Katherine Meadows1, Richard Gibbens2, Caroline Gerrard3, Alain Vuylsteke3. 1. School of Clinical Medicine, University of Cambridge, Cambridge, UK. Electronic address: k.e.meadows@cantab.net. 2. Computer Laboratory, University of Cambridge, Cambridge, UK. 3. Papworth Hospital NHS Foundation Trust, Cambridge, UK.
Abstract
OBJECTIVE: The aim of this study was to develop a statistical model based on patient parameters to predict the length of stay (LOS) in the intensive care unit (ICU) following cardiac surgery in a single center. DESIGN: Data were collected from patients admitted to the ICU following cardiac surgery over a 10-year period (2006-2016). Both the additive and logistic EuroSCORE were calculated, and logistic regression analysis was carried out to formulate a model relating the predicted LOS to the EuroSCORE. This model was used to stratify patients into short stay (less than 48 hours) or long stay (more than 48 hours). SETTING: ICU at Papworth Hospital, Cambridgeshire. PARTICIPANTS: A total of 18,377 consecutive patients who had been in ICU following cardiac surgery (coronary graft bypass surgery, valve surgery, or a combination of both). INTERVENTIONS: This was an observational study. MEASUREMENTS AND MAIN RESULTS: The authors have shown that both the additive and logistic EuroSCORE can be used to stratify cardiac surgical patients in various predicted LOS in ICU. Further adjustments can be made to increase the number of patients correctly identified as either short stay or long stay. Comparison of the model predictions to the data demonstrated a high overall accuracy of 79.77%, and receiver operating characteristic curve analysis showed the area under the curve to be 0.7296. CONCLUSION: This analysis of an extensive data set shows that patient LOS in ICU after cardiac surgery in a single center can be predicted accurately using the simple cardiac operative risk scoring tool EuroSCORE. Using such predictions has the potential to improve ICU resource management. Crown
OBJECTIVE: The aim of this study was to develop a statistical model based on patient parameters to predict the length of stay (LOS) in the intensive care unit (ICU) following cardiac surgery in a single center. DESIGN: Data were collected from patients admitted to the ICU following cardiac surgery over a 10-year period (2006-2016). Both the additive and logistic EuroSCORE were calculated, and logistic regression analysis was carried out to formulate a model relating the predicted LOS to the EuroSCORE. This model was used to stratify patients into short stay (less than 48 hours) or long stay (more than 48 hours). SETTING: ICU at Papworth Hospital, Cambridgeshire. PARTICIPANTS: A total of 18,377 consecutive patients who had been in ICU following cardiac surgery (coronary graft bypass surgery, valve surgery, or a combination of both). INTERVENTIONS: This was an observational study. MEASUREMENTS AND MAIN RESULTS: The authors have shown that both the additive and logistic EuroSCORE can be used to stratify cardiac surgical patients in various predicted LOS in ICU. Further adjustments can be made to increase the number of patients correctly identified as either short stay or long stay. Comparison of the model predictions to the data demonstrated a high overall accuracy of 79.77%, and receiver operating characteristic curve analysis showed the area under the curve to be 0.7296. CONCLUSION: This analysis of an extensive data set shows that patient LOS in ICU after cardiac surgery in a single center can be predicted accurately using the simple cardiac operative risk scoring tool EuroSCORE. Using such predictions has the potential to improve ICU resource management. Crown
Authors: Paweł Czub; Andrzej Cacko; Monika Gawałko; Emanuel Tataj; Jakub Poliński; Kacper Pawlik; Romuald Cichoń; Piotr Hendzel Journal: Medicine (Baltimore) Date: 2018-12 Impact factor: 1.817