Individuals who have suffered a severe brain injury typically require extensive hospitalization in intensive care units (ICUs), where critical treatment decisions are made to maximize their likelihood of recovering consciousness and cognitive function. These treatment decisions can be difficult when the neurological assessment of the patient is limited by unreliable behavioral responses. Reliable objective and quantifiable markers are lacking and there is both (1) a poor understanding of the mechanisms underlying the brain's ability to reconstitute consciousness and cognition after an injury and (2) the absence of a reliable and clinically feasible method of tracking cognitive recovery in ICU survivors. Our goal is to develop and validate a clinically relevant EEG paradigm that can inform the prognosis of unresponsive, brain-injured patients in the ICU. This protocol describes a study to develop a point-of-care system intended to accurately predict outcomes of unresponsive, brain-injured patients in the ICU. We will recruit 200 continuously-sedated brain-injured patients across five ICUs. Between 24 h and 7 days post-ICU admission, high-density EEG will be recorded from behaviorally unresponsive patients before, during and after a brief cessation of pharmacological sedation. Once patients have reached the waking stage, they will be asked to complete an abridged Cambridge Brain Sciences battery, a web-based series of neurocognitive tests. The test series will be repeated every day during acute admission (ICU, ward), or as often as possible given the constraints of ICU and ward care. Following discharge, patients will continue to complete the same test series on weekly, and then monthly basis, for up to 12 months following injury. Functional outcomes will also be assessed up to 12 months post-injury. We anticipate our findings will lead to an increased ability to identify patients, as soon as possible after their brain injury, who are most likely to survive, and to make accurate predictions about their long-term cognitive and functional outcome. In addition to providing critically needed support for clinical decision-making, this study has the potential to transform our understanding of key functional EEG networks associated with consciousness and cognition.
Medical decision making, such as choosing which drugs to prescribe, requires to consider mandatory constraints, e.g. absolute contraindications, but also preferences that may not be satisfiable, e.g. guideline recommendations or patient preferences. The major problem is that these preferences are complex, numerous and come from various sources. The considered criteria are often conflicting and the number of decisions is too large to be explicitly handled. In this paper, we propose a framework for encoding medical preferences using a new connective, called ordered disjunction symbolized by ~×. Intuitively, the preference “Diuretic~×Betablocker means: “Prescribe a Diuretic if possible, but if this is not possible, then prescribe a Betablocker”. We give an inference method for reasoning about the preferences and we show how this framework can be applied to a part of a guideline for hypertension.
Les langages iconiques permettent de représenter des concepts par la combinaison de primitives graphiques (couleurs, pictogrammes...).Les exemples sont nombreux, des panneaux routiers aux icônes des interfaces utilisateur.Cependant, ces langages n'associent pas de sémantique logique à leurs icônes, ce qui peut poser divers problèmes : des combinaisons inconsistantes de primitives graphiques, des interprétations différentes d'une même icône par deux personnes, des difficultés à mettre en correspondance les icônes avec des concepts de ressources termino-ontologiques existantes... Dans cet article, nous proposons une méthode de formalisation de la sémantique d'un langage iconique à l'aide d'une ontologie.Cette méthode a initialement été développée pour le langage iconique VCM (Visualisation des Concepts en Médecine), qui permet de représenter par des icônes les principaux concepts médicaux (antécédents, maladies, traitements...).Nous montrons que cette méthode est généralisable à d'autres langages iconiques en l'appliquant à la signalisation routière.Nous décrivons quatre applications de la formalisation du langage : la vérification de la consistance des icônes constituées, l'alignement semi-automatique des icônes avec une terminologie médicale, la génération d'un lexique des pictogrammes et la génération de libellés pour les icônes.Mots-clefs : icônes,
Background: Although the drug is finished, identifiable, there is no universally accepted standard for naming them. The objective of this work is to evaluate qualitatively the HeTOP drug terminology server by two categories of students: (a) pharmacy students and (b) a control group. Methods: A formal evaluation was built to measure the perception of users about the HeTOP drug server, using the three mains questions about “teaching interest”, “skill interest” (or competence) and “ergonomics”. Results: The three pharmacy student subgroups gave the best and the worst score to the same categories. Conclusion: All three criteria are rated above 6.5 out of 10. The HeTOP drug terminology server is freely available to “non drug” specialists (URL: www.hetop.eu/hetop/drugs/).
The temporal trajectories and neural mechanisms of recovery of cognitive function after a major perturbation of consciousness is of both clinical and neuroscientific interest. The purpose of the present study was to investigate network-level changes in functional brain connectivity associated with the recovery and return of six cognitive functions after general anesthesia. High-density electroencephalograms (EEG) were recorded from healthy volunteers undergoing a clinically relevant anesthesia protocol (propofol induction and isoflurane maintenance), and age-matched healthy controls. A battery of cognitive tests (motor praxis, visual object learning test, fractal-2-back, abstract matching, psychomotor vigilance test, digital symbol substitution test) was administered at baseline, upon recovery of consciousness (ROC), and at half-hour intervals up to 3 h following ROC. EEG networks were derived using the strength of functional connectivity measured through the weighted phase lag index (wPLI). A partial least squares (PLS) analysis was conducted to assess changes in these networks: (1) between anesthesia and control groups; (2) during the 3-h recovery from anesthesia; and (3) for each cognitive test during recovery from anesthesia. Networks were maximally perturbed upon ROC but returned to baseline 30-60 min following ROC, despite deficits in cognitive performance that persisted up to 3 h following ROC. Additionally, during recovery from anesthesia, cognitive tests conducted at the same time-point activated distinct and dissociable functional connectivity networks across all frequency bands. The results highlight that the return of cognitive function after anesthetic-induced unconsciousness is task-specific, with unique behavioral and brain network trajectories of recovery.
Background and Objectives. The onset of pervasive sleep-wake disturbances associated with traumatic brain injury (TBI) is poorly understood. This study aimed to ( a) determine the feasibility of using polysomnography in patients in the acute, hospitalized stage of severe TBI and ( b) explore sleep quality and sleep architecture during this stage of recovery, compared to patients with other traumatic injuries. Methods. A cross-sectional case-control design was used. We examined the sleep of 7 patients with severe TBI (17-47 years; 20.3 ± 15.0 days postinjury) and 6 patients with orthopedic and/or spinal cord injuries (OSCI; 19-58 years; 16.9 ± 4.9 days postinjury). One night of ambulatory polysomnography was performed at bedside. Results. Compared to OSCI patients, TBI patients showed a significantly longer duration of nocturnal sleep and earlier nighttime sleep onset. Sleep efficiency was low and comparable in both groups. All sleep stages were observed in both groups with normal proportions according to age. Conclusion. Patients in the acute stage of severe TBI exhibit increased sleep duration and earlier sleep onset, suggesting that the injured brain enhances sleep need and/or decreases the ability to maintain wakefulness. As poor sleep efficiency could compromise brain recovery, further studies should investigate whether strategies known to optimize sleep in healthy individuals are efficacious in acute TBI. While there are several inherent challenges, polysomnography is a useful means of examining sleep in the early stage of recovery in patients with severe TBI.
