Evidence map›Paper›PMID 37725193›Full record

SynthesisNeurosurgical review2023

Training models and simulators for endoscopic transsphenoidal surgery: a systematic review.

Giacomo Santona, Alba Madoglio, Davide Mattavelli, Mario Rigante, Marco Ferrari, Liverana Lauretti, Pierpaolo Mattogno, Claudio Parrilla, Pasquale De Bonis, Jacopo Galli and 5 more

Open access · hybridAbstract readSystematic Review
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
3.4field-weighted citation impact, top 6% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 7 institutions in 1 country.

Giacomo SantonaDepartment of Information Engineering, University of Brescia, Brescia, Italy.
Alba MadoglioDepartment of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara, Italy.
Davide MattavelliOtorhinolaryngology-Head and Neck Surgery, Department of Medical and Surgical Specialties, Radiological Sciences, and Public Health, ASST Spedali Civili of Brescia, University of Brescia, Brescia, Italy.
Mario RiganteOtorhinolaryngology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Marco FerrariSection of Otorhinolaryngology-Head and Neck Surgery, Department of Neurosciences, University of Padua - Azienda Ospedaliera di Padova, Padua, Italy.
Liverana LaurettiNeurosurgery, Department of Neurosciences, Sensory Organs and Thorax, Università Cattolica del Sacro Cuore, Rome, Italy.
Pierpaolo MattognoNeurosurgery, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Claudio ParrillaOtorhinolaryngology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Pasquale De BonisDepartment of Morphology, Surgery and Experimental Medicine, University of Ferrara, Ferrara, Italy.
Jacopo GalliOtorhinolaryngology, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy.
Alessandro OliviNeurosurgery, Department of Neurosciences, Sensory Organs and Thorax, Università Cattolica del Sacro Cuore, Rome, Italy.
Marco Maria FontanellaNeurosurgery, Department of Medical and Surgical Specialties, Radiologic Sciences, and Public Health, University of Brescia - ASST Spedali Civili di Brescia, Brescia, Italy.
Antonio FiorentinoDepartment of Mechanical and Industrial Engineering, University of Brescia, Brescia, Italy.
Mauro SerpelloniDepartment of Information Engineering, University of Brescia, Brescia, Italy.
Francesco DogliettoNeurosurgery, Department of Neurosciences, Sensory Organs and Thorax, Università Cattolica del Sacro Cuore, Rome, Italy. francesco.doglietto@unicatt.it.
University of Brescia · ITAgostino Gemelli University Polyclinic · ITIstituti di Ricovero e Cura a Carattere Scientifico · ITUniversità Cattolica del Sacro Cuore · ITUniversity of Ferrara · ITAzienda Socio Sanitaria Territoriale degli Spedali Civili di Brescia · ITUniversity of Padua · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

EndoscopySkull Base NeoplasmsAnimalsCadaverComputer SimulationDatabases, FactualHumans3D printingAnimal headArachnoidCadaveric headPituitary adenomaTraining modelsTraining simulatorsTranssphenoidal surgery

Identifiers

PMID37725193
PMCPMC10509294
OpenAlexW4386863802

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.