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Predictors of Prolonged Stay in the Intensive Care Unit following Cardiac Surgery

The prediction of intensive care unit length of stay (ICU-LOS) could contribute to more efficient ICU resources' allocation and better planning of care among cardiac surgery patients. The aim of this study was to identify the preoperative and intraoperative predictors for prolonged cardiac surg...

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Detalles Bibliográficos
Autores principales: Eltheni, Rokeia, Giakoumidakis, Konstantinos, Brokalaki, Hero, Galanis, Petros, Nenekidis, Ioannis, Fildissis, George
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Scholarly Research Network 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394383/
https://www.ncbi.nlm.nih.gov/pubmed/22919512
http://dx.doi.org/10.5402/2012/691561
Descripción
Sumario:The prediction of intensive care unit length of stay (ICU-LOS) could contribute to more efficient ICU resources' allocation and better planning of care among cardiac surgery patients. The aim of this study was to identify the preoperative and intraoperative predictors for prolonged cardiac surgery ICU-LOS. An observational cohort study was conducted among 150 consecutive patients, who were admitted to the cardiac surgery ICU of a tertiary hospital of Athens, Greece from September 2010 to January 2011. Multivariate regression analysis revealed that patients with increased creatinine levels preoperatively (odds ratio (OR) 3.0, P = 0.049), history of atrial fibrillation (AF) (OR 6.3, P = 0.012) and high EuroSCORE values (OR 2.6, P = 0.017) had a significant greater probability to stay in the ICU for more than 2 days. In addition, intraoperative hyperglycemia (OR 3.0, P = 0.004) was strongly associated with longer ICU-LOS. In conclusion, the high perioperative risk, the history of AF and renal dysfunction, and the intraoperative hyperglycemia are significant predictors of prolonged ICU stay. The early identification of patients at risk could allow the efficient ICU resources' allocation and the reduction of healthcare costs. This would contribute to nursing care planning depending on the availability of healthcare personnel and ICU bed capacity.