Global neurosurgery: a scoping review detailing the current state of international neurosurgical outreach
Bibliographic record
Abstract
OBJECTIVE: Global neurosurgery is a rapidly emerging field that aims to address the worldwide shortages in neurosurgical care. Many published outreach efforts and initiatives exist to address the global disparity in neurosurgical care; however, there is no centralized report detailing these efforts. This scoping review aims to characterize the field of global neurosurgery by identifying partnerships between high-income countries (HICs) and low- and/or middle-income countries (LMICs) that seek to increase neurosurgical capacity. METHODS: A scoping review was conducted using the Arksey and O'Malley framework. A search was conducted in five electronic databases and the gray literature, defined as literature not published through traditional commercial or academic means, to identify studies describing global neurosurgery partnerships. Study selection and data extraction were performed by four independent reviewers, and any disagreements were settled by the team and ultimately the team lead. RESULTS: The original database search produced 2221 articles, which was reduced to 183 final articles after applying inclusion and exclusion criteria. These final articles, along with 9 additional gray literature references, captured 169 unique global neurosurgery collaborations between HICs and LMICs. Of this total, 103 (61%) collaborations involved surgical intervention, while local training of medical personnel, research, and education were done in 48%, 38%, and 30% of efforts, respectively. Many of the collaborations (100 [59%]) are ongoing, and 93 (55%) of them resulted in an increase in capacity within the LMIC involved. The largest proportion of efforts began between 2005-2009 (28%) and 2010-2014 (17%). The most frequently involved HICs were the United States, Canada, and France, whereas the most frequently involved LMICs were Uganda, Tanzania, and Kenya. CONCLUSIONS: This review provides a detailed overview of current global neurosurgery efforts, elucidates gaps in the existing literature, and identifies the LMICs that may benefit from further efforts to improve accessibility to essential neurosurgical care worldwide.
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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 | 0.026 | 0.104 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.036 | 0.032 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".