The Effect of tPA on Inpatient Rehabilitation after Stroke: A Cost Comparison
Bibliographic record
Abstract
BACKGROUND: Tissue plasminogen activator has been found to significantly improve patient outcomes post stroke. Previous economic evaluations have adjusted for fewer admissions to inpatient rehabilitation but not for decreased length of stay in rehabilitation. Our objective was to estimate the potential cost savings associated with a decreased length of stay in inpatient rehabilitation for patients who receive tissue plasminogen activator compared to those who do not, in a Canadian context. METHODS: Decreased length of stay in inpatient rehabilitation for patients who received tissue plasminogen activator compared to controls was reported previously in a population of 1962 patients admitted to hospital with an ischemic stroke in Ontario between July 1, 2003 and March 31, 2008. Average per diem cost savings associated with the use of tissue plasminogen activator were calculated using a literature based cost estimate. Sensitivity analysis varying the length of stay in inpatient rehabilitation was performed. RESULTS: The estimated mean per diem cost of inpatient rehabilitation derived from the literature was $626. Based on previously reported estimates for reduced length of stay, receipt of tissue plasminogen activator was estimated to result in savings of $939 per patient during inpatient rehabilitation. Sensitivity analysis suggested that these cost savings could range from $501 to $1377 per patient on average. CONCLUSIONS: Future economic evaluations of tissue plasminogen activator should consider adjusting for shortened length of stay in inpatient rehabilitation for patients who receive tissue plasminogen activator.
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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 | 0.005 | 0.017 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.010 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".