Literature DB >> 27198825

Do patient-reported measures of symptoms and health status predict mortality in hemodialysis? An assessment of POS-S Renal and EQ-5D.

Donal J Sexton1, Aoife C Lowney2, Conall M O'Seaghdha3, Marie Murphy2, Tony O'Brien2, Liam F Casserly4, Regina McQuillan5, William D Plant6, Joseph A Eustace6,7, Sinead M Kinsella6, Peter J Conlon3.   

Abstract

Introduction Experience with the use of patient-reported outcome measures such as EQ-5D and the symptom module of the Palliative care Outcome Scale-Renal Version (POS-S Renal) as mortality prediction tools in hemodialysis is limited. Methods A prospective survival study of people receiving hemodialysis (N = 362). The EQ-5D and the POS-S Renal were used to assess symptom burden and self-rated health (with a self-rated component). Participants were followed from instrument completion to death or study end. Competing risks survival analysis was used to evaluate associations with time to death, with renal transplant as a competing risk. Findings 32% (N = 116) of participants died over a median (25th-75th centile) of 2.6 (1.41-3.38) years. Factors most notably associated with mortality adjusted hazard ratio (95%CI) included: lower EQ VAS score 2.7 (1.4, 5.2) P = 0.004 (lowest tertile), higher POS-S Renal score 2.4 (1.3, 4.3) P = 0.004 (highest tertile), and lower EQ-5D score 2.6 (1.3, 5.3) P = 0.01 (lowest tertile) as well as the presence of: "problems with mobility?" 2 (1.1, 3.3) P = 0.01, or "problems with usual activities?" 2.1 (1.4, 3.3), P < 0.001. After age adjustment area under the receiver operating curves (AUC) (95%CI) for mortality were: 0.71 (0.62, 0.79) for EQ VAS score, 0.71 (0.63, 0.80) for POS-S Renal-S Renal score, and 0.76 (0.68, 0.84) for EQ-5D score. AUC 95%CI was highest for our fourth model at 0.79 (0.72, 0.86) comprised of individual elements from both instruments and established risk factors. Discussion EQ VAS scores and predictive models based on combinations of elements from the POS-S Renal and EQ-5D instruments may aid in mortality discrimination and possibly in the delivery of supportive care services.
© 2016 International Society for Hemodialysis.

Entities:  

Keywords:  Mortality; prognostication; quality of life

Mesh:

Year:  2016        PMID: 27198825     DOI: 10.1111/hdi.12415

Source DB:  PubMed          Journal:  Hemodial Int        ISSN: 1492-7535            Impact factor:   1.812


  11 in total

1.  Could the EQ-5D-3L predict all-cause mortality in older Chinese? Evidence from a 5-year longitudinal study in eastern China.

Authors:  Chen-Wei Pan; Rui-Jie Liu; Xue-Jiao Yang; Qing-Hua Ma; Yong Xu; Nan Luo; Pei Wang
Journal:  Qual Life Res       Date:  2021-05-24       Impact factor: 4.147

2.  Varying Association of Extended Hours Dialysis with Quality of Life.

Authors:  Brendan Smyth; Oliver van den Broek-Best; Daqing Hong; Kirsten Howard; Kris Rogers; Li Zuo; Nicholas A Gray; Janak R de Zoysa; Christopher T Chan; Hongli Lin; Ling Zhang; Jinsheng Xu; Alan Cass; Martin Gallagher; Vlado Perkovic; Meg Jardine
Journal:  Clin J Am Soc Nephrol       Date:  2019-10-31       Impact factor: 8.237

3.  A single question regarding mobility in the World Health Organization quality of life questionnaire predicts 3-year mortality in patients receiving chronic hemodialysis.

Authors:  Hsiu-Ho Wang; Miao-Chun Ho; Kuan-Yu Hung; Hui-Teng Cheng
Journal:  Sci Rep       Date:  2017-09-20       Impact factor: 4.379

4.  Quality of life with conservative care compared with assisted peritoneal dialysis and haemodialysis.

Authors:  Osasuyi Iyasere; Edwina A Brown; Lina Johansson; Andrew Davenport; Ken Farrington; Alexander P Maxwell; Helen Collinson; Stanley Fan; Ann-Marie Habib; John Stoves; Graham Woodrow
Journal:  Clin Kidney J       Date:  2018-07-20

Review 5.  Symptom burden amongst patients suffering from end-stage renal disease and receiving dialysis: A literature review.

Authors:  Hong Li; Lantian Xie; Jie Yang; Xiaoli Pang
Journal:  Int J Nurs Sci       Date:  2018-09-19

6.  Using frailty and quality of life measures in clinical care of the elderly in Canada to predict death, nursing home transfer and hospitalisation - the frailty and ageing cohort study.

Authors:  Ted Rosenberg; Patrick Montgomery; Vikki Hay; Rory Lattimer
Journal:  BMJ Open       Date:  2019-11-12       Impact factor: 2.692

7.  Health-related quality of life, palliative care needs and 12-month survival among patients with end stage renal disease in Uganda: protocol for a mixed methods longitudinal study.

Authors:  Peace Bagasha; Mhoira Leng; Elly Katabira; Mila Petrova
Journal:  BMC Nephrol       Date:  2020-12-07       Impact factor: 2.388

8.  Clinical Assessment of Dialysis Recovery Time and Symptom Burden: Impact of Switching Hemodialysis Therapy Mode.

Authors:  Stephanie Bolton; Rachel Gair; Lars-Göran Nilsson; Michael Matthews; Louanne Stewart; Natasha McCullagh
Journal:  Patient Relat Outcome Meas       Date:  2021-11-04

9.  Symptom clusters in chronic kidney disease and their association with people's ability to perform usual activities.

Authors:  Currie Moore; Shalini Santhakumaran; Glen P Martin; Thomas J Wilkinson; Fergus J Caskey; Winnie Magadi; Rachel Gair; Alice C Smith; David Wellsted; Sabine N van der Veer
Journal:  PLoS One       Date:  2022-03-02       Impact factor: 3.240

Review 10.  Patient-Reported Outcomes in Patients with Chronic Kidney Disease and Kidney Transplant-Part 1.

Authors:  Evan Tang; Aarushi Bansal; Marta Novak; Istvan Mucsi
Journal:  Front Med (Lausanne)       Date:  2018-01-15
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