Interventions to improve sensory and motor outcomes for young children with central hypotonia: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To evaluate evidence supporting physical and occupational therapy interventions used to improve sensory and motor outcomes for children 0-6 years with central hypotonia. METHODS: Four electronic databases were searched from 1996 to March 2017. Level of evidence and study conduct was evaluated using American Academy of Cerebral Palsy and Developmental Medicine criteria. Traffic lighting classification identified interventions that were green (proven effective), yellow (possibly effective) or red (proven ineffective or contraindicated). RESULTS: Thirty-seven articles were included. Nine studies measured orthotic interventions while four distinct studies published over nine articles measured treadmill interventions. Remaining studies measured impact of compression garments, massage, motor and sensori-motor interventions, positioning and mobility interventions. CONCLUSIONS: Green light evidence supports treadmill training (to promote ambulation and gait characteristics) and massage (to positively affect muscle tone, motor development and use of vision) for infants with Down syndrome. These interventions are considered Yellow (possibly effective) for other populations. Green light evidence supports impact of orthoses on foot alignment for ambulatory children with hypotonia, while impact on gait characteristics is Yellow light and motor development may be negatively impacted (Red light) in pre-ambulatory children. All other interventions rated Yellow (possibly effective) and therapists should monitor using sensitive outcome measures.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.005 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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".