Ottawa, Ontario, Canada, February 13–16, 2013
Bibliographic record
Abstract
The program consisted of presentations covering original research, symposia, the Dunlop-Dottridge Lecture, workshops, the Great Debate, and a special spotlight on Canadian excellence in rheumatology by the CRA Distinguished Rheumatologist, Distinguished Investigator, Teacher-Educator, and Young Investigator.The contributions presented at the meeting are reflected in the abstracts of the meeting, which we are pleased to publish in this issue.in Alberta First Nations (FN) and non-First Nations (non-FN) populations.Methods: Using population-based healthcare administrative data (years 1993 to 2010), a prevalent OA cohort was determined based on diagnosis codes (2 physician claims within 2 years or 1 hospitalization with ICD9 code 715x, or ICD10 codes M15-19).FN patients were identified based on premium payer status and represent 3.8% of the Alberta population.OA prevalence (fiscal year 2007/2008) and visits to primary care physicians, orthopedic surgeons, and rheumatologists, and hospitalizations (joint replacement and all-cause) were calculated.Results: Age and sex standardized prevalence of OA in FN persons was 160.0 cases/1,000 population, compared to 78.2 cases in non-FN persons (standardized rate ratio 2.06; 95% CI 2.00-2.12).Age and sex standardized prevalence was highest for rural residents (186.7/1,000FN, 88.5/1,000 non-FN) and females (184.9/1,000FN, 93.1/1,000 non-FN).Primary care physician contact for FN persons was more frequent than for non-FN (16.7 vs 10.8 visits/1,000 person-years (py), respectively), with 15% of these visits being coded for OA.FN persons with OA were less likely to see an orthopedic surgeon (290.4FN vs 460.3 non-FN visits/1,000py; rate difference -0.170, 95%CI -0.175 to -0.165).Rheumatology visits were also less frequent for FN persons (39.0 FN vs 51.4 non-FN visits/1,000py; rate difference -0.012, 95%CI -0.014 to -0.010).FN with OA were less likely to have hip or knee replacements (6.2 FN vs 20.0 non-FN surgeries/1,000py; rate difference -0.014, 95% CI -0.015 to -0.013).All-cause hospitalization rates were highest in FN females with OA (355.8 admissions/1,000py) followed by FN males, non-FN males and non-FN females, and for rural compared to urban residents.Conclusion: Our work suggests disparities in OA care in FN persons given an estimated 2-fold higher disease prevalence.This finding may be driven in part by an increased probability of diagnosis through frequent primary care contact.Use of rheumatology and orthopedic services is lower in FN compared to non-FN persons.This may be due to access barriers for FN patients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.261 | 0.067 |
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".