Abstract
Context
Universal screening to identify vulnerable patients who may receive limited benefits
from life-sustaining treatments can facilitate palliative care in dialysis populations.
Objectives
We aimed to develop prediction models for one-year mortality in peritoneal dialysis
(PD) patients.
Methods
This prospective cohort study included 401 adult Taiwanese prevalent PD patients (average
age 56.2 ± 14 years). In addition to obtaining clinical characteristics and laboratory
data, the primary care nurses evaluated the surprise question (SQ) and palliative
care screening tool (PCST) for each patient in March 2015. Multivariate logistic regression
models were conducted to predict the primary outcome of one-year all-cause mortality.
Results
There were 34 (8.5%) patients who died during the first year of follow-up. Patients
allocated to the not surprised group according to the SQ and those who received a
score of ≥4 on the PCST had increased odds of death (odds ratio 24.68 [95% CI 10.66–57.13]
and 12.18 [95% CI 5.66–26.21], respectively). We also developed a clinical risk model
for one-year mortality that included sex, dialysis vintage, coronary artery disease,
malignancy, normalized protein nitrogen appearance, white blood cell count, and serum
albumin and sodium levels. Integrating the SQ, PCST, and clinical risk model exhibited
good discrimination with an area under the receiver operating characteristic curve
of 0.95. Kaplan-Meier analysis showed worse survival in high-risk patients predicted
by the integrated model (log-rank P < 0.001).
Conclusion
Screening with the use of the integrated measurement can identify high-risk PD patients.
This approach may facilitate palliative care interventions for at-risk subpopulations.
Key Words
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Journal of Pain and Symptom ManagementAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Supportive care: time to change our prognostic tools and their use in CKD.Clin J Am Soc Nephrol. 2016; 11: 1892-1901
- 2018 USRDS annual data report: Epidemiology of kidney disease in the United States.National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD2018
- Derivation and validation of a prognostic model to predict mortality in patients with advanced chronic kidney disease.Nephrol Dial Transplant. 2019; 34: 1517-1525
- Incorporating palliative care into the dialysis unit affects patterns near the end of life.Mayo Clin Proc. 2015; 90: 1307-1309
- Treatment intensity at the end of life in older adults receiving long-term dialysis.Arch Intern Med. 2012; 172 (discussion 663–664): 661-663
- 2017 Annual report on kidney disease in Taiwan. National Health Research Institutes, Zhunan, Miaoli County, Taiwan2018
- Five policies to promote palliative care for patients with ESRD.Clin J Am Soc Nephrol. 2013; 8: 1783-1790
- What determines whether a patient initiates chronic renal replacement therapy?.Clin J Am Soc Nephrol. 2013; 8: 1276-1278
- Palliative care for patients with end-stage renal disease: approach to treatment that aims to improve quality of life and relieve suffering for patients (and families) with chronic illnesses.Clin Kidney J. 2017; 10: 68-73
- Shared decision-making in the appropriate initiation of and withdrawal from dialysis. Clinical practice guideline.2nd ed. Renal Physicians Association, Rockville, MD2010
- ANZSN renal supportive care 2013: opinion pieces [corrected].Nephrology (Carlton). 2013; 18: 401-454
- Executive summary of the KDIGO Controversies Conference on supportive care in chronic kidney disease: developing a roadmap to improving quality care.Kidney Int. 2015; 88: 447-459
- Withdrawal from long-term hemodialysis in patients with end-stage renal disease in Taiwan.J Formos Med Assoc. 2013; 112: 589-599
- Risk score to predict mortality in continuous ambulatory peritoneal dialysis patients.Eur J Clin Invest. 2014; 44: 1095-1103
- Improving care through the end of life: launching a primary care clinic-based program.J Palliat Med. 2001; 4: 249-254
- Reliability and utility of the surprise question in CKD stages 4 to 5.Am J Kidney Dis. 2017; 70: 93-101
- Utility of the “surprise” question to identify dialysis patients with high mortality.Clin J Am Soc Nephrol. 2008; 3: 1379-1384
- Predicting six-month mortality for patients who are on maintenance hemodialysis.Clin J Am Soc Nephrol. 2010; 5: 72-79
- Predicting 12-month mortality for peritoneal dialysis patients using the “surprise” question.Perit Dial Int. 2013; 33: 60-66
- How robust is the 'surprise question' in predicting short-term mortality risk in haemodialysis patients?.Nephron Clin Pract. 2013; 123: 185-193
- How accurate is the 'surprise question' at identifying patients at the end of life? A systematic review and meta-analysis.BMC Med. 2017; 15: 139
- Performance of the surprise question compared to prediction models in hemodialysis patients: a prospective study.Am J Nephrol. 2017; 46: 390-396
- Identifying patients in need of a palliative care assessment in the hospital setting: a consensus report from the Center to Advance Palliative Care.J Palliat Med. 2011; 14: 17-23
- Establishment of a renal supportive care program: experience from a rural community hospital in Taiwan.J Formos Med Assoc. 2016; 115: 490-500
- Taiwan renal care system: a learning health-care system.Nephrology (Carlton). 2018; 23: 112-115
- Validation of a simple screening tool for identifying unmet palliative care needs in patients with cancer.J Oncol Pract. 2015; 11: e81-e86
- Content validation of advanced illness criteria of a palliative care screening tool.J Palliat Med. 2018; 21: 1604-1608
- Validation of a concise screening tool for the identification of palliative care needs among inpatients: a prospective study in hospital setting.J Formos Med Assoc. 2019; 118: 883-890
- Development of a risk stratification algorithm to improve patient-centered care and decision making for incident elderly patients with end-stage renal disease.Kidney Int. 2015; 88: 1178-1186
- Elevated white cell count at commencement of peritoneal dialysis predicts overall and cardiac mortality.Kidney Int. 2005; 67: 738-743
- Longitudinal associations between dietary protein intake and survival in hemodialysis patients.Am J Kidney Dis. 2006; 48: 37-49
- Serum creatinine level, a surrogate of muscle mass, predicts mortality in peritoneal dialysis patients.Nephrol Dial Transplant. 2013; 28: 2146-2155
- Hyponatremia as a predictor of mortality in peritoneal dialysis patients.PLoS One. 2014; 9: e111373
- Predicting early death among elderly dialysis patients: development and validation of a risk score to assist shared decision making for dialysis initiation.Am J Kidney Dis. 2015; 66: 1024-1032
- A clinical risk prediction tool for 6-month mortality after dialysis initiation among older adults.Am J Kidney Dis. 2017; 69: 568-575
- NephroTalk: communication tools to enhance patient-centered care.Semin Dial. 2012; 25: 611-616
Article info
Publication history
Published online: April 08, 2020
Accepted:
March 26,
2020
Footnotes
C. -F. L. and C. -I C. contributed equally to this work. J. -W. H. and S. -J. H. share senior authorship of this work.
Identification
Copyright
© 2020 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
