Objectives: To identify the predictors of citation rates for research publication in Neurosciences.Methods: All original articles including meta-analyses (MAs) and systematic reviews (SRs) that were published in Neurosciences during 2011 to 2019 were reviewed. The impact of several predictors on citation rates was assessed using correlation coefficient and mean difference tests.Results: This study examined 231 articles. The mean article citation number was 11.6. The correlation analysis showed a significant association between citation rates and duration from publication in years (p<0.0001), sample size (p<0.0001), study design (p=0.0353), and level of evidence (LOE) (p=0.03). The comparative analysis showed significantly more citations for articles that were published 6-10 years ago (p<0.0001), had a sample size >91 (p=0.0359), were randomized controlled trials (p=0.0353), MAs and SRs (p<0.0001), and level of evidence (LOE)-I (p=0.0004). Retrospective case series had significantly lower citations. The higher and lower citation numbers for publications from Iran and rehabilitation, respectively, may have been influenced by the duration from publication. Conclusion:The most significant predictors of citation rates for Neurosciences publications were the age of articles, population size, study design, and LOE. Awareness of the predictors of citation rates may help researchers enhance the academic impact of their work.

Objectives: To highlight the disparity in the regional distribution of neurosurgical workforce in the Kingdom of Saudi Arabia (KSA) and to correlate the provision of neurosurgeons across the regions with several parameters. Methods: The 13 administrative emirates of provinces in KSA were grouped into five geographical regions (central, western, eastern, southern, and northern). The density of neurosurgeons was calculated for each region. The distribution of neurosurgeons across the regions was correlated with several parameters using Pearson coefficient test.Results: This study examined 238 neurosurgeons working in 85 neurosurgical centers in KSA. The regional median (range) density of neurosurgeons was 7.1 (3.1-10.2) per million population and 9.3 (2.3-23.3) per thousand square kilometer area. The regional provision of neurosurgeons correlated significantly with the distribution of KSA-national (p=0.031), KSA-certified (p=0.0004), Government Hospitals (GHs) (p=0.0012), and private hospitals (PHs) (p=0.0359) funded neurosurgeons. The regional allocation of neurosurgeons also correlated positively with the distribution of the total neurosurgical centers (p=0.048), the PHs centers (p=0.0057) but not the GHs centers (p=0.3296). Furthermore, a mismatch was observed between the regional distribution of the neurosurgical workforce and the provision of neurosurgeons according to their GHs' subdivisions, regional population, and area.Conclusions: The regional distribution of neurosurgeons in KSA was uneven. The density of neurosurgeons was the lowest in the southern and northern regions. There was disparity in the number of neurosurgeons employed by the various GHs' sub-divisions and in the allocation of GHs' neurosurgical centers across the regions. Easy access to quality neurosurgical care is imperative. Policy makers should take this into consideration in the future planning of regional neurosurgical services in KSA.

Clinical trials are at the top of research study designs and tend to attract high citation numbers. Glioblastoma multiforme (GBM) is a multidisciplinary disease that continues to be the subject of peak research interest. In general, the literature relating to the predictors of citation rates in clinical trials remains limited. This review aims to identify the factors that influence citation numbers in high-impact GBM clinical trials. The 100 most cited GBM trials of any phase published from 1975 to 2019 were selected and reviewed. The primary analysis correlated citation numbers of articles with various trial and publication-related predictors using the Pearson correlation coefficient. The secondary analysis compared the mean citation numbers for different subgroups using the mean difference test. The median (range) citation number for the selected 100 trials was 349 (135-16,384). The primary analysis showed a significant correlation between citation numbers of articles and the study population (P = 0.024), trial phase (I-III) (P = 0.0427), and the impact factor (IF) of the journal (P < 0.0001). The secondary analysis demonstrated significantly higher mean citation numbers in all trials with the following features: study population ≥115 (P = 0.0208), phase III (P = 0.0372), treatment protocol including radiotherapy (P = 0.0189), temozolomide (TMZ) therapy (P = 0.0343), IF of the journal ≥14.9 (P = 0.02), and general medical journals (P = 0.28). We conclude that the most significant predictors of citation rates in high-impact GBM trials were the study population, trial phase, and journal’s IF. The treatment protocol was a positive predictor when it included the currently widely accepted treatment modalities (radiotherapy and TZM). Randomization, age of publication, as well as the numbers of arms, authors, centers, countries, and references were not significant predictors. Increasing awareness of the factors that could affect citations may help researchers undertaking clinical trials to enhance the academic impact of their work.