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Integrating Clinical Physiological Knowledge at the Feature and Classifier Levels in Design of a Clinical Decision Support System for Improved Prediction of Intensive Care Unit Outcome
Published in Ervin Sejdić, Tiago H. Falk, Signal Processing and Machine Learning for Biomedical Big Data, 2018
Ali Jalali, Vinay M. Nadkarni, Robert A. Berg, Mohamed Rehman, C. Nataraj
Patients in the intensive care unit (ICU) are among the most critically ill patients in any hospital. For example, approximately 200,000 in-hospital cardiac arrests occur in the United States each year, and only 20% of these patients survive to discharge. In-hospital cardiac arrest is frequently preceded by early warning signs of clinical deterioration that can be recognized and treated by trained in-hospital staff. Those at higher risk (of cardiac arrest, for example) would be in immediate need for extensive monitoring and direct attention from healthcare providers [1]. The implementation of early warning scores leads to improved recognition and treatment of clinical deterioration in hospitalized patients in the general wards. Hence, evaluation of critical deterioration risk for ICU patients has drawn much interest from healthcare providers due to its importance in saving patients’ lives [2–6]. Most of the clinically based studies have focused on providing simple scores that focus on the severity of disease or illness [7]. Basically, these scores add weights to the degree of abnormality of an organ or a disease based on the vital sign measurement, blood gas measurement, or visual inspection of the patients, and attempt to identify patients at high risk. Some of the currently available acuity scores are Acute Physiology and Chronic Health Evaluation (APACHE) III [8], Simplified Acute Physiology Score (SAPS) II [9], Modified Early Warning Scoring (MEWS) [10], Mortality Probability Models (MPM) [11], and Sequential Organ Failure (SOFA) score [12].
Injury Scoring Systems and Injury Classification
Published in Melanie Franklyn, Peter Vee Sin Lee, Military Injury Biomechanics, 2017
Melanie Franklyn, Christine Read-Allsopp
First proposed by Knaus et al. (1981), the Acute Physiology and Chronic Health Evaluation (APACHE) is a severity of illness classification used for predicting mortality in patients admitted to an Intensive Care Unit (ICU). It was revised in 1985 and renamed APACHE II (Knaus et al. 1985). The APACHE II is based on the patient’s age, 12 routine physiological measurements and any pre-existing disease of the patient. The score, which is calculated daily and can be used to evaluate the progress of the patient during their ICU stay, ranges from 0 to 71, with higher scores corresponding to more severe disease and a higher risk of death. The system was again revised in 1991 (Knaus et al. 1991) to become the APACHE III, with both APACHE II and III used in the literature and clinical settings.
Evaluation of gastric emptying in critically ill patients using electrical impedance method: a pilot study
Published in Journal of Medical Engineering & Technology, 2022
Ariful Basher, Mohammad Moniruzzaman, Md. Maruful Islam, Md. Mahbubur Rashid, Iqbal Hossain Chowdhury, Akhtaruzzaman AKM, Khondkar Siddique-e Rabbani
Delayed gastric emptying seemed to be associated with the severity of illness. According to APACHE II score, an indicator of illness severity related to mortality, the observed median value was 25 correlating well with the mortality of 45%. It was found that some components of APACHE II like increased temperature, haematocrit (Hct), mean arterial pressure (MAP), serum creatinine, and high Fraction of inspired oxygen (FiO2) had a more common and strong relationship with delayed gastric emptying (Table 2).