86, 1.76)0.26 Non-cardiovascular death0.77(0.51, 1.15)0.200.95(0.75, 1.22)0.71 * N KD ≤ 1.5 =5,493; N KD = 2-2.5 =25,552; N KD ≥ 3 =6,696

17. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Observed Cause of Death by Country – As Reported

18. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Cause of Death, by Country – Excluding Missing/Unknown Causes of Death

19. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Causes of Death, by Country – Including Imputed Causes

20. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Facility % of Patients with Short Treatment Time (<210 Minutes) 5th 25th 95th 75th Facility Percentile 50th

21. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Facility % of Patients with Low Kt/V (<1.2) 5th 25th 95th 75th Facility Percentile 50th

22. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Facility % of Patients with Large UF Volume (>5.7% of post-weight) 5th 25th 95th 75th Facility Percentile 50th

23. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Facility % of Patients with Low Dialysate K (<3 mEq/L) 5th 25th 95th 75th Facility Percentile 50th

24. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Association of Treatment Practices with Sudden Death Treatment time (per 30 min lower) Sp Kt/V (per 0.1 unit lower) UF volume (per 1% higher) Dialysate K (per 1 mEq/l lower) All-cause mortality Sudden death Hazard Ratio (95% CI) IV approach*Patient model *used predicted treatment from 1 st stage

25. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Medications Higher risk of sudden death was evident for amiodarone prescription (HR=1.44, [1.16-1.81], p=0.001), but not for prescription of other QTI prolonging drugs (HR=1.10, [0.94-1.28], p=0.22). –The association of a higher risk of SD with amiodarone likely reflects a prescription by indication bias. Beta-blockers were associated with a lower risk of sudden death (HR=0.88, [0.78-0.99], p=0.03).

26. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Sensitivity Analyses Our findings were confirmed in a series of sensitivity analyses. –In models restricted to prevalent patients (time on dialysis > 6 months) and to “healthier” patients (non-diabetic participants aged < 65). –When observed causes of death were used in place of imputed causes of death. –When all four practices were included in the same Cox model, indicating that the association of each practice with sudden death was independent of the other three. –When deaths attributed to hyperkalemia were excluded.

27. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Strengths The strengths of the present study are multiple: –Large sample size –Nationally representative patient samples –Prospective data collection –Extensive adjustment for patient characteristics, comorbidities, and lab results –The detailed medication database available in the DOPPS made it possible for the first time to study the impact of drugs that prolong the QTI on the risk of SD –Sensitivity analyses show consistent associations between the modifiable practices and SD –Facility-level IV analyses tend to lessen the risk of patient-level confounding by indication

28. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Limitations Several limitations have to be acknowledged: –As an observational study, we are not able to claim causality. –The number of patients who had received an implantable cardiac defibrillator was too small for studying the impact of their use on the risk of SD. –As in any large clinical database, some errors may be present in coding but these should have favored the null hypothesis. –We did not have information on the time interval between the end of the last HD session and SD. –Finally, we did not have ECG data, regarding the presence of left ventricular hypertrophy, or prolonged QTI, nor potentially relevant biomarker data.

29. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Conclusions (1) Our DOPPS results demonstrate for the first time substantial differences between countries in the proportion of deaths that are reported as sudden. –33.4% in the US, 17.5% in Canada, 17.8% in Europe, 19.2% in ANZ, and 23.2% in Japan The present paper is the first, to our knowledge, to assess in HD patients the association between SD and the prescription of drugs prolonging the QTI on the ECG. –Beta-blockers were associated with a lower risk of SD, in line with their capacity to counteract the increased sympathetic activity common in HD patients

30. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Conclusions (2) We have identified several readily modifiable facility practices associated with an independent risk of SD, both in standard patient-level analyses and in IV analyses based on facility variation in practice: –Specifically, short treatment time, low dialysis dose, high UF volume, and low dialysate K are associated with sudden death, as well as overall mortality. –Since low (<3) dialysate K is commonly used and it is the easiest practice to modify, our study suggests that more careful adaptation of dialysate K level may help minimize the impact of sudden death observed in HD patients. –Clinical trials are needed to test this possibility, and may be feasible for practices such as dialysate potassium where substantial variation in care exists and clinical uncertainty remains significant.

31. Jadoul, et al. Clin J Am Soc Nephrol 2012; 7(5): 765-774 Acknowledgements Our thanks to DOPPS study coordinators, medical directors, and participating patients for their dedicated work. The DOPPS would not be possible without the generous financial support of the following companies who have demonstrated their strong commitment to independent scientific research to improve patient care: –Amgen (since 1996) –Kyowa Hakko Kirin (since 1999, in Japan) –Abbott Laboratories (since 2009) –Sanofi/Genzyme (since 2009) –Baxter Healthcare (since 2011) –Vifor Fresenius Medical Care Renal Pharma Ltd (since 2011) Support from DOPPS sponsors is provided without restrictions on publications.