Effect of Repetitive Transcranial Magnetic Stimulation on Patients with Post-Stroke Cognitive Impairment
Bibliographic record
Abstract
Objective:To observe the improvement of cognitive function and the changes of serum nerve influencing factors and cytokines in patients with stroke treated with repetitive transcranial magnetic stimulation (rTMS).Methods:A total of 100 patients with post-stroke congitive impairment (PSCI) were randomly divided into observation group (n=51) and control group (n=49) by SAS software. The control group received routine treatment. On the basis of routine treatment, the observation group was treated with rTMS once a day, five times a week for eight weeks. Before and after treatment, the cognitive function scores of the two groups were compared, the changes of mini-mental state examination (MMSE) and Montreal cognitive function (MoCA) scores were compared, the activities of daily living (ADL) and auditory verbal learning test (AVLT) were observed. ELISA method was used to observe the changes of brain-derived neurotrophic factor (BDNF), vascular endothelial growth factor (VEGF), interleukin-6(IL-6) and high-sensitivity C-reactive protein (hs-CRP) in the two groups after treatment.Results:There were no significant differences in the scores of MoCA, including orientation (ORT), visual space and executive function (EF), naming (NAM), memory (MEM), attention (ATT), language (LANG) and abstract ability (ABS) before treatment between the two groups (P> 0.05). After eight weeks of treatment, ORT, EF, NAM, MEM, ATT, LANG and ABS in the two groups were significantly higher than those before treatment (P< 0.05, P< 0.01). The MoCA score of the observation group was significantly better than that of the control group (P< 0.05). There were no significant differences in MMSE, AVLT123, AVLT5, AVLT recognition, ADL scores between the two groups before treatment (P> 0.05). After treatment, the MMSE, AVLT123, AVLT5, AVLT recognition and ADL scores of the control group were (21.34±2.35), (9.15±3.36), (2.16±0.32), (15.24±2.62), (68.16±12.35), and those of the observation group were (25.21±3.45), (13.23±3.35), (2.24±1.62), (17.32±6.26), (74.43±15.34), the differences between the two groups were significantly higher than those before treatment (P< 0.05, P< 0.01), and the improvement of the observation group was better than that of the control group after treatment (P< 0.05). There were no significant differences in serum BDNF, VEGF, IL-6 and hs-CRP levels before treatment between the two groups (P> 0.05). After treatment, the serum levels of BDNF, VEGF, IL-6 and hs-CRP in the control group were (6.19±0.75) ng/mL, (113.25±11.35) pg/mL, (9.12±4.23) mmol/L, (3.74±1.47) mmol/L, and the serum levels of BDNF, VEGF, IL-6 and hs-CRP in the observation group were (8.25±0.94) ng/mL, (172.36±18.35) pg/mL, (6.78±3.86) mmol/L, (2.25±1.25) mmol/L, the serum levels of BDNF, VEGF, IL-6 and hs-CRP in the two groups were better than those before treatment (P< 0.05, P< 0.01), and the improvement in the observation group was significantly higher than that in the control group (P< 0.05).Conclusion:rTMS can furtherly improve PSCI by improving cognitive function.
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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) | 0.001 | 0.001 |
| 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 | 0.000 |
| 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".