RESOLVING RESIDUAL ACETABULAR DYSPLASIA FOLLOWING SUCCESSFUL BRACE TREATMENT FOR DEVELOPMENTAL DYSPLASIA OF THE HIP IN INFANTS
Bibliographic record
Abstract
Successful bracing for DDH in infancy is characterized by normal clinical examination and hip ultrasound at the end of treatment. However, radiographic residual acetabular dysplasia (RAD) has been reported in up to 30% of children who had DDH treated in infancy. It is important to predict those that will resolve and those that may need corrective surgery to optimize efficient follow-up protocols. We therefore aimed to identify the prevalence and predictors of RAD at two-years and five-years post bracing and identify factors that predicted spontaneous resolution. This was a single centre, prospective longitudinal cohort study of infants with DDH managed using a published, standardized Pavlik harness protocol between 2012-2016. RAD was measured at two-years mean follow-up using acetabular index-lateral edge (AI-L) and acetabular index-sourcil (AI-S). At five-years, RAD was measured using AI-L, AI-S, centre-edge angle (CEA) and acetabular depth ratio (ADR). At both timepoints, each hip was classified based on published normative values for normal, borderline (1-2 SD), or dysplastic (>2 SD) based on sex, age, and laterality. Of 202 infants that completed the protocol, 181 (90%) had two- and five-years follow-up radiographs. At two-years, in 304 initially pathologic hips, the prevalence of RAD (dysplastic) was 10% and RAD (borderline) was 30%. At five-years, RAD (dysplastic) decreased to 1-3% and RAD (borderline) decreased to < 1 -2%. On logistic regression, no variables were predictive of RAD at two-years. Only AI-L at two-years was predictive of RAD at five-years (p < 0 .001). If both hips were normal at two-years follow-up (n=96), all remained normal at five-years. In those with bilateral borderline hips at two-years (n=21), only two were borderline at five-years, none were dysplastic. In those with either borderline-dysplastic or bilateral dysplasia at two-years (n=26), three (12%) were dysplastic at five-years. The vast majority of RAD at two-years post brace treatment spontaneously resolved by five-years follow-up without surgical intervention. Children with normal radiographs at two-years post brace treatment can be discharged from care. Targeted follow-up for those with abnormal AI-L at two-years will identify those few that may benefit from surgical correction at five-years follow-up. Our evidence-based pragmatic approach to DDH follow-up will inform efficient follow-up protocols and reduce unnecessary exposure to radiography.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".