Evidence map›Paper›PMID 40735348›Full record

ReviewEClinicalMedicine2025

Towards universal early screening for cerebral palsy: a roadmap for automated General Movements Assessment.

Alicia J Spittle, Peter B Marschik, Lars Adde, Nadia Badawi, Rachel Byrne, Arend F Bos, Alain Chatelin, John Coughlan, Francesca Fedeli, Andrea Guzzetta and 14 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in EClinicalMedicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Observational
  4. The future of follow-up: technology-enabled medical and developmental follow-up care for NICU graduates.Journal of perinatology : official journal of the California Perinatal Association · 2026
    Review
  5. Review
  6. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

24 authors.

Alicia J SpittleDepartment of Physiotherapy, Melbourne School of Health Science, University of Melbourne, Melbourne, Australia.
Peter B MarschikDepartment of Child and Adolescent Psychiatry, University Hospital Heidelberg, German Center for Mental Health (DZPG), Heidelberg University, Heidelberg, Germany.
Lars AddeDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, Trondheim, Norway.
Nadia BadawiCerebral Palsy Alliance Research Institute, Brain Mind Centre, Discipline of Child and Adolescent Health, The University of Sydney, Sydney, NSW, Australia.
Rachel ByrneCerebral Palsy Foundation, New York, NY, USA.
Arend F BosDivision of Neonatology, Beatrix Children's Hospital, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
Alain ChatelinFondation Paralysie Cerebrale, Paris, France.
John CoughlanInternational Cerebral Palsy Society, Bath, United Kingdom.
Francesca FedeliFight the Stroke Foundation, Milano, Italy.
Andrea GuzzettaDepartment of Clinical and Experimental Medicine University of Pisa, Italy.
Edmond S L HoSchool of Computing Science, University of Glasgow, Scotland, United Kingdom.
Michelle J JohnsonDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Amanda KwongDepartment of Physiotherapy, Melbourne School of Health Science, University of Melbourne, Melbourne, Australia.
Alistair McEwanCerebral Palsy Alliance Research Institute, Brain Mind Centre, Discipline of Child and Adolescent Health, The University of Sydney, Sydney, NSW, Australia.
Catherine MorganCerebral Palsy Alliance Research Institute, Brain Mind Centre, Discipline of Child and Adolescent Health, The University of Sydney, Sydney, NSW, Australia.
Anderson MughoghoDepartment of Rehabilitation Sciences, Kamuzu University of Health Sciences, Blantyre, Malawi.
Deirdre M MurrayDept of Paediatrics and Child Health, University College Cork, Cork, Ireland.
Silvia OrlandiDepartment of Electrical, Electronic, and Information Engineering "Guglielmo Marconi" - DEI, University of Bologna, Bologna, Italy.
Colleen PeytonDepartment of Physical Therapy and Human Movement Sciences, Feinberg School of Medicine, Northwestern University, Chicago, USA.
Laura A ProsserDepartment of Physical Medicine and Rehabilitation, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Anina Ritterband-RosenbaumElsass Foundation, Gentofte, Denmark.
Truyen TranApplied Artificial Intelligence Institute, Deakin University, Waurn Ponds, Australia.
Dajie ZhangDepartment of Child and Adolescent Psychiatry, University Hospital Heidelberg, German Center for Mental Health (DZPG), Heidelberg University, Heidelberg, Germany.
Elyse PassmoreDevelopmental Imaging Group, Murdoch Children's Research Institute, Melbourne, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cerebral palsy (CP) is the most common lifelong physical disability, affecting millions globally. Early detection and intervention are crucial for improving outcomes, yet many children are diagnosed late. The General Movements Assessment (GMA) is a highly accurate clinical tool for detecting infants at high probability of CP, but access to health professionals trained in the GMA limits its use. Artificial intelligence (AI) has the potential to automate the GMA, increasing accessibility worldwide. We established an interdisciplinary, international consortium for the purpose of developing a roadmap for the ongoing development and implementation of an AI-enabled GMA system for universal CP screening worldwide. The consortium included clinicians (children neurologists, paediatricians, neonatologists, allied health), researchers, engineers, computer scientists, legal experts, and individuals with lived experience, from around the globe (across Africa, Australia, Europe, and North America). The roadmap identifies the following steps and key requirements within: (1) development of standards for AI validation; (2) development of AI-GMA from large and diverse validation sets; (3) development of software tools and clinical pathways; (4) regulatory requisites; and (5) implementation. With the roadmap, AI-enabled screening for CP incorporating state-of-the-art technology can be made possible. Future work will require international collaboration to allow for scaling of data sets, refining automated solutions and translation into practice. Funding: Cerebral Palsy Foundation, Cerebral Palsy Alliance, European Union Born to Get There, the National Health and Medical Research Council.

Indexed as

Artificial intelligenceCerebral palsyEarly detectionGeneral movementsMachine learning

Identifiers

PMID40735348
PMCPMC12304702

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.