Risk Factor Profiles for Individuals With Diagnosed <scp>OA</scp> and With Symptoms Indicative of <scp>OA</scp>: Findings From the Canadian Longitudinal Study on Aging
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The vast majority of published estimates of osteoarthritis (OA) burden are based on an OA diagnosis. These data are limited, as individuals often do not visit a physician until their symptoms are moderate to severe. This study compared individuals with an OA diagnosis to those with OA joint symptoms but without a diagnosis considering a number of sociodemographic and health characteristics. A further distinction was made between individuals with symptoms in one joint site and those with symptoms in multiple joint sites. METHODS: Data are from 23 186 respondents aged 45 to 85 years from the first cycle of the Canadian Longitudinal Study on Aging. A multinomial logistic regression model examined the relationship between sociodemographic- and health-related characteristics and OA status (diagnosed OA, joint symptoms without OA, no OA or joint symptoms). In addition, logistic regression models assessed the relationship between OA status and usually experiencing pain and having some degree of functional limitation. RESULTS: Twenty-one percent of respondents reported a diagnosis of OA, and 25% reported symptoms typical of OA but without an OA diagnosis. Other than being slightly younger, the characteristic profile of individuals with symptoms in two or more joint sites was indistinguishable from that of those with diagnosed OA. CONCLUSION: It may be warranted to consider OA-like multiple joint symptoms when deriving estimates of OA-attributed population health and cost burden.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it