13 research outputs found

    Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

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    Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations

    Variation in Structure and Process of Care in Traumatic Brain Injury: Provider Profiles of European Neurotrauma Centers Participating in the CENTER-TBI Study.

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    INTRODUCTION: The strength of evidence underpinning care and treatment recommendations in traumatic brain injury (TBI) is low. Comparative effectiveness research (CER) has been proposed as a framework to provide evidence for optimal care for TBI patients. The first step in CER is to map the existing variation. The aim of current study is to quantify variation in general structural and process characteristics among centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. METHODS: We designed a set of 11 provider profiling questionnaires with 321 questions about various aspects of TBI care, chosen based on literature and expert opinion. After pilot testing, questionnaires were disseminated to 71 centers from 20 countries participating in the CENTER-TBI study. Reliability of questionnaires was estimated by calculating a concordance rate among 5% duplicate questions. RESULTS: All 71 centers completed the questionnaires. Median concordance rate among duplicate questions was 0.85. The majority of centers were academic hospitals (n = 65, 92%), designated as a level I trauma center (n = 48, 68%) and situated in an urban location (n = 70, 99%). The availability of facilities for neuro-trauma care varied across centers; e.g. 40 (57%) had a dedicated neuro-intensive care unit (ICU), 36 (51%) had an in-hospital rehabilitation unit and the organization of the ICU was closed in 64% (n = 45) of the centers. In addition, we found wide variation in processes of care, such as the ICU admission policy and intracranial pressure monitoring policy among centers. CONCLUSION: Even among high-volume, specialized neurotrauma centers there is substantial variation in structures and processes of TBI care. This variation provides an opportunity to study effectiveness of specific aspects of TBI care and to identify best practices with CER approaches

    Variation in neurosurgical management of traumatic brain injury

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    Background: Neurosurgical management of traumatic brain injury (TBI) is challenging, with only low-quality evidence. We aimed to explore differences in neurosurgical strategies for TBI across Europe. Methods: A survey was sent to 68 centers participating in the Collaborative European Neurotrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. The questionnaire contained 21 questions, including the decision when to operate (or not) on traumatic acute subdural hematoma (ASDH) and intracerebral hematoma (ICH), and when to perform a decompressive craniectomy (DC) in raised intracranial pressure (ICP). Results: The survey was completed by 68 centers (100%). On average, 10 neurosurgeons work in each trauma center. In all centers, a neurosurgeon was available within 30 min. Forty percent of responders reported a thickness or volume threshold for evacuation of an ASDH. Most responders (78%) decide on a primary DC in evacuating an ASDH during the operation, when swelling is present. For ICH, 3% would perform an evacuation directly to prevent secondary deterioration and 66% only in case of clinical deterioration. Most respondents (91%) reported to consider a DC for refractory high ICP. The reported cut-off ICP for DC in refractory high ICP, however, differed: 60% uses 25 mmHg, 18% 30 mmHg, and 17% 20 mmHg. Treatment strategies varied substantially between regions, specifically for the threshold for ASDH surgery and DC for refractory raised ICP. Also within center variation was present: 31% reported variation within the hospital for inserting an ICP monitor and 43% for evacuating mass lesions. Conclusion: Despite a homogeneous organization, considerable practice variation exists of neurosurgical strategies for TBI in Europe. These results provide an incentive for comparative effectiveness research to determine elements of effective neurosurgical care

    Life with Locked-In syndrome

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    peer reviewedThe Locked-In Syndrome (LIS) is classically caused by an anterior pontine vascular lesion and characterized by quadriplegia and anarthria with preserved consciousness and intellectual functioning. We here review the definition, etiologies, diagnosis and prognosis of LIS patients and briefly discuss the few studies on their quality of life and the challenging end-of-life decisions that can be encountered. Some clinicians may consider that LIS is worse than being in a vegetative or in a minimally conscious state. However, preliminary data from chronic LIS survivors show a surprisingly preserved self-scored quality of life and requests of treatment withdrawal or euthanasia, though not absent, are infrequent

    Improving EEG-BCI analysis for low certainty subjects by using dictionary learning

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    The diagnosis of patients with Disorders Of Consciousness represents a challenge in the clinical routine. Recently, Brain Computer Interfaces based in Electroencephalography (EEG-BCI) have been used to detect signs of consciousness in these patients. This approach allows to discover brain responses to command following. Nevertheless, a reliable BCI strategy must to be able to determine the commands with high levels of certainty. Current results reported in the literature evidence that about 25% of the subjects in which BCI is used may have low performances, near to the chance level, even in collaborating subjects. In this work, we propose a novel approach based on dictionary learning representations aimed to improve performance in low certainty subjects. We propose to introduce an intermediate representation scheme, based on sparse dictionaries, before feature selection step. Our main assumption is that by using these representations we can capture more efficiently the EEG signal structure for subjects responses. The results show that using the new representation the weighted average performance in command following outcome the previews proposed methods of 64.8% to 67.9%. Higher improvements in performance were obtained for low certainly subjects. Our results suggests that this approach may improve BCI-EEG performance in low certainly subjects

    Dynamic change of global and local information processing in Propofol-induced loss and recovery of consciousness

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    Whether unique to humans or not, consciousness is a central aspect of our experience of the world. The neural fingerprint of this experience, however, remains one of the least understood aspects of the human brain. In this paper we employ graph-theoretic measures and support vector machine classification to assess, in 12 healthy volunteers, the dynamic reconfiguration of functional connectivity during wakefulness, propofol-induced sedation and loss of consciousness, and the recovery of wakefulness. Our main findings, based on resting-state fMRI, are three-fold. First, we find that propofol-induced anesthesia does not bear differently on long-range versus short-range connections. Second, our multi-stage design dissociated an initial phase of thalamo-cortical and cortico-cortical hyperconnectivity, present during sedation, from a phase of cortico-cortical hypoconnectivity, apparent during loss of consciousness. Finally, we show that while clustering is increased during loss of consciousness, as recently suggested, it also remains significantly elevated during wakefulness recovery. Conversely, the characteristic path length of brain networks (i.e., the average functional distance between any two regions of the brain) appears significantly increased only during loss of consciousness, marking a decrease of global information-processing efficiency uniquely associated with unconsciousness. These findings suggest that propofol-induced loss of consciousness is mainly tied to cortico-cortical and not thalamo-cortical mechanisms, and that decreased efficiency of information flow is the main feature differentiating the conscious from the unconscious brain

    Tracheostomy practice and timing in traumatic brain-injured patients: a CENTER-TBI study

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    Purpose: Indications and optimal timing for tracheostomy in traumatic brain-injured (TBI) patients are uncertain. This study aims to describe the patients’ characteristics, timing, and factors related to the decision to perform a tracheostomy and differences in strategies among different countries and assess the effect of the timing of tracheostomy on patients’ outcomes. Methods: We selected TBI patients from CENTER-TBI, a prospective observational longitudinal cohort study, with an intensive care unit stay ≥ 72 h. Tracheostomy was defined as early (≤ 7 days from admission) or late (> 7 days). We used a Cox regression model to identify critical factors that affected the timing of tracheostomy. The outcome was assessed at 6 months using the extended Glasgow Outcome Score. Results: Of the 1358 included patients, 433 (31.8%) had a tracheostomy. Age (hazard rate, HR = 1.04, 95% CI = 1.01–1.07, p = 0.003), Glasgow coma scale ≤ 8 (HR = 1.70, 95% CI = 1.22–2.36 at 7; p < 0.001), thoracic trauma (HR = 1.24, 95% CI = 1.01–1.52, p = 0.020), hypoxemia (HR = 1.37, 95% CI = 1.05–1.79, p = 0.048), unreactive pupil (HR = 1.76, 95% CI = 1.27–2.45 at 7; p < 0.001) were predictors for tracheostomy. Considerable heterogeneity among countries was found in tracheostomy frequency (7.9–50.2%) and timing (early 0–17.6%). Patients with a late tracheostomy were more likely to have a worse neurological outcome, i.e., mortality and poor neurological sequels (OR = 1.69, 95% CI = 1.07–2.67, p = 0.018), and longer length of stay (LOS) (38.5 vs. 49.4 days, p = 0.003). Conclusions: Tracheostomy after TBI is routinely performed in severe neurological damaged patients. Early tracheostomy is associated with a better neurological outcome and reduced LOS, but the causality of this relationship remains unproven. © 2020, Springer-Verlag GmbH Germany, part of Springer Nature
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