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Record W4317935362 · doi:10.12669/pjms.39.2.6425

Clinical characteristics of cerebral vascular dementia and early diagnostic value of cranial nuclear magnetic resonance

2023· article· en· W4317935362 on OpenAlexaboutno aff
Wenxing Zhou, Lianxia Li, Yan Lang, Hongxin Jiang

Bibliographic record

VenuePakistan Journal of Medical Sciences · 2023
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineDementiaMagnetic resonance imagingStroke (engine)Vascular dementiaMontreal Cognitive AssessmentAtrophyCardiologyInternal medicineRadiology

Abstract

fetched live from OpenAlex

Objective: This study aimed to observe the diagnostic value of cranial magnetic resonance imaging (MRI) in patients with vascular dementia induced by ischemic stroke. Methods: The experiment was designed according to the randomized control principle. Two hundred and eighty patients with ischemic stroke who were admitted to Gucheng County Hospital between June 2019 and June 2021 were selected as research subjects. Patients without vascular dementia after stroke were included in the control group, and patients with vascular dementia after stroke were included in the observation group. The cranial MRI was performed in both groups. Results: Proportions of patients with large and moderate infarct lesions in brain tissues were significantly higher in the observation group than the control group. The data variation of relevant MRI detection indicators of the observation group was more obvious than that of the control group (P<0.05). The mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scores of the observation group were lower than those of the control group (P<0.05), but the HIS score was higher (P>0.05). Patients with changes in brain morphology were more in the observation group than the control group (P<0.05). Conclusion: Patients with vascular dementia induced by ischemic stroke are characterized by cortical atrophy, widening of the cerebral sulcus, large infarct lesion area and sparse cerebral white matter. Cranial MRI can effectively identify these features. The application of cranial MRI has some clinical values for early treatment and prognostic assessment. doi: https://doi.org/10.12669/pjms.39.2.6425 How to cite this: Zhou W, Li L, Lang Y, Jiang H. Clinical characteristics of cerebral vascular dementia and early diagnostic value of cranial nuclear magnetic resonance. Pak J Med Sci. 2023;39(2):508-512. doi: https://doi.org/10.12669/pjms.39.2.6425 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.239
Threshold uncertainty score0.576

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
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 science0.0010.000
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 head0.040
GPT teacher head0.333
Teacher spread0.293 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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