Nonsurgical Treatment of Deformational Plagiocephaly
Bibliographic record
Abstract
OBJECTIVE: To evaluate and summarize the evidence comparing nonsurgical therapies in the treatment of infants with deformational plagiocephaly. DATA SOURCES: Scientific articles and abstracts published in English between January 1978 and August 2007 were searched from 5 online literature databases, along with a manual search of conference proceedings. STUDY SELECTION: Studies were selected and appraised for methodological quality by 2 reviewers independently using a Critical Appraisal Skills Programme form (cohort criteria). INTERVENTIONS: Molding helmet therapy vs head repositioning therapy. MAIN OUTCOME MEASURE: Success rate of the treatment. RESULTS: A total of 3793 references were retrieved. There were no randomized controlled trials. Only 7 cohort studies met the inclusion criteria. Five of the 7 studies presented evidence that molding therapy is more effective than repositioning, even with the biases favoring the repositioning groups. In the molding groups, the asymmetry was more severe and the infants were older. The infants who failed to respond to repositioning therapy were also switched to molding therapy. The treatment outcomes from the other 2 studies were difficult to assess because of flaws in their study design. Finally, the relative improvement of using molding therapy was calculated from one study. It was about 1.3 times greater than with repositioning therapy. CONCLUSION: The studies showed considerable evidence that molding therapy may reduce skull asymmetry more effectively than repositioning therapy. However, definitive conclusions on the relative effectiveness of these treatments were tempered by potential biases in these studies. Further research is warranted.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".