Analgesic Effects of Directed Repetitive Transcranial Magnetic Stimulation in Acute Neuropathic Pain After Spinal Cord Injury
Bibliographic record
Abstract
OBJECTIVES: Central neuropathic pain (CNP) often appears following spinal cord injury (SCI), but current treatments are not always successful. In this study, we evaluated the analgesic effects of repetitive transcranial magnetic stimulation (rTMS) applied over the hand area of the motor cortex in patients with acute CNP after SCI. METHODS: A total of 48 patients with complete or incomplete SCI and acute CNP participated in this study and were randomized to receive either rTMS (10 Hz, 1,500 stimuli; N = 24) or a sham intervention (N = 24) for three weeks. The numeric rating scale (NRS) and Short-Form McGill Pain Questionnaire-2 (Chinese Edition; SF-MPQ-2-CN) were analyzed to assess the degree of pain. Brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF) were collected to explore expression influenced by rTMS. Motor-evoked potential (MEP) latency and maximal amplitude were measured to determine neurophysiological changes. The assessments were carried out at baseline (T0), three days (T1), one week (T2), two weeks (T3), and three weeks (T4) after onset of treatment. RESULTS: The analysis showed significant treatment-time interactions for the quality and intensity of pain, as measured by NRS (P < 0.001, η2 = 0.441) and SF-MPQ-2 (P < 0.001, η2 = 0.590). Compared with the sham group, the NRS and SF-MPQ2-CN scores were significantly lower on the third day (P < 0.001, Cohen's d = 1.135; P = 0.006, Cohen's d = 0.616) and after one week (P < 0.001, Cohen's d = 0.846; P = 0.012, Cohen's d = 0.557) of treatment. In addition, the serum levels of BDNF and NGF were significantly higher in the treated group after three weeks (P = 0.015, Cohen's d = 0.539; P = 0.009, Cohen's d = 0.580), and the MEP amplitude increased by 109.59% (P = 0.033, Cohen's d = 0.464). CONCLUSIONS: These findings indicate that 10 Hz rTMS over the hand area of the motor cortex could alleviate acute CNP in the early phase of SCI and could enhance MEP parameters and modulate BDNF and NGF secretion.
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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".