RISK OF PROXIMAL JUNCTIONAL KYPHOSIS AFTER REVISION OF GROWING ROD CONSTRUCTS
Bibliographic record
Abstract
For early onset scoliosis (EOS) patients with growth-friendly implants, posterior distraction is a known contributor to proximal junctional kyphosis (PJK). Rib-based proximal fixation is thought to potentially reduce the risk of PJK. The effect of revising proximal rib-based implants to rib vs spine-based implants on PJK has not yet been investigated. This study compares risk of PJK for patients converted from rib- to spine-based cranial anchors (RTS) to those revised to rib-based anchors (RTR) as well as the effect of revising the upper instrumented vertebra (UIV) to keeping the same level. In this retrospective cohort study of EOS patients with rib-based growing constructs undergoing revision surgery with a minimum two-year follow-up, we assessed pre-revision, post-revision, and two-year follow-up radiographs. We excluded patients lacking lateral X-rays and attachment data and conducted descriptive analyses. Included were 280 subjects (51% female) with an average age of 7.2 years at revision with RTS patients slightly older (8.6y vs 7.2y). At two years, 32% of all patients developed PJK. This risk was higher in RTS patients compared to RTR patients (42.8% vs 30.2%, p=0.09). RTS patients had a greater pre-revision total spine height (p=0.02), greater post-revision sagittal kyphosis (p=0.04), a more negative two-year sagittal balance (p=0.01) and trended to have more males (p=0.08) compared to RTR; all these factors were associated with a greater risk of PJK. There was no difference in risk at two years of developing PJK among patients revised to a higher level compared to those revised to same level (33.3% vs 30.9%, p=0.74). 32% of all subjects developed PJK at two-year follow-up. The risk of PJK in RTS patients was 40% higher than in RTR patients. While this did not reach statistical significance to the 0.05 level, due to the associations of risk established by literature and replicated in this study, we believe these results to be clinically significant. We intend to re-evaluate this population in the future as more data becomes available. With no demonstrated risk in revision levels, it is worth considering revising fewer levels to maintain flexibility in these growing rods.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".