Changes of brain function and cognitive function in patients with acute cerebellar stroke
Bibliographic record
Abstract
Objective To investigate the changes of brain function and cognitive function in patients with acute cerebellar stroke using amplitude of low-frequency fluctuation (ALFF) and functional connection (FC). Methods The cognitive function assessment and resting state functional magnetic resonance (rs-fMRI) scan were performed on patients with acute cerebellar stroke hospitalized in Taizhou People′s Hospital or Nanjing Brain Hospital from May 2017 to June 2018. The differences of ALFF and FC values were compared. Pearson correlation analysis was used to understand the correlation between FC values and cognitive function scores. A total of 32 patients with acute cerebellar stroke and 34 healthy controls were included. Results Compared with the healthy controls, the scores of Montreal Cognitive Assessment (23.97±6.04 vs 26.56±2.93, t=-2.237, P=0.029), the Rey Auditory Verbal Learning Test (RAVLT; 3(2) vs 6(2), Z=-4.136, P=0.000) were significantly lower, and the time consuming of Trail Making Test (TMT) -B ((251.56±112.62) s vs (164.76±52.37) s) was significantly higher (t=4.054, P=0.000) in the patients with acute cerebellar stroke. The rs-fMRI results showed significant group differences in ALFF values at the four brain regions, including the right frontal lobe, left hippocampus, right cingulate gyrus and cerebellum posterior lobe. The regions that showed significant group differences were set as regions of interest (ROIs), and then the functional connectivity between ROIs and the whole brain were analyzed. The results showed significant positive correlation between the RAVLT scores and the FC values from the left hippocampus to the left frontal lobe (r=0.272, P=0.031). The FC values from the right cingulate gyrus to right inferior parietal lobule were found to be correlated positively with the scores on the TMT-B (r=0.410, P=0.023). Conclusions The patients with cerebellar stroke had cognitive impairment, mainly in memory and executive function. The changes of ALFF and FC values in related brain area from cerebellar stroke enrich our understanding of cerebellar involvement in cognitive performance. Key words: Magnetic resonance imaging; Stroke; 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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".