Family satisfaction with critical care: measurements and messages

PURPOSE OF REVIEW: Family satisfaction in the ICU reflects the extent to which perceived needs and expectations of family members of critically ill patients are met by healthcare professionals. Here, we present recently developed tools to assess family satisfaction, with a special focus on their psychometric properties. Assessing family satisfaction, however, is not of much use if it is not followed by interpretation of the results and, if needed, consecutive measures to improve care of the patients and their families, or improvement in communication and decision-making. Accordingly, this review will outline recent findings in this field. Finally, possible areas of future research are addressed. RECENT FINDINGS: To assess family satisfaction in the ICU, several domains deserve attention. They include, among others, care of the patient, counseling and emotional support of family members, information and decision-making. Overall, communication between physicians or nurses and members of the family remains a key topic, and there are many opportunities to improve. They include not only communication style, timing and appropriate wording but also, for example, assessments to see if information was adequately received and also understood. Whether unfulfilled needs of individual members of the family or of the family as a social system result in negative long-term sequels remains an open question. SUMMARY: Assessing and analyzing family satisfaction in the ICU ultimately will support healthcare professionals in their continuing effort to improve care of critically ill patients and their families.

Attacks on German public figures, 1968-2004: warning behaviors, potentially lethal and non-lethal acts, psychiatric status, and motivations

Fourteen non-terrorist attackers of public figures in Germany between 1968 and 2004 were intensively studied, with a particular focus on warning behaviors, attack behaviors, and the relationship between psychiatric diagnosis, symptoms, and motivations for the assault. A large proportion of the attackers were severely mentally ill, and most likely to be in the potentially lethal rather than the non-lethal group. A new typology of seven warning behaviors was applied to the data, and all were present, most frequently fixation and pathway warning behavior, and least frequently a direct threat. Psychiatric diagnosis could be closely linked to motivation when analyzed at the level of symptom and content of thought, often delusional. Most of the attacks were directed at political figures, and the majority occurred after 1995.

The role of warning behaviors in threat assessment: an exploration and suggested typology

The concept of warning behaviors offers an additional perspective in threat assessment. Warning behaviors are acts which constitute evidence of increasing or accelerating risk. They are acute, dynamic, and particularly toxic changes in patterns of behavior which may aid in structuring a professional's judgment that an individual of concern now poses a threat - whether the actual target has been identified or not. They require an operational response. A typology of eight warning behaviors for assessing the threat of intended violence is proposed: pathway, fixation, identification, novel aggression, energy burst, leakage, directly communicated threat, and last resort warning behaviors. Previous research on risk factors associated with such warning behaviors is reviewed, and examples of each warning behavior from various intended violence cases are presented, including public figure assassination, adolescent and adult mass murder, corporate celebrity stalking, and both domestic and foreign acts of terrorism. Practical applications and future research into warning behaviors are suggested. Copyright © 2011 John Wiley & Sons, Ltd.

The warning-sign hierarchy between quantitative subcortical motor mapping and continuous motor evoked potential monitoring during resection of supratentorial brain tumors

Mapping and monitoring are believed to provide an early warning sign to determine when to stop tumor removal to avoid mechanical damage to the corticospinal tract (CST). The objective of this study was to systematically compare subcortical monopolar stimulation thresholds (1-20 mA) with direct cortical stimulation (DCS)-motor evoked potential (MEP) monitoring signal abnormalities and to correlate both with new postoperative motor deficits. The authors sought to define a mapping threshold and DCS-MEP monitoring signal changes indicating a minimal safe distance from the CST.

An early warning system for hypoglycemic/hyperglycemic events based on fusion of adaptive prediction models

Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia/hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy.

Rising sound intensity: an intrinsic warning cue activating the amygdala

Human subjects overestimate the change of rising intensity sounds compared with falling intensity sounds. Rising sound intensity has therefore been proposed to be an intrinsic warning cue. In order to test this hypothesis, we presented rising, falling, and constant intensity sounds to healthy humans and gathered psychophysiological and behavioral responses. Brain activity was measured using event-related functional magnetic resonance imaging. We found that rising compared with falling sound intensity facilitates autonomic orienting reflex and phasic alertness to auditory targets. Rising intensity sounds produced neural activity in the amygdala, which was accompanied by activity in intraparietal sulcus, superior temporal sulcus, and temporal plane. Our results indicate that rising sound intensity is an elementary warning cue eliciting adaptive responses by recruiting attentional and physiological resources. Regions involved in cross-modal integration were activated by rising sound intensity, while the right-hemisphere phasic alertness network could not be supported by this study.

Capsular warning syndrome mimicking a jacksonian sensory march

A 57-year-old man, operated eight years before for a left frontal falx meningioma, presented with short lasting, stereotyped episodes of paresthesias ascending from the right foot to the hand. A diagnosis of somatosensory seizures with jacksonian march was made. The patient was given antiepilectics but 5 days later, a few hours after another paresthesic episodes, he developed right hemiplegia, hemianesthesia and dysartria due to an infarct of left capsular posterior limb. We deem that in this patient the paresthesic episodes were more likely an expression of a capsular warning syndrome than of parietal epilepsy because of the frontal localization of the surgical lesion, the absence of motor components in all episodes, the negativity of repeated EEG, and the lack of recurrences after stroke. In capsular warning syndrome sensory symptoms mimicking a jacksonian march can be due to ischemic depolarization progressively recruiting the somatotopically arranged sensory fibers in the posterior capsular limb.

Use of audiovisual messages from land user to land user for sharing knowledge about SLM: experiences from a pilot project in Kenya and Tajikistan

The global World Overview of Conservation Approaches and Technologies (WOCAT) initiative has developed standardised tools and methods to compile and evaluate knowledge available about SLM. This knowledge is now combined and enriched with audiovisual information in order to give a voice to land users, reach a broad range of stakeholders, and assist in scaling up SLM to reverse trends of degradation, desertification, and drought. Five video products, adapted to the needs of different target groups, are created and embedded in already existing platforms for knowledge sharing of SLM such as the WOCAT database and Google Earth application. A pilot project was carried out in Kenya and Tajikistan to verify ideas and tools while at the same time assessing the usefulness of the suggested products on the ground. Video has the potential to bridge the gap between different actor groups and enable communication and sharing on different levels and scales: locally, regionally, and globally. Furthermore, it is an innovative tool to link local and scientific knowledge, raise awareness, and support advocacy for SLM. Keywords: Sustainable Land Management (SLM), knowledge sharing, audiovisual messages, video, World Overview of Conservation Approaches and Technologies (WOCAT)

An Early-Warning System for Hypo-/Hyperglycemic Events Based on Fusion of Adaptive Prediction Models

Introduction: Early warning of future hypoglycemic and hyperglycemic events can improve the safety of type 1 diabetes mellitus (T1DM) patients. The aim of this study is to design and evaluate a hypoglycemia / hyperglycemia early warning system (EWS) for T1DM patients under sensor-augmented pump (SAP) therapy. Methods: The EWS is based on the combination of data-driven online adaptive prediction models and a warning algorithm. Three modeling approaches have been investigated: (i) autoregressive (ARX) models, (ii) auto-regressive with an output correction module (cARX) models, and (iii) recurrent neural network (RNN) models. The warning algorithm performs postprocessing of the models′ outputs and issues alerts if upcoming hypoglycemic/hyperglycemic events are detected. Fusion of the cARX and RNN models, due to their complementary prediction performances, resulted in the hybrid autoregressive with an output correction module/recurrent neural network (cARN)-based EWS. Results: The EWS was evaluated on 23 T1DM patients under SAP therapy. The ARX-based system achieved hypoglycemic (hyperglycemic) event prediction with median values of accuracy of 100.0% (100.0%), detection time of 10.0 (8.0) min, and daily false alarms of 0.7 (0.5). The respective values for the cARX-based system were 100.0% (100.0%), 17.5 (14.8) min, and 1.5 (1.3) and, for the RNN-based system, were 100.0% (92.0%), 8.4 (7.0) min, and 0.1 (0.2). The hybrid cARN-based EWS presented outperforming results with 100.0% (100.0%) prediction accuracy, detection 16.7 (14.7) min in advance, and 0.8 (0.8) daily false alarms. Conclusion: Combined use of cARX and RNN models for the development of an EWS outperformed the single use of each model, achieving accurate and prompt event prediction with few false alarms, thus providing increased safety and comfort.