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Record W2801201061 · doi:10.1155/2018/6184260

Effect of Yin‐Xing‐Tong‐Zhi Tablets on Improving Vascular Cognitive Impairment No Dementia

2018· article· en· W2801201061 on OpenAlexaboutno aff
Weidong Pan, Wei Zhu, Qi Gao, Weilong Liao, Penglin Gao, Te Liu

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsCognitive impairmentDementiaInternal medicinePlaceboMedicineMontreal Cognitive AssessmentCognitionGastroenterologyPathologyPsychiatryDisease

Abstract

fetched live from OpenAlex

Objective . Observe the effect of the Chinese herbal extracts, Yin‐Xing‐Tong‐Zhi, in tablet form, on improving vascular cognitive impairment no dementia (VCIND). Methods . Sixty‐eight patients with VCIND were divided randomly into treatment and placebo groups with oral administration of Yin‐Xing‐Tong‐Zhi tablets (YXTZTs) or placebo, respectively, for 24 weeks. Alzheimer’s Disease Assessment Scale‐Cognitive (ADAS‐Cog) subscale score, MMSE score, Clinician’s Interview‐Based Impression of Change Plus Caregiver Input (CIBIC‐Plus) score, expression of interleukin‐ (IL‐) 6, IL‐8, and tumor necrosis factor‐ (TNF‐) α in serum, and variation of blood‐lipid levels were evaluated at different time points. Results . At weeks 12 and 24, the scores for the ADAS‐Cog, CIBIC‐Plus, and MMSE of the treatment group were significantly lower than those of the control group ( P < 0.05). All clinical scales at week 24 of the control group were significantly different from those before treatment ( P < 0.05). Expression of IL‐6, IL‐8, and TNF‐ α in the two groups was reduced significantly with variation of the clinical scales of cognitive impairment. Conclusion . YXTZTs may delay the development of cognitive impairment in VCIND patients by modulating expression of VCIND‐associated proinflammatory factors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.058
GPT teacher head0.332
Teacher spread0.274 · 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.

Study designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

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