Quantifying agitation in sedated ICU patients using heart rate and blood pressure

Modeling and mobile home monitoring of behavioral and psychological symptoms of dementia (BPSD)

With the increasing global aging population, dementia care has rapidly become a major social problem. Current diagnosis of Behavior and Psychological Symptoms of Dementia (BPSD) relies on clinical interviews, and behavioral rating scales based on a period of behavior observation, but these methods are not suitable for identification of occurrence of BPSD in the daily living, which is necessary for providing appropriate interventions for dementia, though, has been studied by few research groups in the literature. To address these issues, in this study developed a BPSD monitoring system consisting of a Psycho-Cognitive (PsyCo) BPSD model, a Behavior-Physio-Environment (BePhyEn) BPSD model, and an implementation platform. The PsyCo BPSD model provides BPSD assessment support to caregivers and care providers, while the BePhyEn BPSD model provides instantaneous alerts for BPSD enabled by a 24-hour home monitoring platform for early intervention, and thereby alleviation of burden to patients and caregivers. Data for acquiring the models were generated through extensive literature review and regularity determined. A mobile robot was utilized as the implementation platform for improving sensitivity of sensors for home monitoring, and elderly individual following algorithms were investigated. Experiments in a virtual home environment showed that, a virtual BPSD elderly individual can be followed safely by the robot, and BPSD occurrence could be identified accurately, demonstrating the possibility of modeling and identification of BPSD in home environment.

Assessment of Leg Massage on Hemodynamic Parameters of Intensive Care Patients: A Parallel Single-Blinded Randomized Controlled Trial

Objective

We aimed to determine the effectiveness of leg massage by a nurse and patients' families on hemodynamic parameters in patients admitted to intensive care units.

Methods

This parallel single-blinded randomized clinical trial involved 75 patients admitted to the intensive care units at Shahid Bahonar Hospital in Kerman, Iran. Patients were assigned to 3 groups by the minimization method (massage by a nurse, massage by the patient's family, and the control group). Swedish massage was used on both legs (each leg for 5 minutes) once a day for 6 days, and the hemodynamic parameters of patients were measured before intervention, at the end of intervention, and 1 week later.

Results

The results showed that mean arterial pressure decreased in all 3 groups 1 week after intervention, which was not statistically significant. Mean heart rate also decreased in all 3 groups 1 week after intervention, which was statistically significant except for massage by family. Mean arterial oxygen saturation significantly decreased in all 3 groups 1 week after intervention but remained normal. The 3 hemodynamic parameters did not differ significantly among the 3 groups.

Conclusion

According to the results of this study, the use of massage has no effect on hemodynamic parameters.

A primer on artificial intelligence for the paediatric cardiologist

The combination of pediatric cardiology being both a perceptual and a cognitive subspecialty demands a complex decision-making model which makes artificial intelligence a particularly attractive technology with great potential. The prototypical artificial intelligence system would autonomously impute patient data into a collaborative database that stores, syncs, interprets and ultimately classifies the patient's profile to specific disease phenotypes to compare against a large aggregate of shared peer health data and outcomes, the current medical body of literature and ongoing trials to offer morbidity and mortality prediction, drug therapy options targeted to each patient's genetic profile, tailored surgical plans and recommendations for timing of sequential imaging. The focus of this review paper is to offer a primer on artificial intelligence and paediatric cardiology by briefly discussing the history of artificial intelligence in medicine, modern and future applications in adult and paediatric cardiology across selected concentrations, and current barriers to implementation of these technologies.

Non-contact monitoring of agitation and use of a sheltering device in patients with dementia in emergency departments: a feasibility study

BACKGROUND

Agitation is common in geriatric patients with cognitive impairment, e.g. in persons with dementia (PWD), who are admitted to an emergency department (ED). It might be a first sign of upcoming delirium and is associated with a higher risk of an unfavorable clinical course. Hence, monitoring of vital signs and enhanced movement as indicators of upcoming agitation is essential in these patients during their stay in the ED. Since PWD rarely tolerate fixed monitoring devices, a novel developed non-contact monitoring system (NCMSys) might represent an appropriate alternative. Aim of this feasibility study was to test the validity of a NCMSys and of the tent-like "Charité Dome" (ChD), aimed to shelter PWD from the busy ED environment. Furthermore, effects of the ChD on wellbeing and agitation of PWD were investigated.

METHODS

Both devices were attached to patient's bed. Tests on technical validity and safety issues of NCMSys and ChD were performed at the iDoc institute with six healthy volunteers. A feasibility study evaluating the reliability of the NCMSys with and without the ChD was performed in the real-life setting of an ED and on a geriatric-gerontopsychiatric ward. 19 patients were included, ten males and nine females; mean age: 77.4 (55-93) years of which 14 were PWD. PWD inclusion criteria were age ≥ 55 years, a dementia diagnosis and a written consent (by patients or by a custodian). Exclusion criteria were acute life-threatening situations and a missing consent.

RESULTS

Measurements of heart rate, changes in movement and sound emissions by the NCMSys were valid, whereas patient movements affected respiratory rate measurements. The ChD did not impact patients' vital signs or movements in our study setting. However, 53% of the PWD (7/13) and most of the patients without dementia (4/5) benefited from its use regarding their agitation and overall wellbeing.

CONCLUSIONS

The results of this feasibility study encourage a future controlled clinical trial in geriatric ED patients, including PWD, to further evaluate if our concept of non-contact measurement of vital signs and movement combined with the "Charité Dome" helps to prevent upcoming agitation in this vulnerable patient group in the ED.

TRIAL REGISTRATION

ICTRP: "Charité-Dome-Study - DRKS00014737" (retrospectively registered).

Evaluation of the Efficacy and Safety of Short-Course Deep Sedation Therapy for the Treatment of Intracerebral Hemorrhage After Surgery: A Non-Randomized Control Study

Background

While mild and moderate sedation have been widely used to reduce sudden agitation in intracerebral hemorrhage (ICH) patients after surgery, agitation is still a frequent problem, which may cause postoperative blood pressure fluctuation. The present study aimed to evaluate the efficacy and safety of short-course deep sedation for the treatment of ICH after surgery.

Material/Methods

A total of 41 ICH patients who received surgery, including traditional craniotomy hematoma removal and decompressive craniectomy, were including in this non-randomized control study. Patients in the deep sedation group received continuous postoperative sedation with a target course for ≤12 hours and reached SAS scores of 1~2. Patients in the traditional sedition group received continuous light sedation and reached SAS scores of 3~4. Additional therapeutic interventions included antihypertensive treatment, mechanical ventilation, tracheotomy, and re-operation.

Results

Patients in the deep sedation group had deeper sedation degree, and lower systolic blood pressure (SBP) and diastolic blood pressure (DBP). Residual hematoma after surgery in patients in the deep sedation group were smaller on the second, seventh, and fourteenth day after surgery (p=0.023, 0.003, 0.004, respectively). The 3-month mortality and quality of life of patients in the deep sedation group were lower and better than that of patients in the traditional sedation group, respectively (p=0.044, p<0.01). No significant difference in the incidence of ventilator-associated pneumonia (VAP) and ICU days were observed between the two groups.

Conclusions

Short-course deep sedation therapy in ICH patients after surgery is efficient in controlling postoperative blood pressure, reducing re-bleeding, and improving clinical prognosis.

Nursing and fuzzy logic: an integrative review

This study conducted an integrative review investigating how fuzzy logic has been used in research with the participation of nurses. The article search was carried out in the CINAHL, EMBASE, SCOPUS, PubMed and Medline databases, with no limitation on time of publication. Articles written in Portuguese, English and Spanish with themes related to nursing and fuzzy logic with the authorship or participation of nurses were included. The final sample included 21 articles from eight countries. For the purpose of analysis, the articles were distributed into categories: theory, method and model. In nursing, fuzzy logic has significantly contributed to the understanding of subjects related to: imprecision or the need of an expert; as a research method; and in the development of models or decision support systems and hard technologies. The use of fuzzy logic in nursing has shown great potential and represents a vast field for research.

Measuring facial grimacing for quantifying patient agitation in critical care

The effective delivery of sedation in critical care relies primarily on an accurate and consistent measure of a patient's agitation level. However, current methods for assessing agitation are subjective and prone to error, often leading to over sedation or cycles between agitation and oversedation. This paper builds on previous work developing agitation sensors based on heart rate and blood pressure variability, and overall whole body motion. In this research, the focus is on real-time measurement of high-resolution facial changes that are observed to occur in agitation. An algorithm is developed that measures the degree of facial grimacing from a single digital camera. The method is demonstrated on simulated patient facial motion to prove the concept. A consistent measure is obtained that is robust to significant random head movement and compares well against visual observation of different levels of grimacing. The method provides a basis for clinical validation.

Automated agitation management accounting for saturation dynamics

Agitation-sedation cycling in critically ill is damaging to patient health and increases length of and cost. A physiologically representative model of the agitation-sedation system is used as a platform to evaluate feedback controllers offering improved agitation management. A heavy-derivative controller with upper and infusion rate bounds maintains minimum plasma concentrations through a low constant infusion, and minimizes outbursts of agitation through strong, timely boluses. controller provides improved agitation management using from 37 critically ill patients, given the saturation of effect at high concentration. Approval was obtained the Canterbury Ethics Board for this research.

Parameter identification and sedative sensitivity analysis of an agitation-sedation model

Sedation administration and agitation management are fundamental activities in any intensive care unit. A lack of objective measures of agitation and sedation, as well as poor understanding of the underlying dynamics, contribute to inefficient outcomes and expensive healthcare. Recent models of agitation-sedation dynamics have enhanced understanding of the underlying dynamics and enable development of advanced protocols for semi-automated sedation administration. In this research, the agitation-sedation model parameters are identified using an integral-based fitting method developed in this work. Parameter variance is then analysed over 37 intensive care unit patients. The parameter identification method is shown to be effective and computationally inexpensive, making it suited to real-time clinical control applications. Sedative sensitivity, an important model parameter, is found to be both patient-specific and time-varying. However, while the variation between patients is observed to be as large as a factor 10, the observed variation in time is smaller, and varies slowly over a period of days rather than hours. The high fitted model performance across all patients show that the agitation-sedation model presented captures the fundamental dynamics of the agitation-sedation system. Overall, these results provide additional insight into the system and clinical dynamics of sedation management.

Physiological modelling of agitation–sedation dynamics including endogenous agitation reduction

Sedation administration and agitation management are fundamental activities in any intensive care unit. A lack of objective measures of agitation and sedation, as well as poor understanding of the underlying dynamics, contribute to inefficient outcomes and expensive healthcare. Recent models of agitation-sedation pharmacodynamics have enhanced understanding of the underlying dynamics and enable development of advanced protocols for semi-automated sedation administration. However, these initial models do not capture all observed dynamics, particularly periods of low sedative infusion. A physiologically representative model that incorporates endogenous agitation reduction (EAR) dynamics is presented and validated using data from 37 critical care patients. High median relative average normalised density (RAND) values of 0.77 and 0.78 support and minimum RAND values of 0.51 and 0.55 for models without and with EAR dynamics respectively show that both models are valid representations of the fundamental agitation-sedation dynamics present in a broad spectrum of intensive care unit (ICU) patients. While the addition of the EAR dynamic increases the ability of the model to capture the observed dynamics of the agitation-sedation system, the improvement is relatively small and the sensitivity of the model to the EAR dynamic is low. Although this may represent a limitation of the model, the inclusion of EAR is shown to be important for accurately capturing periods of low, or no, sedative infusion, such as during weaning prior to extubation.

Heart rate variability analysis: a tool to assess cardiac autonomic function

Heart rate monitoring is commonly used to provide an acute indicator of an individual's cardiovascular status and responsiveness. An increasingly popular technique involves quantifying the very small amounts by which the heart rate changes from one cardiac cycle to the next. This "heart rate variability (HRV) analysis" provides a substantial amount of additional information about the cardiovascular system and enables quantification of cardiac regulatory influences on the autonomic nervous system. The autonomic nervous system consists of two main components: the sympathetic system and the parasympathetic system. The relative influence of these two components on the sino-atrial node of the heart determines the heart rate. A number of physiological factors, including blood pressure and respiratory rate, can have a profound effect on this autonomic "balance." HRV analysis therefore provides a noninvasive method for investigating the dynamic influence of changing physiological parameters on cardiac regulation.

Physiological modelling of agitation–sedation dynamics

Agitation-sedation cycling in critically ill patients, characterized by oscillations between states of agitation and over-sedation, damages patient health and increases length of stay and cost. A model that captures the essential dynamics of the agitation-sedation system and is physiologically representative is developed, and validated using data from 37 critical care patients. It is more physiologically representative than a previously published agitation-sedation model, and captures more realistic and complex dynamics. The median time in the 90% probability band is 90%, and the total drug dose, relative to recorded drug dose data, is a near ideal 101%. These statistical model validation metrics are 5-13% better than a previously validated model. Hence, this research provides a platform to develop and test semi-automated sedation management controllers that offer the significant clinical potential of improved agitation management and reduced length of stay in critical care.