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Low 25-Hydroxyvitamin D Increases the Risk of Cognitive and Emotional Disorders Among Chinese Patients with Cerebral Small Vessel Disease

2024· article· en· W4400464752 on OpenAlexaboutno aff
Jiaxin Zhi, Yanyong Wang, Libo Li, Jiaying Rong, Na Liu, Caili Han, Zhai Liu, Li Shen, Zhen-Yun Yuan, Bing Han

Bibliographic record

VenueCurrent Topics in Nutraceutical Research · 2024
Typearticle
Languageen
FieldMedicine
TopicCerebrovascular and Carotid Artery Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineInternal medicineCognitionNeurologyDiseaseAnxietyVitamin D and neurologyRisk factorHyperintensityPhysical therapyPediatricsPsychiatryMagnetic resonance imagingRadiology

Abstract

fetched live from OpenAlex

The association between 25-hydroxyvitamin D and cognitive impairment and emotional disorder in patients with cerebral small vessel disease is unknown. This retrospective study included, 504 Chinese patients with cerebral small vessel disease admitted to the Department of Neurology of the First Hospital of Hebei Medical University between June 2019 and October 2021. The Montreal Cognitive Assessment and Hamilton Anxiety Scale (14 items) scores were utilized to divide the patients into four groups. The multivariate Cox regression analysis revealed that low 25-hydroxyvitamin D, high homo-cysteine, hyperuricemia, severity of white matter lesions, and a history of hypertension were independent risk factors for cognitive impairment among patients with cerebral small vessel disease. However, a high level of education is a protective factor. Furthermore, the level of 25-hydroxyvitamin D was significantly associated with the changes in brain functional regions. Serum 25-hydroxyvitamin D is a promising biomarker for predicting cognitive and emotional disorders in patients with cerebral small vessel disease and is highly associated with alterations in brain functional regions.

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)0.002
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 score0.030
Threshold uncertainty score0.386

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.024
GPT teacher head0.338
Teacher spread0.315 · 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
Published2024
Admission routes1
Has abstractyes

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