The prevalence of adult de novo scoliosis: A systematic review and meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Primary degenerative scoliosis represents a new scoliosis developing in patients with no prior history of spinal curvature. Researchers sought to determine the prevalence of this type of scoliosis. METHODS: MEDLINE, Embase, CINAHL, Web of Science and PubMed were searched from inception to 28th March, 2018. Studies that assessed adults from the general population for scoliosis using imaging techniques were included. Studies were included only if the study authors had excluded participants with previously diagnosed scoliosis and/or spinal disorders. Mixed-effects logistic-regression was used to establish an overall prevalence estimate with 95% confidence intervals (primary outcome) and to examine the effect of age and sex (secondary outcomes). RESULTS: Four cross-sectional studies and one cohort study, involving 4069 participants (66.6% Female), aged between 41 and 94 years, were eligible for inclusion. Reported prevalence figures ranged from 13 to 68%. The pooled prevalence estimate from the mixed-effects logistic regression analysis was 37.6% (95% CI 18.7-61.8). Females were more likely to suffer from scoliosis compared with males (p < 0.001), with prevalence figures of 41.2% (95% CI 20.7-65.8) versus 27.5% (95% CI 12.2-51.1), respectively. Individuals aged < 60 years had a prevalence of 13% (95% CI 5.2-30.2), whereas the prevalence estimates were substantially higher in the > 60 age group [36% (95% CI 17.4-60.6)]. CONCLUSION: Primary degenerative scoliosis is a highly prevalent condition, especially in females. Further research targeting this type of scoliosis is required to obtain more precise global prevalence estimates and to understand the influence of age and sex.
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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 | 0.012 | 0.030 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".