The Effect of a Physical Therapy Intervention on Motor Developmental Delay in a 6-Month-Old Infant Following a Full-Term Breech Delivery: A Case Report
Bibliographic record
Abstract
Objective: This case report evaluates the effectiveness of a physical therapy intervention, integrating Neurodevelopmental Treatment (NDT) with a parent-led home program, for a 6-month-old infant presenting with motor delay and postural asymmetry following a full-term breech delivery Method: The infant's motor function was assessed using the Alberta Infant Motor Scale (AIMS) and the Gross Motor Function Measure (GMFM) at pre-intervention, post-intervention (8 weeks), and a 12-week follow-up. The 8-week, NDT-based intervention focused on improving postural control and symmetrical movement, with a parent-led home program integrated through education in each session. Results: At the 12-week follow-up, the infant's AIMS percentile rank improved from <5th to the 25th percentile, entering the typical developmental range. Post-intervention (8 weeks), GMFM scores increased by 39.6 percentage points for the ‘Lying & Rolling’ dimension and 37.5 percentage points for the ‘Sitting’ dimension. Initial hypotonia and postural asymmetry were resolved, resulting in functional gains such as symmetrical, bidirectional rolling. Conclusion: An NDT-based intervention combined with a parent-led home program effectively improved both quantitative and qualitative motor functions for this infant with motor delay post-breech delivery. These findings underscore the importance of early, comprehensive intervention that incorporates parental engagement for infants with perinatal risk factors.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".