Currently, many critical care indices are not captured automatically at a granular level, rather are repetitively assessed by overburdened nurses. In this pilot study, we examined the feasibility of using pervasive sensing technology and artificial intelligence for autonomous and granular monitoring in the Intensive Care Unit (ICU). As an exemplary prevalent condition, we characterized delirious patients and their environment. We used wearable sensors, light and sound sensors, and a camera to collect data on patients and their environment. We analyzed collected data to detect and recognize patient’s face, their postures, facial action units and expressions, head pose variation, extremity movements, sound pressure levels, light intensity level, and visitation frequency. We found that facial expressions, functional status entailing extremity movement and postures, and environmental factors including the visitation frequency, light and sound pressure levels at night were significantly different between the delirious and non-delirious patients. Our results showed that granular and autonomous monitoring of critically ill patients and their environment is feasible using a noninvasive system, and we demonstrated its potential for characterizing critical care patients and environmental factors.
Introduction: Delirium is a common post-operative complication in critically ill patients, displaying transient changes in consciousness, inattention, awareness, and organized thought. Not a lot is known about the specific causes of this condition, as it is a complex physiologic state that is currently being unraveled to determine any correlation with imbalances in homeostasis. Objective: The aim of this systematic review is to report on and summarize risk factors associated with the development of postoperative delirium in critically ill adult patients. Methods: This systematic review assessed studies reporting on risk factors for postoperative delirium in critically ill patients. PubMed, PsycINFO, and CINAHL databases were searched for studies. Observational or interventional studies reviewing predictors for postoperative delirium in delirious versus non-delirious patients were included. Results: Fifty-one potential risk factors were identified and divided into eight subgroups. The significance of a specific risk factor for postoperative delirium was found to depend on the patient population in question, but consistently cited significant risk factors across cohorts included high mortality risk, abnormal laboratory values, and use of vasopressors, analgesics, thiopentones, propofol, and benzodiazepines. There was not enough evidence found to definitively state the significance of type of surgery being performed or cognitive impairment on development of this condition. Conclusion: Several risk factors were found to be significantly associated with the development of postoperative delirium, including high risk of mortality, specific medication use, and abnormal laboratory values. Further research needs to be performed to fully define the importance of these individual risk factors across broad critical care population.
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