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      Desarrollo de una herramienta estructurada y un sistema de puntuación para detectar pacientes clínicos con alta necesidad de seguimiento farmacoterapéutico exhaustivo: presentación inicial Translated title: Development of a structured tool and scoring system to detect clinical patients with a high need for exhaustive pharmacotherapeutic follow-up: initial presentation

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          Abstract

          Resumen Objetivos: Analizar y validar los resultados obtenidos con una herramienta para la selección de pacientes clínicos con alta necesidad de seguimiento farmacoterapéutico exhaustivo. Presentar y evaluar un sistema de puntuación en base a factores predisponentes. Métodos: Estudio prospectivo, transversal, observacional y monocéntrico. Se analizaron y validaron los resultados de la herramienta de selección, a partir de los datos extraídos de la historia clínica de ingreso del paciente. Se recabaron datos demográficos y se calculó el porcentaje de selección de la herramienta, el tiempo de estancia, los reingresos y la muerte de los pacientes incluidos. Se construyó un sistema de puntuación a partir del odds ratio de las variables sexo, edad y tipo de ingreso al hospital. Resultados: La herramienta dividió en partes iguales a los pacientes con alta y baja necesidad de seguimiento farmacoterapéutico exhaustivo. Se observó que la edad de los pacientes en el primer grupo, así como también su estancia, cantidad de reingresos y eventos de muerte, era significativamente mayor en comparación con el grupo de baja necesidad. La edad avanzada, el sexo masculino y el ingreso de tipo clínico serían factores predisponentes, en la muestra de estudio, para la alta necesidad de seguimiento farmacoterapéutico. Conclusiones: La herramienta propuesta demostró poseer potencial clínico y operativo para ser implementada. Se construyó un sistema de puntuación teniendo en cuenta el peso de las variables sexo masculino, edad avanzada e ingreso de tipo clínico, el cual mostró resultados similares a los de la herramienta.

          Translated abstract

          Summary Objetives: Analyze and validate the results obtained with a tool for the selection of clinical patients with a high need for exhaustive pharmacotherapeutic follow-up. Present and evaluate a scoring system based on predisposing factors. Methods: Prospective, cross-sectional, observational and monocentric study. The results of the tool were analyzed and validated, based on the data extracted from the patient's admission medical history. Demographic data were collected and the percentage of tool selection, length of stay, readmissions, and death of the included patients were calculated. A scoring system was constructed based on the adds ratio of the variables sex, age and type of hospital admission. Results: The tool divides patients with high and low need for exhaustive pharmacotherapeutic follow-up equally. It was observed that the age of patients in the first group, as well as their stay, number of readmissions, and death events, were significantly higher compared to the low need group. Advanced age, male sex, and clinical admission would be predisposing factors, in the study sample, for exhaustive pharmacotherapeutic follow-up. Conclusions: The proposed tool proved to have clinical and operational potential to be implemented. A scoring system was built with the corresponding weights for the variables male sex, advanced age and clinical admission, which showed results similar to the tool ones.

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          Predictive performance of renal function equations for patients with chronic kidney disease and normal serum creatinine levels.

          Accurate renal function measurements are important for the diagnosis and treatment of kidney disease, proper medication dosing, interpretation of possible uremic symptoms, and decision-making regarding when to initiate renal replacement therapy. Because the use of highly accurate filtration markers to measure renal function has traditionally been limited by cumbersome and costly techniques and the involvement of radioactivity (among other factors), renal function is typically estimated by using specially derived prediction equations. These formulae usually use serum creatinine levels, i.e., a marker of filtration that is insensitive to mild/moderate decreases in GFR. Although attempts have been made to validate certain renal function prediction equations among patients with chronic kidney disease (CKD) with abnormal serum creatinine levels, this is the first study to specifically evaluate the predictive performance of these equations for patients with CKD and serum creatinine levels in the normal range. The results of eight prediction equations for 109 patients with CKD and serum creatinine levels of < or =1.5 mg/dl were compared with standard iohexol GFR values. The most accurate results were obtained with the Cockroft-Gault and Bjornsson equations. The most precise formulae were the Modification of Diet in Renal Disease Study equations, although they were highly biased. Even the most accurate results exhibited levels of error that made them suboptimal for clinical treatment of these patients. These results suggest that measurement of GFR with endogenous or exogenous filtration markers might be the most prudent strategy for the assessment of renal function in the CKD population with normal serum creatinine levels. Further studies are needed to confirm the generalizability of these findings for this patient subgroup.
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            Acute Kidney Injury Network. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury

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              Is Open Access

              MONITORIZACIÓN TERAPÉUTICA DE FÁRMACOS Y ASPECTOS PRÁCTICOS DE FARMACOCINÉTICA

                Author and article information

                Journal
                ofil
                Revista de la OFIL
                Rev. OFIL·ILAPHAR
                Organización de Farmacéuticos Ibero-Latinoamericanos (Madrid, Madrid, Spain )
                1131-9429
                1699-714X
                March 2022
                : 32
                : 1
                : 51-56
                Affiliations
                [1] Buenos Aires orgnameUniversidad de Buenos Aires orgdiv1Farmacia Clínica orgdiv2Servicio de Farmacia Argentina
                [3] Buenos Aires orgnameUniversidad de Buenos Aires orgdiv1Laboratorio de Citostáticos y Laboratorio de Formulaciones Magistrales orgdiv2Servicio de Farmacia Argentina
                [2] Buenos Aires orgnameUniversidad de Buenos Aires orgdiv1Farmacéutica Clínica orgdiv2Servicio de Farmacia Argentina
                Article
                S1699-714X2022000100009 S1699-714X(22)03200100009
                10.4321/s1699-714x2022000100009
                ea414bc6-5f01-44e3-b8e0-7c27dbb6c50f

                This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

                History
                : 04 August 2020
                : 22 September 2020
                Page count
                Figures: 0, Tables: 0, Equations: 0, References: 7, Pages: 6
                Product

                SciELO Spain

                Categories
                Originales

                Pharmacotherapeutic follow-up,algoritmo,factores predisponentes,farmacia clínica,paciente clínico,Seguimiento farmacoterapéutico,algorithm,predisposing factors,clinical pharmacy,clinical patient

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