MétaCan
Menu
Back to cohort
Record W7075691883

Effect of donepezil and memantine on improvement of cognitive function in patients with temporal lobe epilepsy(

2020· article· en· W7075691883 on OpenAlexaboutno aff

Bibliographic record

VenueBushehr University of Medical Sciences Repository (Bushehr University of Medical Sciences) · 2020
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTheoretical and Computational Physics
Canadian institutionsnot available
Fundersnot available
KeywordsDonepezilMemantineCognitionTemporal lobeMontreal Cognitive AssessmentClinical trialIntervention (counseling)Effects of sleep deprivation on cognitive performance
DOInot available

Abstract

fetched live from OpenAlex

Background: Cognitive impairment is a common complication of patients with temporal lobe epilepsy (TLE). Therefore, the aim of this study was to compare the effects of donepezil and memantine on improving the cognitive function of patients with TLE. Materials and Methods: In a clinical trial study, 70 patients with TLE were divided into two groups of 35 each: 10 mg doses of donepezil (first group) and memantine (second group) were applied for 16 weeks. The level of cognitive function of patients in both groups before and after treatment was determined using Montreal Cognitive Assessment (MoCA) test. Results: The mean score of MoCA before and after intervention was 23.55 ± 3.67 and 26.09 ± 2.5, respectively, in the group treated with memantine, and the mean score of intervention was significantly improved (P < 0.001). In the group treated with donepezil, the score before and after the operation was 23.87 ± 3.18 and 24.35 ± 2.17, respectively, and no significant difference was observed in this group (P = 0.38). Conclusion: Hence, memantine was better than donepezil in the improvement of cognitive impairment in patients with TLE.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.198
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBushehr University of Medical Sciences Repository (Bushehr University of Medical Sciences)Same topicTheoretical and Computational PhysicsFrench-language works237,207