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Predicting renal replacement therapy and mortality in CKD.
Am J Kidney Dis. 2007 Oct; 50(4):559-65.AJ

Abstract

BACKGROUND

Prognostic risk scores can help clinicians intervene on higher risk patients and counsel them. Our objective is to identify characteristics that predict the rate of progression to renal replacement therapy (RRT) and evaluate how those characteristics predict mortality and a composite end point (RRT and mortality).

STUDY DESIGN

Retrospective cohort study.

SETTING & PARTICIPANTS

We conducted the study at Kaiser Permanente Northwest, a health maintenance organization. We followed up members with an estimated glomerular filtration rate (eGFR) that indicated chronic kidney disease (2 eGFRs < 60 mL/min/1.73 m(2) [<1.0 mL/s/1.73 m(2)] at least 90 days apart).

PREDICTORS

We measured baseline clinical characteristics between January 1997 and June 2000 by using electronic medical records and patients' histories of hospitalization.

OUTCOMES & MEASUREMENTS

We calculated adjusted hazard ratios and concordance statistics for progression to RRT, mortality, and the composite by using Cox regression.

RESULTS

Patients (n = 6,541) were followed up for up to 5 years. We observed 1.6 progressions to RRT/100 person-years and 11.4 deaths/100 person-years. The 6 characteristics of age, sex, eGFR, diabetes, hypertension, and anemia predicted RRT effectively (c statistic, 0.91). However, hypertension and age predicted in the opposite direction for mortality and its composite end point. The c statistic decreased: mortality (0.70), mortality and RRT (0.71).

LIMITATIONS

Characteristics were measured without a protocol; extensive missing data prevented the evaluation of known risk factors (eg, proteinuria).

CONCLUSIONS

Predicting RRT effectively requires a separate risk score. Predicting the composite end point would favor characteristics that predict mortality because it is 7 times as common as RRT.

Authors+Show Affiliations

Center for Health Research, Kaiser Permanente Northwest, Portland, OR 97227, USA.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Comparative Study
Journal Article

Language

eng

PubMed ID

17900455

Citation

Johnson, Eric S., et al. "Predicting Renal Replacement Therapy and Mortality in CKD." American Journal of Kidney Diseases : the Official Journal of the National Kidney Foundation, vol. 50, no. 4, 2007, pp. 559-65.
Johnson ES, Thorp ML, Yang X, et al. Predicting renal replacement therapy and mortality in CKD. Am J Kidney Dis. 2007;50(4):559-65.
Johnson, E. S., Thorp, M. L., Yang, X., Charansonney, O. L., & Smith, D. H. (2007). Predicting renal replacement therapy and mortality in CKD. American Journal of Kidney Diseases : the Official Journal of the National Kidney Foundation, 50(4), 559-65.
Johnson ES, et al. Predicting Renal Replacement Therapy and Mortality in CKD. Am J Kidney Dis. 2007;50(4):559-65. PubMed PMID: 17900455.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Predicting renal replacement therapy and mortality in CKD. AU - Johnson,Eric S, AU - Thorp,Micah L, AU - Yang,Xiuhai, AU - Charansonney,Olivier L, AU - Smith,David H, PY - 2006/12/18/received PY - 2007/07/05/accepted PY - 2007/9/29/pubmed PY - 2007/10/16/medline PY - 2007/9/29/entrez SP - 559 EP - 65 JF - American journal of kidney diseases : the official journal of the National Kidney Foundation JO - Am J Kidney Dis VL - 50 IS - 4 N2 - BACKGROUND: Prognostic risk scores can help clinicians intervene on higher risk patients and counsel them. Our objective is to identify characteristics that predict the rate of progression to renal replacement therapy (RRT) and evaluate how those characteristics predict mortality and a composite end point (RRT and mortality). STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: We conducted the study at Kaiser Permanente Northwest, a health maintenance organization. We followed up members with an estimated glomerular filtration rate (eGFR) that indicated chronic kidney disease (2 eGFRs < 60 mL/min/1.73 m(2) [<1.0 mL/s/1.73 m(2)] at least 90 days apart). PREDICTORS: We measured baseline clinical characteristics between January 1997 and June 2000 by using electronic medical records and patients' histories of hospitalization. OUTCOMES & MEASUREMENTS: We calculated adjusted hazard ratios and concordance statistics for progression to RRT, mortality, and the composite by using Cox regression. RESULTS: Patients (n = 6,541) were followed up for up to 5 years. We observed 1.6 progressions to RRT/100 person-years and 11.4 deaths/100 person-years. The 6 characteristics of age, sex, eGFR, diabetes, hypertension, and anemia predicted RRT effectively (c statistic, 0.91). However, hypertension and age predicted in the opposite direction for mortality and its composite end point. The c statistic decreased: mortality (0.70), mortality and RRT (0.71). LIMITATIONS: Characteristics were measured without a protocol; extensive missing data prevented the evaluation of known risk factors (eg, proteinuria). CONCLUSIONS: Predicting RRT effectively requires a separate risk score. Predicting the composite end point would favor characteristics that predict mortality because it is 7 times as common as RRT. SN - 1523-6838 UR - https://www.unboundmedicine.com/medline/citation/17900455/Predicting_renal_replacement_therapy_and_mortality_in_CKD_ L2 - https://linkinghub.elsevier.com/retrieve/pii/S0272-6386(07)01035-9 DB - PRIME DP - Unbound Medicine ER -