Literature DB >> 10620547

Predictors of poor outcome in chronic dialysis patients: The Netherlands Cooperative Study on the Adequacy of Dialysis. The NECOSAD Study Group.

M P Merkus1, K J Jager, F W Dekker, R J de Haan, E W Boeschoten, R T Krediet.   

Abstract

In a prospective cohort study, we constructed a composite index of poor outcome that incorporates survival, morbidity, and quality of life (QL). We identified baseline patient and treatment characteristics that predicted poor outcome 1 year after the start of chronic dialysis. Outcome was classified as poor if a patient had died or if at least two of the following criteria were present: (1) 30 days or greater of hospitalization per year, (2) serum albumin level of 30 g/L or less or a malnutrition index score of 11 or greater, (3) a 36-item Medical Outcomes Study (MOS)-Short Form Health Survey Questionnaire (SF-36) physical summary QL score of 2 or more SDs less than the general population mean score, and (4) an SF-36 mental summary QL score of 2 or more SDs less than the general population mean score. Multivariate logistic regression analysis was used to identify independent predictors of poor outcome. Of 250 included patients, 189 were assessable with respect to poor outcome. Of these patients, 47 (25%) were classified as poor. A baseline presence of comorbidity, serum albumin level of 30 g/L or less, physical or mental QL score 2 or more SDs less than the general population mean score, and, to a lesser extent, residual glomerular filtration rate of 2.5 mL/min/1.73 m(2) or less were independently associated with a greater risk for poor outcome. A post hoc analysis indicated a mean arterial blood pressure greater than 107 mm Hg was predictive of poor outcome in patients undergoing peritoneal dialysis. In conclusion, our prognostic model provides a useful tool to identify chronic dialysis patients at risk for poor health status. Strategies aimed at preserving residual renal function, controlling blood pressure, monitoring QL, and consequently giving psychosocial support may reduce the risk for poor outcome.

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Year:  2000        PMID: 10620547     DOI: 10.1016/s0272-6386(00)70304-0

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  28 in total

1.  Quality of life during hemodialysis and study dialysis treatment in patients referred to teaching hospitals in Urmia-Iran in 2007.

Authors:  Nader Aghakhani; Hamid Sharif Nia; Saeed Samad Zadeh; Vahid Toupchi; Saeed Toupchi; Narges Rahbar
Journal:  Caspian J Intern Med       Date:  2011

2.  Renal Perfusion during Hemodialysis: Intradialytic Blood Flow Decline and Effects of Dialysate Cooling.

Authors:  Raanan Marants; Elena Qirjazi; Claire J Grant; Ting-Yim Lee; Christopher W McIntyre
Journal:  J Am Soc Nephrol       Date:  2019-05-03       Impact factor: 10.121

3.  Predicting mortality in incident dialysis patients: an analysis of the United Kingdom Renal Registry.

Authors:  Martin Wagner; David Ansell; David M Kent; John L Griffith; David Naimark; Christoph Wanner; Navdeep Tangri
Journal:  Am J Kidney Dis       Date:  2011-04-12       Impact factor: 8.860

4.  Time to Rethink Our Approach to Patient-Reported Outcome Measures for ESRD.

Authors:  Fredric O Finkelstein; Susan H Finkelstein
Journal:  Clin J Am Soc Nephrol       Date:  2017-08-28       Impact factor: 8.237

Review 5.  Diets and enteral supplements for improving outcomes in chronic kidney disease.

Authors:  Kamyar Kalantar-Zadeh; Noël J Cano; Klemens Budde; Charles Chazot; Csaba P Kovesdy; Robert H Mak; Rajnish Mehrotra; Dominic S Raj; Ashwini R Sehgal; Peter Stenvinkel; T Alp Ikizler
Journal:  Nat Rev Nephrol       Date:  2011-05-31       Impact factor: 28.314

6.  Validity of malnutrition scores for predicting mortality in chronic hemodialysis patients.

Authors:  Flavia R Toledo; Aline A Antunes; Francieli C D Vannini; Liciana V A Silveira; Luis C Martin; Pasqual Barretti; Jacqueline C T Caramori
Journal:  Int Urol Nephrol       Date:  2013-06-21       Impact factor: 2.370

7.  Serum creatinine level, a surrogate of muscle mass, predicts mortality in peritoneal dialysis patients.

Authors:  Jongha Park; Rajnish Mehrotra; Connie M Rhee; Miklos Z Molnar; Lilia R Lukowsky; Sapna S Patel; Allen R Nissenson; Joel D Kopple; Csaba P Kovesdy; Kamyar Kalantar-Zadeh
Journal:  Nephrol Dial Transplant       Date:  2013-06-05       Impact factor: 5.992

Review 8.  Current techniques for assessment of upper extremity vasculature prior to hemodialysis vascular access creation.

Authors:  R N Planken; J H M Tordoir; L E M Duijm; M W de Haan; T Leiner
Journal:  Eur Radiol       Date:  2007-05-08       Impact factor: 5.315

Review 9.  Strategies for the preservation of residual renal function in pediatric dialysis patients.

Authors:  Melissa A Cadnapaphornchai; Isaac Teitelbaum
Journal:  Pediatr Nephrol       Date:  2013-07-19       Impact factor: 3.714

10.  Baseline characteristics of an incident haemodialysis population in Spain: results from ANSWER--a multicentre, prospective, observational cohort study.

Authors:  Rafael Pérez-García; Alejandro Martín-Malo; Joan Fort; Xavier Cuevas; Fina Lladós; Javier Lozano; Fernando García
Journal:  Nephrol Dial Transplant       Date:  2008-11-21       Impact factor: 5.992

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