The clinical research of the repetitive transcranial magnetic stimulation( rTMS) treatment on VCIND cerebral infarction patients
Bibliographic record
Abstract
Objective To investigate the efficacy and safety of r TMS in improving cognitive function of VCIND cerebral infarction patients. Methods VCIND cerebral infarction patients were divided into the r TMS and the control group,both of which were given traditional medication. Low-frequency r TMS stimulation of the contralateral forehead dorsal zone was given to the r TMS group,and patients of control were given sham stimulation. MMSE,Moca,NIHSS,ADL,Hachinski,Fazekas,CHIPS and HAMD-17 score were given to both groups. The scores of the two groups were analyzed. Results 1At baseline,no group differences were discovered( P 0. 05). 2 After 3 months treatment,MMSE and Moca scores weresignificantly improved in r TMS group. However,scores of Moca in r TMS group showed a great improvement than control group( P 0. 01). 3 Moca score was increased gradually with treatment duration in r TMS group and it was significantly enhanced after the third course( P 0. 01). 4 The r TMS group had a significant higher Moca single score in space,executive,language ability and delayed memory 3 months post-treatment compared to that before treatment and control group( P 0. 01, 0. 05). 5 After 3 months,r TMS group showed an increased Moca score in patients without depression than those with depression. Moca score was significantly higher in primary stroke versus comprehensive stroke. Conclusion The r TMS treatment can significantly promote VCIND cognitive function. Cognitive improvement in primary stroke exceeded that in comprehensive stroke. The depressive disorder may impede the cognitive function recovery of VCIND patients.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".