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Cited by 391Dialysis and Renal Disease ManagementPalliative Care and End-of-Life IssuesChronic Kidney Disease and Diabetes

The DOI matches its Crossref record; 50 of the 51 references it cites were found in a registry or an index.

Predicting Six-Month Mortality for Patients Who Are on Maintenance Hemodialysis

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Cohen, Lewis M., Ruthazer, Robin, Moss, Alvin H., Germain, Michael J.·2010·Clinical Journal of the American Society of Nephrology
DOI 10.2215/cjn.03860609PMC PMC2801643
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Abstract

BACKGROUND AND OBJECTIVES: Prognostic information is rarely conveyed by nephrologists because of clinical uncertainty about accuracy. The objective of this study was to develop an integrated prognostic model of 6-mo survival for patients who receive hemodialysis (HD). DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: A short-term prognostic model was developed using prospective data from a derivation cohort of 512 patients who were receiving HD at five dialysis clinics. Patient charts were reviewed for actuarial predictors (e.g., Charlson Comorbidity), and nephrologists answered the "surprise" question (SQ), "Would I be surprised if this patient died within the next 6 mo?" Survival was monitored for up to 24 mo. The prognostic model was tested with a validation cohort of 514 patients from eight clinics. RESULTS: In a Cox multivariate analysis of the derivation cohort, five variables were independently associated with early mortality: Older age (hazard ratio [HR] for a 10-yr increase 1.36; 95% confidence interval [CI] 1.17 to 1.57), dementia (HR 2.24; 95% CI 1.11 to 4.48), peripheral vascular disease (HR 1.88; 95% CI 1.24 to 2.84), decreased albumin (HR for a 1-U increase 0.27; 95% CI 0.15 to 0.50), and SQ (HR 2.71; 95% CI 1.76 to 4.17). Area under the curve for the resulting prognostic model predictions of 6-mo mortality were 0.87 (95% CI 0.82 to 0.92) in the derivation cohort and 0.80 (95% CI 0.73 to 0.88) in the validation cohort. CONCLUSIONS: An integrated 6-mo prognostic tool was developed and validated for the HD population. The instrument may be of value for researchers and clinicians to improve end-of-life care by providing more accurate prognostic information.

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Metadata

Authors
Cohen, L. M., Ruthazer, R., Moss, A. H., & Germain, M. J.
Affiliations
  • Baystate Medical Center (US)
  • Tufts Medical Center (US)
  • West Virginia University (US)
Corresponding author
Cohen, Lewis M.
ORCID
Venue
Clinical Journal of the American Society of Nephrology
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2010-01
Volume
5
Issue
1
Pages
72-79
ISSN
1555-9041 (ISSN-L)
DOI
10.2215/cjn.03860609
PMC
PMC2801643
OpenAlex
W2116257995
Cited by
391
References
51
Citations by year
2026: 7 · 2025: 13 · 2024: 17 · 2023: 20 · 2022: 17 · 2021: 19 · 2020: 27 · 2019: 25 · 2018: 27 · 2017: 34 · 2016: 33 · 2015: 31 · 2014: 25 · 2013: 35 · 2012: 26
FWCI
14.00
Type
journal article
Language
en
Open access
Locations
  • Clinical Journal of the American Society of Nephrology (publishedVersion)
  • Europe PMC (PubMed Central) (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • Robert Wood Johnson Foundation
  • National Institutes of Health (5r21dk076563-02)
  • National Institute of Diabetes and Digestive and Kidney Diseases (5 R21 DK076563-02, R21 DK076563)
Topics
  • Health Sciences › Medicine › Nephrology › Dialysis and Renal Disease Management
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Palliative Care and End-of-Life Issues
  • Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
Keywords
maintenance hemodialysis, 6-month mortality, prognostic model, survival prediction, surprise question, dementia, peripheral vascular disease, serum albumin, age, end-of-life care
MeSH terms
Aged, Female, Renal Dialysis, Humans, Male, Middle Aged, Prognosis, Prospective Studies, Time Factors, Models, Statistical, Survival Rate

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