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Record W4381856609 · doi:10.3389/fnagi.2023.1221548

The correlation between the severity of cerebral microbleeds and serum HMGB1 levels and cognitive impairment in patients with cerebral small vessel disease

2023· article· en· W4381856609 on OpenAlexaboutno aff
Minghua Wang, Junli Liu, Fan Wang, Qing Li, Jian Zhang, Sibei Ji, Shaomin Li, Chengbiao Lu, Jianhua Zhao

Bibliographic record

VenueFrontiers in Aging Neuroscience · 2023
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
FundersXinxiang Medical UniversityNatural Science Foundation of Henan ProvinceNational Natural Science Foundation of China
KeywordsCorrelationCognitive impairmentDiseaseMedicineCognitionInternal medicineCardiologyNeurosciencePsychology

Abstract

fetched live from OpenAlex

Objective The study investigated the correlation and predictive value between the severity of cerebral microbleeds (CMBs) and the level of serum High Mobility Group Protein B1 (HMGB1) and the occurrence of cognitive impairment in patients with cerebral small vessel disease (CSVD). Methods A total of 139 patients with CSVD admitted to the Department of Neurology of the First Affiliated Hospital of Xinxiang Medical University from December 2020 to December 2022 were selected as study subjects. The Montreal Cognitive Assessment (MoCA) scale was used to assess the cognitive function and was divided into the cognitive impairment group and the cognitive normal group. Magnetic Resonance Imaging (MRI) and Susceptibility Weighted Imaging (SWI) were used to screen and assess the severity of CMBs. Serum HMGB1 levels of CSVD patients were measured by enzyme linked immunosorbent assay (ELISA). Multivariable logistic regression analysis was used to explore risk factors for cognitive impairment and CMBs. Pearson correlation analysis was used to investigate the correlation between HMGB1 and cognitive function. Receiver Operating Characteristics (ROC) curves were used to assess the predictive value of HMGB1 for the occurrence of cognitive impairment in patients with CMBs. Results High Mobility Group Protein B1, uric acid (UA), glycosylated hemoglobin (HbA1c), CMBs, lacunar cerebral infarction (LI), years of education, and history of hypertension were risk factors for cognitive impairment (P < 0.05); HMGB1 was significantly and negatively associated with total MoCA score, visuospatial/executive ability, and delayed recall ability (P < 0.05). HMGB1 was significantly and positively correlated with the number of CMBs (P < 0.05). The area under the ROC curve for HMGB1 predicting cognitive impairment in patients with CMBs was 0.807 (P < 0.001). Conclusion Serum HMGB1 levels are associated with the development of cognitive impairment in CSVD patients, and serum HMGB1 levels have a high predictive value for the development of cognitive impairment in CSVD patients with combined CMBs, which can be used for early clinical identification and intervention of vascular cognitive impairment.

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)0.000
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.016
GPT teacher head0.252
Teacher spread0.235 · 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

Citations5
Published2023
Admission routes1
Has abstractyes

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