| Autor: |
Alicia J Spittle, Robert S Ware, Catherine Morgan, Susan Woolfenden, Natasha Amery, Jason Tan, Nadia Badawi, Roslyn N Boyd, Anne McKenzie, Catherine Elliott, Elizabeth Geelhoed, Samudragupta Bora, Mary Sharp, Amy Finlay-Jones, Caroline Alexander, Alison Salt, Desiree Silva, Alishum Ali, David Bloom, Roslyn Ward, Susan Prescott, Vuong Le, Sue-Anne Davidson, Ashleigh Thornton, Lynn Jensen, Jane Valentine, Arlette Coenen, Rose Morie, Jennifer Moore, Madeleine OConnor, Ravisha Srinivasjois, Brad Jongeling, Elayne Downie, Ruth Last, John Wray |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
BMJ Open, Vol 11, Iss 4 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2044-6055 |
| DOI: |
10.1136/bmjopen-2020-041695 |
| Popis: |
Introduction The current diagnostic pathways for cognitive impairment rarely identify babies at risk before 2 years of age. Very early detection and timely targeted intervention has potential to improve outcomes for these children and support them to reach their full life potential. Early Moves aims to identify early biomarkers, including general movements (GMs), for babies at risk of cognitive impairment, allowing early intervention within critical developmental windows to enable these children to have the best possible start to life.Method and analysis Early Moves is a double-masked prospective cohort study that will recruit 3000 term and preterm babies from a secondary care setting. Early Moves will determine the diagnostic value of abnormal GMs (at writhing and fidgety age) for mild, moderate and severe cognitive delay at 2 years measured by the Bayley-4. Parents will use the Baby Moves smartphone application to video their babies’ GMs. Trained GMs assessors will be masked to any risk factors and assessors of the primary outcome will be masked to the GMs result. Automated scoring of GMs will be developed through applying machine-based learning to the data and the predictive value for an abnormal GM will be investigated. Screening algorithms for identification of children at risk of cognitive impairment, using the GM assessment (GMA), and routinely collected social and environmental profile data will be developed to allow more accurate prediction of cognitive outcome at 2 years. A cost evaluation for GMA implementation in preparation for national implementation will be undertaken including exploring the relationship between cognitive status and healthcare utilisation, medical costs, health-related quality of life and caregiver burden.Ethics and dissemination Ethics approval has been granted by the Medical Research Ethics Committee of Joondalup Health Services and the Health Service Human Research Ethics Committee (1902) of Curtin University (HRE2019-0739).Trial registration number ACTRN12619001422112. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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