Rural Residence and Diagnostic Delay for Amyotrophic Lateral Sclerosis in Saskatchewan
Bibliographic record
Abstract
BACKGROUND: Diagnostic delay in amyotrophic lateral sclerosis (ALS) is common. In a recent Canadian study evaluating provincial differences in care, Saskatchewan had the longest delay at 27 months. Since Saskatchewan has a large rural population, this study sought to determine whether geographically determined access to a neurologist at tertiary centers could be contributing to this lengthy delay. METHODS: A retrospective chart review of 171 patients seen in the ALS clinic in Saskatoon, Saskatchewan was performed. Urban or rural location, distance from nearest tertiary center, and clinically relevant data were collected. RESULTS: There was no difference between urban and rural populations for delay in symptom onset to diagnosis. For rural patients, linear regression modeling did not uncover a significant relationship between distance from tertiary center and time to diagnosis. Additionally, there were no differences between urban and rural dwellers either for referral or utilization of feeding tube, noninvasive ventilation, riluzole, or communication devices. Contrary to the previous data showing a 27-month diagnostic delay in Saskatchewan, our study which included a larger provincial population found the mean diagnostic delay was 16.6 months. CONCLUSIONS: This study did not uncover differences in diagnostic delay or ALS care between urban and rural dwellers. Further study is required to determine reproducibility of results.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".