Retrospective Analysis of Congenital Scoliosis
Bibliographic record
Abstract
STUDY DESIGN: Retrospective study of a series of 286 patients with congenital scoliosis (CS). OBJECTIVE: To describe a large cohort of patients with CS and to propose an algorithm for genetic investigations SUMMARY OF BACKGROUND DATA.: CS is characterized by a spine curvature due to congenital malformations of the vertebrae and is frequently associated to other anomalies. The underlying causes remain unclear in most patients, although we know that genetics plays a role in the development of vertebral defects. METHODS: Institutional review board approval was obtained. We performed a retrospective study by consulting the hospital charts of 286 patients with CS seen at the CHU Sainte-Justine, Montreal, from 2004 to 2015. We compile information on radiological findings, associated malformations, and genetic tests. RESULTS: Results showed that 67.1% of patients had associated anomalies affecting different systems. Only a minority of patients had a syndromic diagnosis to explain their CS. Nevertheless, array comparative genomic hybridization performed in a minority of patients showed a high detection rate (31.3% had a chromosomal anomaly among 32 tested). CONCLUSION: We suggest that every patient with CS should have thorough investigations to rule out associated anomalies and that different genetic tests should be offered according to the associated clinical findings. LEVEL OF EVIDENCE: 4.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".