Lacans verbeeldend zelfverstaan als actualisering van Schillebeeckx’ negatieve contrastervaring

Masterthesis Systematische Theologi

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

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 (Formula presented.) and across-study heterogeneity (Formula presented.). 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 (Formula presented.) and (Formula presented.). The relative predictive performance of the competing models and rival prior distributions was assessed using the remaining 50% of the Cochrane Database. On average, (Formula presented.) —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 (Formula presented.), 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/

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

ObjectiveGuidelines 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.MethodsWe 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.ResultsWe 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.SignificanceNo 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 SummaryUnderstanding 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.Paroxysmal Cerebral Disorder

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-11 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. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd

White matter integrity and cerebral network topology in focal epilepsy

Worldwide more than fifty million people suffer from recurrent spontaneous seizures. Seizures are considered to be harmful to the brain and may have adverse long-term behavioral and cognitive consequences in particular in people with focal epilepsies that do not respond to pharmacotherapy. Characterization of seizure related brain damage may provide knowledge to better comprehend the mechanisms underlying the poorly understood comorbidities often encountered in patients with focal epilepsy. In the studies described in the thesis ‘White matter integrity and cerebral network topology in focal epilepsy’ we focused on the characterization of spatiotemporal changes in brain tissue integrity distant from a focal epileptogenic zone and on concomitant modifications of functional connectivity and network topology. In addition, we studied whether this information could improve diagnostic work-up. We i) systematically reviewed and meta-analyzed existing MRI studies in patients with temporal lobe epilepsy, ii) conducted serial structural and functional MRI in two focal epilepsy rat models, from which we identified the remote cerebral consequences using measures of white matter microstructural integrity, white matter volumetry, hippocampal morphometry and functional connectivity and network configuration and iii) developed and validated a diagnostic prediction model based on EEG network topology in children suspected of focal epilepsy. Our data indicates that recurrent seizures in focal epilepsy causes wide-spread structural pathology both in human and rodent brain white matter and hippocampus. These changes in structural integrity relate to altered functional connectivity and global brain network topology. In addition, we found functional EEG network features to improve the predictive power in focal epilepsy diagnosis. Longitudinal prospective cohort studies with repetitive structural and functional measurements are needed to substantiate our novel experimental findings and to reveal the exact seizure-related mechanisms that underlie cerebral damage in focal epilepsy and its clinical consequences

The grateful scientist: what determines the presence of acknowledgements in randomised clinical trial publications?

Objective Randomised clinical trials (RCTs) are complex endeavours that demand extensive collaborative eforts from researchers, institutions, and funding partners. Undoubtedly, there is ample reason to acknowledge these eforts and to be grateful for publication of the results. However, some RCTs explicitly express gratitude in an acknowledgment section whereas other do not. We hypothesized that this would be related to author’s gender and religion, medical field, journal, and year of publication. Design Quantitative analysis of all available full-text randomised clinical trials identified through PubMed. Methods We determined the presence of an acknowledgment section containing explicit words of gratitude in 90,163 full-text publications. The hypotheses were publicly pre-registered before study conduct. We tested the following determinants of the presence of these acknowledgment sections: gender of the first and last author, the percentage of protestant inhabitants in the country of the primary research institution, the year of publication, journal impact factor (JIF), the journal’s medical field (compared to the medical field of surgery). Explorative analyses were performed on the diferent determinants that were associated with received gratitude in the acknowledgement sections. Main outcome measure The presence of an acknowledgment section with explicit words of gratitude. Results In total, 28,897 (32%) RCT publications contained an acknowledgement section with explicit words of gratitude. All hypotheses were confirmed, with a higher likelihood of an acknowledgement section with words of gratitude when the first and/or last author was female (OR 1.28 95% CI 1.24-1.31), an increased percentage of protestant inhabitants in the country of the first author’s afliation (+ 10%; OR = 1.04 95% CI 1.04-1.05), and more recent publication (+ 1 year; OR 1.04 95% CI 1.04-1.05). The journal’s impact factor (- 1 JIF; OR = 0.99 95% CI 0.99-0.99) and RCTs published in surgical journals (OR 0.35 95% CI 0.32-0.38) were associated with a lower likelihood of RCT publications containing words of gratitude. Conclusions Acknowledgement sections with explicit words of gratefulness are more frequently present when researchers are female, from protestant countries, working in non-surgical fields, and published in lower impact factor journals, and this trend has increased over time. To foster a healthy and responsible publication culture, it is important that all individuals, institutions, and groups that have contributed to the research are acknowledged. Credit should go where credit is due, and Christmas is the most suitable period to remind us of the importance of gratitude