Aurélien Mazeraud

Background: Major Depressive Disorder is highly prevalent, and approximately 30% of patients develop treatment-resistant depression (TRD). Electroconvulsive therapy (ECT) remains the most effective treatment for TRD. Given the central role of the subcallosal cingulate (SCC) in depression, we investigated whether baseline SCC functional connectivity predicts ECT response and whether default mode network (DMN) connectivity changes are associated with clinical improvement.Methods: In this longitudinal study, 47 patients with TRD undergoing ECT and 25 matched healthy controls (HC) were recruited. Usable resting-state fMRI were available for 30 patients and 22 HC. Depression severity (Montgomery–Åsberg Depression Rating Scale, MADRS) and rs-fMRI were assessed at baseline, after five ECT sessions, and at the end of treatment. SCC functional connectivity was investigated using seed-based and region-of-interest analyses.Results: ECT was associated with a reduced SCC-medial prefrontal cortex connectivity, a core DMN region (pFDR = 0.001). Higher baseline SCC connectivity with a left prefrontal cluster (MNI:–22, 28, 28) was associated with greater clinical improvement (r = 0.59; p = 0.002). This connectivity was positive in remitters, negative in non-remitters, and near zero in HC. Complementary network-level analyses further identified baseline differences between remitters and non-remitters within a PCC-centered DMN subnetwork.Conclusion: SCC- and DMN-related connectivity patterns were associated with ECT responsiveness. The opposite baseline SCC connectivity observed in remitters and non-remitters suggests distinct functional network states linked to treatment outcome. If replicated, these findings may support the development of biomarker-guided neuromodulation strategies aimed at optimizing response to ECT.

Background: Identifying and addressing long-term health and societal challenges after COVID-19 is a research priority. Objectives: To create an international, multidisciplinary COVID-19 database, and synthesise long-term outcomes, predictors and costs. Design: Systematic identification of COVID-19 data sets and meta-analysis of individual participant data on long-term outcomes after COVID-19. Setting: Contributed data were collected in clinical, community and research settings. Interventions: Interventions from original studies were included as covariates in models. Data sources: MEDLINE, Cochrane Central Register of Controlled Trials, EMBASE, Web of Science, PsycInfo ^® (American Psychological Association, Washington, DC, USA), Cumulative Index to Nursing and Allied Health Literature, World Health Organization Global Index Medicus, Epistemonikos, LitCOVID; World Health Organization International Clinical Trials Registry Platform; ClinicalTrials.gov and supplementary searches for studies (November 2019–November 2021) were searched for studies on > 10 people from cohort, case-control, survey or randomised controlled trial studies, across any setting, describing validated assessment instruments, symptoms, hospitalisation, discharge destination or mortality beyond 28-days after COVID-19 onset. Data were extracted by two independent reviewers. Methods: Principal investigators contributed fully anonymised individual participant data. Demography, equity and symptoms were described. Assessment instruments were mapped to the International Classification of Functioning, Disability and Health. Factors associated with outcomes at 3–6 months, 9–12 months and beyond 12 months of index infection, for n > 500 individual participant data and > 1 data set were described using ratio of difference, point estimates, odds ratio and 95% confidence interval, as appropriate. The Mixed Methods Appraisal Tool described study quality; models were appraised using a Grading of Recommendations Assessment, Development and Evaluation-informed approach; heterogeneity was described using I ² . Outcome measures: Included overall perception of health, multidomain cognitive function, anxiety, depression, stress, post-traumatic stress disorder, fatigue, strength, walking ability, mobility, coping with daily life, breathlessness, mortality, later hospitalisation and health-related quality of life. Results: PRECIOUS collated 116 data sets from 40 countries (individual participant data = 62,849), comprising 20 randomised controlled trials, 13 case-control, 60 cohort 2 longitudinal, 1 survey and 20 other study types. Participants’ median age was 58 years interquartile range (45–68); 34,185 (54.4%) were female; 158 unique symptoms and 137 unique assessment instruments were captured, predominantly describing International Classification of Function, Disability and Health-body functions. Women had poorer outcomes across 30/37 models, compared with men. In 15/37 models, pre-existing lung disease and increasing age were associated with poorer outcomes; hospitalisation, diabetes and chronic kidney disease were each associated with poorer outcomes in 8/37 models. Initial hospitalisation resulted in lower health-related quality of life that did not recover for up to 2 years after initial infection. Heterogeneity was low in 34/37 models; 22/37 models were of moderate and 11/37 were of low quality. Limitations: Use of secondary data limits available covariates, outcomes and time points to those included in primary data sets; evidence was primarily based on high-income countries. There was a lack of data on longer-term healthcare resource use to estimate the costs to the healthcare system. Conclusions: PRECIOUS contributes to the overall picture of long-term COVID-19 outcomes beyond the long-COVID condition and highlights poorer long-term outcomes in women and people with pre-existing comorbidities. Future work: Evidence gaps included healthcare resource use, isolation, loneliness, societal participation and return to work outcomes. Data are needed on the role of health inequity on long-term outcomes. Study registration: This study is registered as PROSPERO (CRD42020224323, IRAS ID: 293578). Funding: This award was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme (NIHR award ref: NIHR132895) and is published in full in Health and Social Care Delivery Research ; Vol. 14, No. 29. See the NIHR Funding and Awards website for further award information.

Encephalopathy is a common complication of sepsis, occurring in up to 70% of patients admitted to the intensive care unit. It is primarily characterized by

La réponse à l’agression est à la fois neuroendocrinienne, neurovégétative et comportementale. Elle implique particulièrement l’amygdale. Celle-ci joue en effet un rôle dans l’anxiété et la peur mais également dans la constitution d’un syndrome de stress post-traumatique (i.e. SSPT). La réponse comportementale à une situation de stress a été peu étudiée chez les patients admis dans un service de Réanimation, alors que des études indiquent qu’une réponse inadaptée de l’axe corticotrope ou du système nerveux autonome serait associée à une surmortalité ou la survenue d’une défaillance multiviscérale. Au décours de leur séjour en réanimation, les patients sont à haut risque de développer des troubles psychologiques (i.e. anxiété, dépression et SSPT) et cognitifs (i.e. affectant préférentiellement la mémoire et les fonctions exécutives) qui ont un impact majeur sur leur qualité de vie et qui seraient proportionnels à la sévérité de leur maladie aiguë et de son retentissement neuro-comportemental. L’objet de notre travail a été d’une part, de décrire quantitativement et qualitativement l’anxiété des patients admis de réanimation et d’en déterminer sa valeur pronostique ; d’autre part, d’étudier le lien entre activation amygdalienne et syndrome post-traumatique dans un modèle murin de sepsis par ligature-ponction caecale (i.e. CLP). Notre étude observationnelle a porté sur 354 patients (Age, 63 ans [49-73] ; Sexe F/H, 137/217) admis dans trois services de réanimation d’Île de France entre Janvier 2014 et Septembre 2016. L’anxiété était en médiane d’intensité modérée, selon l’échelle visuelle analogique (4 [1-6) et le questionnaire STAI (41 [31-53]). La moitié des patients rapportaient se sentir vulnérables (54%) ; considérer leur état grave (67 %) et avoir peur de mourir (45%). Une défaillance d’organe a été observée chez 157 (45%) des patients. Une valeur de STAI ≥ 40 (OR 1,69, 95%CI [1,02-2,84]) était associée à la survenue d’une défaillance d’organe après ajustement sur le score de défaillance d’organe SOFA à J1, la mise en route d’une ventilation mécanique non-invasive (OR 4,93 ; 95%CI [2,9-9,4]) et la gravité d’une pathologie préexistante selon le score Knaus (OC2,01 95%CI [1,21-3,33]) et la peur de mourir (OR 0,55 [0,33-0,92]). Celle-ci était significativement associée à un risque moindre de défaillance parmi les patients ayant une maladie aiguë sévère, définie par un score IGS-2 > 30 (58% vs. 37%). Cette étude indique que l’évaluation de l’anxiété est utile pour estimer le risque d’aggravation des patients de réanimation mais indique également que si son intensité est positivement corrélée à la survenue d’une défaillance, un défaut de perception d’un danger (tel que l’exprimerait la peur de mourir) en augmenterait le risque. Notre étude expérimentale a mis en évidence une activation précoce (i.e. à H6 de la CLP) et transitoire des neurones CAMK-II positif du noyau central de l’amygdale (CeA) et des anomalies tardives (i.e. J15 après CLP) de l’open-field test (test en libre champ) et du Fear-conditionning (test de formation de la mémoire aversive), traduisant respectivement un comportement type anxieux et une hypermémorisation de la peur, qui s’apparenterait à un SSPT. Nous avons procédé à une inhibition pharmacogénétique par transfection virale des neurones CAMKII, qui a entraîné une réduction de l’hyper-mémorisation aversive induite par le sepsis. L’enregistrement électrophysiologique intra-amygadalienne a mis en évidence une activité pro-épileptique ou épileptique chez les souris septiques. L’administration d’un antiépileptique, le levetiracetam au cours des 24 premières heures de la CLP a résulté en une diminution de la mortalité, de l’activation des neurones CAMKII du noyau central de l’amygdale et de l’hyper-mémorisation aversive induites par le sepsis. (...)

Background/Objectives: Artificial intelligence (AI), particularly large language models (LLMs), has demonstrated versatility in various applications but faces challenges in specialized domains like neurology. This study evaluates a specialized LLM’s capability and trustworthiness in complex neurological diagnosis, comparing its performance to neurologists in simulated clinical settings. Methods: We deployed GPT-4 Turbo (OpenAI, San Francisco, CA, US) through Neura (Sciense, New York, NY, US), an AI infrastructure with a dual-database architecture integrating “long-term memory” and “short-term memory” components on a curated neurological corpus. Five representative clinical scenarios were presented to 13 neurologists and the AI system. Participants formulated differential diagnoses based on initial presentations, followed by definitive diagnoses after receiving conclusive clinical information. Two senior academic neurologists blindly evaluated all responses, while an independent investigator assessed the verifiability of AI-generated information. Results: AI achieved a significantly higher normalized score (86.17%) compared to neurologists (55.11%, p < 0.001). For differential diagnosis questions, AI scored 85% versus 46.15% for neurologists, and for final diagnosis, 88.24% versus 70.93%. AI obtained 15 maximum scores in its 20 evaluations and responded in under 30 s compared to neurologists’ average of 9 min. All AI-provided references were classified as relevant with no hallucinatory content detected. Conclusions: A specialized LLM demonstrated superior diagnostic performance compared to practicing neurologists across complex clinical challenges. This indicates that appropriately harnessed LLMs with curated knowledge bases can achieve domain-specific relevance in complex clinical disciplines, suggesting potential for AI as a time-efficient asset in clinical practice.

Mechanical ventilation in myasthenic crisis is not standardized and is at high risk of failure. We investigated liberation from mechanical ventilation during myasthenic crisis using a prolonged spontaneous breathing trials (SBT) and sequential pulmonary function tests (PFT). In this retrospective monocenter study, we included patients admitted for a first episode of myasthenic crisis between January 2001 and January 2018. The primary outcome was the incidence of weaning failure upon first extubation in our cohort of patients with MC. Secondary objectives were to determine risk factors and outcome associated with weaning failure upon first extubation in MC. We also compared the characteristics of patients with prolonged weaning. 126 episodes of MC were analyzed. Patient’s age was 64 [42–76] years with 72/126 (56.5%) being women. The median delay between weaning initiation and first extubation was 6 [3–10] days and the median total length of MV was 14 [10–23] days. 118/126 (93.7%) patients underwent prolonged SBT of 8 h or more prior to first extubation. The overall weaning failure rate was 18/126 (14.3%). Extubation was more often successful when the factor precipitating the myasthenic crisis was identified (86/108 (79.6%) vs. 8/18 (44.4%); p = 0.004), whereas PFT was similar in failure or successes. Most weaning failures upon first extubation attempt (11/18; 61%) were attributed to an insufficient stabilization of myasthenia gravis. Duration of mechanical ventilation, an infectious trigger and maximal inspiratory pressure upon intubation were independent risk factors for prolonged weaning. In myasthenic crisis, a standardized protocol including prolonged SBT and respiratory function tests might improve the success of first extubation without prolonging mechanical ventilation. The results of this single center study warrant further evaluation in interventional trials.

[This corrects the article DOI: 10.2196/30496.].

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