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Record W4388970996 · doi:10.2196/49412

The Primary Prevention of Poststroke Epilepsy in Patients With Middle Cerebral Artery Infarct: Protocol for a Randomized Controlled Trial

2023· article· en· W4388970996 on OpenAlexvenueno aff
Yu-Shiue Chen, Pi‐Shan Sung, Ming‐Chi Lai, Chin‐Wei Huang

Bibliographic record

VenueJMIR Research Protocols · 2023
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersNational Science and Technology CouncilNational Cheng Kung UniversityNational Cheng Kung University Hospital
KeywordsMedicineEpilepsyStroke (engine)Randomized controlled trialEpileptogenesisLevetiracetamInfarctionPlaceboClinical endpointClinical trialPediatricsAnesthesiaInternal medicinePsychiatryMyocardial infarction

Abstract

fetched live from OpenAlex

BACKGROUND: Poststroke epilepsy poses a significant clinical challenge for individuals recovering from strokes, leading to a less favorable long-term outlook and increased mortality rates. Existing studies have primarily concentrated on administering antiseizure or anticonvulsant treatments only after the onset of late-onset seizures, without intervening during the epileptogenesis phase following a stroke. OBJECTIVE: This research protocol is designed to conduct a randomized controlled trial to assess whether the early, preventive introduction of low-dose antiepileptic drug therapy (levetiracetam [LEV] or perampanel [PER]) in patients who have experienced middle cerebral artery (MCA) infarction can reduce the risk of developing poststroke epilepsy (primary prevention). METHODS: Participants with MCA infarction, either with or without reperfusion treatments, will be recruited and promptly receive preventive intervention within 72 hours of the stroke occurrence. These participants will be randomly assigned to receive either PER (4 mg per day), LEV (1000 mg per day), or a placebo that matches the active drugs. This treatment will continue for 12 weeks after allocation. Brain magnetic resonance imaging will be used to confirm the presence of MCA territory infarction, and an electroencephalography will be used to ensure the absence of epileptiform discharges or electrographic seizures at the time of the stroke. All participants will undergo follow-up assessments for 72 weeks after allocation. RESULTS: The primary outcome under evaluation will be the incidence of poststroke epilepsy in the 3 groups following the 18-month study period. Secondary outcomes will encompass the time to the occurrence of the first seizure, the severity of seizures, any treatment-related adverse events, and the modified Rankin scale score at 3 and 18 months. Exploratory outcomes will involve comparing the effectiveness and safety of PER and LEV. CONCLUSIONS: We anticipate that the intervention groups will experience a lower incidence and reduced severity of poststroke epilepsy compared to the control group after 18 months. We aim to establish evidence supporting the potential preventive effects of LEV and PER on poststroke seizures and epilepsy in patients with MCA infarction, as well as to explore the antiepileptogenic potential of both LEV and PER in patients with major ischemic strokes. TRIAL REGISTRATION: ClinicalTrials.gov NCT04858841; https://clinicaltrials.gov/study/NCT04858841. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/49412.

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)0.039
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.062
Threshold uncertainty score0.207

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0390.041
Meta-epidemiology (narrow)0.0080.003
Meta-epidemiology (broad)0.0130.007
Bibliometrics0.0030.004
Science and technology studies0.0030.004
Scholarly communication0.0050.004
Open science0.0040.002
Research integrity0.0080.008
Insufficient payload (model declined to judge)0.0620.010

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 head0.106
GPT teacher head0.472
Teacher spread0.367 · 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 designRandomized trial
Domainnot available
GenreProtocol

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
Published2023
Admission routes1
Has abstractyes

Explore more

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