Levels of Evidence in the Neurosurgical Literature
Bibliographic record
Abstract
BACKGROUND: The importance of evidence-based medicine has been well documented and supported across various surgical subspecialties. OBJECTIVE: To quantify the levels of evidence across publications in the neurosurgical literature, to assess the change in evidence over time, and to indicate predictive factors of higher-level evidence. METHODS: We reviewed the levels of evidence across published clinical studies in 3 neurosurgical journals from 2009 to 2010. Randomized trials were evaluated by use of the Detsky quality of reporting scale. Levels-of-evidence data for the same journals in 1999 were obtained from the literature, and regression analysis was performed to identify predictive factors for higher-level evidence. RESULTS: Of 660 eligible articles, 14 (2.1%) were Level I, 54 (8.2%) were level II, 73 (11.1%) were Level III, 287 (43.5%) were level IV, and 232 (35.2%) were level V. The number of level I studies decreased significantly between 1999 and 2010 (3.4% vs. 2.1%, respectively; P = .01). Seven randomized clinical trials were identified, and 1 trial had significant methodological limitations (mean Detsky index = 16.3; SD = 1.8). Publications with larger sample size were significantly associated with higher levels of evidence (levels I and II; odds ratio, 1.7; 95% confidence interval, 1.45-2.05; P = .001). The ratio of higher levels of evidence to lower levels was 0.11. CONCLUSION: Higher levels of evidence (levels I and II) represent only 1 in 10 neurosurgical clinical papers in the top neurosurgical journals. Increased awareness of the need for better evidence in the field through education and adoption of the levels of evidence may improve the conduct and publication of prospective studies.
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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 | 0.190 | 0.088 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.009 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.005 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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; both teacher heads agree on what is shown here.
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".