Tasneem Karim, Anna Te Velde, Annabel Webb, Catherine Morgan, Nadia Badawi, Iona Novak, Saifuddin Ahmed, Shafiul Islam, Iskander Hossain, Nazrul Islam, Mohammad Muhit, Gulam Khandaker
{"title":"孟加拉国高危人群脑瘫的早期发现","authors":"Tasneem Karim, Anna Te Velde, Annabel Webb, Catherine Morgan, Nadia Badawi, Iona Novak, Saifuddin Ahmed, Shafiul Islam, Iskander Hossain, Nazrul Islam, Mohammad Muhit, Gulam Khandaker","doi":"10.1136/bmjpo-2025-003921","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the predictive validity of best practice early detection tools for cerebral palsy (CP) in a high-risk cohort.</p><p><strong>Study design: </strong>Prospective longitudinal cohort study.</p><p><strong>Setting: </strong>Neonatal intensive care unit of a regional tertiary hospital in Bangladesh.</p><p><strong>Participants: </strong>Neonates with risk factors for CP admitted to Mymensingh Medical College Hospital Neonatal Intensive Care Unit between November 2019 and March 2020.</p><p><strong>Outcome measures: </strong>General Movements Assessment (GMA) at writhing and fidgety periods; Hammersmith Infant Neurological Examination (HINE) and Peabody Developmental Motor Scales Second Edition (PDMS-2) conducted in person at 3, 12 and 24 months. The Developmental Assessment of Young Children (DAYC-2), Ages and Stages Questionnaire (ASQ-3) and Developmental Milestones Chart (DMC) were administered remotely at 6, 9, 12, 18 and 24 months. Due to the impact of COVID-19, a proportion of the cohort was not able to have GMA fidgety videos completed and the first HINE assessment was delayed.</p><p><strong>Results: </strong>A total of 227 infants were enrolled. Of the surviving infants assessed at 24 months, 36 (29%) had a confirmed diagnosis of CP. The most accurate combination of tools for early detection was GMA and HINE at 3 months (sensitivity 0.91; specificity 1.00). The PDMS-2 Total Motor Quotient, with an optimised cut-off of 59, showed high accuracy at 24 months (sensitivity 0.94; specificity 0.99). Among the tools administered remotely, the DAYC-2 PD, DMC (Gross and Fine Motor domains) and ASQ-3 (Gross and Fine Motor domains) demonstrated strong predictive validity-both individually and in combination-at 9, 12, 18 and 24 months, supporting their use as practical alternatives when in-person assessments are not feasible.</p><p><strong>Conclusions: </strong>Despite pandemic-related disruptions, an accurate diagnosis was possible as early as 3 months of age using the best practice tools. Our findings support the practicability of scalable early detection models integrating in-person and remote assessments to improve access to timely diagnosis.</p>","PeriodicalId":9069,"journal":{"name":"BMJ Paediatrics Open","volume":"9 1","pages":""},"PeriodicalIF":2.3000,"publicationDate":"2025-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12506230/pdf/","citationCount":"0","resultStr":"{\"title\":\"Early detection of cerebral palsy among a high-risk cohort in Bangladesh.\",\"authors\":\"Tasneem Karim, Anna Te Velde, Annabel Webb, Catherine Morgan, Nadia Badawi, Iona Novak, Saifuddin Ahmed, Shafiul Islam, Iskander Hossain, Nazrul Islam, Mohammad Muhit, Gulam Khandaker\",\"doi\":\"10.1136/bmjpo-2025-003921\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To evaluate the predictive validity of best practice early detection tools for cerebral palsy (CP) in a high-risk cohort.</p><p><strong>Study design: </strong>Prospective longitudinal cohort study.</p><p><strong>Setting: </strong>Neonatal intensive care unit of a regional tertiary hospital in Bangladesh.</p><p><strong>Participants: </strong>Neonates with risk factors for CP admitted to Mymensingh Medical College Hospital Neonatal Intensive Care Unit between November 2019 and March 2020.</p><p><strong>Outcome measures: </strong>General Movements Assessment (GMA) at writhing and fidgety periods; Hammersmith Infant Neurological Examination (HINE) and Peabody Developmental Motor Scales Second Edition (PDMS-2) conducted in person at 3, 12 and 24 months. The Developmental Assessment of Young Children (DAYC-2), Ages and Stages Questionnaire (ASQ-3) and Developmental Milestones Chart (DMC) were administered remotely at 6, 9, 12, 18 and 24 months. Due to the impact of COVID-19, a proportion of the cohort was not able to have GMA fidgety videos completed and the first HINE assessment was delayed.</p><p><strong>Results: </strong>A total of 227 infants were enrolled. Of the surviving infants assessed at 24 months, 36 (29%) had a confirmed diagnosis of CP. The most accurate combination of tools for early detection was GMA and HINE at 3 months (sensitivity 0.91; specificity 1.00). The PDMS-2 Total Motor Quotient, with an optimised cut-off of 59, showed high accuracy at 24 months (sensitivity 0.94; specificity 0.99). Among the tools administered remotely, the DAYC-2 PD, DMC (Gross and Fine Motor domains) and ASQ-3 (Gross and Fine Motor domains) demonstrated strong predictive validity-both individually and in combination-at 9, 12, 18 and 24 months, supporting their use as practical alternatives when in-person assessments are not feasible.</p><p><strong>Conclusions: </strong>Despite pandemic-related disruptions, an accurate diagnosis was possible as early as 3 months of age using the best practice tools. 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Early detection of cerebral palsy among a high-risk cohort in Bangladesh.
Objective: To evaluate the predictive validity of best practice early detection tools for cerebral palsy (CP) in a high-risk cohort.
Study design: Prospective longitudinal cohort study.
Setting: Neonatal intensive care unit of a regional tertiary hospital in Bangladesh.
Participants: Neonates with risk factors for CP admitted to Mymensingh Medical College Hospital Neonatal Intensive Care Unit between November 2019 and March 2020.
Outcome measures: General Movements Assessment (GMA) at writhing and fidgety periods; Hammersmith Infant Neurological Examination (HINE) and Peabody Developmental Motor Scales Second Edition (PDMS-2) conducted in person at 3, 12 and 24 months. The Developmental Assessment of Young Children (DAYC-2), Ages and Stages Questionnaire (ASQ-3) and Developmental Milestones Chart (DMC) were administered remotely at 6, 9, 12, 18 and 24 months. Due to the impact of COVID-19, a proportion of the cohort was not able to have GMA fidgety videos completed and the first HINE assessment was delayed.
Results: A total of 227 infants were enrolled. Of the surviving infants assessed at 24 months, 36 (29%) had a confirmed diagnosis of CP. The most accurate combination of tools for early detection was GMA and HINE at 3 months (sensitivity 0.91; specificity 1.00). The PDMS-2 Total Motor Quotient, with an optimised cut-off of 59, showed high accuracy at 24 months (sensitivity 0.94; specificity 0.99). Among the tools administered remotely, the DAYC-2 PD, DMC (Gross and Fine Motor domains) and ASQ-3 (Gross and Fine Motor domains) demonstrated strong predictive validity-both individually and in combination-at 9, 12, 18 and 24 months, supporting their use as practical alternatives when in-person assessments are not feasible.
Conclusions: Despite pandemic-related disruptions, an accurate diagnosis was possible as early as 3 months of age using the best practice tools. Our findings support the practicability of scalable early detection models integrating in-person and remote assessments to improve access to timely diagnosis.
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