SynthesisNeurosurgical review2023
Training models and simulators for endoscopic transsphenoidal surgery: a systematic review.
Synthesis in Neurosurgical review, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Acceptance and use of extended reality in surgical training: an umbrella review.Systematic reviews · 2024Pooled it
- The Role of Virtual and Augmented Reality in Transsphenoidal Surgical Approaches to the Sellar and Parasellar Area-A Systematic Review.Journal of clinical medicine · 2026Review
- Frontiers of Innovation and Clinical Application in Endoscopic Endonasal Transsphenoidal Surgery.Journal of clinical medicine · 2026Review
- Use of three-dimensional-printed models for preoperative planning in endoscopic endonasal surgery for tuberculum sellae meningioma: A case report and literature review.Surgical neurology international · 2026Article
- Enhancing skull base tumor management: the combination of 3D printing technology and endoscopic surgical techniques.3D printing in medicine · 2025Article
- Utilities of 3D technology for planning endoscopic endonasal approaches. Case series of anatomical-imaging review.Journal of surgical case reports · 2025Article
- Innovating neurosurgical training: a comprehensive evaluation of a 3D-printed intraventricular neuroendoscopy simulator and systematic review of the literature.Frontiers in surgery · 2024Article
- Enhancing educational experience through establishing a VR database in craniosynostosis: report from a single institute and systematic literature review.Frontiers in surgery · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 7 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Endoscopic transsphenoidal surgery is a novel surgical technique requiring specific training. Different models and simulators have been recently suggested for it, but no systematic review is available. To provide a systematic and critical literature review and up-to-date description of the training models or simulators dedicated to endoscopic transsphenoidal surgery. A search was performed on PubMed and Scopus databases for articles published until February 2023; Google was also searched to document commercially available. For each model, the following features were recorded: training performed, tumor/arachnoid reproduction, assessment and validation, and cost. Of the 1199 retrieved articles, 101 were included in the final analysis. The described models can be subdivided into 5 major categories: (1) enhanced cadaveric heads; (2) animal models; (3) training artificial solutions, with increasing complexity (from "box-trainers" to multi-material, ct-based models); (4) training simulators, based on virtual or augmented reality; (5) Pre-operative planning models and simulators. Each available training model has specific advantages and limitations. Costs are high for cadaver-based solutions and vary significantly for the other solutions. Cheaper solutions seem useful only for the first stages of training. Most models do not provide a simulation of the sellar tumor, and a realistic simulation of the suprasellar arachnoid. Most artificial models do not provide a realistic and cost-efficient simulation of the most delicate and relatively common phase of surgery, i.e., tumor removal with arachnoid preservation; current research should optimize this to train future neurosurgical generations efficiently and safely.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.