Your browser doesn't support javascript.
loading
Learning curves in robotic neurosurgery: a systematic review.
Shlobin, Nathan A; Huang, Jonathan; Wu, Chengyuan.
Afiliação
  • Shlobin NA; Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, 676 N. St. Clair Street, Suite 2210, Chicago, IL, 60611, USA. nathan.shlobin@northwestern.edu.
  • Huang J; Department of Neurological Surgery, Northwestern University Feinberg School of Medicine, 676 N. St. Clair Street, Suite 2210, Chicago, IL, 60611, USA.
  • Wu C; Department of Neurological Surgery, Thomas Jefferson University Hospitals, Philadelphia, PA, USA.
Neurosurg Rev ; 46(1): 14, 2022 Dec 12.
Article em En | MEDLINE | ID: mdl-36504244
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.
Assuntos
Palavras-chave

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cirurgiões / Neurocirurgia Tipo de estudo: Systematic_reviews Limite: Child / Humans Idioma: En Revista: Neurosurg Rev Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Cirurgiões / Neurocirurgia Tipo de estudo: Systematic_reviews Limite: Child / Humans Idioma: En Revista: Neurosurg Rev Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos País de publicação: Alemanha