CT-Based Characterization of Fracture Patterns in Pediatric Lumbar Spondylolysis
Bibliographic record
Abstract
Background: Spondylolysis is a stress fracture of the pars interarticularis. Precise fracture morphology may help dictate management and dictate whether direct repair with an intralaminar screw is possible. The aim of this study was to characterize the specific fracture patterns of the pars interarticularis in pediatric patients with spondylolysis. Methods: This was a single-center retrospective cohort study. Patients were included if they were aged younger than 21 years with lumbar spondylolysis or Grade 1 isthmic spondylolisthesis on computed tomography (CT) imaging. On sagittal CT, total pars length (mm), inferior edge of inferior articular process to spondylolysis (mm), superior edge to spondylolysis (mm), size of spondylolysis gap (mm), and width of pars (mm) at fracture site were measured. The angle of the pars fractures were characterized in reference to the long axis of the pars. Results: There were 32 patients with 59 total spondylolyses included in this study. The mean age was 15.1 ± 1.9 years, and 44% (n = 14) were female. 7 (22%) patients had grade 1 spondylolisthesis. There were 15 fractures (25%) that had less than 0.5-mm gap, and the remaining 44 spondylolysis had a mean gap size of 2.4 ± 1.3 mm (range 0.9-6.4 mm). The mean total pars length was 37.9 ± 3.7 mm (range 31.6-45.8 mm). The mean measurement from the superior edge to the spondylolysis site was 12.1 ± 2.9 mm (range 6.1-18.8 mm). The average percentage of superior edge to spondylolysis/total pars length was 32.0% (range 17%-52%). Pars fracture angles ranged from 77° to 165° to the long axis of the pars. A majority (n = 40, 68%) of the pars fractures were between 110 and 140°. There were 12 fractures (20%) that were <110° and 7 fractures (12%) that were >140°. Conclusions: Pars fractures typically occur approximately one-third of the distance from the superior edge of the pars. However, considerable variability exists in their exact location along the pars. A clearer understanding of these fracture patterns may help refine surgical techniques and improve surgical outcomes for this patient population. Level of Evidence: Level III. See Instructions for Authors for a complete description of levels of evidence.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 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) | 0.001 | 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".