S3013 THE VALUE OF THE SWEDISH NATIONAL THR REGISTER – IMPROVED QUALITY AND SIGNIFICANT COST REDUCTION
Bibliographic record
Abstract
Aims: In 1979 a national observation study of total hip arthroplasties was started in Sweden. The Swedish Hip Register describes the epidemiology of primary and revision surgery and identifies risk factors for failure. Every unit reports details concerning implants, surgical and cementing technique and revision procedures online via the Internet home page (www.jru.orthop.gu.se). Methods: Currently the register contains 203 625 primary total hip arthroplasties performed during 1979–2001 and 18 067 revision procedures. Revision is the failure endpoint definition and modified Kaplan-Meier statistics and Poisson models are used for survival analysis. Each hospital receive their results annually providing a system for continuous improvement. Results: The results show that serious complications have declined significantly despite an increasing number of patients at risk. The revision burden for cemented THR (94% of the implants are cemented) is only 7.5%, which is much lower than in other countries. Over the 22 year period revision for aseptic loosening has been reduced to one quarter. Demographics are important since male gender and young age significantly increase the risk for revision. Cementless implants have in general had a worse outcome than expected but improved during the last decade. Conclusion: Problem areas are the young population and revision surgery which must be improved. The revision burden is about two times higher in all other countries. This finding implies that the register is extremely cost-effective and the reduction in direct costs for the health care service in Sweden corresponds to approximately USD 140 millions over the last ten years.
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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 | 0.009 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.008 |
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".