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Record W2364185933

The Detection of Cerebral Microbleeds by Susceptibility Weighted Imaging and the Relationship between Cerebral Microbleeds and Cognitive Function

2014· article· en· W2364185933 on OpenAlex
Xiao Gui-ron

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueZhongguo quanke yixue · 2014
Typearticle
Languageen
FieldMedicine
TopicIntracerebral and Subarachnoid Hemorrhage Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMontreal Cognitive AssessmentCognitionNeurologyInternal medicinePhysical therapyAudiologyCognitive impairmentPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

Objective To investigate the detection of cerebral microbleeds(CMBs) by susceptibility weighted imaging(SWI),and influence of CMBs on cognitive function. Methods 50 patients who were actually diagnosed with CMBs by SWI in inpatient and outpatient departments of neurology,Shaoxing People's Hospital from January 2012 to August 2013,were selected as CMBs group,during the same period,while 44 sex-,age- and education level- matched physical examination people who were not found to have CMBs by SWI,were selected as control group,their cognitive function was evaluated by MoCA rating scale,MoCA score were compared between the two groups and the cognitive dysfunction caused by CMBs of different regions and different degrees. Results SWI imaging features of CMBs were sharply marginated small round low signal images in brain parenchyma. The total MoCA scores,visuospatial skills and execution function scores,nomenclature scores,attention scores,language scores,abstracting scores,memory scores and directive force scores in CMBs group were significantly lower than those in control group(P 0. 05). The total MoCA scores,visuospatial skills and execution function scores,abstracting scores and memory scores in mild CMBs group,moderate CMBs group and severe CMBs group were significantly lower than those in control group; Nomenclature scores,attention scores and language scores in moderate CMBs group and severe CMBs group were significantly lower than those in control group(P 0. 05). The total MoCA scores,attention scores,abstracting scores and memory scores in moderate CMBs group and severe CMBs group were significantly lower than those in mild CMBs group;Visuospatial skills and execution function scores and language scores in severe CMBs group were significantly lower than those in mild CMBs group(P 0. 05). The total MoCA scores,visuospatial skills and execution function scores,attention scores,lan-guage scores and memory scores in severe CMBs group were significantly lower than those in moderate CMBs group(P 0. 05).According to Spearman correlation analysis results,the CMBs number was negatively correlated with total MoCA scores,visuospatial skills and execution function scores,attention scores,language scores,abstracting scores and memory scores(P 0. 05); Cortico- subcortical CMBs was negatively correlated with total MoCA scores,visuospatial skills and execution function scores,attention scores,language scores and memory scores(P 0. 05); Basal ganglia and thalamus CMBs was negatively correlated with total MoCA scores and language scores(P 0. 05); Brainstem and subtentorial CMBs was negatively correlated with total MoCA scores and visuospatial skills and execution function scores(P 0. 05). Conclusion SWI can clearly display CMBs,CMBs can cause cognitive dysfunction,and the characteristics of cognitive dysfunction varies by the region and degree of CMBs.

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.

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)0.001
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 score0.084
Threshold uncertainty score0.651

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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