Impact of Disability Status on Ischemic Stroke Costs in Canada in the First Year
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Longitudinal, patient-level data on resource use and costs after an ischemic stroke are lacking in Canada. The objectives of this analysis were to calculate costs for the first year post-stroke and determine the impact of disability on costs. METHODOLOGY: The Economic Burden of Ischemic Stroke (BURST) Study was a one-year prospective study with a cohort of ischemic stroke patients recruited at 12 Canadian stroke centres. Clinical history, disability, health preference and resource utilization information was collected at discharge, three months, six months and one year. Resources included direct medical costs (2009 CAN$) such as emergency services, hospitalizations, rehabilitation, physician services, diagnostics, medications, allied health professional services, homecare, medical/assistive devices, changes to residence and paid caregivers, as well as indirect costs. Results were stratified by disability measured at discharge using the modified Rankin Score (mRS): non-disabling stroke (mRS 0-2) and disabling stroke (mRS 3-5). RESULTS: We enrolled 232 ischemic stroke patients (age 69.4 ± 15.4 years; 51.3% male) and 113 (48.7%) were disabled at hospital discharge. The average annual cost was $74,353; $107,883 for disabling strokes and $48,339 for non-disabling strokes. CONCLUSIONS: An average annual cost for ischemic stroke was calculated in which a disabling stroke was associated with a two-fold increase in costs compared to NDS. Costs during the hospitalization to three months phase were the highest contributor to the annual cost. A "back of the envelope" calculation using 38,000 stroke admissions and the average annual cost yields $2.8 billion as the burden of ischemic stroke.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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