SynthesisBMC surgery2024
The learning curve in endoscopic transsphenoidal skull-base surgery: a systematic review.
Synthesis in BMC surgery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- State of the art and future perspectives on the management of spheno-orbital meningiomas: a meta-analysis comparing transorbital and transcranial approaches.Frontiers in oncology · 2026Pooled it
- Training in endoscopic endonasal surgery: EANS young neurosurgeons committee survey.Neurosurgical review · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe endoscopic endonasal transsphenoidal approach (EETA) has revolutionized skull-base surgery; however, it is associated with a steep learning curve (LC), necessitating additional attention from surgeons to ensure patient safety and surgical efficacy. The current literature is constrained by the small sample sizes of studies and their observational nature. This systematic review aims to evaluate the literature and identify strengths and weaknesses related to the assessment of EETA-LC.
methodsA systematic review was conducted following the PRISMA guidelines. PubMed and Google Scholar were searched for clinical studies on EETA-LC using detailed search strategies, including pertinent keywords and Medical Subject Headings. The selection criteria included studies comparing the outcomes of skull-base surgeries involving pure EETA in the early and late stages of surgeons' experience, studies that assessed the learning curve of at least one surgical parameter, and articles published in English.
resultsThe systematic review identified 34 studies encompassing 5,648 patients published between 2002 and 2022, focusing on the EETA learning curve. Most studies were retrospective cohort designs (88%). Various patient assortment methods were noted, including group-based and case-based analyses. Statistical analyses included descriptive and comparative methods, along with regression analyses and curve modeling techniques. Pituitary adenoma (PA) being the most studied pathology (82%). Among the evaluated variables, improvements in outcomes across variables like EC, OT, postoperative CSF leak, and GTR. Overcoming the initial EETA learning curve was associated with sustained outcome improvements, with a median estimated case requirement of 32, ranging from 9 to 120 cases. These findings underscore the complexity of EETA-LC assessment and the importance of sustained outcome improvement as a marker of proficiency.
conclusionsThe review highlights the complexity of assessing the learning curve in EETA and underscores the need for standardized reporting and prospective studies to enhance the reliability of findings and guide clinical practice effectively.
Indexed as
Identifiers
What OpenQuestion holds
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.