Han Yan1,2,3, Lauren Siegel4, Sara Breitbart2, Carolina Gorodetsky5, Hernan D Gonorazky5, Ivanna Yau5, Cristina Go5, Elizabeth Donner5, Suneil K Kalia1,6,7,8,9, Alfonso Fasano8,10,9, Alexander G Weil11,12, Aria Fallah13, George M Ibrahim14,15,16,17. 1. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada. 2. Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario, Canada. 3. Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, Ontario, Canada. 4. Neurosciences and Mental Health Program, The Hospital for Sick Children, Toronto, Ontario, Canada. 5. Division of Neurology, The Hospital for Sick Children, Toronto, Ontario, Canada. 6. University Health Network, Toronto, Ontario, Canada. 7. Division of Neurosurgery, Toronto Western Hospital, Toronto, Canada. 8. Krembil Brain Institute, Toronto, Ontario, Canada. 9. CenteR for Advancing Neurotechnological Innovation to Application (CRANIA), Toronto, Ontario, Canada. 10. Edmond J. Safra Program in Parkinson's Disease, Morton and Gloria Shulman Movement Disorders Clinic, Toronto Western Hospital, University Health Network, Division of Neurology, University of Toronto, Toronto, Ontario, Canada. 11. Faculty of Medicine, Université de Montréal, Montreal, Quebec, Canada. 12. Division of Neurosurgery and Pediatrics, Sainte Justine Hospital, Montreal, Quebec, Canada. 13. Department of Neurosurgery, UCLA Mattel Children's Hospital, David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. 14. Division of Neurosurgery, Department of Surgery, University of Toronto, Toronto, Canada. george.ibrahim@sickkids.ca. 15. Division of Neurosurgery, The Hospital for Sick Children, Toronto, Ontario, Canada. george.ibrahim@sickkids.ca. 16. Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada. george.ibrahim@sickkids.ca. 17. Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada. george.ibrahim@sickkids.ca.
Abstract
PURPOSE: Deep brain stimulation (DBS) is a common tool for the treatment of movement disorders in adults; however, it remains an emerging treatment modality in children with a growing number of indications, including epilepsy and dystonia. The Child & Youth CompreHensIve Longitudinal Database of DBS (CHILD-DBS) study aims to prospectively collect relevant data on quality of life (QoL), safety, efficacy, and long-term neurodevelopmental outcomes following DBS in children. METHODS: Data are collected and managed using the Research Electronic Data Capture (REDCap). This database aims to collect multicentre comprehensive and longitudinal clinical, QoL, imaging and electrophysiologic data for children under the age of 19 undergoing DBS. RESULTS: Both general and indication-specific measures are collected at baseline and at four time points postoperatively: 6 months, 1 year, 2 years, and 3 years. The database encompasses QoL metrics for children, including the PedsQL (Pediatric Quality of Life Inventory, generic), QOLCE (Quality of Life in Childhood Epilepsy Questionnaire, parent-rated), CHU 9D (Child Health Utility 9D), and KIDSCREEN. Caregiver clinical and QoL metrics, including QIDS (Quick Inventory of Depressive Symptomatology), GAD-7 (Generalized Anxiety Disorder 7-item scale), and CarerQoL-7D (The Care-related Quality of Life Instrument), are similarly prospectively collected. Healthcare resource utilization is also assessed before and after DBS. Lastly, stimulation parameters and radiographic and electrophysiologic data are collected within the database. CONCLUSIONS: The development of the current prospective paediatric DBS database with carefully selected physical and psychosocial outcomes and assessments will complement existing efforts to enhance and facilitate multisite collaboration to further understand the role of DBS in childhood.
PURPOSE: Deep brain stimulation (DBS) is a common tool for the treatment of movement disorders in adults; however, it remains an emerging treatment modality in children with a growing number of indications, including epilepsy and dystonia. The Child & Youth CompreHensIve Longitudinal Database of DBS (CHILD-DBS) study aims to prospectively collect relevant data on quality of life (QoL), safety, efficacy, and long-term neurodevelopmental outcomes following DBS in children. METHODS: Data are collected and managed using the Research Electronic Data Capture (REDCap). This database aims to collect multicentre comprehensive and longitudinal clinical, QoL, imaging and electrophysiologic data for children under the age of 19 undergoing DBS. RESULTS: Both general and indication-specific measures are collected at baseline and at four time points postoperatively: 6 months, 1 year, 2 years, and 3 years. The database encompasses QoL metrics for children, including the PedsQL (Pediatric Quality of Life Inventory, generic), QOLCE (Quality of Life in Childhood Epilepsy Questionnaire, parent-rated), CHU 9D (Child Health Utility 9D), and KIDSCREEN. Caregiver clinical and QoL metrics, including QIDS (Quick Inventory of Depressive Symptomatology), GAD-7 (Generalized Anxiety Disorder 7-item scale), and CarerQoL-7D (The Care-related Quality of Life Instrument), are similarly prospectively collected. Healthcare resource utilization is also assessed before and after DBS. Lastly, stimulation parameters and radiographic and electrophysiologic data are collected within the database. CONCLUSIONS: The development of the current prospective paediatric DBS database with carefully selected physical and psychosocial outcomes and assessments will complement existing efforts to enhance and facilitate multisite collaboration to further understand the role of DBS in childhood.
Entities:
Keywords:
Deep brain stimulation; Health resource utilization; Neuroimaging; Paediatric; Quality of life; Registry
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