Predicting development of severe clinically relevant distal junctional kyphosis following adult cervical deformity surgery, with further distinction from mild asymptomatic episodes
Bibliographic record
Abstract
OBJECTIVE: This retrospective cohort study aimed to develop a formal predictive model distinguishing between symptomatic and asymptomatic distal junctional kyphosis (DJK). In this study the authors identified a DJK rate of 32.2%. Predictive models were created that can be used with high reliability to help distinguish between severe symptomatic DJK and mild asymptomatic DJK through the use of surgical factors, radiographic parameters, and patient variables. METHODS: Patients with cervical deformity (CD) were stratified into asymptomatic and symptomatic DJK groups. Symptomatic: 1) DJK angle (DJKA) > 10° and either reoperation due to DJK or > 1 new-onset neurological sequela related to DJK; or 2) either a DJKA > 20° or ∆DJKA > 20°. Asymptomatic: ∆DJK > 10° in the absence of neurological sequelae. Stepwise logistic regressions were used to identify factors associated with these types of DJK. Decision tree analysis established cutoffs. RESULTS: A total of 99 patients with CD were included, with 32.2% developing DJK (34.3% asymptomatic, 65.7% symptomatic). A total of 37.5% of asymptomatic patients received a reoperation versus 62.5% symptomatic patients. Multivariate analysis identified independent baseline factors for developing symptomatic DJK as follows: pelvic incidence (OR 1.02); preoperative cervical flexibility (OR 1.04); and combined approach (OR 6.2). Having abnormal hyperkyphosis in the thoracic spine, more so than abnormal cervical lordosis, was a factor for developing symptomatic disease when analyzed against asymptomatic patients (OR 1.2). Predictive modeling identified factors that were predictive of symptomatic versus no DJK, as follows: myelopathy (modified Japanese Orthopaedic Association score 12-14); combined approach; uppermost instrumented vertebra C3 or C4; preoperative hypermobility; and > 7 levels fused (area under the curve 0.89). A predictive model for symptomatic versus asymptomatic disease (area under the curve 0.85) included being frail, T1 slope minus cervical lordosis > 20°, and a pelvic incidence > 46.3°. Controlling for baseline deformity and disability, symptomatic patients had a greater cervical sagittal vertical axis (4-8 cm: 47.6% vs 27%) and were more malaligned according to their Scoliosis Research Society sagittal vertical axis measurement (OR 0.1) than patients without DJK at 1 year (all p < 0.05). Despite their symptomatology and higher reoperation rate, outcomes equilibrated in the symptomatic cohort at 1 year following revision. CONCLUSIONS: Overall, 32.2% of patients with CD suffered from DJK. Symptomatic DJK can be predicted with high reliability. It can be further distinguished from asymptomatic occurrences by taking into account pelvic incidence and baseline cervicothoracic deformity severity.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".