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Record W3119303536 · doi:10.21608/bjas.2020.134629

Serum Homocysteine Level in Patients with Cerebral Venous Sinus Thrombosis (CVST): Relation to Initial Thrombosis Severity and Outcome

2020· article· en· W3119303536 on OpenAlexaboutno aff
M.A.Al Baklawy, RizkM Khodair, Mohd Faheem, I.A. Abd Elrassoul

Bibliographic record

VenueBenha Journal of Applied Sciences · 2020
Typearticle
Languageen
FieldMedicine
TopicCerebral Venous Sinus Thrombosis
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHomocysteineThrombosisInternal medicineVenous thrombosisCerebral venous sinus thrombosisCardiologyThrombusGastroenterology

Abstract

fetched live from OpenAlex

Serum Homocysteine elevation, has been observed in some cerebral vinous sinus thrombosis patients. There is a complex overlap between homocysteine level and cerebrovascular disease, and the cause and significance of homocysteine rise in cerebral vinous sinus thrombosis are still controversial.To detect serum homocysteine level in patients with cerebral venous sinus thrombosis and its impact on its severity, short term outcome, size of thrombosis. In this case control study, sixteen patients of CVST (13 males & 3 females) and 35 matched control subjects were recruited for this study. Serum homocysteine level was estimated by Enzyme-Linked Immunosorbent Assay (ELISA). Assessment of severity of thrombosis was done based on Canadian Neurological Scale. Assessment of outcome on discharge was done based on Barthel index score. In this study serum homocysteine level was raised in Cerebral Vinous Sinus Thrombosis cases when compared to controls on admission. The mean and standard deviation of homocysteine were 42.5 ± 54.2μmol/l in cases with significant p value of < 0.05. Cases with high homocysteine levels had low severity scores, which indicate poor prognosis. Homocyteine elevation in cerebral vinous sinus thrombosis (CVST) patients was associated with CT changes, severe thrombosis, large thrombus size and bad outcome.

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)0.001
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 score0.007
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.059
GPT teacher head0.298
Teacher spread0.239 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueBenha Journal of Applied SciencesSame topicCerebral Venous Sinus ThrombosisFrench-language works237,207