Literature DB >> 2333868

Death risk in hemodialysis patients: the predictive value of commonly measured variables and an evaluation of death rate differences between facilities.

E G Lowrie1, N L Lew.   

Abstract

Logistic regression analysis was applied to a sample of more than 12,000 hemodialysis patients to evaluate the association of various patient descriptors, treatment time (hours/treatment), and various laboratory tests with the probability of death. Advancing age, white race, and diabetes were all associated with a significantly increased risk of death. Short dialysis times were also associated with high death risk before adjustment for the value of laboratory tests. Of the laboratory variables, low serum albumin less than 40 g/L (less than 4.0 g/dL) was most highly associated with death probability. About two thirds of patients had low albumin. These findings suggest that inadequate nutrition may be an important contributing factor to the mortality suffered by hemodialysis patients. The relative risk profiles for other laboratory tests are presented. Among these, low serum creatinine, not high, was associated with high death risk. Both serum albumin concentration and creatinine were directly correlated with treatment time so that high values for both substances were associated with long treatment times. The data suggest that physicians may select patients with high creatinine for more intense dialysis exposure and patients with low creatinine for less intense treatment. In a separate analysis, observed death rates were compared with rates expected on the basis of case mix for these 237 facilities. The data suggest substantial volatility of observed/expected ratios when facility size is small. Nonetheless, a minority of facilities (less than or equal to 2%) may have higher rates than expected when compared with the pool of all patients in this sample. The effect of various laboratory variables on mortality is substantial, while relatively few facilities have observed death rates that exceed their expected values. Therefore, we suggest that strategies designed to improve the overall mortality statistic for dialysis patients in the United States would be better directed toward improving the quality of care for all patients, particularly high-risk patients, within their usual treatment settings rather than trying to identify facilities with high death rate for possible regulatory intervention.

Entities:  

Mesh:

Year:  1990        PMID: 2333868     DOI: 10.1016/s0272-6386(12)70364-5

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


  221 in total

Review 1.  Mechanisms accelerating muscle atrophy in catabolic diseases.

Authors:  W E Mitch
Journal:  Trans Am Clin Climatol Assoc       Date:  2000

Review 2.  Epidemiology, diagnosis, and management of cardiac disease in chronic renal disease.

Authors:  M J Sarnak; A S Levey
Journal:  J Thromb Thrombolysis       Date:  2000-10       Impact factor: 2.300

3.  Elevated non-high-density lipoprotein cholesterol (non-HDL-C) predicts atherosclerotic cardiovascular events in hemodialysis patients.

Authors:  Tetsuo Shoji; Ikuto Masakane; Yuzo Watanabe; Kunitoshi Iseki; Yoshiharu Tsubakihara
Journal:  Clin J Am Soc Nephrol       Date:  2011-04-21       Impact factor: 8.237

Review 4.  Hyperphosphataemia in renal failure: causes, consequences and current management.

Authors:  Fouad Albaaj; Alastair Hutchison
Journal:  Drugs       Date:  2003       Impact factor: 9.546

5.  Association of cumulatively low or high serum calcium levels with mortality in long-term hemodialysis patients.

Authors:  Jessica E Miller; Csaba P Kovesdy; Keith C Norris; Rajnish Mehrotra; Allen R Nissenson; Joel D Kopple; Kamyar Kalantar-Zadeh
Journal:  Am J Nephrol       Date:  2010-09-03       Impact factor: 3.754

6.  Anthropometrics Identify Wasting in Patients Undergoing Surgery for Encapsulating Peritoneal Sclerosis.

Authors:  Rosalind Campbell; Titus Augustine; Helen Hurst; Ravi Pararajasingam; David van Dellen; Sheilagh Armstrong; Carol Bartley; Linda Birtles; Angela Summers
Journal:  Perit Dial Int       Date:  2014-03-01       Impact factor: 1.756

Review 7.  Managing dyslipidemia in chronic kidney disease.

Authors:  Daniel E Weiner; Mark J Sarnak
Journal:  J Gen Intern Med       Date:  2004-10       Impact factor: 5.128

8.  Serum potassium and adverse outcomes across the range of kidney function: a CKD Prognosis Consortium meta-analysis.

Authors:  Csaba P Kovesdy; Kunihiro Matsushita; Yingying Sang; Nigel J Brunskill; Juan J Carrero; Gabriel Chodick; Takeshi Hasegawa; Hiddo L Heerspink; Atsushi Hirayama; Gijs W D Landman; Adeera Levin; Dorothea Nitsch; David C Wheeler; Josef Coresh; Stein I Hallan; Varda Shalev; Morgan E Grams
Journal:  Eur Heart J       Date:  2018-05-01       Impact factor: 29.983

9.  Absorption and excretion of colestilan in healthy subjects.

Authors:  Koji Takei; Sian Dale; Heather Charles; Akira Sasaki; Shigekazu Nakajima
Journal:  Clin Pharmacokinet       Date:  2010       Impact factor: 6.447

10.  Disorders of lipid metabolism and chronic kidney disease in the elderly.

Authors:  Devasmita Choudhury; Meryem Tuncel; Moshe Levi
Journal:  Semin Nephrol       Date:  2009-11       Impact factor: 5.299

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.