Hôpital Pierre Wertheimer

Spinal muscular atrophy (SMA) types III and IV are the most common late-onset forms, and they progress slowly, making the identification of sensitive biomarkers critical. The Motor Unit Number Index (MUNIX) estimates motor unit loss and may complement traditional electrophysiological measurements such as Compound Muscle Action Potential amplitudes (CMAP). However, their respective performances have never been directly compared in adult SMA. In a French multicenter study (NCT04690998), 71 adult patients with SMA and 24 healthy controls underwent clinical and electrophysiological evaluation. MUNIX, CMAP, and Motor Unit Size Index (MUSIX) were recorded in four muscles, and sum scores (SumMUNIX, SumCMAP, SumMUSIX) were calculated. Reliability was assessed using intraclass correlation coefficients (ICCs), and associations with functional outcomes were explored. MUNIX and CMAP effectively distinguished SMA patients from controls, showing strong test - retest reliability. MUNIX showed the highest discriminative performance (AUC = 0.92), while CMAP demonstrated the strongest and most consistent associations with clinical severity. In multivariate analyses, only CMAP remained independently associated with all functional and strength measures, whereas MUNIX and MUSIX lost significance. MUNIX demonstrated the highest discriminative performance among biomarkers for differentiating SMA from controls, indicating early motor unit loss even when CMAP values were within normal limits. However, disease burden and functional impairment were better reflected by CMAP, probably due to it integrating both motor unit loss and reinnervation. The complementary nature of these profiles supports their combined use (concurrent application), and longitudinal studies are warranted to assess their responsiveness in adult SMA as well as their appropriateness for clinical trial settings.

Management of amyotrophic lateral sclerosis (ALS) is complicated by heterogeneous presentation and unpredictable disease course. This study described disease trajectories before and after initiation of non-invasive ventilation (NIV) therapy in individuals with ALS, examined the relationship between NIV initiation timing and survival and analysed health trajectory clusters. Data were extracted from the French national health insurance reimbursement system database for individuals with ≥1 reimbursement for NIV from January 2015 to December 2019, and ≥1 ALS disease code. Health trajectory clusters were determined using time sequence analysis through K-clustering. We analysed data from 3443 individuals with ALS (58% male, median age 67 years). The median (IQR) time from ALS diagnosis to NIV initiation was 10.8 (4.5-22.2) months and death occurred 21.5 (12.8-33.9) months after diagnosis. Tracheostomy/gastrostomy was performed in 3.9%/33.4% of patients, respectively. Unsupervised machine learning clustering identified four distinct patient groups. NIV initiation was late in two Clusters (A and B); these individuals were younger, had fewer comorbidities and more physiotherapy sessions before/after NIV. Survival after NIV initiation was longer in Clusters B and C; these individuals had lower rates of depression/anxiety, more prescription of mechanical in/exsufflation therapy and fewer home and emergency hospitalisations. Cluster B was unique, showing late NIV initiation and long post-NIV survival. This cluster was more likely to have spinal onset, a higher rate of obstructive sleep apnoea and fewer comorbidities. There was marked heterogeneity between patients with ALS and their care trajectories. Our data do not support a universal benefit for early initiation of NIV therapy.

Background/Objectives: Acute respiratory distress syndrome (ARDS) represents a critical complication in polytrauma patients, characterized by diffuse lung inflammation and bilateral pulmonary infiltrates with mortality rates reaching 45% in intensive care units (ICU). The heterogeneous nature of ARDS and complex clinical presentation in severely injured patients poses substantial diagnostic challenges, necessitating early prediction tools to guide timely interventions. Machine learning (ML) algorithms have emerged as promising approaches for clinical decision support, demonstrating superior performance compared to traditional scoring systems in capturing complex patterns within high-dimensional medical data. Based on the identified research gaps in early ARDS prediction for polytrauma populations, our study aimed to: (i) develop a balanced random forest (BRF) ML model for early ARDS prediction in critically ill polytrauma patients, (ii) identify the most predictive clinical features using ANOVA-based feature selection, and (iii) evaluate model performance using comprehensive metrics addressing class imbalance challenges. Methods: This retrospective cohort study analyzed 407 polytrauma patients admitted to the ICU of the Center of Traumatology and Major Burns of Ben Arous, Tunisia, between 2017 and 2021. We implemented a comprehensive ML pipeline that incorporates Tomek Links undersampling, ANOVA F-test feature selection for the top 10 predictive variables, and SMOTE oversampling with a conservative sampling rate of 0.3. The BRF classifier was trained with class weighting and evaluated using stratified 5-fold cross-validation. Performance metrics included AUROC, PR-AUC, sensitivity, specificity, F1-score, and Matthews correlation coefficient. Results: Among 407 patients, 43 developed ARDS according to the Berlin definition, representing a 10.57% incidence. The BRF model demonstrated exceptional predictive performance with an AUROC of 0.98, a sensitivity of 0.91, a specificity of 0.80, an F1-score of 0.84, and an MCC of 0.70. Precision-recall AUC reached 0.86, demonstrating robust performance despite class imbalance. During stratified cross-validation, AUROC values ranged from 0.93 to 0.99 across folds, indicating consistent model stability. The top 10 selected features included procalcitonin, PaO2 at ICU admission, 24-h pH, massive transfusion, total fluid resuscitation, presence of pneumothorax, alveolar hemorrhage, pulmonary contusion, hemothorax, and flail chest injury. Conclusions: Our BRF model provides a robust, clinically applicable tool for early prediction of ARDS in polytrauma patients using readily available clinical parameters. The comprehensive two-step resampling approach, combined with ANOVA-based feature selection, successfully addressed class imbalance while maintaining high predictive accuracy. These findings support integrating ML approaches into critical care decision-making to improve patient outcomes and resource allocation. External validation in diverse populations remains essential for confirming generalizability and clinical implementation.

a:2:{s:4:"lang";s:2:"en";s:7:"content";s:1235:"<h3></h3> MINORE (NCT04998812) is a prospective Phase IV, open-label study measuring ocrelizumab placental transfer, infant B-cell levels and detailed maternal and infant clinical outcomes, humoral immunity and safety. Thirty-five women were enrolled, 32 of whom received ocrelizumab within 6 months before last menstrual period (LMP) (3–6 months before LMP, n=18; and 0–3 months before LMP, n=14), and three women received ocrelizumab in the first trimester. The primary endpoint was the proportion of infants with B-cell levels below the lower limit of normal (LLN), measured at week 6 (W6) of life. All 35 pregnancies resulted in full-term live births. Ocrelizumab was undetectable in most infants, both in the umbilical cord blood at birth (94.3%, 33/35) and serum at W6 of life (97.0%, 32/33). All infant B-cell levels were above the age-specific LLN at W6 (100%, 34/34). Rates and types of adverse events (AEs) in mothers were in line with expected AEs during pregnancy, delivery, postpartum and infancy. Results of this study indicate that pregnancy planning is compatible with ocrelizumab treatment and support treatment decisions by clinicians and women with MS. ruth.dobson{at}qmul.ac.uk ";}

BackgroundRobust and continuous in vivo differentiation of spinal tracts along the brain–spinal cord axis is limited. We stitched brain and spinal cord diffusion tensor imaging (DTI) to create continuity between the brain and cervical spinal cord, enabling tractography along the central nervous system, producing an atlas of the spinal cord white matter.Materials and methodsThis prospective pilot study included four healthy subjects. Brain and cervical spinal cord 3-T DTI acquisitions were performed. Distortions were corrected using the Functional magnetic resonance imaging of the brain Software Library (FSL) software package. A semiautomatic stitching process was achieved using cross-correlation. Once the highest correlation peak was identified, rigid registration allowed accurate image alignment and fusion. Regions of interest were drawn in the brainstem according to atlas-guided projection tracts. Fiber tracking was performed using a deterministic approach with Diffusion Spectrum Imaging (DSI) Studio.ResultsThe median fiber length from stitched-image tractography (192 mm) was significantly greater than that from both the brain (111.5 mm) and spinal cord (115 mm) fields of view. The white matter fiber atlas described: the corticospinal tract in the medial part of the lateral funiculus; the rubrospinal tract in the lateral funiculus, overlapped with the corticospinal tract; the gracilis and cuneatus tracts in the dorsal columns; the spinothalamic tract in the ventrolateral part of the spinal cord, around the ventral horn; and the spinocerebellar tracts overlapping them, in the lateral funiculus.ConclusionStitching brain and spinal cord DTI fields of view provided an in vivo spinal cord white matter atlas in humans.Relevance statementThis study provides a detailed and individualized mapping of spinal tracts, serving as a potential tool for neurosurgical planning, particularly in procedures involving intramedullary tumors. It also may enhance the accuracy of prognostic assessments in patients with spinal cord injury, multiple sclerosis, or degenerative myelopathy.Key PointsBrain and spinal cord diffusion tensor imaging scans were stitched to map spinal tracts across the central nervous system, enabling detailed three-dimensional imaging of spinal cord pathways.The resulting images showed precise locations of spinal tracts, producing an in vivo atlas of the spinal cord white matter.This tool may help surgeons plan safer operations and better predict outcomes in spinal cord disorders.Graphical

Abstract BACKGROUND Positron emission tomography (PET) is increasingly used in patients with brain tumors, yet its adoption varies across institutions. METHODS To assess the current landscape, a cross-sectional survey was conducted among European Organization for Research and Treatment of Cancer (EORTC) – Brain Tumour Group (BTG) sites between June 2024 and August 2024. RESULTS Out of the 312 sites invited, 103 replies from 20 countries in the Europe/Middle East region were received. PET availability was reported by 96/103 (93.2%) sites, of whom 74 reported PET use in patients with brain tumors. Most frequently, PET was performed in glioma (69/74, 93.2%), followed by brain metastasis (58/74, 78.4%), meningioma (52/74, 70.3%), and CNS lymphoma (46/74, 62.2%). Amino acid PET was used at 62/71 centers (87.3%), mainly in glioma (58/59, 98.3%) and for differentiation of tumor progression from treatment-related changes (58/59, 98.3%), differential diagnosis (54/59, 91.5%), and hotspot delineation (47/59, 79.7%). Somatostatin receptor (SSTR) PET was performed at 50/68 sites (73.5%), predominantly in meningioma (48/49, 98.0%), and for patient selection before radioligand therapy (41/49, 83.7%) as well as for target volume definition in radiotherapy (33/49, 67.3%) and differential diagnosis (27/49, 55.1%). PET was covered by statutory health insurance at 46/59 (78.0%) centers for amino acid PET and 33/49 (67.3%) for SSTR PET according to self-reported information. Main reasons for not performing PET in clinical routine included limited availability of tracers (14/29, 48.3%), high cost (11/29, 37.9%), and PET considered unnecessary by referring physicians (8/29, 27.6%). CONCLUSION PET is widely used among EORTC-BTG sites, although implementation varies and is influenced by factors such as tracer availability, cost, and institutional perceptions. While further data from broader surveys including non-academic institutions is needed, the findings support the implementation of PET as clinical trial endpoint.