MétaCan
Menu
Back to cohort
Record W3015190905 · doi:10.1186/s12883-020-01707-2

Injury of Corticospinal tract and Corticoreticular pathway caused by high-voltage electrical shock: a case report

2020· article· en· W3015190905 on OpenAlexaff
Mathieu Boudier‐Revéret, Ming‐Yen Hsiao, Shaw‐Gang Shyu, Min Cheol Chang

Bibliographic record

VenueBMC Neurology · 2020
Typearticle
Languageen
FieldMedicine
TopicBurn Injury Management and Outcomes
Canadian institutionsCentre Hospitalier de l’Université de Montréal
FundersNational Research Foundation of KoreaNational Research Foundation
KeywordsCorticospinal tractMedicineDiffusion MRIFractional anisotropyWeaknessAnatomyNeuroscienceRadiologyMagnetic resonance imagingPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: We imaged the corticospinal tract (CST) and corticoreticular pathway (CRP) using diffusion tensor tractography (DTT) to evaluate the cause of muscle weakness in a patient who was exposed to high-voltage electricity. CASE PRESENTATION: A 39-year-old man presented with quadriparesis after high-voltage electrical shock from power lines while working about 5.8 years ago. The electrical current entered through the left hand and exited through the occipital area of the head. The degree of weakness on bilateral upper and lower extremities was 3-4 on the Medical Research Council strength scale. Diffusion tensor imaging (DTI) was performed 5.8 years after onset. The CST and CRP were depicted by placing two regions of interest for each neural tract on the two-dimensional fractional anisotropy color map. DTT of the DTI scan showed that the bilateral CST and CRP were thinned compared to those of the healthy control subject. On the nerve conduction test, abnormal findings suggesting peripheral nerve lesion were not observed. Therefore, injury of bilateral CST and CRP seems to have contributed to our patient's weakness after the electrical shock. CONCLUSION: Depiction of neural tracts in the brain using DTT can assist in the accurate and detailed evaluation of the cause of neural deficit after electrical injury.

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 score0.277
Threshold uncertainty score0.656

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBMC NeurologySame topicBurn Injury Management and OutcomesFrench-language works237,207