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1.
Nefrología (Madrid) ; 39(4): 379-387, jul.-ago. 2019. graf, tab
Artigo em Inglês | IBECS | ID: ibc-189759

RESUMO

BACKGROUND AND AIMS: Acute kidney injury (AKI) is associated with higher mortality and length of stay (LOS) for hospitalized patients. To improve outcomes, an electronic detection system could be a useful tool for early diagnosis. METHODS: A fully automated real-time system for detecting decreased glomerular filtration rate in adult patients was developed in our hospital, DETECT-H project. AKI was established according to KDIGO guidelines. RESULTS: In six months, 1241 alerts from 11,022 admissions were issued. Overall incidence of AKI was 7.7%. Highest AKI stage reached was: stage 1 (49.8%), 2 (24.5%) and 3 (25.8%), in-hospital mortality was 10.9%, 22.7%, 33.9% respectively and 57.1% in AKI requiring dialysis; mortality in stable CKD was 4.3%. Median LOS was 8 days versus 5 days for all patients. AKI was associated with a mortality of 3.18 (95% CI 1.80-5.59) and a LOS 1.52 (1.11-2.08) times as high as that for admissions without AKI. Multivariate analysis indicated that a LOS higher than 8 days was associated with AKI. Previous CKD was noted in 31.9% and AKI in 45.3% at discharge. As compared to the use of the detect system, only one third of CKD patients and half of AKI episodes were identified. CONCLUSIONS: CKD and in-hospital AKI are under-recognized entities. Mortality and LOS are increased in-hospital patients with renal dysfunction. AKI severity was associated with higher mortality and LOS. An automated electronic detection system for identifying renal dysfunction would be a useful tool to improve renal outcomes


INTRODUCCIÓN Y OBJETIVOS: El fracaso renal agudo (FRA) aumenta la mortalidad y la estancia hospitalarias (EH). El empleo de sistemas de detección electrónica podría ser una herramienta beneficiosa para mejorar estos resultados. MÉTODOS: Se desarrolló un sistema de detección automático a tiempo real de pacientes ingresados con función renal alterada, denominado proyecto DETECT-H. El FRA se estableció de acuerdo con las guías KDIGO. RESULTADOS: En 6 meses, 1.241 alertas fueron recogidas de 11.022 ingresos. La incidencia global del FRA fue del 7,7%. La distribución en función del estadio máximo del FRA alcanzado fue: estadio 1: 49,8%, estadio 2: 24,5% y estadio 3: 25,8%; con una mortalidad hospitalaria del 10,9, 22,7 y 33,9%, respectivamente. En el caso del FRA con necesidad de diálisis fue del 57,1%. La mortalidad en pacientes con enfermedad renal crónica (ERC) estable fue del 4,3%. La mediana de EH en pacientes detectados fue 8 vs. 5 días para todos los pacientes hospitalizados. El FRA se asoció con una mortalidad 3,18 (1,8-5,59) y una EH 1,52 (1,11-2,08) veces superior que aquellos ingresos sin FRA. El análisis multivariante indicó que el FRA se asociaba con la EH > 8 días. En los informes de alta, la presencia de ERC previa solo fue registrada en el 31,9% de los pacientes con ERC y el FRA hospitalario en el 45,3%. Conclusiones : La ERC y el FRA intrahospitalario son entidades infradiagnosticadas. La mortalidad y la EH están aumentadas en pacientes con disfunción renal. La gravedad del FRA se asoció con mayor mortalidad y EH. Un sistema de detección automático para identificarlos podría ser útil para mejorar estos resultados


Assuntos
Humanos , Masculino , Feminino , Idoso , Idoso de 80 Anos ou mais , Injúria Renal Aguda/diagnóstico , Monitorização Fisiológica/instrumentação , Injúria Renal Aguda/mortalidade , Sistemas Computacionais , Diagnóstico Precoce , Hospitalização , Estudos Retrospectivos , Tempo de Internação
2.
Nefrologia (Engl Ed) ; 39(4): 379-387, 2019.
Artigo em Inglês, Espanhol | MEDLINE | ID: mdl-30558814

RESUMO

BACKGROUND AND AIMS: Acute kidney injury (AKI) is associated with higher mortality and length of stay (LOS) for hospitalized patients. To improve outcomes, an electronic detection system could be a useful tool for early diagnosis. METHODS: A fully automated real-time system for detecting decreased glomerular filtration rate in adult patients was developed in our hospital, DETECT-H project. AKI was established according to KDIGO guidelines. RESULTS: In six months, 1241 alerts from 11,022 admissions were issued. Overall incidence of AKI was 7.7%. Highest AKI stage reached was: stage 1 (49.8%), 2 (24.5%) and 3 (25.8%), in-hospital mortality was 10.9%, 22.7%, 33.9% respectively and 57.1% in AKI requiring dialysis; mortality in stable CKD was 4.3%. Median LOS was 8 days versus 5 days for all patients. AKI was associated with a mortality of 3.18 (95% CI 1.80-5.59) and a LOS 1.52 (1.11-2.08) times as high as that for admissions without AKI. Multivariate analysis indicated that a LOS higher than 8 days was associated with AKI. Previous CKD was noted in 31.9% and AKI in 45.3% at discharge. As compared to the use of the detect system, only one third of CKD patients and half of AKI episodes were identified. CONCLUSIONS: CKD and in-hospital AKI are under-recognized entities. Mortality and LOS are increased in-hospital patients with renal dysfunction. AKI severity was associated with higher mortality and LOS. An automated electronic detection system for identifying renal dysfunction would be a useful tool to improve renal outcomes.


Assuntos
Injúria Renal Aguda/diagnóstico , Monitorização Fisiológica/instrumentação , Injúria Renal Aguda/mortalidade , Idoso , Idoso de 80 Anos ou mais , Sistemas Computacionais , Diagnóstico Precoce , Feminino , Hospitalização , Humanos , Tempo de Internação , Masculino , Estudos Retrospectivos
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