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Record W6980081363

Assessment of cognitive impairment in patients with chronic viral hepatitis

2023· article· en· W6980081363 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsnot available
Fundersnot available
KeywordsViral hepatitisCognitionStage (stratigraphy)Cognitive impairmentChronic hepatitisDiseaseViral diseaseHepatitis BDementia
DOInot available

Abstract

fetched live from OpenAlex

Background: Chronic viral hepatitis is a systemic disease characterized by a wide range of extrahepatic manifestations, one of which is cognitive impairment. Aim and Objectives: To assess cognitive impairment in patients with chronic viral hepatitis at various stages of liver fibrosis and assess factors affecting cognitive dysfunction. Material and Methods: Two hundred thirty three patients with chronic viral hepatitis at the Infectious Diseases Hospital of Shymkent City and the Regional Hepatological Center of Shymkent City were enrolled between March 2021 and January 2022. All patients were surveyed on Montreal Cognitive Assessment (MoCA) to confirm the presence of cognitive impairment. Results: Mild cognitive impairment was detected in 12.7% patients with fibrosis stage F0 , at the stage F1 -20.7% of patients, at the stage F2 - 32.5% of patients, at the stage F3 - 36.8% of patients, at the stage F4 -40% of patients. Subsequent multiple regression analysis showed that older age (p < 0.023) and duration of the disease (p < 0.002) were the variables most closely associated with cognitive impairment. Conclusion: The early identification of cognitive impairment in patients with chronic viral hepatitis is necessary due to the high risk of their progression to the stage of severe cognitive deficit.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.160
GPT teacher head0.566
Teacher spread0.406 · 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 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
Published2023
Admission routes1
Has abstractyes

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Same venueDOAJ (DOAJ: Directory of Open Access Journals)→Same topicHepatitis C virus research→French-language works237,207→