Trends and regional variation in vertebroplasty and kyphoplasty in Switzerland: a population-based small area analysis
Bibliographic record
Abstract
Regional variation in procedure use often reflects the uncertainty about the risks and benefit of procedures. In Switzerland, regional variation in vertebroplasty and balloon kyphoplasty rates was high, although the variation declined between 2013 and 2018. Substantial parts of the variation remained unexplained, and likely signal unequal access and differing physician opinion. PURPOSE: To assess trends and regional variation in percutaneous vertebroplasty (VP) and balloon kyphoplasty (BKP) use across Switzerland. METHODS: We conducted a population-based analysis using patient discharge data from all Swiss acute care hospitals for 2013-2018. We calculated age/sex-standardized mean procedure rates and measures of variation across VP/BKP-specific hospital areas (HSAs). We assessed the influence of potential determinants of variation using multilevel regression models with incremental adjustment for demographics, cultural/socioeconomic, health, and supply factors. RESULTS: We analyzed 7855 discharges with VP/BKP from 31 HSAs. The mean age/sex-standardized procedure rate increased from 16 to 20/100,000 persons from 2013 to 2018. While the variation in procedure rates across HSAs declined, the overall variation remained high (systematic component of variation from 56.8 to 6.9 from 2013 to 2018). Determinants explained 52% of the variation. CONCLUSIONS: VP/BKP procedure rates increased and regional variation across Switzerland declined but remained at a high level. A substantial part of the regional variation remained unexplained by potential determinants of variation.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".