Marginal Dialysis: Patient characteristics influencing outcomes

Transcription

1 Marginal Dialysis: Patient characteristics influencing outcomes Dr Celine Foote Staff specialist, Concord Repatriation General Hospital Post-Doctoral Research Fellow, The George Institute for Global Health

2 Outline Description of marginal dialysis patients Characteristics which influence their outcomes Comorbid burden Cognitive function Frailty Malnutrition Use of risk prediction tools to put these characteristics together

3 We are dialysing large numbers of older patients but this has levelled off in last 5yrs In 2015, 19% of pts (n=513) starting dialysis in Australia were aged 75 New patients per million population New patients Age specific rates - Australia Age ANZDATA Annual Report, Figure 1.3 ANZDATA report 2016 New patients per million population New patients Age specific rates - New Zealand Age ANZDATA Annual Report, Figure 1.3

4 Older patients have substantial comorbid burden Foote et al. NDT 2012

5 High comorbid burden especially DM but falling prevalence of other conditions 60 Diabetes status at RRT entry Australia New Zealand % of patients Non-diabetic Type 1 diabetes Type 2 diabetes 2016 ANZDATA Annual Report, Figure Comorbid conditions at RRT entry Australia Suspected cases included 2016 ANZDATA Annual Report, Figure 1.8 % of patients Coronary Peripheral vascular Lung Cerebrovascular Comorbid conditions at RRT entry New Zealand Suspected cases included 2016 ANZDATA Annual Report, Figure 1.8 Coronary Peripheral vascular Lung Cerebrovascular ANZDATA report 2016

6 In my unit we have used dialysis to treat patients with these characteristics: Patients > 90years old Strongly agree Agree Neutral Disagree Strongly disagree Bed bound patients Foote et al, unpublished data 0 Strongly agree Agree Neutral Disagree Strongly disagree

7 In my unit we have used dialysis to treat patients with these characteristics: 40 Patients with <1 year life expectancy strongly agree agree neutral disagree strongly disagree Foote et al, unpublished data

8 In my unit we have used dialysis to treat patients with these characteristics: Nursing home residents Strongly agree Agree Neutral Disagree Strongly disagree Severely demented patients Foote et al, unpublished data Strongly agree Agree Neutral Disagree Strongly disagree

9 Survival of older dialysis patients is worse than most common cancers prostate cancer 92% breast cancer 89% renal cancer 72% bowel cancer 66% dialysis in Australia aged % Heart failure 52% ovarian cancer 43% dialysis in Australia aged % aged % lung cancer < 14% 5 year survival data from the Cancer Council of Australia ( and ANZDATA 2012 ( JAMA. 2004; 292(3):344.

10 How long older dialysis patients survive is affected by comorbid burden ANZDATA report 2015

11 Dialysis start also impacts on function, cognition and QOL of older patients Older patients have higher risk of functional 1 and cognitive loss 2 and often also have decline in QOL 3 following dialysis commencement 1. Jassal et al, NEJM Murray et al, Neurology Da Silva-Gane et al, CJASN 2012

12 Comorbid burden

13 Higher comorbid score* predicts poorer survival or more Followup (years) Comorbid score HR 95%CI P value < < <0.001 * Includes coronary heart disease, peripheral vascular disease, cerebrovascular disease, chronic lung disease and diabetes Foote et al. NDT 2012

14 There may be no survival advantage with dialysis with increasing comorbidity Murtagh et al. NDT 2007

15 There may be no survival advantage with dialysis with increasing comorbidity Brown et al. CJASN, 2015

16 Cognitive function

17 Mild cognitive impairment is a common but poorly recognized problem 16-38% cognitive impairment in all dialysis pts 1 68% in those aged over 75 2 Documented in only 3% 3 Uncertainty remains as to which cognitive instrument to use 1. KurellaTamura et al. KI Patel et al, HKJN Murray et al, Neurology 2006

18 Mild cognitive impairment leads to independent increased mortality risk Griva et al, AJKD 2010

19 Frailty

20 Frailty is common in CKD patients Prevalence of frailty in CKD population is twice that of general geriatric outpatient community 14% 15% versus 6% 7% 1,2 Prevalence increases markedly in dialysis population and with increasing age 44% in dialysis patients aged<40 and 78% in aged> Shlipak et al, AJKD Roshanravan et al, AJKD Johansen et al JASN 2007

21 Frailty leads to independent and graded increased mortality risk Independent 2.24x increased risk of death 1 Also 1.63x risk of death or hospitalization 1 Risk is graded with each 1-point increase in frailty associated with 1.22x increased risk of death 2 1. Johansen et al JASN Alfaadhel et al, CJASN 2015

22 Frailty has substantial impact on life expectancy Swidler CJASN 2013

23 Malnutrition

24 Malnutrition predicts increased mortality risk but may be poorly characterised Malnutrition prevalence varies between 18%-75% in dialysis patients 1 Older patients are at increased risk 2 Albumin is commonly used as a surrogate Predictor of mortality in general 3 and older dialysis patients 4 but some inconsistency in literature 5 Confounded by inflammation and comorbidity 6 1. Kalantar-Zadeh et al, AJKD Qureshi et al, KI Iseki et al, KI Oliva et al, J Nephrol Chan et al, J of Renal Nutrition Stenvinkel et al, NDT 2002

25 7 point SGA is a better predictor of malnutrition and predicts mortality in pts starting dialysis 7 point Subjective Global Assessment (SGA) is a better predictor of malnutrition Not confounded by inflammation or obesity 1 SGA score is independently associated with mortality in incident dialysis pts 2 Predictive capacity in older dialysis patients 3 1. Chan et al, J of Renal Nutrition De Mutsert et al, Am J Clin Nutr Santin et al, Clin Nutr in press

26 Risk prediction tools

27 Risk tool combining comorbidity, albumin and SQ is useful in predicting prognosis in the general HD population Cohen et al et al. CJASN 2010

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29 Several risk tools are available for older dialysis patients but have limitations Four prediction tools derived in older dialysis pts Derived from French renal registry 1,2, US Medicare 3 and Albertan databases 4 Risk factors assessed are dictated by availability Heart failure, arrhythmia and malignancy were consistent predictors Limited assessment of cognition, functional status Lack of clinical judgment assessment like SQ Only predict short term dialysis survival (3-6 month) 1. Couchoud et al. NDT Couchoud et al, NDT Thamer et al, AJKD Wick et al, AJKD in press

30 Summary Large numbers of older patients with considerable comorbid burden Patient characteristics which influence outcomes include: Comorbid burden Cognitive function Frailty Malnutrition Use of risk prediction tools can assist in prognostication for individual patients

31 Suggestions for next steps. Systematic collection in all older pts approaching ESKD of presence of: Cognitive function Frailty Malnutrition Irrespective of planned treatment pathway Improve prognostication for appropriate use of resources

32 Thank you for your attention

33 Do you systematically test cognitive function on older patients approaching treatment decisions for ESKD? 1. Yes 2. No 3. Uncertain

34 Should a diagnosis of dementia be a contraindication to dialysis? 1. Yes 2. No 3. Uncertain

35 Do you formally assess for frailty in older patients approaching treatment decisions for ESKD? 1. Yes 2. No 3. Uncertain

36 How do you assess for frailty? 1. Fried s criteria 2. Frailty index 3. FRAIL 4. Clinical frailty scale 5. Physician perception 6. Uncertain

37 There are many different ways to measure frailty 1) Physical frailty 2) Frailty index 3) FRAIL 4) Clinical frailty scale

38 Fried et al, J Gerontol A Biol Sci Med Sci 2001 Frailty assessments 1. Fried

39 Frailty assessments 2. Frailty index Number of deficits in an individual /Total number of deficits measured Based on accumulation of illnesses, functional and cognitive declines, and social situations It requires answering 20 or more medical and functional-related questions.

40 Frailty assessments 3. FRAIL Fatigue ("Are you fatigued?") Resistance ("Can you climb one flight of stairs?") Ambulation ("Can you walk one block?") Illnesses (greater than five) Loss of weight (greater than 5 percent) Morley JE et al., J Nutr Health Aging 2012

41 Rockwood et al, Can Med Assoc J 2005 Frailty assessments 4. Clinical Frailty Scale

42 Do you formally assess for malnutrition in older patients approaching treatment decisions for ESKD? 1. Yes 2. No 3. Uncertain

43 How do you assess malnutrition in your elderly ESKD patients? 1. Serum albumin 2. Body mass index 3. Anthropometry 4. Subjective Global Assessment 5. Uncertain

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48 Do we need to capture comorbid burden? Which patients do we target? Which tool to use? Who does it formally (on top of ANZDATA)? How do we utilise the comorbid information?

49 New comorbidity index predicts survival in older dialysis patients Kan et al. Plos One 2013

50 There may be no survival advantage with dialysis with increasing comorbidity SC n=54, dialysis n=17 Chandna et al. NDT 2010

51 Cognitive impairment Need to screen? Who to screen? What tool to screen with? How to interpret finding of cognitive impairment into decision making? Should a diagnosis of dementia be a CI to dialysis

52 Cognitive impairment is a common but poorly recognized problem amongst older ESKD patients Dementia prevalence was 22% in elderly nursing home patients starting dialysis % cognitive impairment on neuropsychological testing in ESKD patients aged over 75 2 Uncertainty remains as to which cognitive instrument to use Multiple screening cognitive assessments exist No validation against clinical diagnoses of dementia in the ESKD population 3 Many are influenced by educational level and language fluency 1. Tamura et al. NEJM Tamura et al. CJASN Tamura et al. KI 2011

53 Dementia leads to increase mortality and dialysis withdrawal Dementia confers independent increased risk of death 1,2 2-yr survival for pts with dementia was 24% versus 66% for pts without dementia (P < 0.001) 2 Also increased dialysis withdrawal (RR 2.01, 95% CI ) 2 1.Kurella et al, NDT Rakowski et al, CJASN 2006

54 Frailty assessments Who to screen? What tool to screen with? How to interpret finding of frailty into decision making?

55 Frailty in dialysis patients leads to independent and graded increased mortality risk Independent 2.24x increased risk of death 1 Also found 1.63 risk of death or hospitalization 1 Each 1-point increase in frailty led to 1.22 increased risk of death 2 1. Johansen et al JASN Alfaadhel et al, CJASN 2015

56 7 point SGA 1. Weight loss 2. Dietary intake 3. GI symptoms (nausea/vomiting/diarrhoea) 4. Functional status (nutrition related) 5. Disease state affecting nutrition requirements 6. Muscle wastage 7. Fat stores 8. Oedema

57 Use of risk prediction tools Which tool? Use with limitations in mind Who uses these?

58 Surprise question (SQ)

59 SQ predicts increased mortality Would I be surprised if this patient died in the next year? Moss et al. CJASN 2008

60 Literature search and survey identified important factors and these were presented to nephrologists and advanced trainees

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62 Respondents chose neither patient for 57.3% of the scenarios,

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64 Cognition, patient choice and expected fall in QOL as most important attributes Furthermore looked at trade-offs: Nephrologists were willing to forgo 12 months of patient survival in order to avoid a substantial decrease in QOL following dialysis start Survival trade-off is similar to 15 months of life expectancy that patients were willing to give up to decrease their travel restrictions 1 1. Morton et al. CMAJ 2011