The Detection of Cerebral Microbleeds by Susceptibility Weighted Imaging and the Relationship between Cerebral Microbleeds and Cognitive Function
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".