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Proteinuria impacts patient survival differentially based on clinical setting: A retrospective cross-sectional analysis of cohorts from a single health system: Retrospective cohort study

BACKGROUND: Chronic kidney disease (CKD) staging is improved by adding proteinuria to glomerular filtration rate (GFR). While proteinuria independently predicts CKD progression and mortality, the clinical setting of proteinuria determination has not been well-studied previously. The objective of our...

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Detalles Bibliográficos
Autores principales: Bezinque, Adam, Parker, Jessica, Babitz, Stephen K., Noyes, Sabrina L., Hu, Susie, Lane, Brian R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6702410/
https://www.ncbi.nlm.nih.gov/pubmed/31452879
http://dx.doi.org/10.1016/j.amsu.2019.07.029
Descripción
Sumario:BACKGROUND: Chronic kidney disease (CKD) staging is improved by adding proteinuria to glomerular filtration rate (GFR). While proteinuria independently predicts CKD progression and mortality, the clinical setting of proteinuria determination has not been well-studied previously. The objective of our study is to determine whether clinical setting differentially impacts survival outcomes. METHODS: Kaplan-Meier and Cox proportional hazards analyses of overall survival were performed retrospectively for cohorts of outpatients (n = 22,918), emergency patients (n = 16,861), and inpatients (n = 12,304) subjected to urinalysis (UA) at a single health system in 2010. GFR (G1-G5) and proteinuria (A1:<30 mg, A2:30–300 mg, A3:>300 mg) were classified under Kidney Disease: Improving Global Outcomes (KDIGO) guidelines. RESULTS: GFR and proteinuria levels varied more in inpatients than in emergency and outpatients. For each clinical population, survival significantly decreased with increasing proteinuria (A1>A2>A3, p < 0.05 for each comparison). The effect of proteinuria on survival differed by clinical setting, with statistical differences in all categories other than A3 in outpatients and emergency patients (p = 0.98). The strongest predictors of mortality were cancer diagnosis (HR: 3.07, p < 0.0001) and very-high KDIGO classification (HR: 2.01, p < 0.0001). Limitations include the retrospective observational study design and single health system analysis. CONCLUSIONS: The value of UA to screen for proteinuria in each clinical setting is evident, but the impact of A2 and A3 level proteinuria on survival varies depending on the clinical scenario in which the determination was made. The clinical setting of proteinuria measurement should be factored into both patient care and clinical research activities.