Challenges and limitations in meta-analyses of complications in neurosurgery: Systematic review with proposed approach and checklist to mitigate errors and improve the assessment of the real-world experience.

Meta-analyses are highly valued in medical science, yet accurately reporting complications in neurosurgical studies remains challenging. Examples include inconsistencies in defining and classifying complications and variations in reporting methods. This lack of reproducibility and comparability, along with other issues related to biases, hinders the ability of meta-analyses to yield significant advancements. This systematic review investigated the challenges and limitations inherent in meta-analyses of complications in neurosurgery. Based on the identified challenges and our group's experience, we developed a practical checklist to mitigate and avoid common errors in meta-analyses of complications in neurosurgery.We searched PubMed, Embase, and Web of Science for studies addressing challenges in assessing complications in neurosurgery. The main findings were qualitatively synthesized to identify common challenges and limitations. The proposed checklist was developed using a modified Delphi technique. Eleven studies were included, uncovering heterogeneity and a lack of standardization regarding the classification of complications in neurosurgery across various authors and institutions. They suggested solutions such as implementing a more uniform classification system. Additionally, the NeuroComp Meta-Analysis Checklist was developed, comprising 23 items divided into 5 domains, with a practical approach and suggestions on how to deal with the challenges when meta-analyzing.We identified numerous challenges and concerns when assessing complications in the neurosurgical field. The NeuroComp Meta-Analysis Checklist incorporated methodologies and approaches we utilized in several previously published meta-analyses. While we acknowledge that the proposal cannot solve all the issues involved in comparing and meta-analyzing complications in neurosurgery, it has the potential to enhance the informativeness of future meta-analyses and help authors mitigate common errors. Ultimately, this tool has the potential to contribute to the advancement of accumulating real-world evidence in neurosurgical science.