79 research outputs found

    Fractional anisotropy shows differential reduction in frontal-subcortical fiber bundles - A longitudinal MRI study of 76 middle-aged and older adults

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    Motivated by the frontal- and white matter (WM) retrogenesis hypotheses and the assumptions that fronto-striatal circuits are especially vulnerable in normal aging, the goal of the present study was to identify fiber bundles connecting subcortical nuclei and frontal areas and obtain site-specific information about age related fractional anisotropy (FA) changes. Multimodal magnetic resonance image acquisitions [3D T1-weighted and diffusion weighted imaging (DWI)] were obtained from healthy older adults (N = 76, range 49–80 years at inclusion) at two time points, 3 years apart. A subset of the participants (N = 24) was included at a third time-point. In addition to the frontal-subcortical fibers, the anterior callosal fiber (ACF) and the corticospinal tract (CST) was investigated by its mean FA together with tract parameterization analysis. Our results demonstrated fronto-striatal structural connectivity decline (reduced FA) in normal aging with substantial inter-individual differences. The tract parameterization analysis showed that the along tract FA profiles were characterized by piece-wise differential changes along their extension rather than being uniformly affected. To the best of our knowledge, this is the first longitudinal study detecting age-related changes in frontal-subcortical WM connections in normal aging.publishedVersio

    Predicting conversion to Alzheimer’s disease in individuals with Mild Cognitive Impairment using clinically transferable features

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    Patients with Mild Cognitive Impairment (MCI) have an increased risk of Alzheimer’s disease (AD). Early identification of underlying neurodegenerative processes is essential to provide treatment before the disease is well established in the brain. Here we used longitudinal data from the ADNI database to investigate prediction of a trajectory towards AD in a group of patients defined as MCI at a baseline examination. One group remained stable over time (sMCI, n = 357) and one converted to AD (cAD, n = 321). By running two independent classification methods within a machine learning framework, with cognitive function, hippocampal volume and genetic APOE status as features, we obtained a cross-validation classification accuracy of about 70%. This level of accuracy was confirmed across different classification methods and validation procedures. Moreover, the sets of misclassified subjects had a large overlap between the two models. Impaired memory function was consistently found to be one of the core symptoms of MCI patients on a trajectory towards AD. The prediction above chance level shown in the present study should inspire further work to develop tools that can aid clinicians in making prognostic decisions.publishedVersio

    Functional activity level reported by an informant is an early predictor of Alzheimer’s disease

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    Background Loss of autonomy in day-to-day functioning is one of the feared outcomes of Alzheimer’s disease (AD), and relatives may have been worried by subtle behavioral changes in ordinary life situations long before these changes are given medical attention. In the present study, we ask if such subtle changes should be given weight as an early predictor of a future AD diagnosis. Methods Longitudinal data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) were used to define a group of adults with a mild cognitive impairment (MCI) diagnosis remaining stable across several visits (sMCI, n=360; 55-91 years at baseline), and a group of adults who over time converted from having an MCI diagnosis to an AD diagnosis (cAD, n=320; 55-88 years at baseline). Eleven features were used as input in a Random Forest (RF) binary classifier (sMCI vs. cAD) model. This model was tested on an unseen holdout part of the dataset, and further explored by three different permutation-driven importance estimates and a comprehensive post hoc machine learning exploration. Results The results consistently showed that measures of daily life functioning, verbal memory function, and a volume measure of hippocampus were the most important predictors of conversion from an MCI to an AD diagnosis. Results from the RF classification model showed a prediction accuracy of around 70% in the test set. Importantly, the post hoc analyses showed that even subtle changes in everyday functioning noticed by a close informant put MCI patients at increased risk for being on a path toward the major cognitive impairment of an AD diagnosis. Conclusion The results showed that even subtle changes in everyday functioning should be noticed when reported by relatives in a clinical evaluation of patients with MCI. Information of these changes should also be included in future longitudinal studies to investigate different pathways from normal cognitive aging to the cognitive decline characterizing different stages of AD and other neurodegenerative disorders.publishedVersio

    Impulsivity and drinking motives predict problem behaviours relating to alcohol use in University students

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    Aims: This study used a four-factor model of impulsivity to investigate inter-relationships between alcohol consumption, impulsivity, motives for drinking and the tendency to engage in alcohol-related problem behaviours. Methods: 400 University students aged 18-25 completed an online survey consisting of the following measures: Urgency, Premeditation, Perseverance and Sensation Seeking Scale (UPPS) to measure impulsivity; Student Alcohol Questionnaire to assess drinking quantity, frequency and rates of problem behaviours; Drinking Motives Questionnaire to assess motives for drinking. Results: The majority of the sample (94.5%) drank alcohol at least monthly. Path analysis revealed direct effects of urgency, sensation seeking and premeditation, as well as the quantity of alcohol consumed, on the tendency to engage in risky behaviours with negative consequences. The effect of urgency was mediated by drinking for coping motives and by a combined effect of drinking for social motives and consumption of wine or spirits. Conversely the effect of sensation seeking was mediated by the quantity of alcohol consumed, irrespective of drink type, and the effect of premeditation was mediated by the consumption of wine and spirits, in combination with enhancement motives. Conclusions: Sensation seeking, urgency and lack of premeditation are related to different motives for drinking and also demonstrate dissociable relationships with the consumption of specific types of alcohol (beer, wine and spirits) and the tendency to engage in risky behaviours associated with alcohol consumption. Screening for high levels of urgency and for severe drinking consequences may be useful predictors of alcohol-related problems in UK University students aged 18 to 25 years

    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 general supportive and preventive intensive care management of traumatic brain injury: a survey in 66 neurotrauma centers participating in the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study

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    Abstract Background General supportive and preventive measures in the intensive care management of traumatic brain injury (TBI) aim to prevent or limit secondary brain injury and optimize recovery. The aim of this survey was to assess and quantify variation in perceptions on intensive care unit (ICU) management of patients with TBI in European neurotrauma centers. Methods We performed a survey as part of the Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) study. We analyzed 23 questions focused on: 1) circulatory and respiratory management; 2) fever control; 3) use of corticosteroids; 4) nutrition and glucose management; and 5) seizure prophylaxis and treatment. Results The survey was completed predominantly by intensivists (n = 33, 50%) and neurosurgeons (n = 23, 35%) from 66 centers (97% response rate). The most common cerebral perfusion pressure (CPP) target was > 60 mmHg (n = 39, 60%) and/or an individualized target (n = 25, 38%). To support CPP, crystalloid fluid loading (n = 60, 91%) was generally preferred over albumin (n = 15, 23%), and vasopressors (n = 63, 96%) over inotropes (n = 29, 44%). The most commonly reported target of partial pressure of carbon dioxide in arterial blood (PaCO2) was 36–40 mmHg (4.8–5.3 kPa) in case of controlled intracranial pressure (ICP) < 20 mmHg (n = 45, 69%) and PaCO2 target of 30–35 mmHg (4–4.7 kPa) in case of raised ICP (n = 40, 62%). Almost all respondents indicated to generally treat fever (n = 65, 98%) with paracetamol (n = 61, 92%) and/or external cooling (n = 49, 74%). Conventional glucose management (n = 43, 66%) was preferred over tight glycemic control (n = 18, 28%). More than half of the respondents indicated to aim for full caloric replacement within 7 days (n = 43, 66%) using enteral nutrition (n = 60, 92%). Indications for and duration of seizure prophylaxis varied, and levetiracetam was mostly reported as the agent of choice for both seizure prophylaxis (n = 32, 49%) and treatment (n = 40, 61%). Conclusions Practice preferences vary substantially regarding general supportive and preventive measures in TBI patients at ICUs of European neurotrauma centers. These results provide an opportunity for future comparative effectiveness research, since a more evidence-based uniformity in good practices in general ICU management could have a major impact on TBI outcome
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