Footprint of publication selection bias on meta-analyses in medicine, environmental sciences, psychology, and economics

Publication selection bias undermines the systematic accumulation of evidence. To assess the extent of this problem, we survey over 68,000 meta-analyses containing over 700,000 effect size estimates from medicine (67,386/597,699), environmental sciences (199/12,707), psychology (605/23,563), and economics (327/91,421). Our results indicate that meta-analyses in economics are the most severely contaminated by publication selection bias, closely followed by meta-analyses in environmental sciences and psychology, whereas meta-analyses in medicine are contaminated the least. After adjusting for publication selection bias, the median probability of the presence of an effect decreased from 99.9% to 29.7% in economics, from 98.9% to 55.7% in psychology, from 99.8% to 70.7% in environmental sciences, and from 38.0% to 29.7% in medicine. The median absolute effect sizes (in terms of standardized mean differences) decreased from d = 0.20 to d = 0.07 in economics, from d = 0.37 to d = 0.26 in psychology, from d = 0.62 to d = 0.43 in environmental sciences, and from d = 0.24 to d = 0.13 in medicine.

Single-channel qEEG characteristics distinguish delirium from no delirium, but not postoperative from non-postoperative delirium

OBJECTIVE

This exploratory study examined quantitative electroencephalography (qEEG) changes in delirium and the use of qEEG features to distinguish postoperative from non-postoperative delirium.

METHODS

This project was part of the DeltaStudy, a cross-sectional,multicenterstudy in Intensive Care Units (ICUs) and non-ICU wards. Single-channel (Fp2-Pz) four-minutes resting-state EEG was analyzed in 456 patients. After calculating 98 qEEG features per epoch, random forest (RF) classification was used to analyze qEEG changes in delirium and to test whether postoperative and non-postoperative delirium could be distinguished.

RESULTS

An area under the receiver operatingcharacteristic curve (AUC) of 0.76 (95% Confidence Interval (CI) 0.71-0.80) was found when classifying delirium with a sensitivity of 0.77 and a specificity of 0.63 at the optimal operating point. The classification of postoperative versus non-postoperative delirium resulted in an AUC of 0.50 (95%CI 0.38-0.61).

CONCLUSIONS

RF classification was able to discriminate delirium from no delirium with reasonable accuracy, while also identifying new delirium qEEG markers like autocorrelation and theta peak frequency. RF classification could not distinguish postoperative from non-postoperative delirium.

SIGNIFICANCE

Single-channel EEG differentiates between delirium and no delirium with reasonable accuracy. We found no distinct EEG profile for postoperative delirium, which may suggest that delirium is one entity, whether it develops postoperatively or not.

Potential merits and flaws of large language models in epilepsy care: A critical review

The current pace of development and applications of large language models (LLMs) is unprecedented and will impact future medical care significantly. In this critical review, we provide the background to better understand these novel artificial intelligence (AI) models and how LLMs can be of future use in the daily care of people with epilepsy. Considering the importance of clinical history taking in diagnosing and monitoring epilepsy-combined with the established use of electronic health records-a great potential exists to integrate LLMs in epilepsy care. We present the current available LLM studies in epilepsy. Furthermore, we highlight and compare the most commonly used LLMs and elaborate on how these models can be applied in epilepsy. We further discuss important drawbacks and risks of LLMs, and we provide recommendations for overcoming these limitations.

Clinical characteristics and diagnoses of 1213 children referred to a first seizure clinic

OBJECTIVE

New-onset seizure-like events (SLEs) are common in children, but differentiating between epilepsy and its mimics is challenging. This study provides an overview of the clinical characteristics, diagnoses, and corresponding etiologies of children evaluated at a first seizure clinic (FSC), which will be helpful for all physicians involved in the care of children with SLEs.

METHODS

We included 1213 children who were referred to the FSC of a Dutch tertiary children's hospital over a 13-year period and described their clinical characteristics, first routine EEG recording results, and the distribution and specification of their eventual epilepsy and non-epilepsy diagnoses. The time interval to correct diagnosis and the diagnostic accuracy of the FSC were evaluated.

RESULTS

"Epilepsy" was eventually diagnosed in 407 children (33.5%), "no epilepsy" in 737 (60.8%), and the diagnosis remained "unclear" in 69 (5.7%). Epileptiform abnormalities were seen in 60.9% of the EEG recordings in the "epilepsy" group, and in 5.7% and 11.6% of the "no epilepsy" and "unclear" group, respectively. Of all children with final "epilepsy" and "no epilepsy" diagnoses, 68.6% already received their diagnosis at FSC consultation, and 2.9% of the children were initially misdiagnosed. The mean time to final diagnosis was 2.0 months, and 91.3% of all children received their final diagnosis within 12 months after the FSC consultation.

SIGNIFICANCE

We describe the largest pediatric FSC cohort to date, which can serve as a clinical frame of reference. The experience and expertise built at FSCs will improve and accelerate diagnosis in children with SLEs.

PLAIN LANGUAGE SUMMARY

Many children experience events that resemble but not necessarily are seizures. Distinguishing between seizures and seizure mimics is important but challenging. Specialized first-seizure clinics can help with this. Here, we report data from 1213 children who were referred to the first seizure clinic of a Dutch children's hospital. One-third of them were diagnosed with epilepsy. In 68.8% of all children-with and without epilepsy-the diagnosis was made during the first consultation. Less than 3% were misdiagnosed. This study may help physicians in what to expect regarding the diagnoses in children who present with events that resemble seizures.

Determinants of Functional Outcome after Pediatric Hemispherotomy

OBJECTIVE

We aimed to evaluate determinants of functional outcome after pediatric hemispherotomy in a large and recent multicenter cohort.

METHODS

We retrospectively investigated the functional outcomes of 455 children who underwent hemispherotomy at 5 epilepsy centers in 2000-2016. We identified determinants of unaided walking, voluntary grasping with the hemiplegic hand, and speaking through Bayesian multivariable regression modeling using missing data imputation.

RESULTS

Seventy-five percent of children were seizure-free, and 44% stopped antiseizure medication at a 5.1-year mean follow-up (range = 1-17.1). Seventy-seven percent of children could walk unaided, 8% could grasp voluntarily, and 68% could speak at the last follow-up. Children were unlikely to walk when they had contralateral magnetic resonance imaging (MRI) abnormalities (40/73, p = 0.04), recurrent seizures following hemispherotomy (62/109, p = 0.04), and moderately (50/61, p = 0.03) or severely impaired (127/199, p = 0.001) postsurgical intellectual functioning, but were likely to walk when they were older at outcome determination (p = 0.01). Children were unlikely to grasp voluntarily with the hand contralateral to surgery when they had Rasmussen encephalitis (0/61, p = 0.001) or Sturge-Weber syndrome (0/32, p = 0.007). Children were unlikely to speak when they had contralateral MRI abnormalities (30/69, p = 0.002) and longer epilepsy duration (p = 0.01), but likely to speak when they had Sturge-Weber syndrome (29/35, p = 0.01), were older at surgery (p = 0.04), and were older at outcome determination (p < 0.001).

INTERPRETATION

Etiology and bilaterality of structural brain abnormalities were key determinants of functional outcome after hemispherotomy. Longer epilepsy duration affected language outcomes. Not surprisingly, walking and talking ability increased with older age at outcome evaluation. ANN NEUROL 2024;95:377-387.

Variation in seizure risk increases from antiseizure medication withdrawal among patients with well-controlled epilepsy: A pooled analysis

OBJECTIVE

Guidelines suggest considering antiseizure medication (ASM) discontinuation in seizure-free patients with epilepsy. Past work has poorly explored how discontinuation effects vary between patients. We evaluated (1) what factors modify the influence of discontinuation on seizure risk; and (2) the range of seizure risk increase due to discontinuation across low- versus high-risk patients.

METHODS

We pooled three datasets including seizure-free patients who did and did not discontinue ASMs. We conducted time-to-first-seizure analyses. First, we evaluated what individual patient factors modified the relative effect of ASM discontinuation on seizure risk via interaction terms. Then, we assessed the distribution of 2-year risk increase as predicted by our adjusted logistic regressions.

RESULTS

We included 1626 patients, of whom 678 (42%) planned to discontinue all ASMs. The mean predicted 2-year seizure risk was 43% [95% confidence interval (CI) 39%-46%] for discontinuation versus 21% (95% CI 19%-24%) for continuation. The mean 2-year absolute seizure risk increase was 21% (95% CI 18%-26%). No individual interaction term was significant after correcting for multiple comparisons. The median [interquartile range (IQR)] risk increase across patients was 19% (IQR 14%-24%; range 7%-37%). Results were unchanged when restricting analyses to only the two RCTs.

SIGNIFICANCE

No single patient factor significantly modified the influence of discontinuation on seizure risk, although we captured how absolute risk increases change for patients that are at low versus high risk. Patients should likely continue ASMs if even a 7% 2-year increase in the chance of any more seizures would be too much and should likely discontinue ASMs if even a 37% risk increase would be too little. In between these extremes, individualized risk calculation and a careful understanding of patient preferences are critical. Future work will further develop a two-armed individualized seizure risk calculator and contextualize seizure risk thresholds below which to consider discontinuation.

PLAIN LANGUAGE SUMMARY

Understanding how much antiseizure medications (ASMs) decrease seizure risk is an important part of determining which patients with epilepsy should be treated, especially for patients who have not had a seizure in a while. We found that there was a wide range in the amount that ASM discontinuation increases seizure risk-between 7% and 37%. We found that no single patient factor modified that amount. Understanding what a patient's seizure risk might be if they discontinued versus continued ASM treatment is critical to making informed decisions about whether the benefit of treatment outweighs the downsides.

Toward responsible clinical n-of-1 strategies for rare diseases

N-of-1 strategies can provide high-quality evidence of treatment efficacy at the individual level and optimize evidence-based selection of off-label treatments for patients with rare diseases. Given their design characteristics, n-of-1 strategies are considered to lay at the intersection between medical research and clinical care. Therefore, whether n-of-1 strategies should be governed by research or care regulations remains a debated issue. Here, we delineate differences between medical research and optimized clinical care, and distinguish the regulations which apply to either. We also set standards for responsible optimized clinical n-of-1 strategies with (off-label) treatments for rare diseases. Implementing clinical n-of-1 strategies as defined here could aid in optimized treatment selection for such diseases.

Methodology reporting improved over time in 176,469 randomized controlled trials

OBJECTIVES

To describe randomized controlled trial (RCT) methodology reporting over time.

STUDY DESIGN AND SETTING

We used a deep learning-based sentence classification model based on the Consolidated Standards of Reporting Trials (CONSORT) statement, considered minimum requirements for reporting RCTs. We included 176,469 RCT reports published between 1966 and 2018. We analyzed the reporting trends over 5-year time periods, grouping trials from 1966 to 1990 in a single stratum. We also explored the effect of journal impact factor (JIF) and medical discipline.

RESULTS

Population, Intervention, Comparator, Outcome (PICO) items were commonly reported during each period, and reporting increased over time (e.g., interventions: 79.1% during 1966-1990 to 87.5% during 2010-2018). Reporting of some methods information has increased, although there is room for improvement (e.g., sequence generation: 10.8-41.8%). Some items are reported infrequently (e.g., allocation concealment: 5.1-19.3%). The number of items reported and JIF are weakly correlated (Pearson's r (162,702) = 0.16, P < 0.001). The differences in the proportion of items reported between disciplines are small (<10%).

CONCLUSION

Our analysis provides large-scale quantitative support for the hypothesis that RCT methodology reporting has improved over time. Extending these models to all CONSORT items could facilitate compliance checking during manuscript authoring and peer review, and support metaresearch.

fMRI connectivity as a biomarker of antipsychotic treatment response: A systematic review

BACKGROUND

Antipsychotic drugs are the first-choice therapy for psychotic episodes, but antipsychotic treatment response (AP-R) is unpredictable and only becomes clear after weeks of therapy. A biomarker for AP-R is currently unavailable. We reviewed the evidence for the hypothesis that functional magnetic resonance imaging functional connectivity (fMRI-FC) is a predictor of AP-R or could serve as a biomarker for AP-R in psychosis.

METHOD

A systematic review of longitudinal fMRI studies examining the predictive performance and relationship between FC and AP-R was performed following PRISMA guidelines. Technical and clinical aspects were critically assessed for the retrieved studies. We addressed three questions: Q1) is baseline fMRI-FC related to subsequent AP-R; Q2) is AP-R related to a change in fMRI-FC; and Q3) can baseline fMRI-FC predict subsequent AP-R?

RESULTS

In total, 28 articles were included. Most studies were of good quality. fMRI-FC analysis pipelines included seed-based-, independent component- / canonical correlation analysis, network-based statistics, and graph-theoretical approaches. We found high heterogeneity in methodological approaches and results. For Q1 (N = 17) and Q2 (N = 18), the most consistent evidence was found for FC between the striatum and ventral attention network as a potential biomarker of AP-R. For Q3 (N = 9) accuracy's varied form 50 till 93%, and prediction models were based on FC between various brain regions.

CONCLUSION

The current fMRI-FC literature on AP-R is hampered by heterogeneity of methodological approaches. Methodological uniformity and further improvement of the reliability and validity of fMRI connectivity analysis is needed before fMRI-FC analysis can have a place in clinical applications of antipsychotic treatment.

Gastrointestinal and eating problems in SCN1A-related seizure disorders

OBJECTIVE

Our study aimed to describe the prevalence and characteristics of gastrointestinal and eating problems in Dravet syndrome (DS) and other SCN1A-related seizure disorders and to determine the association between the occurrence of gastrointestinal and eating problems and core features of DS.

METHODS

Gastrointestinal and eating problems were assessed with a questionnaire in a Dutch cohort of participants with an SCN1A-related seizure disorder. Associations between the number of gastrointestinal and eating problems and core features of DS, seizure severity, level of intellectual disability, impaired mobility, behavioral problems, and use of anti-seizure medication, were explored by multivariate ordinal regression analyses. Symptoms were divided into the categories dysphagia-related, behavioral, and gastrointestinal, and were assessed separately.

RESULTS

One hundred sixty-nine participants with an SCN1A-related seizure disorder, of whom 118 (69.8%) with DS and 51 (30.2%) with Generalized Epilepsy with Febrile Seizures Plus / Febrile Seizures (GEFS+/FS), the non-DS phenotype, were evaluated. Gastrointestinal and eating problems were highly prevalent in DS participants, 50.8% had more than three symptoms compared to 3.9% of non-DS participants. Of participants with DS, 17.8% were fully or partly fed by a gastric tube. Within the three different symptom categories, the most prevalent dysphagia-related symptom was drooling (60.7%), distraction during mealtimes (61.4%) the most prevalent behavioral symptom, and constipation and loss of appetite (both 50.4%) the most prevalent gastrointestinal symptoms. DS participants who use a wheelchair (odds ratio (OR) 4.9 95%CI (1.9-12.8) compared to walking without aid), who use ≥3 anti-seizure medications (ASM) (OR 5.9 95%CI (1.9-18.2) compared to <3 ASM) and who have behavioral problems (OR 3.0 95%CI (1.1-8.1) compared to no behavioral problems) had more gastrointestinal and eating problems.

CONCLUSION

Gastrointestinal and eating problems are frequently reported symptoms in DS. Distinguishing between symptom categories will lead to tailored management of patients at risk, will improve early detection, and enable a timely referral to a dietitian, behavioral expert, and/or speech therapist, ultimately aiming to improve the quality of life of both patients and caregivers.

Continuous Theta-Burst Stimulation of the Contralesional Primary Motor Cortex for Promotion of Upper Limb Recovery After Stroke: A Randomized Controlled Trial

BACKGROUND

Despite improvements in acute stroke therapies and rehabilitation strategies, many stroke patients are left with long-term upper limb motor impairment. We assessed whether an inhibitory repetitive transcranial magnetic stimulation treatment paradigm started within 3 weeks after stroke onset promotes upper limb motor recovery.

METHODS

We performed a single-center randomized, sham-controlled clinical trial. Patients with ischemic stroke or intracerebral hemorrhage and unilateral upper limb motor impairment were randomized to 10 daily sessions of active or sham continuous theta-burst stimulation (cTBS) of the contralesional primary motor cortex combined with standard upper limb therapy, started within 3 weeks after stroke onset. The primary outcome was the change in the Action Research Arm Test score from baseline (pretreatment) at 3 months after stroke. Secondary outcomes included the score on the modified Rankin Scale at 3 months and the length of stay at the rehabilitation center. Statistical analyses were performed using mixed models for repeated measures.

RESULTS

We enrolled 60 patients between April 2017 and February 2021, of whom 29 were randomized to active cTBS and 31 to sham cTBS. One patient randomized to active cTBS withdrew consent before the intervention and was excluded from the analyses. The mean difference in the change in Action Research Arm Test score from baseline at 3 months poststroke was 9.6 points ([95% CI, 1.2-17.9]; P=0.0244) in favor of active cTBS. Active cTBS was associated with better scores on the modified Rankin Scale at 3 months (OR, 0.2 [95% CI, 0.1-0.8]; P=0.0225) and with an 18 days shorter length of stay at the rehabilitation center than sham cTBS ([95% CI, 0.0-36.4]; P=0.0494). There were no serious adverse events.

CONCLUSIONS

Ten daily sessions of cTBS of the contralesional primary motor cortex combined with upper limb training, started within 3 weeks after stroke onset, promote recovery of the upper limb, reduce disability and dependence and leads to earlier discharge from the rehabilitation center.

REGISTRATION

URL: https://trialsearch.who.int/; Unique identifier: NTR6133.

The importance of discriminative power rather than significance when evaluating potential clinical biomarkers in epilepsy research

OBJECTIVE

The quest for epilepsy biomarkers is on the rise. Variables with statistically significant group-level differences are often misinterpreted as biomarkers with sufficient discriminative power. This study aimed to demonstrate the relationship between significant group-level differences and a variable's power to discriminate between individuals.

METHODS

We simulated normal-distributed datasets from hypothetical populations with varying sample sizes (25-800), effect sizes (Cohen's d: .25-2.50), and variability (standard deviation: 10-35) to assess the impact of these parameters on significance and discriminative power. The simulation data were illustrated by assessing the discriminative power of a potential real-case biomarker-the EEG beta band power-to diagnose generalized epilepsy, using data from 66 children with generalized epilepsy and 385 controls. Additionally, we evaluated recently reported epilepsy biomarkers by comparing their effect sizes to our simulation-derived effect size criterion.

RESULTS

Group size affects significance but not discriminative power. Discriminative power is much more related to variability and effect size. Our real data example supported these simulation results by demonstrating that group-level significance does not translate, one to one, into discriminative power. Although we found a significant difference in the beta band power between children with and without epilepsy, the discriminative power was poor due to a small effect size. A Cohen's d of at least 1.25 is required to reach good discriminative power in univariable prediction modeling. Slightly over 60% of the biomarkers in our literature search met this criterion.

SIGNIFICANCE

Rather than statistical significance of group-level differences, effect size should be used as an indicator of a variable's biomarker potential. The minimal required effects size for individual biomarkers-a Cohen's d of 1.25-is large. This calls for multivariable approaches, in which combining multiple variables with smaller effect sizes could increase the overall effect size and discriminative power.

A consensus protocol for functional connectivity analysis in the rat brain

Task-free functional connectivity in animal models provides an experimental framework to examine connectivity phenomena under controlled conditions and allows for comparisons with data modalities collected under invasive or terminal procedures. Currently, animal acquisitions are performed with varying protocols and analyses that hamper result comparison and integration. Here we introduce StandardRat, a consensus rat functional magnetic resonance imaging acquisition protocol tested across 20 centers. To develop this protocol with optimized acquisition and processing parameters, we initially aggregated 65 functional imaging datasets acquired from rats across 46 centers. We developed a reproducible pipeline for analyzing rat data acquired with diverse protocols and determined experimental and processing parameters associated with the robust detection of functional connectivity across centers. We show that the standardized protocol enhances biologically plausible functional connectivity patterns relative to previous acquisitions. The protocol and processing pipeline described here is openly shared with the neuroimaging community to promote interoperability and cooperation toward tackling the most important challenges in neuroscience.

Unrestricted weighted least squares represent medical research better than random effects in 67,308 Cochrane meta-analyses

OBJECTIVE

To evaluate how well meta-analysis mean estimators represent reported medical research and establish which meta-analysis method is better using widely accepted model selection measures: Akaike information criterion (AIC) and Bayesian information criterion (BIC).

STUDY DESIGN AND SETTING

We compiled 67,308 meta-analyses from the Cochrane Database of Systematic Reviews (CDSR) published between 1997 and 2020, collectively encompassing nearly 600,000 medical findings. We compared unrestricted weighted least squares (UWLS) versus random effects (RE); fixed effect (FE) was also secondarily considered.

RESULTS

The probability that a randomly selected systematic review from the CDSR would favor UWLS over RE is 79.4% (CI_95%: 79.1; 79.7). The odds ratio that a Cochrane systematic review would substantially favor UWLS over RE is 9.33 (CI_95%: 8.94; 9.73) using the conventional criterion that a difference in AIC (or BIC) of two or larger represents a 'substantial' improvement. UWLS's advantage over RE is most prominent in the presence of low heterogeneity. However, UWLS also has a notable advantage in high heterogeneity research, across different sizes of meta-analyses and types of outcomes.

CONCLUSIONS

UWLS frequently dominates RE in medical research, often substantially. Thus, the unrestricted weighted least squares should be reported routinely in the meta-analysis of clinical trials.

Not surgical technique, but etiology, contralateral MRI, prior surgery, and side of surgery determine seizure outcome after pediatric hemispherotomy

OBJECTIVE

We aimed to assess determinants of seizure outcome following pediatric hemispherotomy in a contemporary cohort.

METHODS

We retrospectively analyzed the seizure outcomes of 457 children who underwent hemispheric surgery in five European epilepsy centers between 2000 and 2016. We identified variables related to seizure outcome through multivariable regression modeling with missing data imputation and optimal group matching, and we further investigated the role of surgical technique by Bayes factor (BF) analysis.

RESULTS

One hundred seventy seven children (39%) underwent vertical and 280 children (61%) underwent lateral hemispherotomy. Three hundred forty-four children (75%) achieved seizure freedom at a mean follow-up of 5.1 years (range 1 to 17.1). We identified acquired etiology other than stroke (odds ratio [OR] 4.4, 95% confidence interval (CI) 1.1-18.0), hemimegalencephaly (OR 2.8, 95% CI 1.1-7.3), contralateral magnetic resonance imaging (MRI) findings (OR 5.5, 95% CI 2.7-11.1), prior resective surgery (OR 5.0, 95% CI 1.8-14.0), and left hemispherotomy (OR 2.3, 95% CI 1.3-3.9) as significant determinants of seizure recurrence. We found no evidence of an impact of the hemispherotomy technique on seizure outcome (the BF for a model including the hemispherotomy technique over the null model was 1.1), with comparable overall major complication rates for different approaches.

SIGNIFICANCE

Knowledge about the independent determinants of seizure outcome following pediatric hemispherotomy will improve the counseling of patients and families. In contrast to previous reports, we found no statistically relevant difference in seizure-freedom rates between the vertical and horizontal hemispherotomy techniques when accounting for different clinical features between groups.

Transforming epilepsy research: A systematic review on natural language processing applications

Despite improved ancillary investigations in epilepsy care, patients' narratives remain indispensable for diagnosing and treatment monitoring. This wealth of information is typically stored in electronic health records and accumulated in medical journals in an unstructured manner, thereby restricting complete utilization in clinical decision-making. To this end, clinical researchers increasing apply natural language processing (NLP)-a branch of artificial intelligence-as it removes ambiguity, derives context, and imbues standardized meaning from free-narrative clinical texts. This systematic review presents an overview of the current NLP applications in epilepsy and discusses the opportunities and drawbacks of NLP alongside its future implications. We searched the PubMed and Embase databases with a "natural language processing" and "epilepsy" query (March 4, 2022) and included original research articles describing the application of NLP techniques for textual analysis in epilepsy. Twenty-six studies were included. Fifty-eight percent of these studies used NLP to classify clinical records into predefined categories, improving patient identification and treatment decisions. Other applications of NLP had structured clinical information retrieval from electronic health records, scientific papers, and online posts of patients. Challenges and opportunities of NLP applications for enhancing epilepsy care and research are discussed. The field could further benefit from NLP by replicating successes in other health care domains, such as NLP-aided quality evaluation for clinical decision-making, outcome prediction, and clinical record summarization.

Indicators of questionable research practices were identified in 163,129 randomized controlled trials

OBJECTIVES

To explore indicators of the following questionable research practices (QRPs) in randomized controlled trials (RCTs): (1) risk of bias in four domains (random sequence generation, allocation concealment, blinding of participants and personnel, and blinding of outcome assessment); (2) modifications in primary outcomes that were registered in trial registration records (proxy for selective reporting bias); (3) ratio of the achieved to planned sample sizes; and (4) statistical discrepancy.

STUDY DESIGN AND SETTING

Full texts of all human RCTs published in PubMed in 1996-2017 were automatically identified and information was collected automatically. Potential indicators of QRPs included author-specific, publication-specific, and journal-specific characteristics. Beta, logistic, and linear regression models were used to identify associations between these potential indicators and QRPs.

RESULTS

We included 163,129 RCT publications. The median probability of bias assessed using Robot Reviewer software ranged between 43% and 63% for the four risk of bias domains. A more recent publication year, trial registration, mentioning of CONsolidated Standards Of Reporting Trials-checklist, and a higher journal impact factor were consistently associated with a lower risk of QRPs.

CONCLUSION

This comprehensive analysis provides an insight into indicators of QRPs. Researchers should be aware that certain characteristics of the author team and publication are associated with a higher risk of QRPs.

Antiseizure Medication Withdrawal Practice Patterns: A Survey Among Members of the American Academy of Neurology and EpiCARE

Background and Objectives

To describe neurologist practice patterns, challenges, and decision support needs pertaining to withdrawal of antiseizure medications (ASMs) in patients with well-controlled epilepsy.

Methods

We sent an electronic survey to (1) US and (2) European physician members of the American Academy of Neurology and (3) members of EpiCARE, a European Reference Network for rare and complex epilepsies. Analyses included frequencies and percentages, and we showed distributions through histograms and violin plots.

Results

We sent the survey to 4,923 individuals; 463 consented, 411 passed eligibility questions, and 287 responded to at least 1 of these questions. Most respondents indicated that they might ever consider ASM withdrawal, with respondents treating mostly children being more likely ever to consider withdrawal (e.g., medical monotherapy: children 96% vs adults 81%; p < 0.05). The most important factors when making decisions included seizure probability (83%), consequences of seizures (73%), and driving (74%). The top challenges when making decisions included unclear seizure probability (81%), inadequate guidelines (50%), and difficulty communicating probabilities (45%). Respondents would consider withdrawal after a median of 2-year seizure freedom, but also responded that they would begin withdrawal on average only when the postwithdrawal seizure relapse risk in the coming 2 years was less than 15%-30%. Wide variation existed in the use of words or numbers in respondents' counsel methods, for example, percentages vs frequencies or probability of seizure freedom vs seizure. The most highly rated point-of-care methods to inform providers of calculated risk were Kaplan-Meier curves and showing percentages only, rather than pictographs or text recommendations alone.

Discussion

Most surveyed neurologists would consider withdrawing ASMs in seizure-free individuals. Seizure probability was the largest factor driving decisions, yet estimating seizure probabilities was the greatest challenge. Respondents on average indicated that they may withdraw ASM after a minimum seizure-free duration of 2 years, yet also on average were willing to withdraw when seizure risk decreased below 15%-30%, which is lower than most patients' postwithdrawal risk at 2-year seizure freedom and lower than the equivalent even of a first seizure of life. These findings will inform future efforts at developing decision support tools aimed at optimizing ASM withdrawal decisions.

Antiseizure medication withdrawal risk estimation and recommendations: A survey of American Academy of Neurology and EpiCARE members

OBJECTIVE

Choosing candidates for antiseizure medication (ASM) withdrawal in well-controlled epilepsy is challenging. We evaluated (a) the correlation between neurologists' seizure risk estimation ("clinician predictions") vs calculated predictions, (b) how viewing calculated predictions influenced recommendations, and (c) barriers to using risk calculation.

METHODS

We asked US and European neurologists to predict 2-year seizure risk after ASM withdrawal for hypothetical vignettes. We compared ASM withdrawal recommendations before vs after viewing calculated predictions, using generalized linear models.

RESULTS

Three-hundred and forty-six neurologists responded. There was moderate correlation between clinician and calculated predictions (Spearman coefficient 0.42). Clinician predictions varied widely, for example, predictions ranged 5%-100% for a 2-year seizure-free adult without epileptiform abnormalities. Mean clinician predictions exceeded calculated predictions for vignettes with epileptiform abnormalities (eg, childhood absence epilepsy: clinician 65%, 95% confidence interval [CI] 57%-74%; calculated 46%) and surgical vignettes (eg, focal cortical dysplasia 6-month seizure-free mean clinician 56%, 95% CI 52%-60%; calculated 28%). Clinicians overestimated the influence of epileptiform EEG findings on withdrawal risk (26%, 95% CI 24%-28%) compared with calculators (14%, 95% 13%-14%). Viewing calculated predictions slightly reduced willingness to withdraw (-0.8/10 change, 95% CI -1.0 to -0.7), particularly for vignettes without epileptiform abnormalities. The greatest barrier to calculator use was doubting its accuracy (44%).

SIGNIFICANCE

Clinicians overestimated the influence of abnormal EEGs particularly for low-risk patients and overestimated risk and the influence of seizure-free duration for surgical patients, compared with calculators. These data may question widespread ordering of EEGs or time-based seizure-free thresholds for surgical patients. Viewing calculated predictions reduced willingness to withdraw particularly without epileptiform abnormalities.

Frequency of and factors associated with antiseizure medication discontinuation discussions and decisions in patients with epilepsy: A multicenter retrospective chart review

OBJECTIVE

Guidelines suggest considering antiseizure medication (ASM) discontinuation in patients with epilepsy who become seizure-free. Little is known about how discontinuation decisions are being made in practice. We measured the frequency of, and factors associated with, discussions and decisions surrounding ASM discontinuation.

METHODS

We performed a multicenter retrospective cohort study at the University of Michigan (UM) and two Dutch centers: Wilhelmina Children's Hospital (WCH) and Stichting Epilepsie Instellingen Nederland (SEIN). We screened all children and adults with outpatient epilepsy visits in January 2015 and included those with at least one visit during the subsequent 2 years where they were seizure-free for at least one year. We recorded whether charts documented (1) a discussion with the patient about possible ASM discontinuation and (2) any planned attempt to discontinue at least one ASM. We conducted multilevel logistic regressions to determine factors associated with each outcome.

RESULTS

We included 1058 visits from 463 patients. Of all patients who were seizure-free at least one year, 248/463 (53%) had documentation of any discussion and 98/463 (21%) planned to discontinue at least one ASM. Corresponding frequencies for patients who were seizure-free at least 2 years were 184/285 (65%) and 74/285 (26%). The probability of discussing or discontinuing increased with longer duration of seizure freedom. Still, even for patients who were 10 years seizure-free, our models predicated that in only 49% of visits was a discontinuation discussion documented, and in only 16% of visits was it decided to discontinue all ASMs. Provider-to-provider variation explained 18% of variation in whether patients discontinued any ASM.

SIGNIFICANCE

Only approximately half of patients with prolonged seizure freedom had a documented discussion about ASM discontinuation. Discontinuation was fairly rare even among low-risk patients. Future work should further explore barriers to and facilitators of counseling and discontinuation attempts.

Clinical Outcome, Cognition, and Cerebrovascular Reactivity after Surgical Treatment for Moyamoya Vasculopathy: A Dutch Prospective, Single-Center Cohort Study

Background: It remains unclear whether revascularization of moyamoya vasculopathy (MMV) has a positive effect on cognitive function. In this prospective, single-center study, we investigated the effect of revascularization on cognitive function in patients with MMV. We report clinical and radiological outcome parameters and the associations between clinical determinants and change in neurocognitive functioning. Methods: We consecutively included all MMV patients at a Dutch tertiary referral hospital who underwent pre- and postoperative standardized neuropsychological evaluation, [15O]H2O-PET (including cerebrovascular reactivity (CVR)), MRI, cerebral angiography, and completed standardized questionnaires on clinical outcome and quality of life (QOL). To explore the association between patient characteristics, imaging findings, and change in the z-scores of the cognitive domains, we used multivariable linear- and Bayesian regression analysis. Results: We included 40 patients of whom 35 (27 females, 21 children) were treated surgically. One patient died after surgery, and two withdrew from the study. TIA- and headache frequency and modified Rankin scale (mRS) improved (resp. p = 0.001, 0.019, 0.039). Eleven patients (seven children) developed a new infarct during follow-up (31%), five of which were symptomatic. CVR-scores improved significantly (p < 0.0005). The language domain improved (p = 0.029); other domains remained stable. In adults, there was an improvement in QOL. We could not find an association between change in imaging and cognitive scores. Conclusion: In this cohort of Western MMV patients, TIA frequency, headache, CVR, and mRS improved significantly after revascularization. The language domain significantly improved, while others remained stable. We could not find an association between changes in CVR and cognitive scores.

Predictive models for starting antiseizure medication withdrawal following epilepsy surgery in adults

More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications (ASMs). We aimed to identify predictors of seizure recurrence after starting postoperative ASM withdrawal and develop and validate predictive models.

We performed an international multicentre observational cohort study in nine tertiary epilepsy referral centres. We included 850 adults who started ASM withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting ASM withdrawal. We developed a model predicting recurrent seizures, other than focal non-motor aware seizures, using Cox proportional hazards regression in a derivation cohort (n = 231). Independent predictors of seizure recurrence, other than focal non-motor aware seizures, following the start of ASM withdrawal were focal non motor-aware seizures after surgery and before withdrawal (adjusted hazards ratio [aHR] 5.5, 95% confidence interval [CI] 2.7-11.1), history of focal to bilateral tonic-clonic seizures before surgery (aHR 1.6, 95% CI 0.9-2.8), time from surgery to the start of ASM withdrawal (aHR 0.9, 95% CI 0.8-0.9), and number of ASMs at time of surgery (aHR 1.2, 95% CI 0.9-1.6). Model discrimination showed a concordance statistic of 0.67 (95% CI 0.63-0.71) in the external validation cohorts (n = 500). A secondary model predicting recurrence of any seizures (including focal non-motor aware seizures) was developed and validated in a subgroup that did not have focal non-motor aware seizures before withdrawal (n = 639), showing a concordance statistic of 0.68 (95% CI 0.64-0.72). Calibration plots indicated high agreement of predicted and observed outcomes for both models.

We show that simple algorithms, available as graphical nomograms and online tools (predictepilepsy.github.io), can provide probabilities of seizure outcomes after starting postoperative ASMs withdrawal. These multicentre-validated models may assist clinicians when discussing ASM withdrawal after surgery with their patients.

The spatial relationship between the MRI lesion and intraoperative electrocorticography in focal epilepsy surgery

MRI and intraoperative electrocorticography are often used in tandem to delineate epileptogenic tissue in resective surgery for focal epilepsy. Both the resection of the MRI lesion and tissue with high rates of electrographic discharges on electrocorticography, e.g. spikes and high-frequency oscillations (80-500 Hz), leads to a better surgical outcome. How MRI and electrographic markers are related, however, is currently unknown. The aim of this study was to find the spatial relationship between MRI lesions and spikes/high-frequency oscillations.

We retrospectively included 33 pediatric and adult patients with lesional neocortical epilepsy who underwent electrocorticography-tailored surgery (14 female, median age = 13.4 years, range = 0.6-47.0 years). Mesiotemporal lesions were excluded. We used univariable linear regression to find correlations between pre-resection spike/high-frequency oscillation rates on an electrode and its distance to the MRI lesion. We tested straight lines to the centre and the edge of the MRI lesion, and the distance along the cortical surface to determine which of these distances best reflects the occurrence of spikes/high-frequency oscillations. We conducted a moderator analysis to investigate the influence of the underlying pathology type and lesion volume on our results.

We found spike and high-frequency oscillation rates to be spatially linked to the edge of the MRI lesion. The underlying pathology type influenced the spatial relationship between spike/high-frequency oscillation rates and the MRI lesion (pspikes &lt; 0.0001, pripples &lt; 0.0001), while lesion volume did not (pspikes = 0.64, pripples = 0.89). A higher spike rate was associated with a shorter distance to the edge of the lesion for cavernomas (F(1,64)=-1.37, p &lt; 0.0001, η2 = 0.22), focal cortical dysplasias (F(1,570)=-0.25, p &lt; 0.0001, η2 = 0.05), and pleomorphic xanthoastrocytomas (F(1,66)=-0.18, p = 0.01, η2 = 0.09). In focal cortical dysplasias, a higher ripple rate was associated with a shorter distance (F(1,570)=-0.35, p &lt; 0.0001, η2 = 0.05). Conversely, low-grade gliomas showed a positive correlation; the further an electrode was away from the lesion, the higher the rate of spikes (F(1,75) = 0.65, p &lt; 0.0001, η2 = 0.37) and ripples (F(1,75) = 2.67, p &lt; 0.0001, η2 = 0.22).

Pathophysiological processes specific to certain pathology types determine the spatial relationship between the MRI lesion and electrocorticography results. In our analyses, non-tumorous lesions (focal cortical dysplasias, cavernomas) seemed to intrinsically generate spikes and high-frequency oscillations, particularly at the border of the lesion. This advocates for a resection of this tissue. Low-grade gliomas caused epileptogenicity in the peritumoral tissue. Whether a resection of this tissue leads to a better outcome is unclear. Our results suggest that the underlying pathology type should be considered when intraoperative electrocorticography is interpreted.

Intraoperative electrocorticography using high-frequency oscillations or spikes to tailor epilepsy surgery in the Netherlands (the HFO trial): a randomised, single-blind, adaptive non-inferiority trial

Background

Intraoperative electrocorticography is used to tailor epilepsy surgery by analysing interictal spikes or spike patterns that can delineate epileptogenic tissue. High-frequency oscillations (HFOs) on intraoperative electrocorticography have been proposed as a new biomarker of epileptogenic tissue, with higher specificity than spikes. We prospectively tested the non-inferiority of HFO-guided tailoring of epilepsy surgery to spike-guided tailoring on seizure freedom at 1 year.

Methods

The HFO trial was a randomised, single-blind, adaptive non-inferiority trial at an epilepsy surgery centre (UMC Utrecht) in the Netherlands. We recruited children and adults (no age limits) who had been referred for intraoperative electrocorticography-tailored epilepsy surgery. Participants were randomly allocated (1:1) to either HFO-guided or spike-guided tailoring, using an online randomisation scheme with permuted blocks generated by an independent data manager, stratified by epilepsy type. Treatment allocation was masked to participants and clinicians who documented seizure outcome, but not to the study team or neurosurgeon. Ictiform spike patterns were always considered in surgical decision making. The primary endpoint was seizure outcome after 1 year (dichotomised as seizure freedom [defined as Engel 1A–B] vs seizure recurrence [Engel 1C–4]). We predefined a non-inferiority margin of 10% risk difference. Analysis was by intention to treat, with prespecified subgroup analyses by epilepsy type and for confounders. This completed trial is registered with the Dutch Trial Register, Toetsingonline ABR.NL44527.041.13, and ClinicalTrials.gov, NCT02207673.

Findings

Between Oct 10, 2014, and Jan 31, 2020, 78 individuals were enrolled to the study and randomly assigned (39 to HFO-guided tailoring and 39 to spike-guided tailoring). There was no loss to follow-up. Seizure freedom at 1 year occurred in 26 (67%) of 39 participants in the HFO-guided group and 35 (90%) of 39 in the spike-guided group (risk difference –23·5%, 90% CI –39·1 to –7·9; for the 48 patients with temporal lobe epilepsy, the risk difference was –25·5%, –45·1 to –6·0, and for the 30 patients with extratemporal lobe epilepsy it was –20·3%, –46·0 to 5·4). Pathology associated with poor prognosis was identified as a confounding factor, with an adjusted risk difference of –7·9% (90% CI –20·7 to 4·9; adjusted risk difference –12·5%, –31·0 to 5·9, for temporal lobe epilepsy and 5·8%, –7·7 to 19·5, for extratemporal lobe epilepsy). We recorded eight serious adverse events (five in the HFO-guided group and three in the spike-guided group) requiring hospitalisation. No patients died.

Interpretation

HFO-guided tailoring of epilepsy surgery was not non-inferior to spike-guided tailoring on intraoperative electrocorticography. After adjustment for confounders, HFOs show non-inferiority in extratemporal lobe epilepsy. This trial challenges the clinical value of HFOs as an epilepsy biomarker, especially in temporal lobe epilepsy. Further research is needed to establish whether HFO-guided intraoperative electrocorticography holds promise in extratemporal lobe epilepsy.

Funding

UMCU Alexandre Suerman, EpilepsieNL, RMI Talent Fellowship, European Research Council, and MING Fund.

Individualised prediction of drug resistance and seizure recurrence after medication withdrawal in people with juvenile myoclonic epilepsy: A systematic review and individual participant data meta-analysis

BACKGROUND

A third of people with juvenile myoclonic epilepsy (JME) are drug-resistant. Three-quarters have a seizure relapse when attempting to withdraw anti-seizure medication (ASM) after achieving seizure-freedom. It is currently impossible to predict who is likely to become drug-resistant and safely withdraw treatment. We aimed to identify predictors of drug resistance and seizure recurrence to allow for individualised prediction of treatment outcomes in people with JME.

METHODS

We performed an individual participant data (IPD) meta-analysis based on a systematic search in EMBASE and PubMed - last updated on March 11, 2021 - including prospective and retrospective observational studies reporting on treatment outcomes of people diagnosed with JME and available seizure outcome data after a minimum one-year follow-up. We invited authors to share standardised IPD to identify predictors of drug resistance using multivariable logistic regression. We excluded pseudo-resistant individuals. A subset who attempted to withdraw ASM was included in a multivariable proportional hazards analysis on seizure recurrence after ASM withdrawal. The study was registered at the Open Science Framework (OSF; https://osf.io/b9zjc/).

FINDINGS

Our search yielded 1641 articles; 53 were eligible, of which the authors of 24 studies agreed to collaborate by sharing IPD. Using data from 2518 people with JME, we found nine independent predictors of drug resistance: three seizure types, psychiatric comorbidities, catamenial epilepsy, epileptiform focality, ethnicity, history of CAE, family history of epilepsy, status epilepticus, and febrile seizures. Internal-external cross-validation of our multivariable model showed an area under the receiver operating characteristic curve of 0·70 (95%CI 0·68-0·72). Recurrence of seizures after ASM withdrawal (n = 368) was predicted by an earlier age at the start of withdrawal, shorter seizure-free interval and more currently used ASMs, resulting in an average internal-external cross-validation concordance-statistic of 0·70 (95%CI 0·68-0·73).

INTERPRETATION

We were able to predict and validate clinically relevant personalised treatment outcomes for people with JME. Individualised predictions are accessible as nomograms and web-based tools.

FUNDING

MING fonds.

Development and validation of a machine-learning algorithm to predict the relevance of scientific articles within the field of teratology

The Dutch Teratology Information Service Lareb counsels healthcare professionals and patients about medication use during pregnancy and lactation. To keep the evidence up to date, employees perform a standardized weekly PubMed query where relevant literature is identified manually. We aimed to develop an accurate machine-learning algorithm to predict the relevance of PubMed entries, thereby reducing the labor-intensive task of manually screening the articles. We fine-tuned a pre-trained natural language processing transformer model to identify relevant entries. We split 15,540 labeled entries into case-control-balanced train, validation, and test datasets. Additionally, we externally validated the model prospectively with 1288 labeled entries obtained from weekly queries after developing the model. This dataset was also independently labeled by a team of six experienced human raters to evaluate our model's performance. The validation of our machine learning model on the retrospectively collected outheld dataset obtained an area under the sensitivity-versus-specificity curve of 89.3 % (CI: 88.2- 90.4). In the prospective external validation of the model, our model classified relevant literature with a sensitivity versus specificity curve area of 87.4 % (CI: 85.0-89.8). Our model achieved a higher sensitivity than the human raters' team without sacrificing too much specificity. The team of human raters showed weak to moderate levels of agreement in their article classifications (kappa range 0.40-0.64). The human selection of the latest relevant literature is indispensable to keep the teratology information up to date. We show that automatic preselection of relevant abstracts using machine learning is possible without sacrificing the selection performance.

Incidence of and predictors for antiseizure medication gaps in Medicare beneficiaries with epilepsy: a retrospective cohort study

BACKGROUND

For the two-thirds of patients with epilepsy who achieve seizure remission on antiseizure medications (ASMs), patients and clinicians must weigh the pros and cons of long-term ASM treatment. However, little work has evaluated how often ASM discontinuation occurs in practice. We describe the incidence of and predictors for sustained ASM fill gaps to measure discontinuation in individuals potentially eligible for ASM withdrawal.

METHODS

This was a retrospective cohort of Medicare beneficiaries. We included patients with epilepsy by requiring International Classification of Diseases codes for epilepsy/convulsions plus at least one ASM prescription each year 2014-2016, and no acute visit for epilepsy 2014-2015 (i.e., potentially eligible for ASM discontinuation). The main outcome was the first day of a gap in ASM supply (30, 90, 180, or 360 days with no pills) in 2016-2018. We displayed cumulative incidence functions and identified predictors using Cox regressions.

RESULTS

Among 21,819 beneficiaries, 5191 (24%) had a 30-day gap, 1753 (8%) had a 90-day gap, 803 (4%) had a 180-day gap, and 381 (2%) had a 360-day gap. Predictors increasing the chance of a 180-day gap included number of unique medications in 2015 (hazard ratio [HR] 1.03 per medication, 95% confidence interval [CI] 1.01-1.05) and epileptologist prescribing physician (≥25% of that physician's visits for epilepsy; HR 2.37, 95% CI 1.39-4.03). Predictors decreasing the chance of a 180-day gap included Medicaid dual eligibility (HR 0.75, 95% CI 0.60-0.95), number of unique ASMs in 2015 (e.g., 2 versus 1: HR 0.37, 95% CI 0.30-0.45), and greater baseline adherence (> 80% versus ≤80% of days in 2015 with ASM pill supply: HR 0.38, 95% CI 0.32-0.44).

CONCLUSIONS

Sustained ASM gaps were rarer than current guidelines may suggest. Future work should further explore barriers and enablers of ASM discontinuation to understand the optimal discontinuation rate.

Clinical Trial Registration Patterns and Changes in Primary Outcomes of Randomized Clinical Trials From 2002 to 2017

This cross-sectional study evaluates the existence and timing of trial registration for randomized clinical trials (RCTs) published from 2002 to 2017 as well as substantive changes to the primary outcomes entered into registry information after those studies started.

Reappraisal of the Medical Research Council Antiepileptic Drug Withdrawal Study: contamination‐adjusted and dose‐response re‐analysis

Objective

The 1991 Medical Research Council (MRC) Study compared seizure relapse for seizure‐free patients randomized to withdraw vs continue of antiseizure medications (ASMs). We re‐analyzed this trial to account for crossover between arms using contamination‐adjusted intention to treat (CA ITT) methods, to explore dose‐response curves, and to validate predictions against external data. ITT assesses the effect of being randomized to withdraw, as‐treated analysis assesses the confounded effect of withdrawing, but CA ITT assesses the unconfounded effect of actually withdrawing.

Methods

CA ITT involves two stages. First, we used randomized arm to predict whether patients withdrew their ASM (logistic) or total daily ASM dose (linear). Second, we used those values to predict seizure occurrence (logistic).

Results

The trial randomized 503 patients to withdraw and 501 patients to continue ASMs. We found that 316 of 376 patients (88%) who were randomized to withdraw decreased their dose at every pre‐seizure visit, compared with 35 of 424 (8%) who were randomized to continue (p < .01). Adjusted odds ratios of a 2‐year seizure for those who withdrew vs those who did not was 1.3 (95% confidence interval [CI] 0.9–1.9) in the as‐treated analysis, 2.5 (95% CI 1.9–3.4) comparing those randomized to withdraw vs continue for ITT, and 3.1 (95% CI 2.1–4.5) for CA ITT. Probabilities (withdrawal vs continue) were 28% vs 24% (as‐treated), 40% vs 22% (ITT), and 43% vs 21% (CA ITT). Differences between ITT and CA ITT were greater when varying the predictor (reaching zero ASMs) or outcome (1‐year seizures). As‐treated dose‐response curves demonstrated little to no effects, but larger effects in CA ITT analysis. MRC data overpredicted risk in Lossius data, with moderate discrimination (areas under the curve ~0.70).

Significance

CA ITT results (the effect of actually withdrawing ASMs on seizures) were slightly greater than ITT effects (the effect of recommend withdrawing ASMs on seizures). How these findings affect clinical practice must be individualized.

Analysis of 567,758 randomized controlled trials published over 30 years reveals trends in phrases used to discuss results that do not reach statistical significance

The power of language to modify the reader's perception of interpreting biomedical results cannot be underestimated. Misreporting and misinterpretation are pressing problems in randomized controlled trials (RCT) output. This may be partially related to the statistical significance paradigm used in clinical trials centered around a P value below 0.05 cutoff. Strict use of this P value may lead to strategies of clinical researchers to describe their clinical results with P values approaching but not reaching the threshold to be "almost significant." The question is how phrases expressing nonsignificant results have been reported in RCTs over the past 30 years. To this end, we conducted a quantitative analysis of English full texts containing 567,758 RCTs recorded in PubMed between 1990 and 2020 (81.5% of all published RCTs in PubMed). We determined the exact presence of 505 predefined phrases denoting results that approach but do not cross the line of formal statistical significance (P < 0.05). We modeled temporal trends in phrase data with Bayesian linear regression. Evidence for temporal change was obtained through Bayes factor (BF) analysis. In a randomly sampled subset, the associated P values were manually extracted. We identified 61,741 phrases in 49,134 RCTs indicating almost significant results (8.65%; 95% confidence interval (CI): 8.58% to 8.73%). The overall prevalence of these phrases remained stable over time, with the most prevalent phrases being "marginally significant" (in 7,735 RCTs), "all but significant" (7,015), "a nonsignificant trend" (3,442), "failed to reach statistical significance" (2,578), and "a strong trend" (1,700). The strongest evidence for an increased temporal prevalence was found for "a numerical trend," "a positive trend," "an increasing trend," and "nominally significant." In contrast, the phrases "all but significant," "approaches statistical significance," "did not quite reach statistical significance," "difference was apparent," "failed to reach statistical significance," and "not quite significant" decreased over time. In a random sampled subset of 29,000 phrases, the manually identified and corresponding 11,926 P values, 68,1% ranged between 0.05 and 0.15 (CI: 67. to 69.0; median 0.06). Our results show that RCT reports regularly contain specific phrases describing marginally nonsignificant results to report P values close to but above the dominant 0.05 cutoff. The fact that the prevalence of the phrases remained stable over time indicates that this practice of broadly interpreting P values close to a predefined threshold remains prevalent. To enhance responsible and transparent interpretation of RCT results, researchers, clinicians, reviewers, and editors may reduce the focus on formal statistical significance thresholds and stimulate reporting of P values with corresponding effect sizes and CIs and focus on the clinical relevance of the statistical difference found in RCTs.

Memantine treatment does not affect compulsive behavior or frontostriatal connectivity in an adolescent rat model for quinpirole-induced compulsive checking behavior

RATIONALE

Compulsivity often develops during childhood and is associated with elevated glutamate levels within the frontostriatal system. This suggests that anti-glutamatergic drugs, like memantine, may be an effective treatment.

OBJECTIVE

Our goal was to characterize the acute and chronic effect of memantine treatment on compulsive behavior and frontostriatal network structure and function in an adolescent rat model of compulsivity.

METHODS

Juvenile Sprague-Dawley rats received repeated quinpirole, resulting in compulsive checking behavior (n = 32; compulsive) or saline injections (n = 32; control). Eight compulsive and control rats received chronic memantine treatment, and eight compulsive and control rats received saline treatment for seven consecutive days between the 10th and 12th quinpirole/saline injection. Compulsive checking behavior was assessed, and structural and functional brain connectivity was measured with diffusion MRI and resting-state fMRI before and after treatment. The other rats received an acute single memantine (compulsive: n = 12; control: n = 12) or saline injection (compulsive: n = 4; control: n = 4) during pharmacological MRI after the 12th quinpirole/saline injection. An additional group of rats received a single memantine injection after a single quinpirole injection (n = 8).

RESULTS

Memantine treatment did not affect compulsive checking nor frontostriatal structural and functional connectivity in the quinpirole-induced adolescent rat model. While memantine activated the frontal cortex in control rats, no significant activation responses were measured after single or repeated quinpirole injections.

CONCLUSIONS

The lack of a memantine treatment effect in quinpirole-induced compulsive adolescent rats may be partly explained by the interaction between glutamatergic and dopaminergic receptors in the brain, which can be evaluated with functional MRI.

An updated systematic review and meta-analysis of brain network organization in focal epilepsy: Looking back and forth

Abnormalities of the brain network organization in focal epilepsy have been extensively quantified. However, the extent and directionality of abnormalities are highly variable and subtype insensitive. We conducted meta-analyses to obtain a more accurate and epilepsy type-specific quantification of the interictal global brain network organization in focal epilepsy. By using random-effects models, we estimated differences in average clustering coefficient, average path length, and modularity between patients with focal epilepsy and controls, based on 45 studies with a total sample size of 1,468 patients and 1,021 controls. Structural networks had a significant lower level of integration in patients with epilepsy as compared to controls, with a standardized mean difference of -0.334 (95 % confidence interval -0.631 to -0.038; p-value 0.027). Functional networks did not differ between patients and controls, except for the beta band clustering coefficient. Our meta-analyses show that differences in the brain network organization are not as well defined as individual studies often propose. We discuss potential pitfalls and suggestions to enhance the yield and clinical value of network studies.

Development and Validation of Prediction Models for Developmental and Intellectual Outcome Following Pediatric Epilepsy Surgery

BACKGROUND AND OBJECTIVES

To (1) identify predictors of postoperative intelligence and developmental quotients (IQ/DQ) and (2) develop and validate clinically applicable IQ/DQ prediction models.

METHODS

We retrospectively analyzed neuropsychological outcomes and their possible determinants for children treated in Bethel and Utrecht since 1990. We performed separate analyses for patients with IQ and those with only DQ available. We developed prediction models based on presurgical determinants to predict dichotomized levels of performance (IQ≥85, IQ≥70, DQ≥50).

RESULTS

IQ/DQ data before and two years after surgery were available for 492 patients (IQ n=365, DQ n=127). At a cutoff-level ±10 points, the chance of improvement was considerably higher than the chance of deterioration (IQ 37.3% vs. 6.6% and DQ 31.5% vs. 15.0%, respectively). Presurgical IQ/DQ was the strongest predictor of postoperative cognition (IQ r=0.85, p<.001, DQ: r=0.57, p<.001).Two IQ models were developed in the Bethel cohort (n=258) and externally validated in the Utrecht cohort (n=102). For DQ, we developed the model in the Bethel cohort and used 10-fold cross-validation. Models allowed good prediction at all three cutoff-levels (correct classification for IQ≥85=86%, IQ≥70=91%, DQ≥50=76%). External validation of the IQ models showed high accuracy (IQ≥85: 0.82, CI 0.75-0.91, IQ≥70: 0.84, CI 0.77-0.92) and excellent discrimination (ROC curves IQ≥85: AUC 0.90, CI 0.84-0.96; IQ≥70: AUC 0.92, CI 0.87-0.97).

DISCUSSION

After epilepsy surgery in children, the risk of cognitive deterioration is very low. Presurgical development has a strong impact on the postoperative trajectory. The presented models can improve presurgical counseling of patients and parents by reliably predicting cognitive outcomes.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that for children undergoing epilepsy surgery presurgical IQ/DQ was the strongest predictor of postoperative cognition.

Bayesian model-averaged meta-analysis in medicine

We outline a Bayesian model-averaged (BMA) meta-analysis for standardized mean differences in order to quantify evidence for both treatment effectiveness δ and across-study heterogeneity τ . We construct four competing models by orthogonally combining two present-absent assumptions, one for the treatment effect and one for across-study heterogeneity. To inform the choice of prior distributions for the model parameters, we used 50% of the Cochrane Database of Systematic Reviews to specify rival prior distributions for δ and τ . The relative predictive performance of the competing models and rival prior distributions was assessed using the remaining 50% of the Cochrane Database. On average, ℋ 1 r -the model that assumes the presence of a treatment effect as well as across-study heterogeneity-outpredicted the other models, but not by a large margin. Within ℋ 1 r , predictive adequacy was relatively constant across the rival prior distributions. We propose specific empirical prior distributions, both for the field in general and for each of 46 specific medical subdisciplines. An example from oral health demonstrates how the proposed prior distributions can be used to conduct a BMA meta-analysis in the open-source software R and JASP. The preregistered analysis plan is available at https://osf.io/zs3df/.

Remote Corticospinal Tract Degeneration After Cortical Stroke in Rats May Not Preclude Spontaneous Sensorimotor Recovery

Background. Recovery of motor function after stroke appears to be related to the integrity of axonal connections in the corticospinal tract (CST) and corpus callosum, which may both be affected after cortical stroke. Objective. In the present study, we aimed to elucidate the relationship of changes in measures of the CST and transcallosal tract integrity, with the interhemispheric functional connectivity and sensorimotor performance after experimental cortical stroke. Methods. We conducted in vivo diffusion magnetic resonance imaging (MRI), resting-state functional MRI, and behavior testing in twenty-five male Sprague Dawley rats recovering from unilateral photothrombotic stroke in the sensorimotor cortex. Twenty-three healthy rats served as controls. Results. A reduction in the number of reconstructed fibers, a lower fractional anisotropy, and higher radial diffusivity in the ipsilesional but intact CST, reflected remote white matter degeneration. In contrast, transcallosal tract integrity remained preserved. Functional connectivity between the ipsi- and contralesional forelimb regions of the primary somatosensory cortex significantly reduced at week 8 post-stroke. Comparably, usage of the stroke-affected forelimb was normal at week 28, following significant initial impairment between day 1 and week 8 post-stroke. Conclusions. Our study shows that post-stroke motor recovery is possible despite degeneration in the CST and may be supported by intact neuronal communication between hemispheres.

Epilepsy in a health district in North-West Cameroon: Clinical characteristics and treatment gap

INTRODUCTION

Epilepsy is a common yet misunderstood condition in Cameroon, including in the Batibo Health district.

METHODS

This cross-sectional study describes epilepsy clinical characteristics, the treatment gap, and associated factors in a rural district in Cameroon. After screening for epilepsy using a door-to-door survey, physicians confirmed suspected cases of epilepsy. Detailed information on the medical, seizure, and treatment history was collected from everyone with epilepsy, followed by a general and neurological examination.

RESULTS

We diagnosed 546 people with active epilepsy (at least one seizure in the previous 12 months). The mean age of people with active epilepsy was 25.2 years (SD: 11.1). The mean age at first seizure was 12.5 years (SD: 8.2). Convulsive seizures (uncertain whether generalized or focal) were the most common seizure types (60%), while 41% had focal-onset seizures. About 60% of people had seizures at least monthly. One-quarter of participants had had at least one episode of status epilepticus. Anti-seizure medication (ASM) was taken by 85%, but most were receiving inappropriate treatment or were non-adherent, hence the high treatment gap (80%). Almost a third had had seizure-related injuries. Epilepsy was responsible for low school attendance; 74% of school dropouts were because of epilepsy.

CONCLUSION

The high proportion of focal-onset seizures suggests acquired causes (such as neurocysticercosis and onchocerciasis, both endemic in this area). The high epilepsy treatment gap and the high rates of status epilepticus and epilepsy-related injuries underscore the high burden of epilepsy in this rural Cameroonian health district.

Epidemiology of Epilepsy in Nigeria: A Community-Based Study From 3 Sites

BACKGROUND

We determined the prevalence, incidence, and risk factors for epilepsy in Nigeria.

METHODS

We conducted a door-to-door survey to identify cases of epilepsy in 3 regions. We estimated age-standardized prevalence adjusted for nonresponse and sensitivity and the 1-year retrospective incidence for active epilepsy. To assess potential risk factors, we conducted a case-control study by collecting sociodemographic and risk factor data. We estimated odds ratios using logistic regression analysis and corresponding population attributable fractions (PAFs).

RESULTS

We screened 42,427 persons (age ≥6 years), of whom 254 had confirmed active epilepsy. The pooled prevalence of active epilepsy per 1,000 was 9.8 (95% confidence interval [CI] 8.6-11.1), 17.7 (14.2-20.6) in Gwandu, 4.8 (3.4-6.6) in Afikpo, and 3.3 (2.0-5.1) in Ijebu-Jesa. The pooled incidence per 100,000 was 101.3 (95% CI 57.9-167.6), 201.2 (105.0-358.9) in Gwandu, 27.6 (3.3-128.0) in Afikpo, and 23.9 (3.2-157.0) in Ijebu-Jesa. Children's significant risk factors included febrile seizures, meningitis, poor perinatal care, open defecation, measles, and family history in first-degree relatives. In adults, head injury, poor perinatal care, febrile seizures, family history in second-degree relatives, and consanguinity were significant. Gwandu had more significant risk factors. The PAF for the important factors in children was 74.0% (71.0%-76.0%) and in adults was 79.0% (75.0%-81.0%).

CONCLUSION

This work suggests varied epidemiologic numbers, which may be explained by differences in risk factors and population structure in the different regions. These variations should differentially determine and drive prevention and health care responses.

The methodological quality of 176,620 randomized controlled trials published between 1966 and 2018 reveals a positive trend but also an urgent need for improvement

Many randomized controlled trials (RCTs) are biased and difficult to reproduce due to methodological flaws and poor reporting. There is increasing attention for responsible research practices and implementation of reporting guidelines, but whether these efforts have improved the methodological quality of RCTs (e.g., lower risk of bias) is unknown. We, therefore, mapped risk-of-bias trends over time in RCT publications in relation to journal and author characteristics. Meta-information of 176,620 RCTs published between 1966 and 2018 was extracted. The risk-of-bias probability (random sequence generation, allocation concealment, blinding of patients/personnel, and blinding of outcome assessment) was assessed using a risk-of-bias machine learning tool. This tool was simultaneously validated using 63,327 human risk-of-bias assessments obtained from 17,394 RCTs evaluated in the Cochrane Database of Systematic Reviews (CDSR). Moreover, RCT registration and CONSORT Statement reporting were assessed using automated searches. Publication characteristics included the number of authors, journal impact factor (JIF), and medical discipline. The annual number of published RCTs substantially increased over 4 decades, accompanied by increases in authors (5.2 to 7.8) and institutions (2.9 to 4.8). The risk of bias remained present in most RCTs but decreased over time for allocation concealment (63% to 51%), random sequence generation (57% to 36%), and blinding of outcome assessment (58% to 52%). Trial registration (37% to 47%) and the use of the CONSORT Statement (1% to 20%) also rapidly increased. In journals with a higher impact factor (>10), the risk of bias was consistently lower with higher levels of RCT registration and the use of the CONSORT Statement. Automated risk-of-bias predictions had accuracies above 70% for allocation concealment (70.7%), random sequence generation (72.1%), and blinding of patients/personnel (79.8%), but not for blinding of outcome assessment (62.7%). In conclusion, the likelihood of bias in RCTs has generally decreased over the last decades. This optimistic trend may be driven by increased knowledge augmented by mandatory trial registration and more stringent reporting guidelines and journal requirements. Nevertheless, relatively high probabilities of bias remain, particularly in journals with lower impact factors. This emphasizes that further improvement of RCT registration, conduct, and reporting is still urgently needed.

Many randomized controlled trials (RCTs) are biased and difficult to reproduce due to methodological flaws and poor reporting. Analysis of 176,620 RCTs published between 1966 and 2018 reveals that the risk of bias in RCTs generally decreased. Nevertheless, relatively high probabilities of bias remain, showing that further improvement of RCT registration, conduct, and reporting is still urgently needed.

Activation response and functional connectivity change in rat cortex after bilateral transcranial direct current stimulation-An exploratory study

Transcranial direct current stimulation (tDCS) is a noninvasive brain stimulation technique implicated as a promising adjunct therapy to improve motor function through the neuromodulation of brain networks. Particularly bilateral tDCS, which affects both hemispheres, may yield stronger effects on motor learning than unilateral stimulation. Therefore, the aim of this exploratory study was to develop an experimental model for simultaneous magnetic resonance imaging (MRI) and bilateral tDCS in rats, to measure instant and resultant effects of tDCS on network activity and connectivity. Naïve, male Sprague‐Dawley rats were divided into a tDCS (n = 7) and sham stimulation group (n = 6). Functional MRI data were collected during concurrent bilateral tDCS over the sensorimotor cortex, while resting‐state functional MRI and perfusion MRI were acquired directly before and after stimulation. Bilateral tDCS induced a hemodynamic activation response, reflected by a bilateral increase in blood oxygenation level‐dependent signal in different cortical areas, including the sensorimotor regions. Resting‐state functional connectivity within the cortical sensorimotor network decreased after a first stimulation session but increased after a second session, suggesting an interaction between multiple tDCS sessions. Perfusion MRI revealed no significant changes in cerebral blood flow after tDCS. Our exploratory study demonstrates successful application of an MRI‐compatible bilateral tDCS setup in an animal model. Our results indicate that bilateral tDCS can locally modulate neuronal activity and connectivity, which may underlie its therapeutic potential.

Imaging Markers for the Characterization of Gray and White Matter Changes from Acute to Chronic Stages after Experimental Traumatic Brain Injury

Despite clinical symptoms, a large majority of people with mild traumatic brain injury (TBI) have normal computed tomography (CT) and magnetic resonance imaging (MRI) scans. Therefore, present-day neuroimaging tools are insufficient to diagnose or classify low grades of TBI. Advanced neuroimaging techniques, such as diffusion-weighted and functional MRI, may yield novel biomarkers that may aid in the diagnosis of TBI. Therefore, the present study had two aims: first, to characterize the development of MRI-based measures of structural and functional changes in gray and white matter regions from acute to chronic stages after mild and moderate TBI; and second, to identify the imaging markers that can most accurately predict outcome after TBI. To these aims, 52 rats underwent serial functional (resting-state) and structural (T1-, T2-, and diffusion-weighted) MRI before and 1 h, 1 day, 1 week, 1 month and 3-4 months after mild or moderate experimental TBI. All rats underwent behavioral testing. Histology was performed in subgroups of rats at different time points. Early after moderate TBI, axial and radial diffusivities were increased, and fractional anisotropy was reduced in the corpus callosum and bilateral hippocampi, which normalized over time and was paralleled by recovery of sensorimotor function. Correspondingly, histology revealed decreased myelin staining early after TBI, which was not detected at chronic stages. No significant changes in individual outcome measures were detected after mild TBI. However, multivariate analysis showed a significant additive contribution of diffusion parameters in the distinction between control and different grades of TBI-affected brains. Therefore, combining multiple imaging markers may increase the sensitivity for TBI-related pathology.

Seizure outcome and use of antiepileptic drugs after epilepsy surgery according to histopathological diagnosis: a retrospective multicentre cohort study

BACKGROUND

Surgery is a widely accepted treatment option for drug-resistant focal epilepsy. A detailed analysis of longitudinal postoperative seizure outcomes and use of antiepileptic drugs for different brain lesions causing epilepsy is not available. We aimed to analyse the association between histopathology and seizure outcome and drug freedom up to 5 years after epilepsy surgery, to improve presurgical decision making and counselling.

METHODS

In this retrospective, multicentre, longitudinal, cohort study, patients who had epilepsy surgery between Jan 1, 2000, and Dec 31, 2012, at 37 collaborating tertiary referral centres across 18 European countries of the European Epilepsy Brain Bank consortium were assessed. We included patients of all ages with histopathology available after epilepsy surgery. Histopathological diagnoses and a minimal dataset of clinical variables were collected from existing local databases and patient records. The primary outcomes were freedom from disabling seizures (Engel class 1) and drug freedom at 1, 2, and 5 years after surgery. Proportions of individuals who were Engel class 1 and drug-free were reported for the 11 main categories of histopathological diagnosis. We analysed the association between histopathology, duration of epilepsy, and age at surgery, and the primary outcomes using random effects multivariable logistic regression to control for confounding.

FINDINGS

9147 patients were included, of whom seizure outcomes were available for 8191 (89·5%) participants at 2 years, and for 5577 (61·0%) at 5 years. The diagnoses of low-grade epilepsy associated neuroepithelial tumour (LEAT), vascular malformation, and hippocampal sclerosis had the best seizure outcome at 2 years after surgery, with 77·5% (1027 of 1325) of patients free from disabling seizures for LEAT, 74·0% (328 of 443) for vascular malformation, and 71·5% (2108 of 2948) for hippocampal sclerosis. The worst seizure outcomes at 2 years were seen for patients with focal cortical dysplasia type I or mild malformation of cortical development (50·0%, 213 of 426 free from disabling seizures), those with malformation of cortical development-other (52·3%, 212 of 405 free from disabling seizures), and for those with no histopathological lesion (53·5%, 396 of 740 free from disabling seizures). The proportion of patients being both Engel class 1 and drug-free was 0-14% at 1 year and increased to 14-51% at 5 years. Children were more often drug-free; temporal lobe surgeries had the best seizure outcomes; and a longer duration of epilepsy was associated with reduced chance of favourable seizure outcomes and drug freedom. This effect of duration was evident for all lesions, except for hippocampal sclerosis.

INTERPRETATION

Histopathological diagnosis, age at surgery, and duration of epilepsy are important prognostic factors for outcomes of epilepsy surgery. In every patient with refractory focal epilepsy presumed to be lesional, evaluation for surgery should be considered.

FUNDING

None.

Structural and functional MRI of altered brain development in a novel adolescent rat model of quinpirole-induced compulsive checking behavior

Obsessive-compulsive disorder (OCD) is increasingly considered to be a neurodevelopmental disorder. However, despite insights in neural substrates of OCD in adults, less is known about mechanisms underlying compulsivity during brain development in children and adolescents. Therefore, we developed an adolescent rat model of compulsive checking behavior and investigated developmental changes in structural and functional measures in the frontostriatal circuitry. Five-weeks old Sprague Dawley rats were subcutaneously injected with quinpirole (n = 21) or saline (n = 20) twice a week for five weeks. Each injection was followed by placement in the middle of an open field table, and compulsive behavior was quantified as repeated checking behavior. Anatomical, resting-state functional and diffusion MRI at 4.7T were conducted before the first and after the last quinpirole/saline injection to measure regional volumes, functional connectivity and structural integrity in the brain, respectively. After consecutive quinpirole injections, adolescent rats demonstrated clear checking behavior and repeated travelling between two open-field zones. MRI measurements revealed an increase of regional volumes within the frontostriatal circuits and an increase in fractional anisotropy (FA) in white matter areas during maturation in both experimental groups. Quinpirole-injected rats showed a larger developmental increase in FA values in the internal capsule and forceps minor compared to control rats. Our study points toward a link between development of compulsive behavior and altered white matter maturation in quinpirole-injected adolescent rats, in line with observations in pediatric patients with compulsive phenotypes. This novel animal model provides opportunities to investigate novel treatments and underlying mechanisms for patients with early-onset OCD specifically.

Distinct structure-function relationships across cortical regions and connectivity scales in the rat brain

An improved understanding of the structure-function relationship in the brain is necessary to know to what degree structural connectivity underpins abnormal functional connectivity seen in disorders. We integrated high-field resting-state fMRI-based functional connectivity with high-resolution macro-scale diffusion-based and meso-scale neuronal tracer-based structural connectivity, to obtain an accurate depiction of the structure-function relationship in the rat brain. Our main goal was to identify to what extent structural and functional connectivity strengths are correlated, macro- and meso-scopically, across the cortex. Correlation analyses revealed a positive correspondence between functional and macro-scale diffusion-based structural connectivity, but no significant correlation between functional connectivity and meso-scale neuronal tracer-based structural connectivity. Zooming in on individual connections, we found strong functional connectivity in two well-known resting-state networks: the sensorimotor and default mode network. Strong functional connectivity within these networks coincided with strong short-range intrahemispheric structural connectivity, but with weak heterotopic interhemispheric and long-range intrahemispheric structural connectivity. Our study indicates the importance of combining measures of connectivity at distinct hierarchical levels to accurately determine connectivity across networks in the healthy and diseased brain. Although characteristics of the applied techniques may affect where structural and functional networks (dis)agree, distinct structure-function relationships across the brain could also have a biological basis.

Diet as connecting factor: Functional brain connectivity in relation to food intake and sucrose tasting, assessed with resting-state functional MRI in rats

Eating disorders and obesity form a major health problem in Western Society. To be able to provide adequate treatment and prevention, it is necessary to understand the neural mechanisms underlying the development of eating disorders and obesity. Specific brain networks have been shown to be involved in feeding behavior. We therefore hypothesized that functional connectivity in neural networks involved in feeding behavior is dependent on the status of homeostatic energy balance, thus on being hungry or satiated. To test our hypothesis, we measured functional connectivity and amplitudes of neural signals within neural networks in relation to food intake and sucrose tasting in rats. Therefore, 16 male Wistar rats, of which eight were food-restricted and eight were satiated, underwent resting-state functional magnetic resonance imaging (rs-fMRI) at 9.4 T. Subsequently, half of these animals underwent a sucrose tasting procedure followed by a second rs-fMRI scan. Functional connectivity and amplitude of low-frequency signal fluctuations were statistically analyzed in a linear mixed model. Although we did not detect a significant effect of food intake on functional connectivity before sucrose tasting, there was a trend toward interaction between group (satiated vs. hungry) and treatment (sucrose tasting). Functional connectivity between feeding-related regions tended to decrease stronger upon sucrose tasting in satiated rats as compared to food-restricted rats. Furthermore, rs-fMRI signal amplitudes decreased stronger upon sucrose tasting in satiated rats, as compared to food-restricted rats. These findings indicate that food intake and sucrose tasting can affect functional network organization, which may explain the specific patterns in feeding behavior.

The road ahead in clinical network neuroscience

Clinical network neuroscience, the study of brain network topology in neurological and psychiatric diseases, has become a mainstay field within clinical neuroscience. Being a multidisciplinary group of clinical network neuroscience experts based in The Netherlands, we often discuss the current state of the art and possible avenues for future investigations. These discussions revolve around questions like "How do dynamic processes alter the underlying structural network?" and "Can we use network neuroscience for disease classification?" This opinion paper is an incomplete overview of these discussions and expands on ten questions that may potentially advance the field. By no means intended as a review of the current state of the field, it is instead meant as a conversation starter and source of inspiration to others.

Design and Evaluation of a Rodent-Specific Transcranial Magnetic Stimulation Coil: An In Silico and In Vivo Validation Study

Background

Rodent models are fundamental in unraveling cellular and molecular mechanisms of transcranial magnetic stimulation (TMS)‐induced effects on the brain. However, proper translation of human TMS protocols to animal models have been restricted by the lack of rodent‐specific focal TMS coils.

Objective

We aimed to improve TMS focalization in rodent brain with a novel small, cooled, and rodent‐specific TMS coil.

Methods

A rodent‐specific 25‐mm figure‐of‐eight TMS coil was developed. Stimulation focalization was simulated in silico for the rodent coil and a commercial human 50‐mm figure‐of‐eight TMS coil. Both coils were also compared in vivo by electromyography measurements of brachialis motor evoked potential (MEP) responses to TMS at different brain sites in anesthetized rats (n = 6). Focalization was determined from the coils' level of stimulation laterality. Differences in MEPs were statistically analyzed with repeated‐measures, within‐subjects, ANOVA.

Results

In silico simulation results deemed the human coil insufficient for unilateral stimulation of the rat motor cortex, whereas lateralized electrical field induction was projected attainable with the rodent coil. Cortical, in vivo MEP amplitude measurements from multiple points in each hemisphere, revealed unilateral activation of the contralateral brachialis muscle, in absence of ipsilateral brachialis activation, with both coils.

Conclusion

Computer simulations motivated the design of a smaller rodent‐specific TMS coil, but came short in explaining the capability of a larger commercial human coil to induce unilateral MEPs in vivo. Lateralized TMS, as demonstrated for both TMS coils, corroborates their use in translational rodent studies, to elucidate mechanisms of action of therapeutic TMS protocols.

A systematic review on the quantitative relationship between structural and functional network connectivity strength in mammalian brains

The mammalian brain is composed of densely connected and interacting regions, which form structural and functional networks. An improved understanding of the structure-function relation is crucial to understand the structural underpinnings of brain function and brain plasticity after injury. It is currently unclear how functional connectivity strength relates to structural connectivity strength. We obtained an overview of recent papers that report on correspondences between quantitative functional and structural connectivity measures in the mammalian brain. We included network studies in which functional connectivity was measured with resting-state fMRI, and structural connectivity with either diffusion-weighted MRI or neuronal tract tracers. Twenty-seven of the 28 included studies showed a positive structure-function relationship. Large inter-study variations were found comparing functional connectivity strength with either quantitative diffusion-based (correlation coefficient (r) ranges: 0.18-0.82) or neuronal tracer-based structural connectivity measures (r = 0.24-0.74). Two functional datasets demonstrated lower structure-function correlations with neuronal tracer-based (r = 0.22 and r = 0.30) than with diffusion-based measures (r = 0.49 and r = 0.65). The robust positive quantitative structure-function relationship supports the hypothesis that structural connectivity provides the hardware from which functional connectivity emerges. However, methodological differences between the included studies complicate the comparison across studies, which emphasize the need for validation and standardization in brain structure-function studies.

The power of language: Functional brain network topology of deaf and hearing in relation to sign language experience

Prolonged auditory sensory deprivation leads to brain reorganization. This is indicated by functional enhancement in remaining sensory systems and known as cross-modal plasticity. In this study we investigated differences in functional brain network topology between deaf and hearing individuals. We also studied altered functional network responses between deaf and hearing individuals with a recording paradigm containing an eyes-closed and eyes-open condition. Electroencephalography activity was recorded in a group of sign language-trained deaf (N = 71) and hearing people (N = 122) living in rural Africa. Functional brain networks were constructed from the functional connectivity between fourteen electrodes distributed over the scalp. Functional connectivity was quantified with the phase lag index based on bandpass filtered epochs of brain signal. We studied the functional connectivity between the auditory, somatosensory and visual cortex and performed whole-brain minimum spanning tree analysis to capture network backbone characteristics. Functional connectivity between different regions involved in sensory information processing tended to be stronger in deaf people during the eyes-closed condition in both the alpha and beta frequency band. Furthermore, we found differences in functional backbone topology between deaf and hearing individuals. The backbone topology altered during transition from the eyes-closed to eyes-open condition irrespective of deafness, but was more pronounced in deaf individuals. The transition of backbone strength was different between individuals with congenital, pre-lingual or post-lingual deafness. Functional backbone characteristics correlated with the experience of sign language. Overall, our study revealed more insights in functional network reorganization caused by auditory deprivation and cross-modal plasticity. It further supports the idea of a brain plasticity potential in deaf and hearing people. The association between network organization and acquired sign language experience reflects the ability of ongoing brain adaptation in people with hearing disabilities.