High Incidence of Vertebral Fractures in Children With Acute Lymphoblastic Leukemia 12 Months After the Initiation of Therapy
Bibliographic record
Abstract
PURPOSE: Vertebral fractures due to osteoporosis are a potential complication of childhood acute lymphoblastic leukemia (ALL). To date, the incidence of vertebral fractures during ALL treatment has not been reported. PATIENT AND METHODS: We prospectively evaluated 155 children with ALL during the first 12 months of leukemia therapy. Lateral thoracolumbar spine radiographs were obtained at baseline and 12 months. Vertebral bodies were assessed for incident vertebral fractures using the Genant semiquantitative method, and relevant clinical indices such as spine bone mineral density (BMD), back pain, and the presence of vertebral fractures at baseline were analyzed for association with incident vertebral fractures. RESULTS: Of the 155 children, 25 (16%; 95% CI, 11% to 23%) had a total of 61 incident vertebral fractures, of which 32 (52%) were moderate or severe. Thirteen (52%) of the 25 children with incident vertebral fractures also had fractures at baseline. Vertebral fractures at baseline increased the odds of an incident fracture at 12 months by an odds ratio of 7.3 (95% CI, 2.3 to 23.1; P = .001). In addition, for every one standard deviation reduction in spine BMD Z-score at baseline, there was 1.8-fold increased odds of incident vertebral fracture at 12 months (95% CI, 1.2 to 2.7; P = .006). CONCLUSION: Children with ALL have a high incidence of vertebral fractures after 12 months of chemotherapy, and the presence of vertebral fractures and reductions in spine BMD Z-scores at baseline are highly associated clinical features.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".