The Utility of Administrative Data for Surveillance of Comorbidity in Multiple Sclerosis: A Validation Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Although comorbidity is important in multiple sclerosis (MS), few validated methods for its assessment exist. We validated and applied administrative case definitions for several comorbidities in MS. METHODS: Using provincial administrative data we identified persons with MS and a matched general population cohort. Case definitions for chronic lung disease (CLD), epilepsy, inflammatory bowel disease (IBD), irritable bowel syndrome (IBS) and migraine were developed using administrative data, and validated against medical records. We applied these definitions to estimate the age-standardized prevalence of these comorbidities in the MS and matched cohorts. RESULTS: Versus medical records, administrative case definitions showed moderate agreement for CLD (ĸ = 0.41), migraine (ĸ = 0.51), and epilepsy (ĸ = 0.44), fair agreement for IBS (ĸ = 0.36) and could not be calculated for IBD (small sample size). The 2005 prevalence of CLD was similar in the MS (15.6%) and general populations (14.4%). The prevalence of the remaining comorbidities was higher in the MS than the general populations: epilepsy (4.12 vs. 1.12%), IBD (0.78 vs. 0.65%), IBS (12.2 vs. 6.80%) and migraine (23.0 vs. 16.5%). CONCLUSIONS: Administrative data are valid for tracking CLD, epilepsy, and migraine in MS. The prevalence of epilepsy, IBD, IBS and migraine is increased in MS versus the general population.
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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 | 0.006 | 0.048 |
| 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