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Articles by A. S Levey
Total Records ( 2 ) for A. S Levey
  C. E Gordon , K Uhlig , J Lau , C. H Schmid , A. S Levey and J. B. Wong

Background and objectives: Hepatitis C virus (HCV) infection is prevalent in hemodialysis patients and causes excess mortality. Interferon (IFN) treatment of chronic HCV infection in hemodialysis patients results in high sustained virological response (SVR) rates 6 mo after treatment. The authors aimed to identify factors associated with SVR in hemodialysis patients through analysis of individual patient data obtained from systematic review of published literature.

Design, setting, participants & measurements: Medline was searched from 1966 through February 2009, and prospective studies describing IFN treatment of hemodialysis patients with chronic HCV infection with published individual patient data were included. To identify factors associated with SVR, logistic regression was applied with adjustment for study.

Results: Twenty studies of IFN treatment provided data on 428 patients. Overall SVR was 45% and in univariate analyses was higher with: 1) three million units or higher three times weekly of IFN; 2) treatment for at least 6 mo; 3) treatment completion; 4) lower baseline HCV RNA; 5) female gender; and 6) early virological negativity. Although limited by missing data, these relationships persisted in multivariate regression.

Conclusions: SVR is more likely with larger IFN dose, longer treatment duration, treatment completion, female gender, lower HCV RNA and early virological negativity. For appropriate treatment candidates, regimens should consist of three million units of IFN three times weekly for at least 6 mo, with patients encouraged to complete the full course.

  D Miskulin , J Bragg Gresham , B. W Gillespie , F Tentori , R. L Pisoni , H Tighiouart , A. S Levey and F. K. Port

Background and objectives: Abstracting information about comorbid illnesses from the medical record can be time-consuming, particularly when a large number of conditions are under consideration. We sought to determine which conditions are most prognostic and whether comorbidity continues to contribute to a survival model once laboratory and clinical parameters have been accounted for.

Design, setting, participants, & measurements: Comorbidity data were abstracted from the medical records of Dialysis Outcomes and Practice Pattern Study (DOPPS) I, II, and III participants using a standardized questionnaire. Models that were composed of different combinations of comorbid conditions and case-mix factors were compared for explained variance (R2) and discrimination (c statistic).

Results: Seventeen comorbid conditions account for 96% of the total explained variance that would result if 45 comorbidities that were expected to be predictive of survival were added to a demographics-adjusted survival model. These conditions together had more discriminatory power (c statistic 0.67) than age alone (0.63) or serum albumin (0.60) and were equivalent to a combination of routine laboratory and clinical parameters (0.67). The strength of association of the individual comorbidities lessened when laboratory/clinical parameters were added, but all remained significant. The total R2 of a model adjusted for demographics and laboratory/clinical parameters increased from 0.13 to 0.17 upon addition of comorbidity.

Conclusions: A relatively small list of comorbid conditions provides equivalent discrimination and explained variance for survival as a more extensive characterization of comorbidity. Comorbidity adds to the survival model a modest amount of independent prognostic information that cannot be substituted by clinical/laboratory parameters.

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