Lower airway microbiota compositions differ between influenza, COVID-19 and bacteria-related acute respiratory distress syndromes.

BACKGROUND: Acute respiratory distress syndrome (ARDS) is responsible for 400,000 deaths annually worldwide. Few improvements have been made despite five decades of research, partially because ARDS is a highly heterogeneous syndrome including various types of aetiologies. Lower airway microbiota is involved in chronic inflammatory diseases and recent data suggest that it could also play a role in ARDS. Nevertheless, whether the lower airway microbiota composition varies between the aetiologies of ARDS remain unknown. The aim of this study is to compare lower airway microbiota composition between ARDS aetiologies, i.e. pulmonary ARDS due to influenza, SARS-CoV-2 or bacterial infection. METHODS: Consecutive ARDS patients according to Berlin's classification requiring invasive ventilation with PCR-confirmed influenza or SARS-CoV-2 infections and bacterial infections (> 105 CFU/mL on endotracheal aspirate) were included. Endotracheal aspirate was collected at admission, V3-V4 and ITS2 regions amplified by PCR, deep-sequencing performed on MiSeq sequencer (Illumina®) and data analysed using DADA2 pipeline. RESULTS: Fifty-three patients were included, 24 COVID-19, 18 influenza, and 11 bacterial CAP-related ARDS. The lower airway bacteriobiota and mycobiota compositions (ß-diversity) were dissimilar between the three groups (p = 0.05 and p = 0.01, respectively). The bacterial α-diversity was significantly lower in the bacterial CAP-related ARDS group compared to the COVID-19 ARDS group (p = 0.04). In contrast, influenza-related ARDS patients had higher lung mycobiota α-diversity than the COVID-19-related ARDS (p = 0 < 01). CONCLUSION: Composition of lower airway microbiota (both microbiota and mycobiota) differs between influenza, COVID-19 and bacterial CAP-related ARDS. Future studies investigating the role of lung microbiota in ARDS pathophysiology should take aetiology into account.

Vulnerability of Thalamic Nuclei at CSF Interface During the Entire Course of Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Thalamic atrophy can be used as a proxy for neurodegeneration in multiple sclerosis (MS). Some data point toward thalamic nuclei that could be affected more than others. However, the dynamic of their changes during MS evolution and the mechanisms driving their differential alterations are still uncertain. METHODS: We paired a large cohort of 1,123 patients with MS with the same number of healthy controls, all scanned with conventional 3D-T1 MRI. To highlight the main atrophic regions at the thalamic nuclei level, we validated a segmentation strategy consisting of deep learning-based synthesis of sequences, which were used for automatic multiatlas segmentation. Then, through a lifespan-based approach, we could model the dynamics of the 4 main thalamic nuclei groups. RESULTS: All analyses converged toward a higher rate of atrophy for the posterior and medial groups compared with the anterior and lateral groups. We also demonstrated that focal MS white matter lesions were associated with atrophy of groups of nuclei when specifically located within the associated thalamocortical projections. The volumes of the most affected posterior group, but also of the anterior group, were better associated with clinical disability than the volume of the whole thalamus. DISCUSSION: These findings point toward the thalamic nuclei adjacent to the third ventricle as more susceptible to neurodegeneration during the entire course of MS through potentiation of disconnection effects by regional factors. Because this information can be obtained even from standard T1-weighted MRI, this paves the way toward such an approach for future monitoring of patients with MS.

A spinal cord neuroprosthesis for locomotor deficits due to Parkinson's disease.

People with late-stage Parkinson's disease (PD) often suffer from debilitating locomotor deficits that are resistant to currently available therapies. To alleviate these deficits, we developed a neuroprosthesis operating in closed loop that targets the dorsal root entry zones innervating lumbosacral segments to reproduce the natural spatiotemporal activation of the lumbosacral spinal cord during walking. We first developed this neuroprosthesis in a non-human primate model that replicates locomotor deficits due to PD. This neuroprosthesis not only alleviated locomotor deficits but also restored skilled walking in this model. We then implanted the neuroprosthesis in a 62-year-old male with a 30-year history of PD who presented with severe gait impairments and frequent falls that were medically refractory to currently available therapies. We found that the neuroprosthesis interacted synergistically with deep brain stimulation of the subthalamic nucleus and dopaminergic replacement therapies to alleviate asymmetry and promote longer steps, improve balance and reduce freezing of gait. This neuroprosthesis opens new perspectives to reduce the severity of locomotor deficits in people with PD.

Improved Functionnectome by dissociating the contributions of white matter fiber classes to functional activation.

Integrating the underlying brain circuit's structural and functional architecture is required to explore the functional organization of cognitive networks. In that regard, we recently introduced the Functionnectome. This structural-functional method combines an fMRI acquisition with tractography-derived white matter connectivity data to map cognitive processes onto the white matter. However, this multimodal integration faces three significant challenges: (1) the necessarily limited overlap between tractography streamlines and the grey matter, which may reduce the amount of functional signal associated with the related structural connectivity; (2) the scrambling effect of crossing fibers on functional signal, as a single voxel in such regions can be structurally connected to several cognitive networks with heterogeneous functional signals; and (3) the difficulty of interpretation of the resulting cognitive maps, as crossing and overlapping white matter tracts can obscure the organization of the studied network. In the present study, we tackled these problems by developing a streamline-extension procedure and dividing the white matter anatomical priors between association, commissural, and projection fibers. This approach significantly improved the characterization of the white matter involvement in the studied cognitive processes. The new Functionnectome priors produced are now readily available, and the analysis workflow highlighted here should also be generalizable to other structural-functional approaches. We improved the Functionnectome approach to better study the involvement of white matter in brain function by separating the analysis of the three classes of white matter fibers (association, commissural, and projection fibers). This step successfully clarified the activation maps and increased their statistical significance.

Supervised tractogram filtering using Geometric Deep Learning.

A tractogram is a virtual representation of the brain white matter. It is composed of millions of virtual fibers, encoded as 3D polylines, which approximate the white matter axonal pathways. To date, tractograms are the most accurate white matter representation and thus are used for tasks like presurgical planning and investigations of neuroplasticity, brain disorders, or brain networks. However, it is a well-known issue that a large portion of tractogram fibers is not anatomically plausible and can be considered artifacts of the tracking procedure. With Verifyber, we tackle the problem of filtering out such non-plausible fibers using a novel fully-supervised learning approach. Differently from other approaches based on signal reconstruction and/or brain topology regularization, we guide our method with the existing anatomical knowledge of the white matter. Using tractograms annotated according to anatomical principles, we train our model, Verifyber, to classify fibers as either anatomically plausible or non-plausible. The proposed Verifyber model is an original Geometric Deep Learning method that can deal with variable size fibers, while being invariant to fiber orientation. Our model considers each fiber as a graph of points, and by learning features of the edges between consecutive points via the proposed sequence Edge Convolution, it can capture the underlying anatomical properties. The output filtering results highly accurate and robust across an extensive set of experiments, and fast; with a 12GB GPU, filtering a tractogram of 1M fibers requires less than a minute.

FIESTA: Autoencoders for accurate fiber segmentation in tractography.

White matter bundle segmentation is a cornerstone of modern tractography to study the brain's structural connectivity in domains such as neurological disorders, neurosurgery, and aging. In this study, we present FIESTA (FIbEr Segmentation in Tractography using Autoencoders), a reliable and robust, fully automated, and easily semi-automatically calibrated pipeline based on deep autoencoders that can dissect and fully populate white matter bundles. This pipeline is built upon previous works that demonstrated how autoencoders can be used successfully for streamline filtering, bundle segmentation, and streamline generation in tractography. Our proposed method improves bundle segmentation coverage by recovering hard-to-track bundles with generative sampling through the latent space seeding of the subject bundle and the atlas bundle. A latent space of streamlines is learned using autoencoder-based modeling combined with contrastive learning. Using an atlas of bundles in standard space (MNI), our proposed method segments new tractograms using the autoencoder latent distance between each tractogram streamline and its closest neighbor bundle in the atlas of bundles. Intra-subject bundle reliability is improved by recovering hard-to-track streamlines, using the autoencoder to generate new streamlines that increase the spatial coverage of each bundle while remaining anatomically correct. Results show that our method is more reliable than state-of-the-art automated virtual dissection methods such as RecoBundles, RecoBundlesX, TractSeg, White Matter Analysis and XTRACT. Our framework allows for the transition from one anatomical bundle definition to another with marginal calibration efforts. Overall, these results show that our framework improves the practicality and usability of current state-of-the-art bundle segmentation framework.

Atlasing white matter and grey matter joint contributions to resting-state networks in the human brain.

Over the past two decades, the study of resting-state functional magnetic resonance imaging has revealed that functional connectivity within and between networks is linked to cognitive states and pathologies. However, the white matter connections supporting this connectivity remain only partially described. We developed a method to jointly map the white and grey matter contributing to each resting-state network (RSN). Using the Human Connectome Project, we generated an atlas of 30 RSNs. The method also highlighted the overlap between networks, which revealed that most of the brain's white matter (89%) is shared between multiple RSNs, with 16% shared by at least 7 RSNs. These overlaps, especially the existence of regions shared by numerous networks, suggest that white matter lesions in these areas might strongly impact the communication within networks. We provide an atlas and an open-source software to explore the joint contribution of white and grey matter to RSNs and facilitate the study of the impact of white matter damage to these networks. In a first application of the software with clinical data, we were able to link stroke patients and impacted RSNs, showing that their symptoms aligned well with the estimated functions of the networks.

The arcuate fasciculus: Combining structure and function into surgical considerations.

BACKGROUND: Two Centuries from today, Karl Friedrich Burdach attributed the nomenclature "arcuate fasciculus" to a white matter (WM) pathway connecting the frontal to the temporal cortices by arching around the Sylvian fissure. Although this label remained essentially unvaried, the concepts related to it and the characterization of the structural properties of this bundle evolved along with the methodological progress of the past years. Concurrently, the functional relevance of the arcuate fasciculus (AF) classically restricted to the linguistic domain has extended to further cognitive abilities. These features make it a relevant structure to consider in a large variety of neurosurgical procedures. OBJECTIVE: Herein, we build on our previous review uncovering the connectivity provided by the Superior Longitudinal System, including the AF, and provide a handy representation of the structural organization of the AF by considering the frequency of defined reports in the literature. By adopting the same approach, we implement an account of which functions are mediated by this WM bundle. We highlight how this information can be transferred to the neurosurgical field by presenting four surgical cases of glioma resection requiring the evaluation of the relationship between the AF and the nearby structures, and the safest approaches to adopt. CONCLUSIONS: Our cumulative overview reports the most common wiring patterns and functional implications to be expected when approaching the study of the AF, while still considering seldom descriptions as an account of interindividual variability. Given its extension and the variety of cortical territories it reaches, the AF is a pivotal structure for different cognitive functions, and thorough understanding of its structural wiring and the functions it mediates is necessary for preserving the patient's cognitive abilities during glioma resection.

Early non-invasive ventilation and high-flow nasal oxygen therapy for preventing endotracheal intubation in hypoxemic blunt chest trauma patients: the OptiTHO randomized trial.

BACKGROUND: The benefit-risk ratio of prophylactic non-invasive ventilation (NIV) and high-flow nasal oxygen therapy (HFNC-O2) during the early stage of blunt chest trauma remains controversial because of limited data. The main objective of this study was to compare the rate of endotracheal intubation between two NIV strategies in high-risk blunt chest trauma patients. METHODS: The OptiTHO trial was a randomized, open-label, multicenter trial over a two-year period. Every adult patients admitted in intensive care unit within 48 h after a high-risk blunt chest trauma (Thoracic Trauma Severity Score ≥ 8), an estimated PaO2/FiO2 ratio < 300 and no evidence of acute respiratory failure were eligible for study enrollment (Clinical Trial Registration: NCT03943914). The primary objective was to compare the rate of endotracheal intubation for delayed respiratory failure between two NIV strategies: i) a prompt association of HFNC-O2 and "early" NIV in every patient for at least 48 h with vs. ii) the standard of care associating COT and "late" NIV, indicated in patients with respiratory deterioration and/or PaO2/FiO2 ratio ≤ 200 mmHg. Secondary outcomes were the occurrence of chest trauma-related complications (pulmonary infection, delayed hemothorax or moderate-to-severe ARDS). RESULTS: Study enrollment was stopped for futility after a 2-year study period and randomization of 141 patients. Overall, 11 patients (7.8%) required endotracheal intubation for delayed respiratory failure. The rate of endotracheal intubation was not significantly lower in patients treated with the experimental strategy (7% [5/71]) when compared to the control group (8.6% [6/70]), with an adjusted OR = 0.72 (95%IC: 0.20-2.43), p = 0.60. The occurrence of pulmonary infection, delayed hemothorax or delayed ARDS was not significantly lower in patients treated by the experimental strategy (adjusted OR = 1.99 [95%IC: 0.73-5.89], p = 0.18, 0.85 [95%IC: 0.33-2.20], p = 0.74 and 2.14 [95%IC: 0.36-20.77], p = 0.41, respectively). CONCLUSION: A prompt association of HFNC-O2 with preventive NIV did not reduce the rate of endotracheal intubation or secondary respiratory complications when compared to COT and late NIV in high-risk blunt chest trauma patients with non-severe hypoxemia and no sign of acute respiratory failure. CLINICAL TRIAL REGISTRATION: NCT03943914, Registered 7 May 2019.

Validate your white matter tractography algorithms with a reappraised ISMRM 2015 Tractography Challenge scoring system.

Since 2015, research groups have sought to produce the ne plus ultra of tractography algorithms using the ISMRM 2015 Tractography Challenge as evaluation. In particular, since 2017, machine learning has made its entrance into the tractography world. The ISMRM 2015 Tractography Challenge is the most used phantom during tractography validation, although it contains limitations. Here, we offer a new scoring system for this phantom, where segmentation of the bundles is now based on manually defined regions of interest rather than on bundle recognition. Bundles are now more reliably segmented, offering more representative metrics for future users. New code is available online. Scores of the initial 96 submissions to the challenge are updated. Overall, conclusions from the 2015 challenge are confirmed with the new scoring, but individual tractogram scores have changed, and the data is much improved at the bundle- and streamline-level. This work also led to the production of a ground truth tractogram with less broken or looping streamlines and of an example of processed data, all available on the Tractometer website. This enhanced scoring system and new data should continue helping researchers develop and evaluate the next generation of tractography techniques.

Generative Sampling in Bundle Tractography using Autoencoders (GESTA).

Current tractography methods use the local orientation information to propagate streamlines from seed locations. Many such seeds provide streamlines that stop prematurely or fail to map the true white matter pathways because some bundles are "harder-to-track" than others. This results in tractography reconstructions with poor white and gray matter spatial coverage. In this work, we propose a generative, autoencoder-based method, named GESTA (Generative Sampling in Bundle Tractography using Autoencoders), that produces streamlines achieving better spatial coverage. Compared to other deep learning methods, our autoencoder-based framework uses a single model to generate streamlines in a bundle-wise fashion, and does not require to propagate local orientations. GESTA produces new and complete streamlines for any given white matter bundle, including hard-to-track bundles. Applied on top of a given tractogram, GESTA is shown to be effective in improving the white matter volume coverage in poorly populated bundles, both on synthetic and human brain in vivo data. Our streamline evaluation framework ensures that the streamlines produced by GESTA are anatomically plausible and fit well to the local diffusion signal. The streamline evaluation criteria assess anatomy (white matter coverage), local orientation alignment (direction), and geometry features of streamlines, and optionally, gray matter connectivity. The GESTA framework offers considerable gains in bundle overlap using a reduced set of seeding streamlines with a 1.5x improvement for the "Fiber Cup", and 6x for the ISMRM 2015 Tractography Challenge datasets. Similarly, it provides a 4x white matter volume increase on the BIL&GIN callosal homotopic dataset, and successfully populates bundles on the multi-subject, multi-site, whole-brain in vivo TractoInferno dataset. GESTA is thus a novel deep generative bundle tractography method that can be used to improve the tractography reconstruction of the white matter.

Association between early nutrition support and 28-day mortality in critically ill patients: the FRANS prospective nutrition cohort study.

BACKGROUND: Current guidelines suggest the introduction of early nutrition support within the first 48 h of admission to the intensive care unit (ICU) for patients who cannot eat. In that context, we aimed to describe nutrition practices in the ICU and study the association between the introduction of early nutrition support (< 48 h) in the ICU and patient mortality at day 28 (D28) using data from a multicentre prospective cohort. METHODS: The 'French-Speaking ICU Nutritional Survey' (FRANS) study was conducted in 26 ICUs in France and Belgium over 3 months in 2015. Adult patients with a predicted ICU length of stay > 3 days were consecutively included and followed for 10 days. Their mortality was assessed at D28. We investigated the association between early nutrition (< 48 h) and mortality at D28 using univariate and multivariate propensity-score-weighted logistic regression analyses. RESULTS: During the study period, 1206 patients were included. Early nutrition support was administered to 718 patients (59.5%), with 504 patients receiving enteral nutrition and 214 parenteral nutrition. Early nutrition was more frequently prescribed in the presence of multiple organ failure and less frequently in overweight and obese patients. Early nutrition was significantly associated with D28 mortality in the univariate analysis (crude odds ratio (OR) 1.69, 95% confidence interval (CI) 1.23-2.34) and propensity-weighted multivariate analysis (adjusted OR (aOR) 1.05, 95% CI 1.00-1.10). In subgroup analyses, this association was stronger in patients ≤ 65 years and with SOFA scores ≤ 8. Compared with no early nutrition, a significant association was found of D28 mortality with early enteral (aOR 1.06, 95% CI 1.01-1.11) but not early parenteral nutrition (aOR 1.04, 95% CI 0.98-1.11). CONCLUSIONS: In this prospective cohort study, early nutrition support in the ICU was significantly associated with increased mortality at D28, particularly in younger patients with less severe disease. Compared to no early nutrition, only early enteral nutrition appeared to be associated with increased mortality. Such findings are in contrast with current guidelines on the provision of early nutrition support in the ICU and may challenge our current practices, particularly concerning patients at low nutrition risk. Trial registration ClinicalTrials.gov Identifier: NCT02599948. Retrospectively registered on November 5th 2015.

The structural connectivity of the human angular gyrus as revealed by microdissection and diffusion tractography.

The angular gyrus (AG) has been described in numerous studies to be consistently activated in various functional tasks. The angular gyrus is a critical connector epicenter linking multiple functional networks due to its location in the posterior part of the inferior parietal cortex, namely at the junction between the parietal, temporal, and occipital lobes. It is thus crucial to identify the different pathways that anatomically connect this high-order association region to the rest of the brain. Our study revisits the three-dimensional architecture of the structural AG connectivity by combining state-of-the-art postmortem blunt microdissection with advanced in vivo diffusion tractography to comprehensively describe the association, projection, and commissural fibers that connect the human angular gyrus. AG appears as a posterior "angular stone" of associative connections belonging to mid- and long-range dorsal and ventral fibers of the superior and inferior longitudinal systems, respectively, to short-range parietal, occipital, and temporal fibers, including U-shaped fibers in the posterior transverse system. Thus, AG is at a pivotal dorso-ventral position reflecting its critical role in the different functional networks, particularly in language elaboration and spatial attention and awareness in the left and right hemispheres, respectively. We also reveal striatal, thalamic, and brainstem connections and a typical inter-hemispheric homotopic callosal connectivity supporting the suggested AG role in the integration of sensory input for modulating motor control and planning. The present description of AG's highly distributed wiring diagram may drastically improve intraoperative subcortical testing and post-operative neurologic outcomes related to surgery in and around the angular gyrus.

Proposal of a Multi-Criteria Model for the Evaluation of Territorial Development Plans: An Application in Chile's Lagging Areas.

The evaluation of Territorial Development Plans (TDP) is a challenge most Latin American countries face. The problem arises in establishing a model to evaluate TDP that meets the criteria and indicators established in a national policy or regulatory framework under local needs. This study proposes an application to evaluate the TDP of the lagging areas in Chile based on the AHP multi-criteria methodology. This methodology allows to objectively unify the evaluation of the different plans, combining the different dimensions, objectives, scales, and judgments of the experts present in the evaluation process without sacrificing the quality, reliability, and participation of the actors involved. The model is flexible to changes in the criteria, as it can be updated according to the needs over time. An efficient and effective tool is provided to support decision-makers in formulating better development plans to bridge the gaps in territorial groups with high vulnerability.

The influence of regions of interest on tractography virtual dissection protocols: general principles to learn and to follow.

Efficient communication across fields of research is challenging, especially when they are at opposite ends of the physical and digital spectrum. Neuroanatomy and neuroimaging may seem close to each other. When neuroimaging studies try to isolate structures of interest, according to a specific anatomical definition, a variety of challenges emerge. It is a non-trivial task to convert the neuroanatomical knowledge to instructions and rules to be executed in neuroimaging software. In the process called "virtual dissection" used to isolate coherent white matter structure in tractography, each white matter pathway has its own set of landmarks (regions of interest) used as inclusion and exclusion criteria. The ability to segment and study these pathways is critical for scientific progress, yet, variability may depend on region placement, and be influenced by the person positioning the region (i.e., a rater). When raters' variability is taken into account, the impact made by each region of interest becomes even more difficult to interpret. A delicate balance between anatomical validity, impact on the virtual dissection and raters' reproducibility emerge. In this work, we investigate this balance by leveraging manual delineation data of a group of raters from a previous study to quantify which set of landmarks and criteria contribute most to variability in virtual dissection. To supplement our analysis, the variability of each pathway with a region-by-region exploration was performed. We present a detailed exploration and description of each region, the causes of variability and its impacts. Finally, we provide a brief overview of the lessons learned from our previous virtual dissection projects and propose recommendations for future virtual dissection protocols as well as perspectives to reach better community agreement when it comes to anatomical definitions of white matter pathways.

Tractostorm 2: Optimizing tractography dissection reproducibility with segmentation protocol dissemination.

The segmentation of brain structures is a key component of many neuroimaging studies. Consistent anatomical definitions are crucial to ensure consensus on the position and shape of brain structures, but segmentations are prone to variation in their interpretation and execution. White-matter (WM) pathways are global structures of the brain defined by local landmarks, which leads to anatomical definitions being difficult to convey, learn, or teach. Moreover, the complex shape of WM pathways and their representation using tractography (streamlines) make the design and evaluation of dissection protocols difficult and time-consuming. The first iteration of Tractostorm quantified the variability of a pyramidal tract dissection protocol and compared results between experts in neuroanatomy and nonexperts. Despite virtual dissection being used for decades, in-depth investigations of how learning or practicing such protocols impact dissection results are nonexistent. To begin to fill the gap, we evaluate an online educational tractography course and investigate the impact learning and practicing a dissection protocol has on interrater (groupwise) reproducibility. To generate the required data to quantify reproducibility across raters and time, 20 independent raters performed dissections of three bundles of interest on five Human Connectome Project subjects, each with four timepoints. Our investigation shows that the dissection protocol in conjunction with an online course achieves a high level of reproducibility (between 0.85 and 0.90 for the voxel-based Dice score) for the three bundles of interest and remains stable over time (repetition of the protocol). Suggesting that once raters are familiar with the software and tasks at hand, their interpretation and execution at the group level do not drastically vary. When compared to previous work that used a different method of communication for the protocol, our results show that incorporating a virtual educational session increased reproducibility. Insights from this work may be used to improve the future design of WM pathway dissection protocols and to further inform neuroanatomical definitions.

[Place of biomarkers in the renutrition of patients with serious Covid-19 infection: discussion around a clinical case]. / Place des biomarqueurs dans la renutrition des patients ayant une infection grave à Covid-19 : discussion autour d'un cas clinique.

Covid-19 infection is a potentially serious disease. Overweight, obesity, and diabetes are comorbidities frequently found in the severe form of the disease. Appropriate nutritional management of the patient is an integral part of care. We will discuss the renutrition of a 76-year-old, obese (BMI = 35kg/m2), malnourished patient, according to the 2021 Haute Autorité de santé criteria, with Covid-19 infection, admitted to the intensive care unit at the Bordeaux University Hospital for an acute respiratory distress syndrome. Adaptation of nutritional intakes was achieved by clinical and biological monitoring. A refeeding syndrome was treated on the first day of hospitalization in the intensive care unit. After thiamine supplementation and when kalemia and phosphatemia have been normalized, renutrition was started. Parenteral nutrition as a complement to oral nutrition was used. Parenteral nutrition was well tolerated; recommended caloric and protein intakes were achieved by the fourth day of hospitalization. The clinical evolution was favorable. In conclusion, patients with Covid-19 infection should be considered malnourished when admitted to the intensive care unit. Macro and micronutrient intakes adapted to metabolically stressed patients are essential. Biological monitoring including monitoring of ionogram, phosphate, uremia, creatinine, liver function tests and blood glucose is essential in the nutritional management of patients with serious Covid-19 infection.

Performance of the Kleihauer Betke test in the prediction of neonatal anemia.

OBJECTIVES: The aim of this study was to correlate antenatal Kleihauer (KT) test results with fetal hemoglobin at birth to find a threshold for predicting severe fetal anemia. The secondary objectives were to assess the impact of KT on obstetric management and to study the correlation between the middle cerebral artery peack systolic velocity and fetal anemia. RESULTS: One thousand forty-six KT were positive over the 10-year period, but only 147 were included from 88 patients, of which 17 fetuses were anemic. Demographic and obstetric characteristics were similar between anemic and non-anemic groups. As regards new-born, there was a higher risk of prematurity among anemic as long as a lower birth rate in accordance. While a negative correlation was observed between KT and hemoglobin at birth, no KT upper threshold could be found that was both sensitive and specific. In addition, there was no case of fetal anemia when KT was repeated, even though it increased. KT showed little usefulness in obstetrics management to help improving neonatal care for anemia. Conversely, the MCA PSV demonstrated good performance in this matter and the ROC curve area was 0.91 (figure). DISCUSSION: Feto-maternal hemorrhage is a rare but grave pathology which could lead to anemia. The most common clinical sign is reduced fetal movement and it was the main indication to perform a KT. Cardiotocography patterns suggestive of anemia are sinusoidal, micro-oscillatory and non-reactive monitoring. Ultrasound features were polyhydramnios, hydrop fetalis and increased MCA peack systolic velocity. KT was correlated with MCA PSV and with hemoglobin level at birth. However, the latter showed a better diagnostic performance. MCA PSV measurement is a powerful test to screen for fetal anemia, and should be part of the regular training of obstetricians. Indeed, this technic gives immediate and reliable results, while those of KT are delayed. CONCLUSION: The KT should not be used as a tool to screen for fetal anemia but rather as a test to explain a fetal anemia. However, the MCA PSV is reliable in this matter and give immediate result, thus obstetrician should be trained to routinely perform it.

Prevalence of white matter pathways coming into a single white matter voxel orientation: The bottleneck issue in tractography.

Characterizing and understanding the limitations of diffusion MRI fiber tractography is a prerequisite for methodological advances and innovations which will allow these techniques to accurately map the connections of the human brain. The so-called "crossing fiber problem" has received tremendous attention and has continuously triggered the community to develop novel approaches for disentangling distinctly oriented fiber populations. Perhaps an even greater challenge occurs when multiple white matter bundles converge within a single voxel, or throughout a single brain region, and share the same parallel orientation, before diverging and continuing towards their final cortical or sub-cortical terminations. These so-called "bottleneck" regions contribute to the ill-posed nature of the tractography process, and lead to both false positive and false negative estimated connections. Yet, as opposed to the extent of crossing fibers, a thorough characterization of bottleneck regions has not been performed. The aim of this study is to quantify the prevalence of bottleneck regions. To do this, we use diffusion tractography to segment known white matter bundles of the brain, and assign each bundle to voxels they pass through and to specific orientations within those voxels (i.e. fixels). We demonstrate that bottlenecks occur in greater than 50-70% of fixels in the white matter of the human brain. We find that all projection, association, and commissural fibers contribute to, and are affected by, this phenomenon, and show that even regions traditionally considered "single fiber voxels" often contain multiple fiber populations. Together, this study shows that a majority of white matter presents bottlenecks for tractography which may lead to incorrect or erroneous estimates of brain connectivity or quantitative tractography (i.e., tractometry), and underscores the need for a paradigm shift in the process of tractography and bundle segmentation for studying the fiber pathways of the human brain.

Augmented Renal Clearance, Muscle Catabolism and Urinary Nitrogen Loss: Implications for Nutritional Support in Critically Ill Trauma Patients.

The main objective of this pilot study was to determine the association between augmented renal clearance (ARC), urinary nitrogen loss and muscle wasting in critically ill trauma patients. We conducted a retrospective analysis of a local database in 162 critically ill trauma patients without chronic renal dysfunction. Nutritional-related parameters and 24 h urinary biochemical analyses were prospectively collected and averaged over the first ten days after admission. Augmented renal clearance was defined by a mean creatinine clearance (CLCR) > 130 mL/min/1.73 m2. The main outcome was the cumulated nitrogen balance at day 10. The secondary outcome was the variation of muscle psoas cross-sectional area (ΔCSA) calculated in the subgroup of patients who underwent at least two abdominal CT scans during the ICU length of stay. Overall, there was a significant correlation between mean CLCR and mean urinary nitrogen loss (normalized coefficient: 0.47 ± 0.07, p < 0.0001). ARC was associated with a significantly higher urinary nitrogen loss (17 ± 5 vs. 14 ± 4 g/day, p < 0.0001) and a lower nitrogen balance (-6 ± 5 vs. -4 ± 5 g/day, p = 0.0002), without difference regarding the mean protein intake (0.7 ± 0.2 vs. 0.7 ± 0.3 g/kg/day, p = 0.260). In the subgroup of patients who underwent a second abdominal CT scan (N = 47), both ΔCSA and %ΔCSA were higher in ARC patients (-33 [-41; -25] vs. -15 [-29; -5] mm2/day, p = 0.010 and -3 [-3; -2] vs. -1 [-3; -1] %/day, p = 0.008). Critically ill trauma patients with ARC are thus characterized by a lower nitrogen balance and increased muscle loss over the 10 first days after ICU admission. The interest of an increased protein intake (>1.5 g/kg/day) in such patients remains a matter of controversy and must be confirmed by further randomized trials.