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Modeling a Predictive Energy Equation Specific for Maintenance Hemodialysis.
Byham-Gray, Laura D; Parrott, J Scott; Peters, Emily N; Fogerite, Susan Gould; Hand, Rosa K; Ahrens, Sean; Marcus, Andrea Fleisch; Fiutem, Justin J.
Afiliación
  • Byham-Gray LD; Rutgers University, Newark, New Jersey, USA.
  • Parrott JS; Rutgers University, Newark, New Jersey, USA.
  • Peters EN; Rutgers University, Newark, New Jersey, USA.
  • Fogerite SG; Rutgers University, Newark, New Jersey, USA.
  • Hand RK; Case Western Reserve University, Cleveland, Ohio, USA.
  • Ahrens S; Rutgers University, Newark, New Jersey, USA.
  • Marcus AF; Rutgers University, Newark, New Jersey, USA.
  • Fiutem JJ; Case Western Reserve University, Cleveland, Ohio, USA.
JPEN J Parenter Enteral Nutr ; 42(3): 587-596, 2018 03.
Article en En | MEDLINE | ID: mdl-29187037
BACKGROUND: Hypermetabolism is theorized in patients diagnosed with chronic kidney disease who are receiving maintenance hemodialysis (MHD). We aimed to distinguish key disease-specific determinants of resting energy expenditure to create a predictive energy equation that more precisely establishes energy needs with the intent of preventing protein-energy wasting. MATERIALS AND METHODS: For this 3-year multisite cross-sectional study (N = 116), eligible participants were diagnosed with chronic kidney disease and were receiving MHD for at least 3 months. Predictors for the model included weight, sex, age, C-reactive protein (CRP), glycosylated hemoglobin, and serum creatinine. The outcome variable was measured resting energy expenditure (mREE). Regression modeling was used to generate predictive formulas and Bland-Altman analyses to evaluate accuracy. RESULTS: The majority were male (60.3%), black (81.0%), and non-Hispanic (76.7%), and 23% were ≥65 years old. After screening for multicollinearity, the best predictive model of mREE (R2 = 0.67) included weight, age, sex, and CRP. Two alternative models with acceptable predictability (R2 = 0.66) were derived with glycosylated hemoglobin or serum creatinine. Based on Bland-Altman analyses, the maintenance hemodialysis equation that included CRP had the best precision, with the highest proportion of participants' predicted energy expenditure classified as accurate (61.2%) and with the lowest number of individuals with underestimation or overestimation. CONCLUSIONS: This study confirms disease-specific factors as key determinants of mREE in patients on MHD and provides a preliminary predictive energy equation. Further prospective research is necessary to test the reliability and validity of this equation across diverse populations of patients who are receiving MHD.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diálisis Renal / Metabolismo Energético / Insuficiencia Renal Crónica Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: JPEN J Parenter Enteral Nutr Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Diálisis Renal / Metabolismo Energético / Insuficiencia Renal Crónica Tipo de estudio: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: JPEN J Parenter Enteral Nutr Año: 2018 Tipo del documento: Article País de afiliación: Estados Unidos
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