Role of Obesity on the Risk for Total Hip or Knee Arthroplasty: Reply
Bibliographic record
Abstract
Reply: We thank Drs. Gursu and Aydin for their interest in our article. The purpose of our study was not to implicate obesity as a cause of hip or knee arthrosis, but rather to determine the effect of unhealthy weight on the progression of the arthritic process. Large-scale population studies have suggested arthrosis of the hip or knee is found in as much as 55% of the population, with 7% of patients having severe disease and approximately 2% progressing to total joint replacement. Our investigations have suggested a strong cross-sectional relationship between rates of total hip and knee arthroplasties with increasing obesity classes. Our hypothesis has been obesity leads to more rapid progression of already damaged hips or knees, leading to increasing rates of joint arthroplasty. We believe our national study based on the Canadian population has clearly shown obesity increases the relative risk ratio for the need of total hip and total knee arthroplasties, with patients with arthritis of the knee having the greatest risk. We also concur with Drs. Gursu and Aydin that additional research in this important field is warranted. Obesity is a worldwide health concern for its effect not only on hip and knee replacement rates but also on a myriad of other diseases.
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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 | 0.004 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.016 | 0.021 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".