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Record W4250828527 · doi:10.21203/rs.2.20965/v2

The general movements assessment in term and late-preterm infants diagnosed with neonatal encephalopathy, as a predictive tool of cerebral palsy by two years of age: a scoping review protocol.

2020· review· en· W4250828527 on OpenAlexaff
Judy Seesahai, Maureen Luther, Carmen Cindy Rhoden, Paige Church, Elizabeth Asztalos, Rudaina Banihani

Bibliographic record

VenueResearch Square · 2020
Typereview
Languageen
FieldMedicine
TopicNeonatal and fetal brain pathology
Canadian institutionsHealth Sciences CentreSunnybrook Health Science Centre
Fundersnot available
KeywordsNeonatal encephalopathyCerebral palsyMedicinePediatricsEncephalopathyTerm (time)Protocol (science)Physical medicine and rehabilitationPsychiatryPathology

Abstract

fetched live from OpenAlex

Abstract Background Prediction of long-term neurodevelopmental outcomes remains an elusive goal for neonatology. Clinical and socioeconomic outcome markers have not proven to be adequately reliable1,2. The limitation in prognostication includes those term and late-preterm infants born with neonatal encephalopathy (NE). NE describes those infants born with an atypical neurological exam and is by definition heterogeneous in etiology3. The specific etiology may not be clear for months to years later but the presentation is characterized by central nervous system disruption4 and is associated with an increased risk for long-term neurodevelopmental challenges including cerebral palsy (CP). Infants presenting with NE are managed now with therapeutic hypothermia as the standard of care; this is presumptive management, and is time sensitive should the etiology be hypoxia/ischemia (Hypoxic Ischemic Encephalopathy (HIE)), in term and late-preterm neonates4,5. Therapeutic hypothermia reduces the likelihood of challenging outcomes by containing any potential ongoing neurological injury. It does not, however, completely eradicate the possibility of long-term neurodevelopmental disability6. For parents of infants affected by NE, the desire for accurate prognostication is of tantamount importance7. This information can guide decisions around early intervention and, in severe cases, withdrawal of care for those infants with severe involvement. For those infants that survive NE and are at increased risk for CP, recent international recommendations now call for early detection and intervention of CP in order to improve functional outcomes1,8,9. These recommendations are based on mounting evidence for better detection tools as well as the benefits of early intervention. Historically, clinical and radiological predictors of neurological outcomes were used to classify the degree of NE. Severity scoring systems include the classical grading by Sarnat and Sarnat10 in 1976, to the newer scores by Miller et al.11 in 2004, with added parameters such as oral feeding difficulties and the presence of seizures. Radiologically, specific findings of diffusion restriction on magnetic resonance imaging (MRI) have been linked to later development of CP4. These predictors, however, were not sufficiently accurate1,2 and the high costs of imaging as well as shortages in access further restricts the utility. Neurological examinations have historically been limited in predictive value but recent emerging evidence with an observational tool, the General Movements Assessment (GMA) developed by Dr. Heinz Prechtl has demonstrated strong predictive value12, 13. The GMA is a non-invasive, cost-effective tool with demonstrated reliability for identifying infants at risk for neuromotor impairment14. General movements (GMs) are complex, highly variable, whole-body movements which emerge in the fetus and progress through an age-specific developmental trajectory, dissipating by the end of the first four to five months of life13. Developmental progression and variety, or lack thereof, are indicators of nervous system integrity and can reflect neurodevelopmental outcomes15. Cramped synchronized (CS) and absent fidgety movements are considered abnormal GMAs, demonstrating developmental stereotypy13. Several researchers have looked at the GMA from different aspects. A preliminary search of PROSPERO, MEDLINE, the Cochrane Database of Systematic Reviews and the Joanna Briggs Institute (JBI) Database of Systematic Reviews and Implementation Reports was conducted to assess this research. There were two current systematic reviews on GMA, one in 201816 and the other in 20178. In addition, eight older reviews were identified: seven systematic reviews13,17-22 and one literature review23 done between 2001 to 2013. The search also revealed three pending reviews identified around the topic of the predictive value of GMA24-26. These pending reviews were all systematic reviews. The key characteristics and main findings of the above reviews on GMA are presented in Table 1, Appendix I. In general, the latest systematic review, by Kwong et al. in 201816, compared assessments of GMA and found that the Prechtl method had the best prediction of CP. In the 2017 systematic review by Novak et al.8, their group reviewed the evidence for the best tools for early, accurate diagnosis and intervention in neonates at risk for CP. They considered all gestational ages (GA) and all diagnoses for neonates that were high-risk. They recommended a combined approach for early CP diagnosis including history, neuroimaging, standardized neurological, and standardized motor assessments, to facilitate timely diagnosis and intervention. The other systematic reviews and literature review were all more than five years ago with the latest in 201313. The findings of these older reviews are also summarized in Table 1. Similar to the latest two reviews, the older reviews either looked at preterms or all GA groups and diagnoses. Of the three pending systematic reviews identified in PROSPERO, the oldest review protocol (Kwong et al.)26 was registered in 2016 by similar authors of the 2018 review mentioned above. The next review protocol was registered in February 2018 by Raghuram et al.24, and plans restrictions to preterms with all diagnoses, specifically examining automated movement recognition technology with the GMA. The third review protocol, registered in April 2018, by Angélica Valencia25 is limited to preterm neonates and is evaluating the type of method used for the recognition of the GMA, not the relationship of the GMA to neuromotor outcomes. None of these reviews specifically look at the population we identified for this scoping review, that is, term and late-preterm neonates with NE. Thus, a gap exists in the literature to clearly identify the evidence for this specific population. The objective of this review is therefore, to identify the scope of the research with regards to the GMA and its ability to predict CP, in term and late-preterm newborns with a diagnosis of NE, and to identify the gaps in the literature.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.025
Threshold uncertainty score0.135

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.030
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0120.010
Bibliometrics0.0120.009
Science and technology studies0.0030.002
Scholarly communication0.0040.003
Open science0.0040.004
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0160.002

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.039
GPT teacher head0.441
Teacher spread0.402 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes1
Has abstractyes

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