SynthesisNeurosurgical review2022
Learning curves in robotic neurosurgery: a systematic review.
Synthesis in Neurosurgical review, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 3 of them syntheses 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
13 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Contemporary analysis of the learning curve for robotic-assisted total hip arthroplasty emerging technologies.Journal of robotic surgery · 2024Pooled it
- Navigating the learning curve: assessing caseload and comparing outcomes before and after the learning curve of computer-navigated total hip arthroplasty.Journal of robotic surgery · 2024Pooled it
- Usefulness of Robotic Stereotactic Assistance (ROSANeurologia medico-chirurgica · 2024Pooled it
- Neuroendoscopic-assisted abdominal wall puncture technique in ventriculoperitoneal shunt surgery: implication for clinical treatment.BMC surgery · 2026Article
- Robotic Surgery in Pediatric Epilepsy : Current Evidence, Clinical Impact, and Future Directions.Journal of Korean Neurosurgical Society · 2026Article
- [Spinal robotics vs. cone-beam navigation : A multidimensional comparison of both procedures].Orthopadie (Heidelberg, Germany) · 2026Review
- Ethical considerations in randomization for neurosurgical oncology trials: A scoping review.Neuro-oncology practice · 2026Review
- Factors Shaping Public Perceptions of a Range of Robotic Technologies in Surgery: Cross-Sectional Web-Based Survey.JMIR human factors · 2025Article
- Learning Curves Associated With Robotic Total Hip Arthroplasty: A Scoping Review.Orthopaedic surgery · 2025Article
- Global trends and hotspots in the learning curves of robotic-assisted surgery: a bibliometric and visualization analysis.Journal of robotic surgery · 2025Review
- Advancements in Imaging and Neurosurgical Techniques for Brain Tumor Resection: A Comprehensive Review.Cureus · 2024Review
- Safety and Complications Related to Emerging Technologies.Neurospine · 2024Article
- Clinical experiences and learning curves from robot-assisted neurosurgical biopsies with Stealth Autoguide™.Neuro-oncology advancesArticle
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
The transition to performing procedures robotically generally entails a period of adjustment known as a learning curve as the surgeon develops a familiarity with the technology. However, no study has comprehensively examined robotic learning curves across the field of neurosurgery. We conducted a systematic review to characterize the scope of literature on robotic learning curves in neurosurgery, assess operative parameters that may involve a learning curve, and delineate areas for future investigation. PubMed, Embase, and Scopus were searched. Following deduplication, articles were screened by title and abstract for relevance. Remaining articles were screened via full text for final inclusion. Bibliographic and learning curve data were extracted. Of 746 resultant articles, 32 articles describing 3074 patients were included, of which 23 (71.9%) examined spine, 4 (12.5%) pediatric, 4 (12.5%) functional, and 1 (3.1%) general neurosurgery. The parameters assessed for learning curves were heterogeneous. In total, 8 (57.1%) of 14 studies found reduced operative time with increased cases, while the remainder demonstrated no learning curve. Six (60.0%) of 10 studies reported reduced operative time per component with increased cases, while the remainder indicated no learning curve. Radiation time, radiation time per component, robot time, registration time, setup time, and radiation dose were assessed by ≤ 4 studies each, with 0-66.7% of studies demonstrated a learning curve. Four (44.4%) of 9 studies on accuracy showed improvement over time, while the others indicated no improvement over time. The number of cases required to reverse the learning curve ranged from 3 to 75. Learning curves are common in robotic neurosurgery. However, existing studies demonstrate high heterogeneity in assessed parameters and the number of cases that comprise the learning curve. Future studies should seek to develop strategies to reduce the number of cases required to reach the learning curve.
Indexed as
Identifiers
36504244What 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.