ORCID Profile
0000-0003-2399-7678
Current Organisations
Arekha middle secondary school, ministry of education
,
Faculdade de Medicina da Universidade Lisboa
,
Hospital de Santa Maria. Centro Hospitalar Universitário Lisboa Norte
,
Universidade de Lisboa
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Cold Spring Harbor Laboratory
Date: 24-07-2022
DOI: 10.1101/2022.07.22.22277802
Abstract: 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 (auras) before starting ASM withdrawal. We developed a model predicting recurrent seizures, other than auras, using Cox proportional hazards regression in a derivation cohort (n=231). Independent predictors of seizure recurrence, other than auras, following the start of ASM withdrawal were focal-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 auras) was developed and validated in a subgroup that did not have auras 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.
Publisher: Oxford University Press (OUP)
Date: 23-11-2022
Abstract: More than half of adults with epilepsy undergoing resective epilepsy surgery achieve long-term seizure freedom and might consider withdrawing antiseizure medications. We aimed to identify predictors of seizure recurrence after starting postoperative antiseizure medication 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 antiseizure medication withdrawal following resective epilepsy surgery and were free of seizures other than focal non-motor aware seizures before starting antiseizure medication 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 antiseizure medication withdrawal were focal non-motor aware seizures after surgery and before withdrawal [adjusted hazard 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 antiseizure medication withdrawal (aHR 0.9, 95% CI 0.8–0.9) and number of antiseizure medications 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 antiseizure medication withdrawal. These multicentre-validated models may assist clinicians when discussing antiseizure medication withdrawal after surgery with their patients.
Publisher: Shanlax International Journals
Date: 12-2021
DOI: 10.34293/EDUCATION.V10I1.4435
Abstract: This quasi experimental study examined the effect of technology based teaching approaches on the 6th grade students’ learning in social studies subject. The participants of the study included two classes of 6th grade students: control group (n=25) and experimental group (n=24) in one of the middle schools in Bhutan. The research instruments consisted of experimental group treatment, survey questionnaire and semi-structured interview questions. The result suggested that there is an affirmative effect of technology based teaching approaches on the 6th grade students’ social studies learning achievement test. It was found that mean test scores of the experimental group were higher than the control group on pretest and post test analysis. Further, the findings from the study established that students had a positive perception of learning through technology based instructions, as learners enjoyed, and were better able to understand, what has been taught. The findings from the study concluded that teaching through technology based approaches enhanced students’ learning in the classroom, so, it is recommended that teachers apply technology based instructions as a tool to maximize student learning. In addition, building of smart classrooms through digitalization could support students with learning difficulties in different subjects.
Location: Bhutan
Location: Portugal
No related grants have been discovered for Carla Bentes.