دورية أكاديمية
Neurosurgical simulation models developed in Latin America and the Caribbean: a scoping review.
العنوان: | Neurosurgical simulation models developed in Latin America and the Caribbean: a scoping review. |
---|---|
المؤلفون: | Cuello JF; Neurosurgery Department, Hospital Cordero, San Fernando, Argentina. cuello.jf85@gmail.com., Bardach A; Instituto de Efectividad Clínica y Sanitaria (IECS-CONICET), Buenos Aires, Argentina.; Centro de Investigaciones Epidemiológicas y Salud Pública (CIESP-IECS), CONICET, Buenos Aires, Argentina., Gromadzyn G; Neurosurgery Department, Hospital Garrahan, Buenos Aires, Argentina., Ruiz Johnson A; Neurosurgery Department, Hospital Garrahan, Buenos Aires, Argentina., Comandé D; Instituto de Efectividad Clínica y Sanitaria (IECS-CONICET), Buenos Aires, Argentina., Aguirre E; Neurosurgery Department, Hospital Cordero, San Fernando, Argentina., Ruvinsky S; Research Department, Hospital Garrahan, Buenos Aires, Argentina. |
المصدر: | Neurosurgical review [Neurosurg Rev] 2023 Dec 30; Vol. 47 (1), pp. 24. Date of Electronic Publication: 2023 Dec 30. |
نوع المنشور: | Systematic Review; Journal Article; Review |
اللغة: | English |
بيانات الدورية: | Publisher: Springer Berlin Heidelberg Country of Publication: Germany NLM ID: 7908181 Publication Model: Electronic Cited Medium: Internet ISSN: 1437-2320 (Electronic) Linking ISSN: 03445607 NLM ISO Abbreviation: Neurosurg Rev Subsets: MEDLINE |
أسماء مطبوعة: | Publication: Berlin : Springer Berlin Heidelberg Original Publication: Berlin : Walter De Gruyter |
مواضيع طبية MeSH: | Neurosurgery*/education , Neuroendoscopy*, Animals ; Humans ; Latin America ; Neurosurgical Procedures/education ; Caribbean Region |
مستخلص: | Simulation training is an educational tool that provides technical and cognitive proficiency in a risk-free environment. Several models have recently been presented in Latin America and the Caribbean (LAC). However, many of them were presented in non-indexed literature and not included in international reviews. This scoping review aims to describe the simulation models developed in LAC for neurosurgery training. Specifically, it focuses on assessing the models developed in LAC, the simulated neurosurgical procedures, the model's manufacturing costs, and the translational outcomes. Simulation models developed in LAC were considered, with no language or time restriction. Cadaveric, ex vivo, animal, synthetic, and virtual/augmented reality models were included for cranial and spinal procedures. We conducted a review according to the PRISMA-ScR, including international and regional reports from indexed and non-indexed literature. Two independent reviewers screened articles. Conflicts were resolved by a third reviewer using Covidence software. We collected data regarding the country of origin, recreated procedure, type of model, model validity, and manufacturing costs. Upon screening 917 studies, 69 models were developed in LAC. Most of them were developed in Brazil (49.28%). The most common procedures were related to general neurosurgery (20.29%), spine (17.39%), and ventricular neuroendoscopy and cerebrovascular (15.94% both). Synthetic models were the most frequent ones (38.98%). The manufacturing cost ranged from 4.00 to 2005.00 US Dollars. To our knowledge, this is the first scoping review about simulation models in LAC, setting the basis for future research studies. It depicts an increasing number of simulation models in the region, allowing a wide range of neurosurgical training in a resource-limited setting. (© 2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.) |
References: | Cobb MI, Taekman JM, Zomorodi AR, Gonzalez LF, Turner DA (2016) Simulation in neurosurgery-a brief review and commentary. World Neurosurg 89:583–6. https://doi.org/10.1016/j.wneu.2015.11.068. (PMID: 10.1016/j.wneu.2015.11.06826704209) Toma AK, Camp S, Watkins LD, Grieve J, Kitchen ND (2009) External ventricular drain insertion accuracy. Neurosurgery 65(6):1197–1201. https://doi.org/10.1227/01.neu.0000356973.39913.0b. (PMID: 10.1227/01.neu.0000356973.39913.0b19934980) Rolston JD, Bernstein M (2015) Neurosurgery clinics of North America. Errors Neurosurg 26(2):149–55. https://doi.org/10.1016/j.nec.2014.11.011. (PMID: 10.1016/j.nec.2014.11.011) Meyer HS, Wagner A, Obermueller T et al (2022) Assessment of the incidence and nature of adverse events and their association with human error in neurosurgery. A prospective observation. Brain Spine 2(100853). https://doi.org/10.1016/j.bas.2021.100853. Nowitzke AM (2005) Assessment of the learning curve for lumbar microendoscopic discectomy. Neurosurgery 56(4):755–762. https://doi.org/10.1227/01.neu.0000156470.790. (PMID: 10.1227/01.neu.0000156470.79015792514) Ryang Y-M, Villard J, Obermüller T et al (2015) Learning curve of 3D fluoroscopy image–guided pedicle screw placement in the thoracolumbar spine. Spine J 15(3):467–476. https://doi.org/10.1016/j.spinee.2014.10.003. (PMID: 10.1016/j.spinee.2014.10.00325315133) Whang EE, Mello MM, Ashley SW et al (2003) Implementing resident work hour limitations: lessons from the New York State experience. Ann Surg 237:449–455. https://doi.org/10.1097/01.SLA.0000059966.07463.19. (PMID: 10.1097/01.SLA.0000059966.07463.19126771361514465) Whang EE, Perez A, Ito H, Mello MM, Ashley SW, Zinner MJ (2003) Work hours reform: perceptions and desires of contemporary surgical residents. J Am Coll Surg 197(4):624–630. https://doi.org/10.1016/S1072-7515(03)00602-1. (PMID: 10.1016/S1072-7515(03)00602-114522334) Kurup V, Matei V, Ray J (2017) Role of in-situ simulation for training in healthcare: opportunities and challenges. Curr Opin Anaesthesiol 30(6):755–760. https://doi.org/10.1097/ACO.0000000000000514. (PMID: 10.1097/ACO.000000000000051428968283) Delisle M, Ward MAR, Pradarelli JC, Panda N, Howard JD, Hannenberg AA (2019) Comparing the learning effectiveness of healthcare simulation in the observer versus active role: systematic review and meta-analysis. Simul Healthc 14(5):318–32. https://doi.org/10.1097/SIH.0000000000000377. Rosen MA, Hunt EA, Pronovost PJ, Federowicz MA, Weaver SJ (2012) In situ simulation in continuing education for the health care professions: a systematic review. J Contin Educ Health Prof Fall 32(4):243–254. https://doi.org/10.1002/chp.21152. (PMID: 10.1002/chp.21152) Rehder R, Abd-El-Barr M, Hooten K, Weinstock P, Madsen JR, Cohen AR (2016) The rol of simulation in neurosurgery. Childs Nerv Syst 32:43–54. https://doi.org/10.1007/s00381-015-2923-z. (PMID: 10.1007/s00381-015-2923-z26438547) Bradley P (2006) The history of simulation in medical education and possible future directions. Med Educ 40:245–262. https://doi.org/10.1111/j.1365-2929.2006.02394.x. (PMID: 10.1111/j.1365-2929.2006.02394.x) Singh H, Kalami M, Acosta-Torres S, El Ahmadieh TY, Loya J, Ganju A (2013) History of simulation in medicine: from Resusci Annie to the Ann Myers Medical Center. Neurosurgery 73(1):9–14. https://doi.org/10.1227/NEU.0000000000000093. (PMID: 10.1227/NEU.000000000000009324051890) Coelho G, Zanon N, Warf B (2014) The role of simulation in neurosurgery. Child Nerv Syst 30:1997–2000. https://doi.org/10.1007/s00381-014-2548-7. (PMID: 10.1007/s00381-014-2548-7) Patel EA, Aydin A, Cearns M, Dasgupta P, Ahmed K (2020) A systematic review of simulation-based training in neurosurgery, Part 1: Cranial Neurosurgery. World Neurosurg 133:e850–e873. https://doi.org/10.1016/j.wneu.2019.08.262. (PMID: 10.1016/j.wneu.2019.08.26231541755) Patel EA, Aydin A, Cearns M, Dasgupta P, Ahmed K (2020) A systematic review of simulation-based training in neurosurgery, Part 2: spinal and pediatric surgery, neurointerventional radiology, and nontechnical skills. World Neurosurg 133:e874–e892. https://doi.org/10.1016/j.wneu.2019.08.263. (PMID: 10.1016/j.wneu.2019.08.26331541754) Kirkman MA, Ahmed M, Albert AF, Wilson MH, Nandi D, Sevdalis N (2014) The use of simulation in neurosurgical education and training. A systematic review. J Neurosurg 121(2):228–246. https://doi.org/10.3171/2014.5.JNS131766. (PMID: 10.3171/2014.5.JNS13176624949680) Peters MDJ, Marnie C, Tricco AC et al. (2020) Updated methodological guidance for the conduct of scoping reviews. JBI Evid Synth 18(10):2119–26. https://doi.org/10.11124/jbies-20-00167. Tricco AC, Lillie E, Zarin W et al (2016) A scoping review on the conduct and reporting of scoping reviews. BMC Med Res Methodol 16:15. https://doi.org/10.1186/s12874-016-0116-4. (PMID: 10.1186/s12874-016-0116-4268571124746911) Munn Z, Peters MDJ, Stern C, Tufanaru C, McArthur A, Aromataris E (2018) Systematic review or scoping review? Guidance for authors when choosing between a systematic or scoping review approach. BMC Med Res Methodol 18(1):143. https://doi.org/10.1186/s12874-018-0611-x. (PMID: 10.1186/s12874-018-0611-x304539026245623) Arksey H, O’Malley L (2005) Scoping studies: towards a methodological framework. Int J Soc Res Methodol 8(1):19–32. https://doi.org/10.1080/1364557032000119616. (PMID: 10.1080/1364557032000119616) Levac D, Colquhoun H, O’Brien KK (2010) Scoping studies: advancing the methodology. Implement Sci 5(1):69. https://doi.org/10.1186/1748-5908-5-69. (PMID: 10.1186/1748-5908-5-69208546772954944) McGaghie WC, Issenberg SB, Barsuk JH, Wayne DB (2014) A critical review of simulation-based mastery learning with translational outcomes. Med Educ 48(4):375–385. https://doi.org/10.1111/medu.12391. (PMID: 10.1111/medu.1239124606621) Agha RA, Fowler AJ (2015) The role and validity of surgical simulation. Int Surg 100(2):350–357. https://doi.org/10.9738/INTSURG-D-14-00004.1. (PMID: 10.9738/INTSURG-D-14-00004.1256924414337453) Milburn JA, Khera G, Hornby ST, Malone PS, Fitzgerald JE (2012) Introduction, availability and role of simulation in surgical education and training: review of current evidence and recommendations from the Association of Surgeons in Training. Int J Surg 10(8):393–398. https://doi.org/10.1016/j.ijsu.2012.05.005. (PMID: 10.1016/j.ijsu.2012.05.00522609475) Hasan O, Ayaz A, Jessar M, Docherty C, Hashmi P (2019) The need for simulation in surgical education in developing countries. The wind of change. Review article. J Pak Med Assoc 69(1):S62–S68. Alvarez-Peña C, Rocca Fernández U, Rosell P, Ramos A (2000) Neuroendoscopía cerebral: experiencia previa en modelos experimentales y aplicación clínica. An Fac Med (Perú) 61(2):89–98. (PMID: 10.15381/anales.v61i2.4319) Coelho G, Chaves TMF, Goes AF, Del Massa EC, Moraes O, Yoshida M (2018) Multimaterial 3D printing preoperative planning for frontoethmoidal meningoencephalocele surgery. Childs Nerv Syst 34(4):749–756. https://doi.org/10.1007/s00381-017-3616-6. (PMID: 10.1007/s00381-017-3616-629067504) Coelho G, Kondageski C, Vaz-Guimarães Filho F et al (2011) Frameless image-guided neuroendoscopy training in real simulators. Minim Invasive Neurosurg 54(3):115–118. https://doi.org/10.1055/s-0031-1283170. Coelho G, Rabelo NN, Adani LB et al (2020) The craniosynostosis puzzle: new simulation model for neurosurgical training. World Neurosurg 138:e299–e304. https://doi.org/10.1016/j.wneu.2020.02.098. (PMID: 10.1016/j.wneu.2020.02.09832109642) Coelho G, Zymberg S, Lyra M, Zanon N, Warf B (2015) New anatomical simulator for pediatric neuroendoscopic practice. Childs Nerv Syst 31(2):213–219. https://doi.org/10.1007/s00381-014-2538-9. (PMID: 10.1007/s00381-014-2538-925183391) Coelho G, Figueiredo EG, Rabelo NN, Teixeira MJ, Zanon N (2019) Development and evaluation of a new pediatric mixed-reality model for neurosurgical training. J Neurosurg Pediatr 2:1–10. https://doi.org/10.3171/2019.2.PEDS18597. (PMID: 10.3171/2019.2.PEDS18597) Coelho G, Rabelo NN, Varjão E et al (2021) A hybrid simulation model for pre-operative planning of transsphenoidal encephalocele. Neurosurg Rev 44(3):1767–1774. https://doi.org/10.1007/s10143-020-01361-9. (PMID: 10.1007/s10143-020-01361-932772297) Coelho G, Rabelo NN, Vieira E et al (2020) Augmented reality and physical hybrid model simulation for preoperative planning of metopic craniosynostosis surgery. Neurosurg Focus 48(3):E19. https://doi.org/10.3171/2019.12.FOCUS19854. Coelho G, Vieira EV, Rabelo NN et al (2021) Preoperative planning modalities for meningoencephalocele: new proof of concept. World Neurosurg 151:124–131. https://doi.org/10.1016/j.wneu.2021.04.132. (PMID: 10.1016/j.wneu.2021.04.13233964493) Coelho G, Defino HLA (2018) The role of mixed reality simulation for surgical training in spine: phase 1 validation. Spine (Phila Pa 1976). 43(22):1609–1616. https://doi.org/10.1097/BRS.0000000000002856. Villegas R, Jara I, Montilla G, Villegas H (2006) Software para planificación de neurocirugías y su aplicación en una cirugía estereotáxica de aracnoidocele. Acta cient venez 57(3):107–115. Abdala N, Oliveira R, Alves Junior J, Spinola T (2007) Modelo simulador para treinamento de punção transpedicular em vertebroplastia percutânea. Radiol bras 40(4):231–234. https://doi.org/10.1590/S0100-39842007000400005. (PMID: 10.1590/S0100-39842007000400005) Paiva WS, Amorim R, Bezerra DA, Masini M (2007) Aplication of the stereolithography technique in complex spine surgery. Arq Neuropsiquiatr 65(2B):443–445. https://doi.org/10.1590/s0004-282x2007000300015. (PMID: 10.1590/s0004-282x200700030001517665012) Filho FV, Coelho G, Cavalheiro S, Lyra M, Zymberg ST (2011) Quality assessment of a new surgical simulator for neuroendoscopic training. Neurosurg Focus 30(4):E17. https://doi.org/10.3171/2011.2.FOCUS10321. (PMID: 10.3171/2011.2.FOCUS1032121456928) Leal AG, Pagnan LB, Kondo RT, Foggiatto JA, Agnoletto GJ, Ramina R (2016) Elastomers three-dimensional biomodels proven to be a trustworthy representation of the angiotomographic images. Arq europsiquiatr 74(9):713–717. https://doi.org/10.1590/0004-282X20160113. (PMID: 10.1590/0004-282X20160113) Ghizoni E, de Souza JP, Raposo-Amaral CE (2018) 3D-printed craniosynostosis model: new simulation surgical tool. World Neurosurg 109:356–361. https://doi.org/10.1016/j.wneu.2017.10.025. (PMID: 10.1016/j.wneu.2017.10.02529061457) Kulcheski ÁL, Stieven-Filho E, Nunes CP, Milcent PAA, Dau L, I-Graells XS (2015) Validation of an endoscopic flavectomy training model. Rev Col Bras Cir. 48:e202027910. https://doi.org/10.1590/0100-6991e-20202901. Espinoza DL, González Carranza V, Chico-Ponce de León F, Martinez AM (2015) PsT1: a low-cost optical simulator for psychomotor skills training in neuroendoscopy. World Neurosurg 83(6):1074–1079. https://doi.org/10.1016/j.wneu.2014.12.022. (PMID: 10.1016/j.wneu.2014.12.02225527875) Yasuda E, Minghinelli F, Renedo D, Devoto P, Pina L, Lovaglio A (2019) ¿Cómo entrenar para el uso del exoscopio? Utilización de un novedoso simulador de exoscopía de bajo costo por residentes de neurocirugía. Rev Argent Neurocir 33(4):261–265. https://doi.org/10.59156/revista.v33i4.15. Liñares JM, Argañaraz R, Sáenz A, Martinez P, Bailez M, Mantese B (2019) Modelo de neuroendoscopia ventricular “INARUS.” Rev Argent Neurocir 33(3):166–171. Cuello JF, Gromadzyn G, Martinez P, Mantese B (2022) A low-cost simulation model for endoscopic-assisted sagittal craniosynostosis repair. World Neurosurg Aug 164:381–387. https://doi.org/10.1016/j.wneu.2022.06.025. (PMID: 10.1016/j.wneu.2022.06.025) Cuello JF, Saenz A, Liñares JM et al (2020) Low-cost stereotactic brain biopsy simulation model. World Neurosurg 138:285–290. https://doi.org/10.1016/j.wneu.2020.03.062. (PMID: 10.1016/j.wneu.2020.03.06232200018) Figueiredo Souza JR, Barros Filho EM, JucÁ CEB, Rolim JPML (2020) Endovascular technique simulator for neuroradiology learning. Arq Neuropsiquiatr 78(9):535–540. https://doi.org/10.1590/0004-282X20200028. (PMID: 10.1590/0004-282X20200028) Grillo FW, Souza VH, Matsuda RH et al (2018) Patient-specific neurosurgical phantom: assessment of visual quality, accuracy, and scaling effects. 3D Print Med. 4(1):3. https://doi.org/10.1186/s41205-018-0025-8. Mery F, Méndez-Orellana C, Torres J et al (2021) 3D simulation of aneurysm clipping: data analysis. Data Brief 3(37):107258. https://doi.org/10.1016/j.dib.2021.107258. (PMID: 10.1016/j.dib.2021.107258) Lombardo E, Velez M, Verger S (2022) Resección de osteoma osteoide vertebral asistida por planificación 3D. Presentación de un caso. Rev Asoc Argent Ortop Traumatol 87(3):378–386. https://doi.org/10.15417/issn.1852-7434.2022.87.3.1206. Nanni F, Vialle E, Foggiattob JA, Silva KW, Mello Neto H (2019) Development of a patient-specific guide for high cervical spine fixation. Rev bras ortop 54(1):20–25. https://doi.org/10.1016/j.rbo.2017.09.011. (PMID: 10.1016/j.rbo.2017.09.011) Santorcuato F (2008) Simulador humano-artificial para entrenamiento y estudio de técnicas neuroendoscópicas intraventriculares. Rev Chil Neurocir 30:32–35. Di Pietrantonio A, Pipolo D, Nicolau S et al (2019) Fresado de hueso temporal: modelo de bajo costo y aplicación sencilla. Rev Argent Neurocir 33(2):82–90. Nicolato AA (2020) Modelo híbrido utilizando placentas humanas para treinamento de Embolectomia Arterial Cerebral [PhD thesis] Universidade Federal de Minas Gerais. https://repositorio.ufmg.br/handle/1843/38136. Almeida DB, Hunhevicz S, Bordignon K et al (2006) A model for foramen ovale puncture training: technical note. Acta Neurochir (Wien) 148(8):881–883. https://doi.org/10.1007/s00701-006-0817-2. (PMID: 10.1007/s00701-006-0817-216791431) Baranauskas MB, Margarido CB, Panossian C, Silva ED, Campanella MA, Kimachi PP (2008) Simulation of ultrasound-guided peripheral nerve block: learning curve of CET-SMA/HSL Anesthesiology residents. Rev Bras Anestesiol 58(2):106–11. https://doi.org/10.1590/s0034-70942008000200003. Lorias-Espinoza D, Carranza VG, de León FC, Escamirosa FP, Martinez AM (2016) A low-cost, passive navigation training system for image-guided spinal intervention. World Neurosurg 95:322–328. https://doi.org/10.1016/j.wneu.2016.08.006. (PMID: 10.1016/j.wneu.2016.08.00627535635) Teodoro-Vite S, Pérez-Lomelí JS, Domínguez-Velasco CF, Hernández-Valencia AF, Capurso-García MA, Padilla-Castañeda MA (2021) A high-fidelity hybrid virtual reality simulator of aneurysm clipping repair with brain Sylvian fissure exploration for vascular neurosurgery training. Simul Healthc 16(4):285–294. https://doi.org/10.1097/SIH.0000000000000489. (PMID: 10.1097/SIH.000000000000048932701862) Ferrarez CE, Bertani R, Leite Batista DM et al (2020) Superficial temporal artery-middle cerebral artery bypass ex vivo hybrid simulator: face, content, construct, and concurrent validity. World Neurosurg 142:e378–e384. https://doi.org/10.1016/j.wneu.2020.07.027. (PMID: 10.1016/j.wneu.2020.07.02732673808) Gallardo FC, Martin C, Targa Garcia AA, Bustamante JL, Nuñez M, Feldman SE (2020) Home program for acquisition and maintenance of microsurgical skills during the coronavirus disease 2019 outbreak. World Neurosurg 143:557-563.e1. https://doi.org/10.1016/j.wneu.2020.07.114. (PMID: 10.1016/j.wneu.2020.07.114327111507375971) Petrone S, Cofano F, Nicolosi F et al (2022) Virtual-augmented reality and life-like neurosurgical simulator for training: first evaluation of a hands-on experience for residents. Front Surg 19(9):862948. https://doi.org/10.3389/fsurg.2022.862948. (PMID: 10.3389/fsurg.2022.862948) Davids J, Manivannan S, Darzi A, Giannarou S, Ashrafian H, Marcus HJ (2021) Simulation for skills training in neurosurgery: a systematic review, meta-analysis, and analysis of progressive scholarly acceptance. Neurosurg Rev 44(4):1853–1867. https://doi.org/10.1007/s10143-020-01378-0. (PMID: 10.1007/s10143-020-01378-032944808) Oliveira LM, Figueiredo EG (2019) Simulation training methods in neurological surgery. Asian J Neurosurg 14(2):364–370. https://doi.org/10.4103/ajns.AJNS_269_18. (PMID: 10.4103/ajns.AJNS_269_18311432486516032) Pedreira DAL, Oliveira R, Valente PR, Abou-Jamra RC, Araújo A, Saldiva PH (2007) Validation of the ovine fetus as an experimental model for the human myelomeningocele defect. Acta Cir Bras 22(3):168–173. https://doi.org/10.1590/s0102-86502007000300003. (PMID: 10.1590/s0102-8650200700030000317546288) Gonzalez F, Pintos A, Vargas L, Torres R (2002) Cirugia toracoscopica de la columna dorsal: experiencia en animales. Rev Asoc Argent Ortop Traumatol 67(3):195–198. Gotfryd AO, Paula FC, Sauma ML et al (2022) Minimally invasive swine spine surgery training: technical aspects, benefits, and anatomical limitations. Einstein (Sao Paulo). 16;20:eAO6318. https://doi.org/10.31744/einstein_journal/2022AO6318. Jaimovich SG, Bailez M, Asprea M, Jaimovich R (2016) Neurosurgical training with simulators: a novel neuroendoscopy model. Childs Nerv Syst 32(2):345–349. https://doi.org/10.1007/s00381-015-2936-7. (PMID: 10.1007/s00381-015-2936-726493056) Simkin DJ, Greene JA, Jung J, Sacks BC, Fessler HE (2017) The death of animals in medical school. N Engl J Med 376(8):713–715. https://doi.org/10.1056/NEJMp1612992. González Romo N, Zunino FR (2021) Minimally invasive mini-orbitozygomatic approach for clipping an anterior communicating artery aneurysm: virtual reality surgical planning. Arq Bras Neurocir 40(3):288–293. https://doi.org/10.1055/s-0040-1719004. (PMID: 10.1055/s-0040-1719004) Heredia-Pérez SA, Harada K, Padilla-Castañeda MA, Marques-Marinho M, Márquez-Flores JA, Mitsuishi M (2019) Virtual reality simulation of robotic transsphenoidal brain tumor resection: Evaluating dynamic motion scaling in a master-slave system. Int J Med Robot 15(1):e1953. https://doi.org/10.1002/rcs.1953. (PMID: 10.1002/rcs.195330117272) Chawla S, Devi S, Calvachi P, Gormley WB, Rueda-Esteban R (2022) Evaluation of simulation models in neurosurgical training according to face, content, and construct validity: a systematic review. Acta Neurochir (Wien) 164(4):947–966. https://doi.org/10.1007/s00701-021-05003-x. (PMID: 10.1007/s00701-021-05003-x35122126) Oliveira MM, Araujo AB, Nicolato A et al (2016) Face, content, and construct validity of brain tumor microsurgery simulation using a human placenta model. Oper Neurosurg (Hagerstown) 12(1):61–67. https://doi.org/10.1227/NEU.0000000000001030. (PMID: 10.1227/NEU.000000000000103029506248) Ribeiro de Oliveira MM, Nicolato A, Santos M et al (2016) Face, content, and construct validity of human placenta as a haptic training tool in neurointerventional surgery. J Neurosurg 124(5):1238–1244. https://doi.org/10.3171/2015.1.JNS141583. (PMID: 10.3171/2015.1.JNS14158326452122) Oliveira MM, Wendling L, Malheiros JA et al (2018) Human placenta simulator for intracranial-intracranial bypass: vascular anatomy and 5 bypass techniques. World Neurosurg 119:e694–e702. https://doi.org/10.1016/j.wneu.2018.07.246. (PMID: 10.1016/j.wneu.2018.07.24630098435) de Oliveira MMR, Nicolato A, Malheiros JA et al (2021) Stroke microsurgical thrombectomy human placenta simulator. World Neurosurg 148:e115–e120. https://doi.org/10.1016/j.wneu.2018.07.246. (PMID: 10.1016/j.wneu.2018.07.24633444832) Argañaraz R, Sáenz A, Liñares JM, Martinez P, Bailez M, Mantese B (2020) New simulator for neuroendoscopy: a realistic and attainable model. World Neurosurg 134:33–38. https://doi.org/10.1016/j.wneu.2019.10.092. (PMID: 10.1016/j.wneu.2019.10.09231655233) Cobo EJ, Pereira Borge FR, Pereira Riverón R (2005) Modelo simulador para entrenamiento en neuroendoscopia y neuroanatomía. Rev Cuba Cir 44(1). chrome-extension: https://www.redalyc.org/pdf/2812/281222989009.pdf. Romero AD, Zicarelli CA, Pinto FC, Pasqualucci CA, Aguiar PH (2009) Simulation of endoscopic third ventriculostomy in fresh cadaveric specimens. Minim Invasive Neurosurg Jun 52(3):103–106. https://doi.org/10.1055/s-0029-1231080. Mattei TA, Meneses MS, Milano JB, Ramina R, Borges CR (2010) Implementando o treinamento da técnica “free-hand” para instrumentação com parafusos pediculares na residência de neurocirurgia. J Bras Neurocir 21(2):80–87. Ferreira CD, Matushita H, Silva BR et al (2014) Proposal of a new method to induce ventricular system dilation to simulate the features of hydrocephalus and provide an anatomical model for neuroendoscopy training. Childs Nerv Syst 30(7):1209–1215. https://doi.org/10.1007/s00381-013-2346-7. (PMID: 10.1007/s00381-013-2346-724389583) Alvarado MT, Peña G, Aristizabal G (2015) Modelo animal experimental para adiestramiento en realización anastomosis extra intraracraneales e intracraneales, con técnicas microquirúrgicas. Rev chil neurocir 41(1):76–82. Massa D, Rasmussen J, Kornfeld S, Plou P, Padilla F, Villaescusa M (2020) Programa de Simulación Neuroquirúrgica. Rev Argent Neurocir 34(1):45–54. https://doi.org/10.59156/revista.v34i01.23. Gallardo FC, Bustamante JL, Martin C (2020) Novel simulation model with pulsatile flow system for microvascular training, research, and improving patient surgical outcomes. World Neurosurg 143:11–16. https://doi.org/10.1016/j.wneu.2020.07.116. (PMID: 10.1016/j.wneu.2020.07.11632712401) de Oliveira MMR, Ferrarez CE, Ramos TM et al (2018) Learning brain aneurysm microsurgical skills in a human placenta model: predictive validity. J Neurosurg 128(3):846–852. https://doi.org/10.3171/2016.10.JNS162083. (PMID: 10.3171/2016.10.JNS16208328338438) McGuire LS, Fuentes A, Alaraj A (2021) Three-dimensional modeling in training, simulation, and surgical planning in open vascular and endovascular neurosurgery: a systematic review of the literature. World Neurosurg 154:53–63. https://doi.org/10.1016/j.wneu.2021.07.057. (PMID: 10.1016/j.wneu.2021.07.05734293525) Carlos GF, Enrrique FS, Aylen Andrea TG et al (2022) Introducing a realistic, low-cost simulation model for clipping of brain aneurysms. World Neurosurg 158:305-311.e1. https://doi.org/10.1016/j.wneu.2021.11.012. (PMID: 10.1016/j.wneu.2021.11.01234774805) Drummond-Braga B, Peleja SB, Macedo G et al (2016) Coconut model for learning first steps of craniotomy techniques and cerebrospinal fluid leak avoidance. World Neurosurg 96:191–194. https://doi.org/10.1016/j.wneu.2016.08.118. Aurich LA, Silva Junior LF, Monteiro FM, Ottoni AN, Jung GS, Ramina R (2014) Microsurgical training model with nonliving swine head. Alternative for neurosurgical education. Acta Cir Bras 29(6):405–409. https://doi.org/10.1590/s0102-86502014000600010. |
فهرسة مساهمة: | Keywords: High fidelity simulation training; Neurosurgery; Neurosurgical procedure; Simulation training |
تواريخ الأحداث: | Date Created: 20231230 Date Completed: 20240103 Latest Revision: 20240103 |
رمز التحديث: | 20240103 |
DOI: | 10.1007/s10143-023-02263-2 |
PMID: | 38159156 |
قاعدة البيانات: | MEDLINE |
تدمد: | 1437-2320 |
---|---|
DOI: | 10.1007/s10143-023-02263-2 |