Transcriptional Atlas of Intestinal Immune Cells Reveals that Neuropeptide α-CGRP Modulates Group 2 Innate Lymphoid Cell Responses.

Signaling abnormalities in immune responses in the small intestine can trigger chronic type 2 inflammation involving interaction of multiple immune cell types. To systematically characterize this response, we analyzed 58,067 immune cells from the mouse small intestine by single-cell RNA sequencing (scRNA-seq) at steady state and after induction of a type 2 inflammatory reaction to ovalbumin (OVA). Computational analysis revealed broad shifts in both cell-type composition and cell programs in response to the inflammation, especially in group 2 innate lymphoid cells (ILC2s). Inflammation induced the expression of exon 5 of Calca, which encodes the alpha-calcitonin gene-related peptide (α-CGRP), in intestinal KLRG1+ ILC2s. α-CGRP antagonized KLRG1+ ILC2s proliferation but promoted IL-5 expression. Genetic perturbation of α-CGRP increased the proportion of intestinal KLRG1+ ILC2s. Our work highlights a model where α-CGRP-mediated neuronal signaling is critical for suppressing ILC2 expansion and maintaining homeostasis of the type 2 immune machinery.

Dissection and integration of bursty transcriptional dynamics for complex systems.

RNA velocity estimation is a potentially powerful tool to reveal the directionality of transcriptional changes in single-cell RNA-sequencing data, but it lacks accuracy, absent advanced metabolic labeling techniques. We developed an approach, TopicVelo, that disentangles simultaneous, yet distinct, dynamics by using a probabilistic topic model, a highly interpretable form of latent space factorization, to infer cells and genes associated with individual processes, thereby capturing cellular pluripotency or multifaceted functionality. Focusing on process-associated cells and genes enables accurate estimation of process-specific velocities via a master equation for a transcriptional burst model accounting for intrinsic stochasticity. The method obtains a global transition matrix by leveraging cell topic weights to integrate process-specific signals. In challenging systems, this method accurately recovers complex transitions and terminal states, while our use of first-passage time analysis provides insights into transient transitions. These results expand the limits of RNA velocity, empowering future studies of cell fate and functional responses.

Identifying somatic fingerprints of cancers defined by germline and environmental risk factors.

Numerous studies over the past generation have identified germline variants that increase specific cancer risks. Simultaneously, a revolution in sequencing technology has permitted high-throughput annotations of somatic genomes characterizing individual tumors. However, examining the relationship between germline variants and somatic alteration patterns is hugely challenged by the large numbers of variants in a typical tumor, the rarity of most individual variants, and the heterogeneity of tumor somatic fingerprints. In this article, we propose statistical methodology that frames the investigation of germline-somatic relationships in an interpretable manner. The method uses meta-features embodying biological contexts of individual somatic alterations to implicitly group rare mutations. Our team has used this technique previously through a multilevel regression model to diagnose with high accuracy tumor site of origin. Herein, we further leverage topic models from computational linguistics to achieve interpretable lower-dimensional embeddings of the meta-features. We demonstrate how the method can identify distinctive somatic profiles linked to specific germline variants or environmental risk factors. We illustrate the method using The Cancer Genome Atlas whole-exome sequencing data to characterize somatic tumor fingerprints in breast cancer patients with germline BRCA1/2 mutations and in head and neck cancer patients exposed to human papillomavirus.

Inflammation and Cholesterol as Predictors of Cardiovascular Events Among 13 970 Contemporary High-Risk Patients With Statin Intolerance.

BACKGROUND: Among patients treated with statin therapy to guideline-recommended cholesterol levels, residual inflammatory risk assessed by high-sensitivity C-reactive protein (hsCRP) is at least as strong a predictor of future cardiovascular events as is residual risk assessed by low-density lipoprotein cholesterol (LDLC). Whether these relationships are present among statin-intolerant patients with higher LDLC levels is uncertain but has implications for the choice of preventive therapies, including bempedoic acid, an agent that reduces both LDLC and hsCRP. METHODS: The multinational CLEAR-Outcomes trial (Cholesterol Lowering via Bempedoic Acid, an ACL-Inhibiting Regimen Outcomes Trial) randomly allocated 13 970 statin-intolerant patients to 180 mg of oral bempedoic acid daily or matching placebo and followed them for a 4-component composite of incident myocardial infarction, stroke, coronary revascularization, or cardiovascular death, and for all-cause mortality. Quartiles of increasing baseline hsCRP and LDLC were assessed as predictors of future adverse events after adjustment for traditional risk factors and randomized treatment assignment. RESULTS: Compared with placebo, bempedoic acid reduced median hsCRP by 21.6% and mean LDLC levels by 21.1% at 6 months. Baseline hsCRP was significantly associated with the primary composite end point of major cardiovascular events (highest versus lowest hsCRP quartile; hazard ratio [HR], 1.43 [95% CI, 1.24-1.65]), cardiovascular mortality (HR, 2.00 [95% CI, 1.53-2.61]), and all-cause mortality (HR, 2.21 [95% CI, 1.79-2.73]). By contrast, the relationship of baseline LDLC quartile (highest versus lowest) to future events was smaller in magnitude for the primary composite cardiovascular end point (HR, 1.19 [95% CI, 1.04-1.37]) and neutral for cardiovascular mortality (HR, 0.90 [95% CI, 0.70-1.17]) and all-cause mortality (HR, 0.95 [95% CI, 0.78-1.16]). Risks were high for those with elevated hsCRP irrespective of LDLC level. Bempedoic acid demonstrated similar efficacy in reducing cardiovascular events across all levels of hsCRP and LDLC. CONCLUSIONS: Among contemporary statin-intolerant patients, inflammation assessed by hsCRP predicted risk for future cardiovascular events and death more strongly than hyperlipidemia assessed by LDLC. Compared with placebo, bempedoic acid had similar efficacy for reducing cardiovascular risk across hsCRP and LDLC strata. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02993406.

Concomitant Left Atrial Appendage Occlusion and Transcatheter Aortic Valve Replacement Among Patients With Atrial Fibrillation.

BACKGROUND: Atrial fibrillation (AF) is common in patients undergoing transcatheter aortic valve replacement (TAVR) and is associated with increased risk of bleeding and stroke. While left atrial appendage occlusion (LAAO) is approved as an alternative to anticoagulants for stroke prevention in patients with AF, placement of these devices in patients with severe aortic stenosis, or when performed at the same time as TAVR, has not been extensively studied. METHODS: WATCH-TAVR (WATCHMAN for Patients with AF Undergoing TAVR) was a multicenter, randomized trial evaluating the safety and effectiveness of concomitant TAVR and LAAO with WATCHMAN in AF patients. Patients were randomized 1:1 to TAVR + LAAO or TAVR + medical therapy. WATCHMAN patients received anticoagulation for 45 days followed by dual antiplatelet therapy until 6 months. Anticoagulation was per treating physician preference for patients randomized to TAVR + medical therapy. The primary noninferiority end point was all-cause mortality, stroke, and major bleeding at 2 years between the 2 strategies. RESULTS: The study enrolled 349 patients (177 TAVR + LAAO and 172 TAVR + medical therapy) between December 2017 and November 2020 at 34 US centers. The mean age of patients was 81 years, and the mean scores for CHA2DS2-VASc and HAS-BLED (Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile INR, Elderly, Drugs/alcohol concomitantly) were 4.9 and 3.0, respectively. At baseline, 85.4% of patients were taking anticoagulants and 71.3% patients were on antiplatelet therapy. The cohorts were well-balanced for baseline characteristics. The incremental LAAO procedure time was 38 minutes, and the median contrast volume used for combined procedures was 119 mL versus 70 mL with TAVR alone. At the 24-month follow-up, 82.5% compared with 50.8% of patients were on any antiplatelet therapy, and 13.9% compared with 66.7% of patients were on any anticoagulation therapy in TAVR + LAAO compared with TAVR + medical therapy group, respectively. For the composite primary end point, TAVR + LAAO was noninferior to TAVR + medical therapy (22.7 versus 27.3 events per 100 patient-years for TAVR + LAAO and TAVR + medical therapy, respectively; hazard ratio, 0.86 [95% CI, 0.60-1.22]; Pnoninferiority<0.001). CONCLUSIONS: Concomitant WATCHMAN LAAO and TAVR is noninferior to TAVR with medical therapy in severe aortic stenosis patients with AF. The increased complexity and risks of the combined procedure should be considered when concomitant LAAO is viewed as an alternative to medical therapy for patients with AF undergoing TAVR. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT03173534.

Implementation Science to Achieve Equity in Heart Failure Care: A Scientific Statement From the American Heart Association.

Guideline-directed medical therapies and guideline-directed nonpharmacological therapies improve quality of life and survival in patients with heart failure (HF), but eligible patients, particularly women and individuals from underrepresented racial and ethnic groups, are often not treated with these therapies. Implementation science uses evidence-based theories and frameworks to identify strategies that facilitate uptake of evidence to improve health. In this scientific statement, we provide an overview of implementation trials in HF, assess their use of conceptual frameworks and health equity principles, and provide pragmatic guidance for equity in HF. Overall, behavioral nudges, multidisciplinary care, and digital health strategies increased uptake of therapies in HF effectively but did not include equity goals. Few HF studies focused on achieving equity in HF by engaging stakeholders, quantifying barriers and facilitators to HF therapies, developing strategies for equity informed by theory or frameworks, evaluating implementation measures for equity, and titrating strategies for equity. Among these HF equity studies, feasibility was established in using various educational strategies to promote organizational change and equitable care. A couple include ongoing randomized controlled pragmatic trials for HF equity. There is great need for additional HF implementation trials designed to promote delivery of equitable guideline-directed therapy.

RefTM: reference-guided topic modeling of single-cell chromatin accessibility data.

Single-cell analysis is a valuable approach for dissecting the cellular heterogeneity, and single-cell chromatin accessibility sequencing (scCAS) can profile the epigenetic landscapes for thousands of individual cells. It is challenging to analyze scCAS data, because of its high dimensionality and a higher degree of sparsity compared with scRNA-seq data. Topic modeling in single-cell data analysis can lead to robust identification of the cell types and it can provide insight into the regulatory mechanisms. Reference-guided approach may facilitate the analysis of scCAS data by utilizing the information in existing datasets. We present RefTM (Reference-guided Topic Modeling of single-cell chromatin accessibility data), which not only utilizes the information in existing bulk chromatin accessibility and annotated scCAS data, but also takes advantage of topic models for single-cell data analysis. RefTM simultaneously models: (1) the shared biological variation among reference data and the target scCAS data; (2) the unique biological variation in scCAS data; (3) other variations from known covariates in scCAS data.

Integrating topic modeling and word embedding to characterize violent deaths.

SignificanceWe introduce an approach to identify latent topics in large-scale text data. Our approach integrates two prominent methods of computational text analysis: topic modeling and word embedding. We apply our approach to written narratives of violent death (e.g., suicides and homicides) in the National Violent Death Reporting System (NVDRS). Many of our topics reveal aspects of violent death not captured in existing classification schemes. We also extract gender bias in the topics themselves (e.g., a topic about long guns is particularly masculine). Our findings suggest new lines of research that could contribute to reducing suicides or homicides. Our methods are broadly applicable to text data and can unlock similar information in other administrative databases.

Stages of Valvular Heart Disease Among Older Adults in the Community: The Atherosclerosis Risk in Communities Study.

BACKGROUND: Limited data exist on American College of Cardiology/American Heart Association valvular heart disease (VHD) stage prevalence, progression, and association with incident cardiovascular diseases in late life. METHODS: Participants in the ARIC study (Atherosclerosis Risk in Communities), a prospective community-based cohort study, underwent protocol echocardiography at ARIC visits 5 (2011-2013) and 7 (2018-2019), and their aortic stenosis, aortic regurgitation, mitral stenosis, and mitral regurgitation stage were defined according to American College of Cardiology/American Heart Association guidelines. The overall VHD stage prevalence at visit 5 was measured. The associations between VHD stages and incident adjudicated death, heart failure, coronary heart disease, stroke, and atrial fibrillation were assessed with Cox proportional hazard models adjusted for age, sex, race, hypertension, diabetes, prior myocardial infarction, heart failure, body mass index, study center, systolic blood pressure, estimated glomerular filtration rate, and low-density lipoprotein at visit 5. Longitudinal changes in VHD stage prevalence over ≈6 years were estimated with inverse probability of attrition weights to account for participant attrition. RESULTS: Among 6118 ARIC participants, the mean±SD age was 76±5 years, 42% were male, and 22% reported Black race. Stage A VHD was present in 39%, stage B in 17%, and stage C/D in 1.1%;, 0.7% had previously undergone valve replacement or repair. A graded association was observed between stage A, B, and C/D VHD and risk of all-cause mortality, incident heart failure, incident atrial fibrillation, and incident coronary heart disease, but not incident stroke. Similar findings were observed for stages of each valvular lesion individually. During the 6.6 years (interquartile range, 6.1-7.0 years) between visits 5 and 7 (mean age, 81±4 years), the prevalence of freedom from VHD stage decreased from 43% to 24%, whereas the prevalence of stage C/D VHD increased from 1% to 7%. CONCLUSIONS: Subclinical VHD is common in older adults, with 39% at risk (stage A) and 17% with progressive VHD (stage B), and is independently associated with risk of incident cardiovascular events. VHD stages progress over 6 years in late life, with a several-fold increase in prevalence of severe VHD (stage C/D), highlighting the public health importance of interventions to mitigate VHD progression.

Single-Cell Meta-Analysis of Neutrophil Activation in Kawasaki Disease and Multisystem Inflammatory Syndrome in Children Reveals Potential Shared Immunological Drivers.

BACKGROUND: Kawasaki disease (KD) and multisystem inflammatory syndrome in children (MIS-C) share similar clinical manifestations, including cardiovascular complications, suggesting similar underlying immunopathogenic processes. Aberrant neutrophil activation may play a crucial role in the shared pathologies of KD and MIS-C; however, the associated pathogenic mechanisms and molecular drivers remain unknown. METHODS: We performed a single-cell meta-analysis of neutrophil activation with 103 pediatric single-cell transcriptomic peripheral blood mononuclear cell data across 9 cohorts, including healthy controls, KD, MIS-C, compared with dengue virus infection, juvenile idiopathic arthritis, and pediatric celiac disease. We used a series of computational analyses to investigate the shared neutrophil transcriptional programs of KD and MIS-C that are linked to systemic damage and cardiac pathologies, and suggested Food and Drug Administration-approved drugs to consider as KD and MIS-C treatment. RESULTS: We meta-analyzed 521 950 high-quality cells. We found that blood signatures associated with risks of cardiovascular events are enriched in neutrophils of KD and MIS-C. We revealed the expansion of CD177+ neutrophils harboring hyperactivated effector functions in both KD and MIS-C, but not in healthy controls or in other viral-, inflammatory-, or immune-related pediatric diseases. KD and MIS-C CD177+ neutrophils had highly similar transcriptomes, marked by conserved signatures and pathways related to molecular damage. We found the induction of a shared neutrophil expression program, potentially regulated by SPI1 (Spi-1 proto-oncogene), which confers enhanced effector functions, especially neutrophil degranulation. CD177 and shared neutrophil expression program expressions were associated with acute stages and attenuated during KD intravenous immunoglobulin treatment and MIS-C recovery. Network analysis identified hub genes that correlated with the high activation of CD177+ neutrophils. Disease-gene association analysis revealed that the KD and MIS-C CD177+ neutrophils' shared expression program was associated with the development of coronary and myocardial disorders. Last, we identified and validated TSPO (translocator protein) and S100A12 (S100 calcium-binding protein A12) as main molecular targets, for which the Food and Drug Administration-approved drugs methotrexate, zaleplon, metronidazole, lorazepam, clonazepam, temazepam, and zolpidem, among others, are primary candidates for drug repurposing. CONCLUSIONS: Our findings indicate that CD177+ neutrophils may exert systemic pathological damage contributing to the shared morbidities in KD and MIS-C. We uncovered potential regulatory drivers of CD177+ neutrophil hyperactivation and pathogenicity that may be targeted as a single therapeutic strategy for either KD or MIS-C.

Air Pollution and Stroke: What Nurses Need to Know.

Air pollution exposure is linked to an increased risk of stroke. Elevated levels of pollution (carbon monoxide, carbon dioxide, nitrous oxide, sulfur dioxide, coarse particulate matter [PM10], and especially fine particulate matter [PM2.5]) cause systemic inflammation after the particles are inhaled and lodge into lung tissue, causing an increased incidence of stroke, hospitalizations for stroke, and stroke mortality. Until air pollution levels are remediated, assessing Air Quality Index (AQI) and following the guidelines to decrease illness from exposure is imperative. AQI levels are reported hourly, identifying ambient PM2.5 and ozone levels. When AQI levels are low, the risk of exposure to PM2.5 is low. As the AQI increases, there is more risk. It is important to take steps to decrease exposure to PM2.5, especially for those with cardiovascular comorbidities such as diabetes and those with previous stroke events. This is important information for nurses to understand and share with their patients as a risk reduction strategy.

More Than a Decade Since the Latest CONSORT Non-inferiority Trials Extension: Do Infectious Diseases Trials Do Enough?

More than a decade after the Consolidated Standards of Reporting Trials group released a reporting items checklist for non-inferiority randomized controlled trials, the infectious diseases literature continues to underreport these items. Trialists, journals, and peer reviewers should redouble their efforts to ensure infectious diseases studies meet these minimum reporting standards.

Multiscale analysis of count data through topic alignment.

Topic modeling is a popular method used to describe biological count data. With topic models, the user must specify the number of topics $K$. Since there is no definitive way to choose $K$ and since a true value might not exist, we develop a method, which we call topic alignment, to study the relationships across models with different $K$. In addition, we present three diagnostics based on the alignment. These techniques can show how many topics are consistently present across different models, if a topic is only transiently present, or if a topic splits into more topics when $K$ increases. This strategy gives more insight into the process of generating the data than choosing a single value of $K$ would. We design a visual representation of these cross-model relationships, show the effectiveness of these tools for interpreting the topics on simulated and real data, and release an accompanying R package, alto.

Reporting of Harms in Randomized Controlled Trials Published in Urology Journals: An Updated Analysis.

PURPOSE: Harms are often overlooked, but important, outcomes of randomized controlled trial reporting. Our goal was to determine if harms reporting has improved in high-impact urology journals. MATERIALS AND METHODS: Randomized controlled trials published in The Journal of Urology®, Urology, European Urology, and BJU International in 2012 and 2020 were analyzed. Each randomized controlled trial was evaluated by 2 authors in a masked-duplicate fashion to evaluate for adherence to harms reporting guidelines recommended by the Consolidated Standards of Reporting Trials (CONSORT) group. RESULTS: One hundred and thirty-two published studies met inclusion criteria. Between 2012 and 2020, there was a statistically significant increase in the median number of harms criteria reported between 2012 and 2020 (5.3 vs 7.2; P = .01). Methods criteria demonstrating the greatest improvements included item #3 "which harms were assessed," item #4a "when harm information was collected," and item #4b "methods to attribute harm to intervention." Results sections with the most improvement in reporting include item #6 "reasons for patient withdrawal," item #8a "effect size for harms," and item #8b "stratified serious + minor harms." CONCLUSIONS: Reporting of adverse events in randomized trials published in several top urology journals has demonstrated marked improvement. Studies published in 2020 reported approximately 70% of CONSORT-Harms criteria-an increase of nearly 40% since 2004. While these improvements mark significant change, deficits remain present and should be addressed to provide clinicians with the most complete perspective possible.

Comparison of Clinical Decision Support Tools to Improve Pediatric Lipid Screening.

OBJECTIVE: To test whether different clinical decision support tools increase clinician orders and patient completions relative to standard practice and each other. STUDY DESIGN: A pragmatic, patient-randomized clinical trial in the electronic health record was conducted between October 2019 and April 2020 at Geisinger Health System in Pennsylvania, with 4 arms: care gap-a passive listing recommending screening; alert-a panel promoting and enabling lipid screen orders; both; and a standard practice-no guideline-based notification-control arm. Data were analyzed for 13 346 9- to 11-year-old patients seen within Geisinger primary care, cardiology, urgent care, or nutrition clinics, or who had an endocrinology visit. Principal outcomes were lipid screening orders by clinicians and completions by patients within 1 week of orders. RESULTS: Active (care gap and/or alert) vs control arm patients were significantly more likely (P < .05) to have lipid screening tests ordered and completed, with ORs ranging from 1.67 (95% CI 1.28-2.19) to 5.73 (95% CI 4.46-7.36) for orders and 1.54 (95% CI 1.04-2.27) to 2.90 (95% CI 2.02-4.15) for completions. Alerts, with or without care gaps listed, outperformed care gaps alone on orders, with odds ratios ranging from 2.92 (95% CI 2.32-3.66) to 3.43 (95% CI 2.73-4.29). CONCLUSIONS: Electronic alerts can increase lipid screening orders and completions, suggesting clinical decision support can improve guideline-concordant screening. The study also highlights electronic record-based patient randomization as a way to determine relative effectiveness of support tools. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04118348.

A cross-sectional time series of cardiometabolic health education format preferences across sociodemographic groups.

AIMS: Health education is integral to cardiometabolic disease (CMD) management. This study aimed to assess whether and how education preferences have changed over time, and whether trends differ by sociodemographic characteristics (education status, age, ethnicity, and sex). METHODS: A cross-sectional questionnaire was deployed across five counties in the East Midlands, UK between 2017 and 2022 to adults with CMD (type 2 diabetes, cardiovascular disease or cerebrovascular disease). Respondent demographic data were collected alongside health education preferences. Statistical analyses ascertained whether demographic characteristics influenced preferences. The distribution of preferences over time was charted to identify trends. RESULTS: A total of 4301 eligible responses were collected. Face-to-face one-to-one education was preferred (first choice for 75.1% of participants) but popularity waned over the five-year period. Trends were similar amongst demographic groups. Online education showed a U-shaped trend: In 2017, 44% of respondents ranked it as acceptable, peaking at 53% in 2019, but declining again, to below base line, 43%, by 2022. This modality was more popular with participants aged younger than 65 years, but popularity in people older than 65 years increased over the study period. The popularity of printed information also declined over time across all demographic groups except those of South Asian ethnicity, for whom it remained static. CONCLUSIONS: The overwhelming preference for face-to-face one-to-one health education from a doctor or nurse highlights the importance of preserving access to this modality, even in the face of current NHS pressures and trends towards digitalisation. Trends are changing, and should continue to be monitored, including between different sociodemographic groups.

Tracing topics and trends in drug-resistant epilepsy research using a natural language processing-based topic modeling approach.

Epilepsy is a common neurological disorder affecting over 70 million people worldwide. Although many patients achieve seizure control with anti-epileptic drugs (AEDs), 30%-40% develop drug-resistant epilepsy (DRE), where seizures persist despite adequate trials of AEDs. DRE is associated with reduced quality of life, increased mortality and morbidity, and greater socioeconomic challenges. The continued intractability of DRE has fueled exponential growth in research that aims to understand and treat this serious condition. However, synthesizing this vast and continuously expanding DRE literature to derive insights poses considerable difficulties for investigators and clinicians. Conventional review methods are often prolonged, hampering the timely application of findings. More-efficient approaches to analyze the voluminous research are needed. In this study, we utilize a natural language processing (NLP)-based topic modeling approach to examine the DRE publication landscape, uncovering key topics and trends. Documents were retrieved from Scopus, preprocessed, and modeled using BERTopic. This technique employs transformer models like BERT (Bidirectional Encoder Representations from Transformers) for contextual understanding, thereby enabling accurate topic categorization. Analysis revealed 18 distinct topics spanning various DRE research areas. The 10 most common topics, including "AEDs," "Neuromodulation Therapy," and "Genomics," were examined further. "Cannabidiol," "Functional Brain Mapping," and "Autoimmune Encephalitis" emerged as the hottest topics of the current decade, and were examined further. This NLP methodology provided valuable insights into the evolving DRE research landscape, revealing shifting priorities and declining interests. Moreover, we demonstrate an efficient approach to synthesizing and visualizing patterns within extensive literature that could be applied to other research fields.

Clinical practice guidelines on the management of status epilepticus in adults: A systematic review.

OBJECTIVE: Status epilepticus (SE) is the second most common neurological emergency in adults. Despite improvements in the management of acute neurological conditions over the last decade, mortality is still durably high. Because a gap has emerged between SE management based on clinical practice guidelines (CPGs) and actual clinical practice, we conducted a systematic review of CPGs, assessing their quality, outlining commonalities and discrepancies in recommendations, and highlighting research gaps. METHODS: We searched the PubMed and EMBASE databases and other gray literature sources (nine among guideline registries, evidence-based medicine databases, point-of-care tools; seven websites of governmental organizations and international neurologic societies) in December 2021 (updated in November 2023). The units of analysis were CPGs that included recommendations on the diagnostic and/or therapeutic management of SE in adults. The quality of the CPGs was assessed using the AGREE II tool. RESULTS: Fifteen CPGs were included. The "Applicability" domain was assigned the lowest median score of 10%. The domains "Stakeholder Involvement", "Rigor of Development," and "Editorial Independence" were as well generally underrated. Recommendations on general and diagnostic management and on organizational interventions were fragmented and scattered. Recommendations on pre-hospital and hospital treatment of early-onset and refractory SE were broadly agreed, whereas there was less agreement on the treatment model and medications for established SE and super-refractory SE. SIGNIFICANCE: The CPGs for the management of SE developed in recent years are flawed by several methodological issues and discrepancies in the coverage of important topics. The gap between CPG-based management of SE and actual clinical practice may be due in part to the inherent limitations of the CPGs produced so far.

'Spin' in urology non-randomised studies comparing therapeutic interventions: a temporal analysis.

OBJECTIVE: To determine the prevalence of 'spin' (i.e., reporting practices that distort the interpretation of results by positively reflecting negative findings or downplaying potential harms) strategies and level of spin in urological observational studies and whether the use of spin has changed over time. MATERIALS AND METHODS: MEDLINE and Embase were searched to identify observational studies comparing therapeutic interventions in the top five urology journals and major urological subspecialty journals, published between 2000 and 2001, 2010 and 2011, and 2020 and 2021. RESULTS: A total of 235 studies were included. Spin was identified in 81% of studies, with a median of two strategies per study. The most commonly used strategies were inadequate implication for clinical practice (30%), causal language or causal claim (29%), and use of linguistic spin (29%). Moderate to high levels of spin were found in 55% of conclusions. From 2000 to 2020, the average number of strategies used has significantly decreased each decade (H = 27.459, P < 0.001), and the median level of spin in conclusions was significantly lower in studies published in the 2020s and 2010s than in the 2000s (H = 11.649, P = 0.003). CONCLUSIONS: Our results suggest that 81% of urological observational studies comparing therapeutic interventions contained spin. Over the past two decades, the use of spin has significantly declined, but this remains an area for improvement, with 70% of included studies published in the 2020s employing spin. Medical writing should scrupulously avoid words or phrases that are not supported by data in the manuscript.

Simplifying synthesis of the expanding glioblastoma literature: a topic modeling approach.

PURPOSE: Our study aims to discover the leading topics within glioblastoma (GB) research, and to examine if these topics have "hot" or "cold" trends. Additionally, we aim to showcase the potential of natural language processing (NLP) in facilitating research syntheses, offering an efficient strategy to dissect the landscape of academic literature in the realm of GB research. METHODS: The Scopus database was queried using "glioblastoma" as the search term, in the "TITLE" and "KEY" fields. BERTopic, an NLP-based topic modeling (TM) method, was used for probabilistic TM. We specified a minimum topic size of 300 documents and 5% probability cutoff for outlier detection. We labeled topics based on keywords and representative documents and visualized them with word clouds. Linear regression models were utilized to identify "hot" and "cold" topic trends per decade. RESULTS: Our TM analysis categorized 43,329 articles into 15 distinct topics. The most common topics were Genomics, Survival, Drug Delivery, and Imaging, while the least common topics were Surgical Resection, MGMT Methylation, and Exosomes. The hottest topics over the 2020s were Viruses and Oncolytic Therapy, Anticancer Compounds, and Exosomes, while the cold topics were Surgical Resection, Angiogenesis, and Tumor Metabolism. CONCLUSION: Our NLP methodology provided an extensive analysis of GB literature, revealing valuable insights about historical and contemporary patterns difficult to discern with traditional techniques. The outcomes offer guidance for research directions, policy, and identifying emerging trends. Our approach could be applied across research disciplines to summarize and examine scholarly literature, guiding future exploration.