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Abstract Psychotic major depression (PMD) is hypothesized to be a distinct clinical entity from nonpsychotic major depression (NPMD). However, neurobiological evidence supporting this notion is scarce. The aim of this study is to identify gray matter volume (GMV) differences between PMD and NPMD and their longitudinal change following electroconvulsive therapy (ECT). Structural magnetic resonance imaging (MRI) data from 8 independent sites in the Global ECT-MRI Research Collaboration (GEMRIC) database (n = 108; 56 PMD and 52 NPMD; mean age 71.7 in PMD and 70.2 in NPMD) were analyzed. All participants underwent MRI before and after ECT. First, cross-sectional whole-brain voxel-wise GMV comparisons between PMD and NPMD were conducted at both time points. Second, in a flexible factorial model, a main effect of time and a group-by-time interaction were examined to identify longitudinal effects of ECT on GMV and longitudinal differential effects of ECT between PMD and NPMD, respectively. Compared with NPMD, PMD showed lower GMV in the prefrontal, temporal and parietal cortex before ECT; PMD showed lower GMV in the medial prefrontal cortex (MPFC) after ECT. Although there was a significant main effect of time on GMV in several brain regions in both PMD and NPMD, there was no significant group-by-time interaction. Lower GMV in the MPFC was consistently identified in PMD, suggesting this may be a trait-like neural substrate of PMD. Longitudinal effect of ECT on GMV may not explain superior ECT response in PMD, and further investigation is needed.

Neuroimaging has played an important part in advancing our understanding of the neurobiology of obsessive–compulsive disorder (OCD). At the same time, neuroimaging studies of OCD have had notable limitations, including reliance on relatively small samples. International collaborative efforts to increase statistical power by combining samples from across sites have been bolstered by the ENIGMA consortium; this provides specific technical expertise for conducting multi‐site analyses, as well as access to a collaborative community of neuroimaging scientists. In this article, we outline the background to, development of, and initial findings from ENIGMA's OCD working group, which currently consists of 47 samples from 34 institutes in 15 countries on 5 continents, with a total sample of 2,323 OCD patients and 2,325 healthy controls. Initial work has focused on studies of cortical thickness and subcortical volumes, structural connectivity, and brain lateralization in children, adolescents and adults with OCD, also including the study on the commonalities and distinctions across different neurodevelopment disorders. Additional work is ongoing, employing machine learning techniques. Findings to date have contributed to the development of neurobiological models of OCD, have provided an important model of global scientific collaboration, and have had a number of clinical implications. Importantly, our work has shed new light on questions about whether structural and functional alterations found in OCD reflect neurodevelopmental changes, effects of the disease process, or medication impacts. We conclude with a summary of ongoing work by ENIGMA‐OCD, and a consideration of future directions for neuroimaging research on OCD within and beyond ENIGMA.

Neuroanatomical findings on youth anxiety disorders are notoriously difficult to replicate, small in effect size and have limited clinical relevance. These concerns have prompted a paradigm shift toward highly powered (that is, big data) individual-level inferences, which are data driven, transdiagnostic and neurobiologically informed. Here we built and validated supervised neuroanatomical machine learning models for individual-level inferences, using a case–control design and the largest known neuroimaging database on youth anxiety disorders: the ENIGMA-Anxiety Consortium (N = 3,343; age = 10–25 years; global sites = 32). Modest, yet robust, brain-based classifications were achieved for specific anxiety disorders (panic disorder), but also transdiagnostically for all anxiety disorders when patients were subgrouped according to their sex, medication status and symptom severity (area under the receiver operating characteristic curve, 0.59–0.63). Classifications were driven by neuroanatomical features (cortical thickness, cortical surface area and subcortical volumes) in fronto-striato-limbic and temporoparietal regions. This benchmark study within a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data.The study performed on a large, heterogeneous and multisite sample of youth with anxiety disorders reveals that only modest classification performances can be realistically achieved with machine learning using neuroanatomical data.

Cytokines have pivotal roles in immunity, making them attractive as therapeutics for a variety of immune-related disorders. However, the widespread clinical use of cytokines has been limited by their short blood half-lives and severe side effects caused by low specificity and unfavourable biodistribution. Innovations in bioengineering have aided in advancing our knowledge of cytokine biology and yielded new technologies for cytokine engineering. In this Review, we discuss how the development of bioanalytical methods, such as sequencing and high-resolution imaging combined with genetic techniques, have facilitated a better understanding of cytokine biology. We then present an overview of therapeutics arising from cytokine re-engineering, targeting and delivery, mRNA therapeutics and cell therapy. We also highlight the application of these strategies to adjust the immunological imbalance in different immune-mediated disorders, including cancer, infection and autoimmune diseases. Finally, we look ahead to the hurdles that must be overcome before cytokine therapeutics can live up to their full potential.Cytokines are key regulators of the immune system and can be recombinantly designed as therapeutics for immune-related disorders. However, the severe toxicity of recombinant cytokines limits their clinical translation. In this Review, the authors highlight bioengineering approaches for the design of clinically applicable and safe cytokine-based therapeutics.

Background The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of the course of the disease and investigate potential treatment strategies. In this study, we present the Dutch Data Warehouse (DDW), the first multicenter electronic health record (EHR) database with full-admission data from critically ill COVID-19 patients. Methods A nation-wide data sharing collaboration was launched at the beginning of the pandemic in March 2020. All hospitals in the Netherlands were asked to participate and share pseudonymized EHR data from adult critically ill COVID-19 patients. Data included patient demographics, clinical observations, administered medication, laboratory determinations, and data from vital sign monitors and life support devices. Data sharing agreements were signed with participating hospitals before any data transfers took place. Data were extracted from the local EHRs with prespecified queries and combined into a staging dataset through an extract–transform–load (ETL) pipeline. In the consecutive processing pipeline, data were mapped to a common concept vocabulary and enriched with derived concepts. Data validation was a continuous process throughout the project. All participating hospitals have access to the DDW. Within legal and ethical boundaries, data are available to clinicians and researchers. Results Out of the 81 intensive care units in the Netherlands, 66 participated in the collaboration, 47 have signed the data sharing agreement, and 35 have shared their data. Data from 25 hospitals have passed through the ETL and processing pipeline. Currently, 3464 patients are included in the DDW, both from wave 1 and wave 2 in the Netherlands. More than 200 million clinical data points are available. Overall ICU mortality was 24.4%. Respiratory and hemodynamic parameters were most frequently measured throughout a patient's stay. For each patient, all administered medication and their daily fluid balance were available. Missing data are reported for each descriptive. Conclusions In this study, we show that EHR data from critically ill COVID-19 patients may be lawfully collected and can be combined into a data warehouse. These initiatives are indispensable to advance medical data science in the field of intensive care medicine.

Introduction Bariatric surgery aims for optimal patient outcomes, often evaluated through the percentage total weight loss (%TWL). Quality registries employ funnel plots for outcome comparisons between hospitals. However, funnel plots are traditionally used for dichotomous outcomes, requiring %TWL to be dichotomized, potentially limiting feedback quality. This study evaluates whether a funnel plot around the median %TWL has better discriminatory performance than binary funnel plots for achieving at least 20% and 25% TWL. Methods All hospitals performing bariatric surgery were included from the Dutch Audit for Treatment of Obesity. A funnel plot around the median was constructed using 5-year %TWL data. Hospitals positioned above the 95% control limit were colored green and those below red. The same hospitals were plotted in the binary funnel plots for 20% and 25% TWL and colored according to their performance in the funnel plot around the median. We explored the hospital’s procedural mix in relation to %TWL performance as possible explanatory factors. Results The median-based funnel plot identified four underperforming and four outperforming hospitals, while only one underperforming and no outperforming hospitals were found with the binary funnel plot for 20% TWL. The 25% TWL binary funnel plot identified two underperforming and three outperforming hospitals. The proportion of sleeve gastrectomies performed per hospital may explain part of these results as it was negatively associated with median %TWL ( β  =  − 0.09, 95% confidence interval [− 0.13 to − 0.04]). Conclusion The funnel plot around the median discriminated better between hospitals with significantly worse and better performance than funnel plots for dichotomized %TWL outcomes. Graphical Abstract

Evaluation of post-mortem brain tissue provides insight in biological heterogeneity in dementia, often showing multiple coexisting pathologies across diagnoses. Individual or combined contributions of specific (co-)pathologies to ante-mortem diagnostic accuracy remains largely unknown. We hypothesized that discordance between the primary pathological and clinical diagnosis is related to the presence of (multiple) co-pathologies. We extracted clinical and pathological diagnostic data of 202 dementia patients from the Amsterdam Dementia Cohort (ADC) with available post-mortem autopsy reports from the Netherlands Brain Bank (NBB) between 1993-2022. Pearson chi-square tests were performed to compare the number of co-pathologies between diagnostically concordant and discordant cases, stratified by primary pathological diagnosis (R v.4.2.1). 13 primary pathological diagnoses were observed in our cohort (Table 1;Figure 1), most frequently AD (n = 89, 44%), FTLD-TDP (n = 28, 14%), and LBD (n = 23, 11%). In total, 158/202 (78%) cases had concordant clinical and primary pathological diagnoses. Amongst pathological groups the highest concordance was found in AD (80/89, 90%), followed by FTLD-TDP (25/28, 89%) and LBD (15/23, 65%). Age at death did not differ between concordant and discordant cases. Next, we characterized the occurrence of co-pathologies (Table 1;Figure 2), and observed ≥1 co-pathologies most frequently in LBD cases (21/23, 91%), followed by AD (73/89, 82%), and FTLD-TDP (22/28, 79%). In AD cases, prevalent co-pathologies were CAA (55/89, 62%), LBD (36/89, 40%), and ARTAG (15/89, 17%). In FTLD-TDP cases, prevalent co-pathologies were hippocampal sclerosis (9/28, 32%), and CAA (8/28, 29%). In LBD the most frequent co-pathology was AD (16/23, 70%). On average, the number of co-pathologies was slightly higher in concordant compared to discordant cases, but this difference was non-significant (p = 0.4). In individual pathological groups (AD, FTLD-TDP, LBD) there was also no significant difference in the number of co-pathologies between concordant and discordant cases (p =0.7, p =0.4, p =0.5). Our results highlight the pathological heterogeneity within a large memory clinic cohort, and show that neurodegenerative diseases rarely present in isolation. Although diagnostic discordance was not explained by the number of co-pathologies or age at death, additionally investigating severity of co-pathologies might provide insight into interactions between co-pathologies and clinical phenotypes.

ObjectiveEvaluate the cost-effectiveness of laparoscopic ileocaecal resection compared with infliximab in patients with ileocaecal Crohn’s disease failing conventional therapy.DesignA multicentre randomised controlled trial was performed in 29 centres in The Netherlands and the UK. Adult patients with Crohn’s disease of the terminal ileum who failed >3 months of conventional immunomodulators or steroids without signs of critical strictures were randomised to laparoscopic ileocaecal resection or infliximab. Outcome measures included quality-adjusted life-years (QALYs) based on the EuroQol (EQ) 5D-3L Questionnaire and the Inflammatory Bowel Disease Questionnaire (IBDQ). Costs were measured from a societal perspective. Analyses were performed according to the intention-to-treat principle. Missing cost and effect data were imputed using multiple imputation. Cost-effectiveness planes and cost-effectiveness acceptability curves were estimated to show uncertainty.ResultsIn total, 143 patients were randomised. Mean Crohn’s disease total direct healthcare costs per patient at 1 year were lower in the resection group compared with the infliximab group (mean difference €−8931; 95% CI €−12 087 to €−5097). Total societal costs in the resection group were lower than in the infliximab group, however not statistically significant (mean difference €−5729, 95% CI €−10 606 to €172). The probability of resection being cost-effective compared with infliximab was 0.96 at a willingness to pay (WTP) of €0 per QALY gained and per point improvement in IBDQ Score. This probability increased to 0.98 at a WTP of €20 000/QALY gained and 0.99 at a WTP of €500/point of improvement in IBDQ Score.ConclusionLaparoscopic ileocaecal resection is a cost-effective treatment option compared with infliximab.Clinical trial registration numberDutch Trial Registry NTR1150; EudraCT number 2007-005042-20 (closed on 14 October 2015).

Introduction Determining the optimal timing for extubation can be challenging in the intensive care. In this study, we aim to identify predictors for extubation failure in critically ill patients with COVID-19. Methods We used highly granular data from 3464 adult critically ill COVID patients in the multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and data from life support devices. All intubated patients with at least one extubation attempt were eligible for analysis. Transferred patients, patients admitted for less than 24 h, and patients still admitted at the time of data extraction were excluded. Potential predictors were selected by a team of intensive care physicians. The primary and secondary outcomes were extubation without reintubation or death within the next 7 days and within 48 h, respectively. We trained and validated multiple machine learning algorithms using fivefold nested cross-validation. Predictor importance was estimated using Shapley additive explanations, while cutoff values for the relative probability of failed extubation were estimated through partial dependence plots. Results A total of 883 patients were included in the model derivation. The reintubation rate was 13.4% within 48 h and 18.9% at day 7, with a mortality rate of 0.6% and 1.0% respectively. The grandient-boost model performed best (area under the curve of 0.70) and was used to calculate predictor importance. Ventilatory characteristics and settings were the most important predictors. More specifically, a controlled mode duration longer than 4 days, a last fraction of inspired oxygen higher than 35%, a mean tidal volume per kg ideal body weight above 8 ml/kg in the day before extubation, and a shorter duration in assisted mode (< 2 days) compared to their median values. Additionally, a higher C-reactive protein and leukocyte count, a lower thrombocyte count, a lower Glasgow coma scale and a lower body mass index compared to their medians were associated with extubation failure. Conclusion The most important predictors for extubation failure in critically ill COVID-19 patients include ventilatory settings, inflammatory parameters, neurological status, and body mass index. These predictors should therefore be routinely captured in electronic health records.

Background A large number of studies have shown an association between inherited thrombophilia and recurrent miscarriage. It has been hypothesized that anticoagulant therapy might reduce the number of miscarriages and stillbirth in these women. In the absence of randomized controlled trials evaluating the efficacy of anticoagulant therapy in women with inherited thrombophilia and recurrent miscarriage, a randomized trial with adequate power that addresses this question is needed. The objective of the ALIFE2 study is therefore to evaluate the efficacy of low-molecular-weight heparin (LMWH) in women with inherited thrombophilia and recurrent miscarriage, with live birth as the primary outcome. Methods/Design Randomized study of LMWH plus standard pregnancy surveillance versus standard pregnancy surveillance alone. Study population: pregnant women of less than 7 weeks’ gestation, and confirmed inherited thrombophilia with a history of 2 or more miscarriages or intra-uterine fetal deaths, or both. Setting: multi-center study in centers from the Dutch Consortium of Fertility studies; centers outside the Netherlands are currently preparing to participate. Intervention: LMWH enoxaparin 40 mg subcutaneously once daily started prior to 7 weeks gestational age plus standard pregnancy surveillance or standard pregnancy surveillance alone. Main study parameters/endpoints: the primary efficacy outcome is live birth. Secondary efficacy outcomes include adverse pregnancy outcomes, such as miscarriage, pre-eclampsia, syndrome of hemolysis, elevated liver enzymes and low platelets (HELLP syndrome), fetal growth restriction, placental abruption, premature delivery and congenital malformations. Safety outcomes include bleeding episodes, thrombocytopenia and skin reactions. Discussion After an initial period of slow recruitment, the recruitment rate for the study has increased. Improved awareness of the study and acknowledgement of the need for evidence are thought to be contributing to the improved recruitment rates. We aim to increase the number of recruiting centers in order to increase enrollment into the ALIFE2 study. The study website can be accessed via www.ALIFE2study.org . Trial registration The ALIFE2 study was registered on 19 March 2012 under registration number NTR3361