Outcome Prediction in a Surgical ICU Using Automatically Calculated SAPS II Scores
نویسندگان
چکیده
منابع مشابه
comparison between saps 3 and APACHE ii in surgical patients admitted to a brazilian ICU
Objectives The aim of this study was to compare the discriminatory power of two prognostic scores, SAPS 3 and APACHE II, in surgical patients. Methods Retrospectively collected data from all surgical patients admitted to a Brazilian hospital ICU between January 2011 and December 2013 were analyzed. The standardized mortality ratio (SMR) was computed for mortality prediction. The predictive abil...
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introduction: using physiologic scoring systems for identifying high-risk patients for mortality has been considered recently. this study was designed to evaluate the values of acute physiology and chronic health evaluation ii (apache ii) and simplified acute physiologic score (saps ii) models in prediction of 1-month mortality of critically ill patients. methods: the present prospective cross ...
متن کاملComparison of APACHE II and SAPS II Scoring Systems in Prediction of Critically Ill Patients’ Outcome
INTRODUCTION Using physiologic scoring systems for identifying high-risk patients for mortality has been considered recently. This study was designed to evaluate the values of Acute Physiology and Chronic Health Evaluation II (APACHE II) and Simplified Acute Physiologic Score (SAPS II) models in prediction of 1-month mortality of critically ill patients. METHODS The present prospective cross ...
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BACKGROUND The aim of the Simplified Acute Physiology Score (SAPS) II and SAPS 3 is to predict the mortality of patients admitted to intensive care units (ICUs). Previous studies have suggested that the calibration of these scores may vary across countries, centers, and/or characteristics of patients. In the present study, we aimed to assess determinants of the calibration of these scores. ME...
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Exponential surge in health care data, such as longitudinal data from electronic health records (EHR), sensor data from intensive care unit (ICU), etc., is providing new opportunities to discover meaningful data-driven characteristics and patterns ofdiseases. Recently, deep learning models have been employedfor many computational phenotyping and healthcare prediction tasks to achieve state-of-t...
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ژورنال
عنوان ژورنال: Anaesthesia and Intensive Care
سال: 2003
ISSN: 0310-057X,1448-0271
DOI: 10.1177/0310057x0303100509