NDLI: Considerations in the statistical analysis of hemodialysis patient survival.

Please wait, while we are loading the content...

Renal volume, renin-angiotensin-aldosterone system, hypertension, and left ventricular hypertrophy in patients with autosomal dominant polycystic kidney disease.

Activation of canonical Wnt signaling meets with podocytopathy.

Managing conflicts of interest: the road ahead.

ASN policy on managing conflicts of interest.

Does a statistical method suggest a new pathobiology for hemodialysis patients?

Functional effector memory T cells enrich the peritoneal cavity of patients treated with peritoneal dialysis.

Viral RNA and DNA trigger common antiviral responses in mesangial cells.

Year: 2009 Volume: 20 Issue: 8

Year: 2009 Volume: 20 Issue: 7

Year: 2009 Volume: 20 Issue: 6

Year: 2009 Volume: 20 Issue: 5

Year: 2009 Volume: 20 Issue: 4

Year: 2009 Volume: 20 Issue: 3

Year: 2009 Volume: 20 Issue: 2

Year: 2009 Volume: 20 Issue: 1

Year: 2008 Volume: 19

Year: 2007 Volume: 18

Year: 2006 Volume: 17

Year: 2005 Volume: 16

Year: 2004 Volume: 15

Year: 2003 Volume: 14

Year: 2001 Volume: 12

Year: 2000 Volume: 11

Year: 1993 Volume: 4

Considerations in the statistical analysis of hemodialysis patient survival.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Argyropoulos, Christos Chang, Chung-Chou H. Plantinga, Laura Fink, Nancy Powe, Neil Unruh, Mark
Description	Country affiliation: United States Author Affiliation: Argyropoulos C ( Renal-Electrolyte Division, University of Pittsburgh Medical Center, Pittsburgh, PA 15261, USA. argyropoulosc@upmc.edu)
Abstract	The association of hemodialysis dosage with patient survival is controversial. Here, we tested the hypothesis that methods for survival analysis may influence conclusions regarding dialysis dosage and mortality. We analyzed all-cause mortality by proportional hazards and accelerated failure time regression models in a cohort of incident hemodialysis patients who were followed for 9 yr. Both models identified age, race, heart failure, physical functioning, and comorbidity scores as important predictors of patient survival. Using proportional hazards, there was no statistically significant association between mortality and Kt/V (hazard ratio 0.72; 95% confidence interval 0.45 to 1.14). In contrast, using accelerated failure time models, each 0.1-U increment of Kt/V improved adjusted median patient survival by 3.50% (95% confidence interval 0.20 to 7.08%). Proportional hazard models also yielded less accurate estimates for median survival. These findings are consistent with an additive damage model for the survival of patients who are on hemodialysis. In this conceptual model, the assumptions of the proportional hazard model are violated, leading to underestimation of the importance of dialysis dosage. These results suggest that future studies of dialysis adequacy should consider this additive damage model when selecting methods for survival analysis. Accelerated failure time models may be useful adjuncts to the Cox model when studying outcomes of dialysis patients.
File Format	HTM / HTML
ISSN	10466673
e-ISSN	15333450
DOI	10.1681/ASN.2008050551
Journal	Journal of the American Society of Nephrology
Issue Number	9
Volume Number	20
Language	English
Publisher	American Society of Nephrology
Publisher Date	2009-09-01
Publisher Place	United States
Access Restriction	Open
Subject Keyword	Discipline Nephrology Kidney Failure, Chronic Mortality Therapy Renal Dialysis Statistics & Numerical Data Cohort Studies Comorbidity Predictive Value Of Tests Proportional Hazards Models Quality Of Life Regression Analysis Reproducibility Of Results Research Support, N.i.h., Extramural Research Support, U.s. Gov't, P.h.s.
Content Type	Text
Resource Type	Article
Subject	Nephrology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Key comorbid conditions that are predictive of survival among hemodialysis patients.

Inpatient hemodialysis initiation: reasons, risk factors and outcomes.

A comorbidity index for mortality prediction in Chinese patients with ESRD receiving hemodialysis.

Association between serum 2-microglobulin level and infectious mortality in hemodialysis patients.

Nephrologist caseload and hemodialysis patient survival in an urban cohort.

Predictors of death and dialysis in severe AKI: the UPHS-AKI cohort.

Peritoneal protein clearance and not peritoneal membrane transport status predicts survival in a contemporary cohort of peritoneal dialysis patients.

Independent effects of systemic and peritoneal inflammation on peritoneal dialysis survival.

Uncorrected and Albumin-Corrected Calcium, Phosphorus, and Mortality in Patients Undergoing Maintenance Dialysis.

Considerations in the statistical analysis of hemodialysis patient survival.

Similar Documents

Key comorbid conditions that are predictive of survival among hemodialysis patients.

Inpatient hemodialysis initiation: reasons, risk factors and outcomes.

A comorbidity index for mortality prediction in Chinese patients with ESRD receiving hemodialysis.

Association between serum 2-microglobulin level and infectious mortality in hemodialysis patients.

Nephrologist caseload and hemodialysis patient survival in an urban cohort.

Predictors of death and dialysis in severe AKI: the UPHS-AKI cohort.

Peritoneal protein clearance and not peritoneal membrane transport status predicts survival in a contemporary cohort of peritoneal dialysis patients.

Independent effects of systemic and peritoneal inflammation on peritoneal dialysis survival.

Uncorrected and Albumin-Corrected Calcium, Phosphorus, and Mortality in Patients Undergoing Maintenance Dialysis.

Considerations in the statistical analysis of hemodialysis patient survival.