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Record W4414780886 · doi:10.1186/s12883-025-04436-6

Prediction of late seizures after ischemic stroke using cognitive scores

2025· article· en· W4414780886 on OpenAlexaboutno aff
Hiroya Ohara, Hironori Shimizu, Masami Yamanaka, Nanami Yamada, Naoya Kikutsuji, Hiromi Kanesaki, Takahiro Kanda, Keisuke Honda, Masako Kinoshita, Kazuma Sugie

Bibliographic record

VenueBMC Neurology · 2025
Typearticle
Languageen
FieldMedicine
TopicEpilepsy research and treatment
Canadian institutionsnot available
FundersJapan Society for the Promotion of ScienceNakatani Foundation for Advancement of Measuring Technologies in Biomedical Engineering
KeywordsNeurologyIschemic strokeCognitionNeurochemistryNeurosurgeryStroke (engine)

Abstract

fetched live from OpenAlex

BACKGROUND: Late seizures are well-known sequelae after stroke. Previous history of stroke and dementia is common etiology of epilepsy, however, the effect of cognitive impairment on late seizures has not been fully investigated. We investigated the clinical significance of cognitive scores in predicting the occurrence of post-stroke late seizures. METHODS: Adult patients with acute cerebral infarction were analyzed. Their cognitive function was evaluated using the Addenbrooke's Cognitive Examination (ACE)-III and the Japanese version of Montreal Cognitive Assessment (MoCA-J) within two weeks after stroke. Factors associated with late seizures and accuracy of cognitive scores to predict late seizures were analyzed. RESULTS: Of 45 patients enrolled (28 males, age 77.2 ± 8.5 years, mean ± SD), eight patients had late seizures within 123.8 ± 126.5 days after cerebral infarction. Cognitive evaluation was performed at 8.0 ± 3.9 days. ACE-III and MoCA-J scores were significantly lower in patients with late seizures than in those without late seizures (ACE-III: 27.5 ± 17.3 vs. 59.1 ± 27.2, MoCA-J: 7.6 ± 5.9 vs. 15.4 ± 8.6, p < 0.05, unpaired t-test). Receiver operating characteristic curve analysis revealed that area under curve of ACE-III was larger than that of MoCA-J and size of cerebral infarction. The optimum cut-off scores of ACE-III were ≤ 58.5 (Sensitivity: 1.00, specificity: 0.62) and ≤ 45.0 (0.88, 0.73). Kaplan-Meier estimates showed that each cut-off score significantly associated with late seizures. Sizes of infarcts and of cortical lesion were not significantly different between patients with and without late seizures. ROC curve and Kaplan-Meier survival analyses showed a significant association between size of infarct and late seizures, however, ACE-III scores more strongly associated with late seizures than the size of infarct did. CONCLUSION: Cognitive scores, especially ACE-III, within two weeks after cerebral infarction can be useful for predicting post-stroke late seizures.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.254

Codex and Gemma teacher scores by category

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

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 head0.037
GPT teacher head0.316
Teacher spread0.279 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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
Published2025
Admission routes1
Has abstractyes

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