IFIBIO HOUSSAY   25014
INSTITUTO DE FISIOLOGIA Y BIOFISICA BERNARDO HOUSSAY
Unidad Ejecutora - UE
congresos y reuniones científicas
Título:
A multivariate relationship between laboratory data during the evolution of typical Hemolytic Uremic Syndrome children population
Autor/es:
CASAL, JJ; PORPORATO, M; ZOTTA, E; IBARRA, C
Reunión:
Congreso; REUNIÓN DE SOCIEDADES DE BIOCIENCIAS 2020; 2020
Resumen:
Hemolytic uremic syndrome (HUS) is a systemic disease characterized by variable degrees of acute nephropathy, thrombocytopenia and microangiopathic hemolytic anemia. Laboratory and clinical parameters contribute very closely to progression of HUS. To better understand HUS evolution, the association between a set of laboratory data and a set of clinical parameters of a HUS population isinvestigated in this study.We conducted a retrospective study of patients (n = 20) attended with diagnosis of typical HUS in the Pediatric Service of the Hospital Posadas from January 2012 to July 2020. 70% were women, with a mean age of 2.19 year. All laboratory data including those from the emergency department (admission), hospitalization, up to the first post-discharge check-up by external clinics were standardized in innovative report formats.We perform the graphical representation of the evolution over time of several of the important clinical parameters (creatinine, hematocrit, hemoglobin, among others). We find the creatinine curve relevant with well-defined moments in its evolution: rise, plateau and decline. We emphasize that 50% of the patients present a similar descent slope (- 0.353 +/- 0.022 mg/dL/day) regardless of the maximum value reached by creatinine. Also, analytic platform KNIME was used to evaluate the multivariate relationship between laboratory data and the evolution plasma creatinine values. We observed a strong correlation between the plasma values of creatinine-urea (positive, r = 0,818), platelets-uric acid (negative, r = 0,610) and direct bilirubin-uric acid (positive r = 0,735).The study should be complemented with the comparison of qualitative variables, as well as with new parameters such as albuminuria, podocyturia, etc.), in order to generate a model of prediction of patient evolution during the acute period of HUS the disease and after it.