Uncovering Rheumatologic Disease in the Northwest Territories: First Comprehensive Baseline Study and Comparative Insights
Bibliographic record
Abstract
Objectives This study aims to capture baseline demographic and rheumatologic history of patients referred from the Northwest Territories (NWT), for which available data is both scarce and outdated, to identify areas for patient care improvement in a unique and underserved population. Methods In 2022-2023, the NWT Health and Social Services Authority redirected all known established and newly referred Rheumatology patients to receive care in Edmonton. This provided a unique point-in-time opportunity to collect and report baseline information in the Alberta Health Services electronic record, ConnectCare, including demographics, disease history, and follow-up times; and to compare results with an Edmonton Rheumatology patient cohort. Results 425 patients were identified (70% female). Of 251 patients with documented ethnicity, 69%, 26%, 4%, and 1% were of Indigenous, Caucasian, Asian, and African descent, respectively. 288 (68%) previously saw Rheumatology in NWT; the remainder were new referrals. Most frequent diagnoses in established patients were rheumatoid arthritis (RA, 47%), psoriatic arthritis (PsA, 16%), and ankylosing spondylitis (AS, 10%); this includes 50 patients who were not assessed due to patient no-show or cancellation. Patients waited on average, 1.9 years from their last rheumatology visit. For new referrals, 76 (55%) received degenerative/mechanical or non-rheumatic diagnoses; 18% canceled or did not show. Of the remaining 36 patients, top diagnoses were RA (28%), gout (14%), PsA (11%), and AS (11%) Top new rheumatologic diagnoses from 2022-2023 in the Edmonton area seen by Rheumatologists using ConnectCare were RA (26%), crystal arthropathy (11%), and vasculitis (9%), with PsA and AS each comprising ~7%. 1 patient overall was diagnosed with vasculitis in the NWT cohort, compared to 4% in the entire Edmonton cohort. Conclusion Our study provides the broadest epidemiologic dataset of patients with rheumatologic diseases in the Northwest Territories and is the first to comprehensively differentiate between the various rheumatologic diseases seen in this population. Interestingly, there is a signal of higher rates of psoriatic arthritis and ankylosing spondylitis, and lower rates of vasculitis, compared to historical data in the Edmonton catchment areas. Furthermore, 86 patients (20%) were not assessed due to patient cancelations or no-shows; in addition to a nearly 2-year wait time for established patients, this highlights issues in care for both new and established diseases. Given the population demographics, this may disproportionately impact Indigenous and female patients, but whether this is due to a flawed referral process or travel limitations requires further exploration.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".