INCREASED RISK OF UNDERGOING HIP ARTHROPLASTY AT A YOUNGER AGE IN OBESE AUSTRALIANS
Bibliographic record
Abstract
Obesity is a known risk factor for hip osteoarthritis. The aim of this study was to compare the incidence of obesity in Australians undergoing hip replacements (HR) for osteoarthritis to the general population. A cohort study was conducted comparing data from the Australian Bureau of Statistics and the Australian Orthopaedic Association National Joint Replacement Registry (AOANJRR) from 2017-18. Body mass index (BMI) data for patients undergoing primary total hip replacement and resurfacing for osteoarthritis were obtained from the AOANJRR. The distribution of HR patients by BMI category was compared to the general population, in age and sex sub-groups. During the study period, 32,495 primary HR were performed for osteoarthritis in Australia. Compared to the general population, there was a higher incidence of Class I, II, and III obesity in patients undergoing HR in both sexes aged 35 to 74 years old. Class III obese females and males undergoing HR were on average 6 to 7 years younger than their normal weight counterparts. Class III obese females and males aged 55-64 years old were 2.9 and 1.7 times more likely to undergo HR, respectively (p<0.001). There is a strong association between increased BMI and relative risk of undergoing HR. Similar findings have been noted in the United States of America, Canada, United Kingdom, Sweden and Spain. A New Zealand Registry study and recent meta-analysis have also found a concerning trend of Class III obese patients undergoing HR at a younger age. Obese Australians are at increased risk of undergoing HR at a younger age. A national approach to address the prevalence of obesity is needed.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".