Name as Many AEDs as You Can in One Minute: Antiepileptic Drugs and the Disruption of Verbal Fluency Networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Chang BS
PROVIDER: S-EPMC5898254 | biostudies-literature | 2018 Mar-Apr
REPOSITORIES: biostudies-literature
Publications
Name as Many AEDs as You Can in One Minute: Antiepileptic Drugs and the Disruption of Verbal Fluency Networks.
Epilepsy currents 20180301 2
Similar Datasets
Project description:Definition of preleukemia has evolved. It was first used to describe the myelodysplastic syndrome (MDS) with a propensity to progress to acute myeloid leukemia (AML). Individuals with germline mutations of either RUNX1, CEBPA, or GATA2 can also be called as preleukemic because they have a markedly increased incidence of evolution into AML. Also, alkylating chemotherapy or radiation can cause MDS/preleukemia, which nearly always progress to AML. More recently, investigators noted that AML patients who achieved complete morphological remission after chemotherapy often have clonal hematopoiesis predominantly marked by either DNMT3A, TET2 or IDH1/2 mutations, which were also present at diagnosis of AML. This preleukemic clone represents involvement of an early hematopoietic stem cells, which is resistant to standard therapy. The same clonal hematopoietic mutations have been identified in older 'normal' individuals who have a modest increased risk of developing frank AML. These individuals have occasionally been said, probably inappropriately, to have a preleukemia clone. Our evolving understanding of the term preleukemia has occurred by advancing technology including studies of X chromosome inactivation, cytogenetics and more recently deep nucleotide sequencing.
| S-EPMC5339433 | biostudies-literature
Project description:The review presents data from the last few years on bioanalytical methods used in therapeutic drug monitoring (TDM) of the 1st-3rd generation and the newest antiepileptic drug (AEDs) cenobamate in patients with various forms of seizures. Chemical classification, structure, mechanism of action, pharmacokinetic data and therapeutic ranges for total and free fractions and interactions were collected. The primary data on bioanalytical methods for AEDs determination included biological matrices, sample preparation, dried blood spot (DBS) analysis, column resolution, detection method, validation parameters, and clinical utility. In conclusion, the most frequently described method used in AED analysis is the LC-based technique (HPLC, UHPLC, USLC) combined with highly sensitive mass detection or fluorescence detection. However, less sensitive UV is also used. Capillary electrophoresis and gas chromatography have been rarely applied. Besides the precipitation of proteins or LLE, an automatic SPE is often a sample preparation method. Derivatization was also indicated to improve sensitivity and automate the analysis. The usefulness of the methods for TDM was also highlighted.
| S-EPMC7663638 | biostudies-literature
Project description: Not available
| S-EPMC5967591 | biostudies-literature
Project description:Verbal fluency impairment is common in patients with Parkinson's disease (PD), but the effect of drugs on verbal fluency in PD patients has not been comprehensively evaluated. We conducted a network meta-analysis based on four online databases to compare the effect of drugs on verbal fluency in PD patients. This study was performed and reported according to PRISMA-NMA guidelines. In total, 6 out of 3707 articles (three RCTS and three cross-sectional studies) covering eight drug regimens were included (five for letter fluency, five for semantic fluency). In terms of letter fluency, the ranking of the overall efficacy of included drug regimens was: levodopa, levodopa combined with pramipexole, rotigotine, cabergoline, pramipexole, pergolide, but no drug regimen presented a significant advantage over the others. In terms of semantic fluency, the ranking of the overall efficacy of included drug regimens was: rotigotine, levodopa, cabergoline, pergolide, pramipexole, among which, levodopa alone (SMD = 0.93, 95%CI: 0.28-1.59) and rotigotine alone (SMD = 1.18, 95%CI: 0.28-2.09) were statistically superior to pramipexole, while no significant difference was identified between all the other drug regimens. Levodopa and rotigotine seem to be more appropriate choices for PD patients with verbal fluency impairment. Further study is needed to illustrate the efficacy of drugs on verbal fluency in PD patients.
| S-EPMC9688928 | biostudies-literature
Project description:IntroductionIn recent decades, researchers have defined novel methods for scoring verbal fluency tasks. In this work, we evaluate novel scores based on speed of word responses.MethodsWe transcribed verbal fluency recordings from 641 cases of incident cognitive impairment (ICI) and matched controls, all participants in a large national epidemiological study. Timing measurements of utterances were used to calculate a speed score for each recording. Traditional raw and speed scores were entered into Cox proportional hazards (CPH) regression models predicting time to ICI.ResultsConcordance of the CPH model with speed scores was 0.599, an improvement of 3.4% over a model with only raw scores and demographics. Scores with significant effects included animals raw and speed scores, and letter F speed score.DiscussionNovel verbal fluency scores based on response times could enable use of remotely administered fluency tasks for early detection of cognitive decline.Highlights The current work evaluates prognostication with verbal fluency speed scores. These speed scores improve survival models predicting cognitive decline. Cases with progressive decline have some characteristics suggestive of Alzheimer's disease. The subset of acute decliners is probably pathologically heterogeneous.
| S-EPMC9074715 | biostudies-literature
Project description:Semantic verbal fluency (sVF) tasks are commonly used in clinical diagnostic batteries as well as in a research context. When performing sVF tasks to assess executive functions (EFs) the sum of correctly produced words is the main measure. Although previous research indicates potentially better insights into EF performance by the use of finer grained sVF information, this has not yet been objectively evaluated. To investigate the potential of employing a finer grained sVF feature set to predict EF performance, healthy monolingual German speaking participants (n = 230) were tested with a comprehensive EF test battery and sVF tasks, from which features including sum scores, error types, speech breaks and semantic relatedness were extracted. A machine learning method was applied to predict EF scores from sVF features in previously unseen subjects. To investigate the predictive power of the advanced sVF feature set, we compared it to the commonly used sum score analysis. Results revealed that 8 / 14 EF tests were predicted significantly using the comprehensive sVF feature set, which outperformed sum scores particularly in predicting cognitive flexibility and inhibitory processes. These findings highlight the predictive potential of a comprehensive evaluation of sVF tasks which might be used as diagnostic screening of EFs.
| S-EPMC7994566 | biostudies-literature
Project description:Background: Verbal fluency (VF) has been associated with several cognitive functions, but the cognitive processes underlying verbal fluency deficits in Multiple Sclerosis (MS) are controversial. Further knowledge about VF could be useful in clinical practice, because these tasks are brief, applicable, and reliable in MS patients. In this study, we aimed to evaluate the cognitive processes related to VF and to develop machine-learning algorithms to predict those patients with cognitive deficits using only VF-derived scores. Methods: Two hundred participants with MS were enrolled and examined using a comprehensive neuropsychological battery, including semantic and phonemic fluencies. Automatic linear modeling was used to identify the neuropsychological test predictors of VF scores. Furthermore, machine-learning algorithms (support vector machines, random forest) were developed to predict those patients with cognitive deficits using only VF-derived scores. Results: Neuropsychological tests associated with attention-executive functioning, memory, and language were the main predictors of the different fluency scores. However, the importance of memory was greater in semantic fluency and clustering scores, and executive functioning in phonemic fluency and switching. Machine learning algorithms predicted general cognitive impairment and executive dysfunction, with F1-scores over 67-71%. Conclusions: VF was influenced by many other cognitive processes, mainly including attention-executive functioning, episodic memory, and language. Semantic fluency and clustering were more explained by memory function, while phonemic fluency and switching were more related to executive functioning. Our study supports that the multiple cognitive components underlying VF tasks in MS could serve for screening purposes and the detection of executive dysfunction.
| S-EPMC7859643 | biostudies-literature
Project description:Women are thought to fare better in verbal abilities, especially in verbal-fluency and verbal-memory tasks. However, the last meta-analysis on sex/gender differences in verbal fluency dates from 1988. Although verbal memory has only recently been investigated meta-analytically, a comprehensive meta-analysis is lacking that focuses on verbal memory as it is typically assessed, for example, in neuropsychological settings. On the basis of 496 effect sizes and 355,173 participants, in the current meta-analysis, we found that women/girls outperformed men/boys in phonemic fluency (ds = 0.12-0.13) but not in semantic fluency (ds = 0.01-0.02), for which the sex/gender difference appeared to be category-dependent. Women/girls also outperformed men/boys in recall (d = 0.28) and recognition (ds = 0.12-0.17). Although effect sizes are small, the female advantage was relatively stable over the past 50 years and across lifetime. Published articles reported stronger female advantages than unpublished studies, and first authors reported better performance for members of their own sex/gender. We conclude that a small female advantage in phonemic fluency, recall, and recognition exists and is partly subject to publication bias. Considerable variance suggests further contributing factors, such as participants' language and country/region.
| S-EPMC9896545 | biostudies-literature
Project description: Not available
| S-EPMC1570847 | biostudies-literature
Project description:BackgroundThere have been conflicting reports on whether conventional verbal fluency measures can predict the prognosis of individuals at clinical high risk (CHR) for psychosis. We aimed to investigate whether verbal fluency task measures that represent semantic processing more directly than conventional measures could be more reliable predictors of later remission in CHR individuals.MethodsWe recruited CHR individuals and healthy controls to participate in a baseline verbal fluency assessment. We identified semantic clusters within the verbal fluency task responses based on cosine similarity between consecutive words, calculated from the word embedding model. Binomial logistic regression was performed to test whether average semantic cluster size and number of words produced could be predictors of remission in CHR individuals.ResultsOur study sample included 96 CHR individuals and 178 healthy controls. According to clinical assessment at the last follow-up, 23 CHR individuals were classified as remitters and 73 as nonremitters, including 29 individuals who converted to psychosis. The CHR remitters showed larger average and maximum semantic cluster sizes than CHR nonremitters and healthy controls. Average semantic cluster size, but not the number of words, was a significant predictor of later remission in CHR individuals.LimitationsOur sample included only native Korean speakers.ConclusionA verbal fluency task measure that more specifically represents semantic processing may be a better neurocognitive predictive marker for remission in CHR individuals than conventional verbal fluency measures. Our results provide an explanation for heterogeneous reports on whether verbal fluency can predict prognosis in CHR individuals and suggest that semantic processing is a putative cognitive predictor of their prognosis.
| S-EPMC10620004 | biostudies-literature