Global trends and hotspots of neuromodulation in spinal cord injury: a study based on bibliometric analysis
Bibliographic record
Abstract
OBJECTIVE: Spinal cord injury (SCI) is a debilitating condition that can result in permanent disability. Neuromodulation is a promising technology that has gained popularity as a treatment for SCI. This study aims to analyze the published literature to investigate the global trends and hotspots in research on neuromodulation in the context of SCI. METHODS: All relevant publications on the topic of neuromodulation in SCI from January 1, 2005, to September 17, 2024, were acquired from the Web of Science Core Collection database. Bibliometric analysis was performed to evaluate the publication distribution by country, institution, author, and journal, as well as keyword, using CiteSpace, VOSviewer, and Scimago Graphica software. RESULTS: Overall, 3,211 publications were eligible for inclusion in the analysis. The publication number in 2005 and 2024 were 77 and 222, respectively. A steady increasing trend in the publication number over the past two decades was observed. The Unites States published 1544 articles with 52,521 citations, ranking first regarding publication number and total citations. Case Western Reserve University was the most productive institution that published 181 papers. All of the highly productive institutions were located in the United States, Canada, and Australia. The University of California Los Angeles harvested 6626 total citations and 81.8 average citations, ranking first among the productive institutions. Gorgey AS published 60 articles and ranked first regarding total publication number. Edgerton VR harvested 4333 citations and ranked first among the authors for total citations. The analysis of high-yielding journals suggested that Journal of Spinal Cord Medicine was the most productive journal with 133 publications. Spinal Cord yielded 4200 citations and ranked first among the journals for total citations. The keyword analysis identified "functional electrical stimulation" and "spinal cord stimulation" as research hotspots. CONCLUSION: This study delineates the current knowledge landscape and research trends on the topic of neuromodulation in SCI. The findings highlight the growing interest in this field and underscore the significance of neuromodulation in SCI research.
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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 | 0.006 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.095 | 0.132 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".