13th International Conference on Conservative Management of Spinal Deformities and First Joint Meeting of the International Research Society on Spinal Deformities and the Society on Scoliosis Orthopaedic and Rehabilitation Treatment – SOSORT-IRSSD 2016 meeting
Bibliographic record
Abstract
sagittal balance and predictive equations to determine lumbopelvic compensatory patterns (LPCP).These equations are used to guide surgical decision making and technique selection.Although other lumbopelvic compensation equations are available, these have not been compared with the SRS-Schwab equation. ObjectivesThe aim was to evaluate sagittal balance and LPCP in younger and older adults with scoliosis and to compare the two most commonly used LPCP predictive equations (SRS-Schwab and Legaye).Methods EOS radiographic data from 41 adults with scoliosis (coronal Cobb > 10°; 51 ± 19 years) stratified into younger (n = 20) and older (n = 21) groups above and below the mean age was retrospectively analysed.T-tests were used to compare group characteristics and Fisher's exact tests were used to evaluate differences in SVA (sagittal vertical axis), PT (pelvic tilt) and PI (pelvic incidence)-LL (lumbar lordosis) mismatch thresholds.Agreement between SRS-Schwab and Legaye classification was evaluated using Kappa tests and Bland Altman plots.Results and discussion 62% of the older group and 10% of the younger group exceeded the SVA threshold of 40 mm (p < .001).86% of the older group and 20% of the younger group exceeded the 20° pelvic retroversion threshold (p < 0.001).Normal PI-LL mismatch ranges were more prevalent in the younger group (70%) than the older group (28%) (p < .001)when analysed through the SRS-Schwab equation.Legaye equation analysis revealed no difference in the prevalence of normal PI-LL ranges between the younger (15%) and older group (10%) (P = .66).Lumbar hyperlordosis was more prevalent in the younger (25%) than older group (5%) (p < .001)when analysed through the SRS-Schwab equation but no difference was observed between the younger (10%) and older group (0%) (p > .05)when analysed through the Legaye equation.Lumbar hypolordosis was more prevalent in the older (67%) than the younger group (5%) (p < .001)but no difference was observed between the older (90%) and younger group (75%) when analysed through the Legaye predictive equation (P = .33).Agreement between the SRS-Schwab and Legaye equations was poor for the whole (κ = 0.148), older (κ = 0.277) and young groups (κ = 0.039). Conclusion and significanceThis study confirms that older patients more often exhibit higher SVA and pelvic retroversion than younger patients.Whilst analysis through SRS-Schwab classification reveals that younger patients more often exhibit lumbar hyperlordosis than older patients who more often exhibit lumbar hypolordosis, analysis through the Legaye equations revealed no differences.There is poor agreement between the SRS-Schwab and Legaye classification equations.Clinicians are cautioned to exercise clinical judgement when evaluating their patients with these equations until more research is done.O3
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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.048 | 0.012 |
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".