Practical Review of the Cost of Diagnosis and Management of Positional Plagiocephaly
Bibliographic record
Abstract
Positional plagiocephaly has garnered increased research interest since the introduction of the Back to Sleep campaign in the 1990s, and the subsequent increase in infants with cranial deformity. Research has focused on treatment outcomes and developing new modalities to address asymmetric heads. Little attention has been given to the cost of treatment and diagnosis. This study aimed to summarize the literature and provide an overview of the costs associated with a diagnosis of positional plagiocephaly. Methods: A literature review was performed by searching PubMed and Ovid Embase to identify studies pertaining to the "cost" of plagiocephaly diagnosis or treatment through direct financial factors, disturbance to daily routines (ie, through treatment prolongation), or related stress. Results: Twenty-nine peer-reviewed studies were included. Treatment options for plagiocephaly are stratified by severity and age of diagnosis, with different pathways available to treat different stages of asymmetry. The common factor across all treatment modalities is that earlier diagnosis unequivocally leads to better aesthetic outcomes and shorter treatment times. This leads to lower costs for treatment, a lower stress burden for parents, and lower costs for the healthcare system in the future through reduction of long-term effects. Our theoretical cost model suggests that early diagnosis at 4 months can lead to a treatment cost of $1495, when compared with $5195 for detection of deformity at or after 6 months. Conclusion: The dramatic cost disparity between early and late diagnosis highlights the need for reliable methods to accurately detect cranial deformity early in an infant's life.
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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 | 0.006 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.019 | 0.003 |
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".