CIHI Survey: Hospitalization for Elective Joint Replacements in Canada
Bibliographic record
Abstract
ne in 10 Canadians is affected by osteoarthritis (OA), a degenerative disorder affecting the joints, ligaments, tendons, bones and other components of the musculoskeletal system (Arthritis Society 2008; Badley and Glazier 2004). Hip and knee replacement procedures are undertaken as a treatment when patients are experiencing severe pain and limited mobility, usually associated with arthritis or another disorder. Over a period of a decade, beginning 1994–1995, Canadians increasingly accessed healthcare services for joint replacement. During this time, an increase of 87% was observed in hospitalizations for hip and knee replacements (CIHI 2006). The age standardized rate almost doubled for knee replacement surgery over the 10-year period from 50.1 in 1994–1995 to 90.8 in 2004–2005 (CIHI 2006). For hip replacement surgery, the age standardized rate increased by one fifth (CIHI 2006). Some of this growth may be attributed to an increase in life expectancy as well as an increasing prevalence of arthritis, which is anticipated as the population ages (Perruccio 2004). Jo in t r ep l a c ement procedures are one of the five priority areas identified by the federal government for increased efforts towards access to care for Canadians. The increasing number of procedures being performed motivated the implementation of a study to gain better understanding about the profile of joint replacement patients. As part of our objective we sought to characterize elective joint replacement surgical rates in Canada and their demographic makeup and their post-surgical outcomes (complications leading to joint replacement revisions).
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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 | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".