Role of child neurologists and neurodevelopmentalists in the diagnosis of cerebral palsy
Bibliographic record
Abstract
OBJECTIVE: To contextualize the role of child neurologists and neurodevelopmentalists (CNs/NDDs) in cerebral palsy (CP) care, we review the changing landscape of CP diagnosis and survey stakeholder CNs/NDDs regarding their roles in CP care. METHODS: The optimal roles of the multiple specialties involved in CP care are currently unclear, particularly regarding CP diagnosis. We developed recommendations regarding the role of CNs/NDDs noting (1) increasing complexity of CP diagnosis given a growing number of genetic etiologies and treatable motor disorders that can be misdiagnosed as CP and (2) the views of a group of physician stakeholders (CNs/NDDs from the Child Neurology Society Cerebral Palsy Special Interest Group). RESULTS: CNs/NDDs felt that they were optimally suited to diagnose CP. Many (76%) felt that CNs/NDDs should always be involved in CP diagnosis. However, 42% said that their patients with CP were typically not diagnosed by CNs/NDDs, and 18% did not receive referrals to establish the diagnosis of CP at all. CNs/NDDs identified areas of their expertise critical for CP diagnosis including knowledge of the neurologic examination across development and early identification of features atypical for CP. This contrasts with their views on CP management, where CNs/NDDs felt that they could contribute to the medical team, but were necessary primarily when neurologic coexisting conditions were present. DISCUSSION: Given its increasing complexity, we recommend early referral for CP diagnosis to a CN/NDD or specialist with comparable expertise. This contrasts with current consensus guidelines, which either do not address or do not recommend specific specialist referral for CP diagnosis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.056 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".