Prevalence and management of osteoarthritis in primary care: an epidemiologic cohort study from the Canadian Primary Care Sentinel Surveillance Network
Bibliographic record
Abstract
BACKGROUND: Osteoarthritis is a common chronic condition that affects many older Canadians and is a considerable cause of disability. Our objective was to describe the epidemiology of osteoarthritis in patients aged 30 years and older using electronic medical records (EMRs) in a Canadian primary care population. METHODS: In this retrospective cohort study, we analyzed the EMRs of 207 610 patients over 30 years of age (extracted on December 31, 2012) who had at least one clinic visit during the preceding 2 years. We calculated the age-sex standardized prevalence of diagnosed osteoarthritis and its association with comorbidities and covariates available in the Canadian Primary Care Sentinel Surveillance Network database. RESULTS: The estimated prevalence of diagnosed osteoarthritis was 14.2% (15.6% among women, 12.4% among men). The diagnosis of osteoarthritis was associated with several comorbidities: hypertension (prevalence ratio [PR] 1.17, 95% confidence interval [CI] 1.15-1.18), depression (PR 1.26, 95% CI 1.22-1.3), chronic obstructive pulmonary disease (COPD) (PR 1.16, 95% CI 1.11-1.21) and epilepsy (PR 1.27, 95% CI 1.13-1.43). In addition, 56.6% of patients had received a prescription for a range of nonsteroidal anti-inflammatory drugs, 45% of which were topical. Opioid medications were prescribed to 33% of patients for pain management. CONCLUSION: Osteoarthritis is a common disease in middle-aged and older Canadians. It is more common in women than in men and is associated with comorbid conditions. Most patients with osteoarthritis received pharmacotherapy for inflammation and pain management. As the Canadian population ages, osteoarthritis will become an increasing burden for individuals and the health care system.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".