193 research outputs found

    Sensory Function and Psychological Factors in Children With Complex Regional Pain Syndrome Type 1

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    Objective: To assess thermal-sensory thresholds and psychosocial factors in children with Complex Regional Pain Syndrome Type 1 (CRPS-I) compared to healthy children. Methods: We conducted quantitative sensory testing on 34 children with CRPS-I and 56 pain-free children. Warm, cool, heat, and cold stimuli were applied to the forearm. Children with CRPS-I had the protocol administered to the pain site and the contralateral-pain site. Participants completed the self-report Behavior Assessment System for Children. Results: Longer pain durations (\u3e5.1 months) were associated with decreased sensitivity to cold pain on the pain site (P =.04). Higher pain-intensity ratings were associated with elevated anxiety scores (P =.03). Anxiety and social stress were associated with warmth sensitivity (both P \u3c.05) on the contralateral-pain site. Conclusions: Pain duration is an important factor in assessing pediatric CRPS-I. Hyposensitivity in the affected limb may emerge due to degeneration of nociceptive nerves. Anxiety may contribute to thermal-sensory perception in childhood CRPS-I

    Tract-Based Spatial Statistics in Preterm-Born Neonates Predicts Cognitive and Motor Outcomes at 18 Months.

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    BACKGROUND AND PURPOSE: Adverse neurodevelopmental outcome is common in children born preterm. Early sensitive predictors of neurodevelopmental outcome such as MR imaging are needed. Tract-based spatial statistics, a diffusion MR imaging analysis method, performed at term-equivalent age (40 weeks) is a promising predictor of neurodevelopmental outcomes in children born very preterm. We sought to determine the association of tract-based spatial statistics findings before term-equivalent age with neurodevelopmental outcome at 18-months corrected age. MATERIALS AND METHODS: Of 180 neonates (born at 24-32-weeks\u27 gestation) enrolled, 153 had DTI acquired early at 32 weeks\u27 postmenstrual age and 105 had DTI acquired later at 39.6 weeks\u27 postmenstrual age. Voxelwise statistics were calculated by performing tract-based spatial statistics on DTI that was aligned to age-appropriate templates. At 18-month corrected age, 166 neonates underwent neurodevelopmental assessment by using the Bayley Scales of Infant Development, 3rd ed, and the Peabody Developmental Motor Scales, 2nd ed. RESULTS: Tract-based spatial statistics analysis applied to early-acquired scans (postmenstrual age of 30-33 weeks) indicated a limited significant positive association between motor skills and axial diffusivity and radial diffusivity values in the corpus callosum, internal and external/extreme capsules, and midbrain (P \u3c .05, corrected). In contrast, for term scans (postmenstrual age of 37-41 weeks), tract-based spatial statistics analysis showed a significant relationship between both motor and cognitive scores with fractional anisotropy in the corpus callosum and corticospinal tracts (P \u3c .05, corrected). Tract-based spatial statistics in a limited subset of neonates (n = 22) scanned at CONCLUSIONS: The strength of the association between fractional anisotropy values and neurodevelopmental outcome scores increased from early-to-late-acquired scans in preterm-born neonates, consistent with brain dysmaturation in this population

    Semi-automatic segmentation of the fetal brain from magnetic resonance imaging

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    Background: Volumetric measurements of fetal brain maturation in the third trimester of pregnancy are key predictors of developmental outcomes. Improved understanding of fetal brain development trajectories may aid in identifying and clinically managing at-risk fetuses. Currently, fetal brain structures in magnetic resonance images (MRI) are often manually segmented, which requires both time and expertise. To facilitate the targeting and measurement of brain structures in the fetus, we compared the results of five segmentation methods applied to fetal brain MRI data to gold-standard manual tracings. Methods: Adult women with singleton pregnancies (n = 21), of whom five were scanned twice, approximately 3 weeks apart, were recruited [26 total datasets, median gestational age (GA) = 34.8, IQR = 30.9–36.6]. T2-weighted single-shot fast spin echo images of the fetal brain were acquired on 1.5T and 3T MRI scanners. Images were first combined into a single 3D anatomical volume. Next, a trained tracer manually segmented the thalamus, cerebellum, and total cerebral volumes. The manual segmentations were compared with five automatic methods of segmentation available within Advanced Normalization Tools (ANTs) and FMRIB’s Linear Image Registration Tool (FLIRT) toolboxes. The manual and automatic labels were compared using Dice similarity coefficients (DSCs). The DSC values were compared using Friedman’s test for repeated measures. Results: Comparing cerebellum and thalamus masks against the manually segmented masks, the median DSC values for ANTs and FLIRT were 0.72 [interquartile range (IQR) = 0.6–0.8] and 0.54 (IQR = 0.4–0.6), respectively. A Friedman’s test indicated that the ANTs registration methods, primarily nonlinear methods, performed better than FLIRT (p \u3c 0.001). Conclusion: Deformable registration methods provided the most accurate results relative to manual segmentation. Overall, this semi-automatic subcortical segmentation method provides reliable performance to segment subcortical volumes in fetal MR images. This method reduces the costs of manual segmentation, facilitating the measurement of typical and atypical fetal brain development

    Quantitative assessment of white matter injury in preterm neonates: Association with outcomes.

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    OBJECTIVE: To quantitatively assess white matter injury (WMI) volume and location in very preterm neonates, and to examine the association of lesion volume and location with 18-month neurodevelopmental outcomes. METHODS: Volume and location of WMI was quantified on MRI in 216 neonates (median gestational age 27.9 weeks) who had motor, cognitive, and language assessments at 18 months corrected age (CA). Neonates were scanned at 32.1 postmenstrual weeks (median) and 68 (31.5%) had WMI; of 66 survivors, 58 (87.9%) had MRI and 18-month outcomes. WMI was manually segmented and transformed into a common image space, accounting for intersubject anatomical variability. Probability maps describing the likelihood of a lesion predicting adverse 18-month outcomes were developed. RESULTS: WMI occurs in a characteristic topology, with most lesions occurring in the periventricular central region, followed by posterior and frontal regions. Irrespective of lesion location, greater WMI volumes predicted poor motor outcomes ( CONCLUSIONS: The predictive value of frontal lobe WMI volume highlights the importance of lesion location when considering the neurodevelopmental significance of WMI. Frontal lobe lesions are of particular concern

    White matter injury predicts disrupted functional connectivity and microstructure in very preterm born neonates

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    © 2018 The Authors Objective: To determine whether the spatial extent and location of early-identified punctate white matter injury (WMI) is associated with regionally-specific disruptions in thalamocortical-connectivity in very-preterm born neonates. Methods: 37 very-preterm born neonates (median gestational age: 28.1 weeks; interquartile range [IQR]: 27–30) underwent early MRI (median age 32.9 weeks; IQR: 32–35), and WMI was identified in 13 (35%) neonates. Structural T1-weighted, resting-state functional Magnetic Resonance Imaging (rs-fMRI, n = 34) and Diffusion Tensor Imaging (DTI, n = 31) sequences were acquired using 3 T-MRI. A probabilistic map of WMI was developed for the 13 neonates demonstrating brain injury. A neonatal atlas was applied to the WMI maps, rs-fMRI and DTI analyses to extract volumetric, functional and microstructural data from regionally-specific brain areas. Associations of thalamocortical-network strength and alterations in fractional anisotropy (FA, a measure of white-matter microstructure) with WMI volume were assessed in general linear models, adjusting for age at scan and cerebral volumes. Results: WMI volume in the superior (β = −0.007; p =.02) and posterior corona radiata (β = −0.01; p =.01), posterior thalamic radiations (β = −0.01; p =.005) and superior longitudinal fasciculus (β = −0.02; p =.001) was associated with reduced connectivity strength between thalamus and parietal resting-state networks. WMI volume in the left (β = −0.02; p =.02) and right superior corona radiata (β = −0.03; p =.008), left posterior corona radiata (β = −0.03; p =.01), corpus callosum (β = −0.11; p \u3c.0001) and right superior longitudinal fasciculus (β = −0.02; p =.02) was associated with functional connectivity strength between thalamic and sensorimotor networks. Increased WMI volume was also associated with decreased FA values in the corpus callosum (β = −0.004, p =.015). Conclusions: Regionally-specific alterations in early functional and structural network complexity resulting from WMI may underlie impaired outcomes

    Automatic segmentation of the hippocampus for preterm neonates from early-in-life to term-equivalent age.

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    INTRODUCTION: The hippocampus, a medial temporal lobe structure central to learning and memory, is particularly vulnerable in preterm-born neonates. To date, segmentation of the hippocampus for preterm-born neonates has not yet been performed early-in-life (shortly after birth when clinically stable). The present study focuses on the development and validation of an automatic segmentation protocol that is based on the MAGeT-Brain (Multiple Automatically Generated Templates) algorithm to delineate the hippocampi of preterm neonates on their brain MRIs acquired at not only term-equivalent age but also early-in-life. METHODS: First, we present a three-step manual segmentation protocol to delineate the hippocampus for preterm neonates and apply this protocol on 22 early-in-life and 22 term images. These manual segmentations are considered the gold standard in assessing the automatic segmentations. MAGeT-Brain, automatic hippocampal segmentation pipeline, requires only a small number of input atlases and reduces the registration and resampling errors by employing an intermediate template library. We assess the segmentation accuracy of MAGeT-Brain in three validation studies, evaluate the hippocampal growth from early-in-life to term-equivalent age, and study the effect of preterm birth on the hippocampal volume. The first experiment thoroughly validates MAGeT-Brain segmentation in three sets of 10-fold Monte Carlo cross-validation (MCCV) analyses with 187 different groups of input atlases and templates. The second experiment segments the neonatal hippocampi on 168 early-in-life and 154 term images and evaluates the hippocampal growth rate of 125 infants from early-in-life to term-equivalent age. The third experiment analyzes the effect of gestational age (GA) at birth on the average hippocampal volume at early-in-life and term-equivalent age using linear regression. RESULTS: The final segmentations demonstrate that MAGeT-Brain consistently provides accurate segmentations in comparison to manually derived gold standards (mean Dice\u27s Kappa \u3e 0.79 and Euclidean distance CONCLUSIONS: MAGeT-Brain is capable of segmenting hippocampi accurately in preterm neonates, even at early-in-life. Hippocampal asymmetry with a larger right side is demonstrated on early-in-life images, suggesting that this phenomenon has its onset in the 3rd trimester of gestation. Hippocampal volume assessed at the time of early-in-life and term-equivalent age is linearly associated with GA at birth, whereby smaller volumes are associated with earlier birth

    Early protein intake predicts functional connectivity and neurocognition in preterm born children

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    © 2021, The Author(s). Nutritional intake can promote early neonatal brain development in very preterm born neonates (\u3c 32 weeks’ gestation). In a group of 7-year-old very preterm born children followed since birth, we examined whether early nutrient intake in the first weeks of life would be associated with long-term brain function and neurocognitive skills at school age. Children underwent resting-state functional MRI (fMRI), intelligence testing (Wechsler Intelligence Scale for Children, 5th Ed) and visual-motor processing (Beery-Buktenica, 5th Ed) at 7 years. Relationships were assessed between neonatal macronutrient intakes, functional connectivity strength between thalamic and default mode networks (DMN), and neuro-cognitive function using multivariable regression. Greater functional connectivity strength between thalamic networks and DMN was associated with greater intake of protein in the first week (β = 0.17; 95% CI 0.11, 0.23, p \u3c 0.001) but lower intakes of fat (β = − 0.06; 95% CI − 0.09, − 0.02, p = 0.001) and carbohydrates (β = − 0.03; 95% CI − 0.04, − 0.01, p = 0.003). Connectivity strength was also associated with protein intake during the first month (β = 0.22; 95% CI 0.06, 0.37, p = 0.006). Importantly, greater thalamic-DMN connectivity strength was associated with higher processing speed indices (β = 26.9; 95% CI 4.21, 49.49, p = 0.02) and visual processing scores (β = 9.03; 95% CI 2.27, 15.79, p = 0.009). Optimizing early protein intake may contribute to promoting long-term brain health in preterm-born children

    Budget impact analysis of medicines : updated systematic review and implications

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    This evaluation determines whether published studies to date meet the key characteristics identified for budget impact analyses (BIA) for medicines, accomplished through a systematic review and assessment against identified key characteristics. Studies from 2001 to 2015 on "budget impact analysis" with "drug" interventions were assessed, selected based on their titles/abstracts and full texts, with their characteristics checked according to key criteria. Out of 1984 studies, 92 were identified. Of these, 95% were published in Europe and the USA. 2012 saw the largest number of publications (16%) with a decline thereafter. 48% met up to 6 or 7 out of the 9 key characteristics. Only 22% stated no conflict of interest. The results indicate low adherence to the key characteristics that should be considered for BIAs and strong conflict of interest. This is an issue since BIAs can be of fundamental importance in managing the entry of new medicines including reimbursement decisions

    Risk sharing arrangements for pharmaceuticals: potential considerations and recommendations for European payers

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    <p>Abstract</p> <p>Background</p> <p>There has been an increase in 'risk sharing' schemes for pharmaceuticals between healthcare institutions and pharmaceutical companies in Europe in recent years as an additional approach to provide continued comprehensive and equitable healthcare. There is though confusion surrounding the terminology as well as concerns with existing schemes.</p> <p>Methods</p> <p>Aliterature review was undertaken to identify existing schemes supplemented with additional internal documents or web-based references known to the authors. This was combined with the extensive knowledge of health authority personnel from 14 different countries and locations involved with these schemes.</p> <p>Results and discussion</p> <p>A large number of 'risk sharing' schemes with pharmaceuticals are in existence incorporating both financial-based models and performance-based/outcomes-based models. In view of this, a new logical definition is proposed. This is "<it>risk sharing' schemes should be considered as agreements concluded by payers and pharmaceutical companies to diminish the impact on payers' budgets for new and existing schemes brought about by uncertainty and/or the need to work within finite budgets</it>". There are a number of concerns with existing schemes. These include potentially high administration costs, lack of transparency, conflicts of interest, and whether health authorities will end up funding an appreciable proportion of a new drug's development costs. In addition, there is a paucity of published evaluations of existing schemes with pharmaceuticals.</p> <p>Conclusion</p> <p>We believe there are only a limited number of situations where 'risk sharing' schemes should be considered as well as factors that should be considered by payers in advance of implementation. This includes their objective, appropriateness, the availability of competent staff to fully evaluate proposed schemes as well as access to IT support. This also includes whether systematic evaluations have been built into proposed schemes.</p
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