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1.
Am J Nephrol ; 2024 Jun 18.
Artículo en Inglés | MEDLINE | ID: mdl-38889694

RESUMEN

INTRODUCTION: Acute kidney injury (AKI) requiring treatment with renal replacement therapy (RRT) is a common complication after admission to an intensive care unit (ICU) and is associated with significant morbidity and mortality. However, the prevalence of RRT use and the associated outcomes in critically patients across the globe are not well described. Therefore, we describe the epidemiology and outcomes of patients receiving RRT for AKI in ICUs across several large health system jurisdictions. METHODS: Retrospective cohort analysis using nationally representative and comparable databases from seven health jurisdictions in Australia, Brazil, Canada, Denmark, New Zealand, Scotland, and the United States (USA) between 2006-2023, depending on data availability of each dataset. Patients with history of end-stage kidney disease receiving chronic RRT and patients with a history of renal transplant were excluded. RESULTS: A total of 4,104,480 patients in the ICU cohort and 3,520,516 patients in the mechanical ventilation cohort were included. Overall, 156,403 (3.8%) patients in the ICU cohort and 240,824 (6.8%) patients in the mechanical ventilation cohort were treated with RRT for AKI. In the ICU cohort, the proportion of patients treated with RRT was lowest in Australia and Brazil (3.3%) and highest in Scotland (9.2%). The in-hospital mortality for critically ill patients treated with RRT was almost four-fold higher (57.1%) than those not receiving RRT (16.8%). The mortality of patients treated with RRT varied across the health jurisdictions from 37-65%. CONCLUSION: The outcomes of patients who receive RRT in ICUs throughout the world vary widely. Our research suggests differences in access to and provision of this therapy are contributing factors.

2.
Intensive Care Med ; 45(11): 1599-1607, 2019 11.
Artículo en Inglés | MEDLINE | ID: mdl-31595349

RESUMEN

PURPOSE: To study whether ICU staffing features are associated with improved hospital mortality, ICU length of stay (LOS) and duration of mechanical ventilation (MV) using cluster analysis directed by machine learning. METHODS: The following variables were included in the analysis: average bed to nurse, physiotherapist and physician ratios, presence of 24/7 board-certified intensivists and dedicated pharmacists in the ICU, and nurse and physiotherapist autonomy scores. Clusters were defined using the partition around medoids method. We assessed the association between clusters and hospital mortality using logistic regression and with ICU LOS and MV duration using competing risk regression. RESULTS: Analysis included data from 129,680 patients admitted to 93 ICUs (2014-2015). Three clusters were identified. The features distinguishing between the clusters were: the presence of board-certified intensivists in the ICU 24/7 (present in Cluster 3), dedicated pharmacists (present in Clusters 2 and 3) and the extent of nurse autonomy (which increased from Clusters 1 to 3). The patients in Cluster 3 exhibited the best outcomes, with lower adjusted hospital mortality [odds ratio 0.92 (95% confidence interval (CI), 0.87-0.98)], shorter ICU LOS [subhazard ratio (SHR) for patients surviving to ICU discharge 1.24 (95% CI 1.22-1.26)] and shorter durations of MV [SHR for undergoing extubation 1.61(95% CI 1.54-1.69)]. Cluster 1 had the worst outcomes. CONCLUSION: Patients treated in ICUs combining 24/7 expert intensivist coverage, a dedicated pharmacist and nurses with greater autonomy had the best outcomes. All of these features represent achievable targets that should be considered by policy makers with an interest in promoting equal and optimal ICU care.


Asunto(s)
Mortalidad Hospitalaria/tendencias , Admisión y Programación de Personal/normas , Aprendizaje Automático no Supervisado/tendencias , Brasil , Análisis por Conglomerados , Capacidad de Camas en Hospitales/estadística & datos numéricos , Humanos , Unidades de Cuidados Intensivos/organización & administración , Unidades de Cuidados Intensivos/estadística & datos numéricos , Tiempo de Internación/estadística & datos numéricos , Tiempo de Internación/tendencias , Modelos Logísticos , Enfermeras y Enfermeros/estadística & datos numéricos , Enfermeras y Enfermeros/provisión & distribución , Oportunidad Relativa , Puntuaciones en la Disfunción de Órganos , Admisión y Programación de Personal/clasificación , Admisión y Programación de Personal/estadística & datos numéricos , Fisioterapeutas/estadística & datos numéricos , Fisioterapeutas/provisión & distribución , Médicos/estadística & datos numéricos , Médicos/provisión & distribución , Estudios Retrospectivos , Factores de Tiempo
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