Optimizing Discharge Planning
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The length of stay (LOS) is the main cost-determining factor for inpatients with acute stroke. Although studies have identified variables associated with LOS, few have analyzed predictors of longer stay after receiving thrombolytic therapy for acute stroke. METHODS: We studied all consecutive acute stroke patients receiving intravenous recombinant tissue plasminogen activator (rtPA) admitted to the London Health Sciences Center, in London, Ontario, Canada, from 1999 to 2003. Longer stay was defined as LOS > or =7 days after admission. Demographic as well as baseline clinical, laboratory, and imaging variables were analyzed to identify predictors of LOS. Significant variables were entered into a multivariate logistic regression analysis. RESULTS: Among 216 acute stroke patients receiving rtPA, the median LOS was 6 days. LOS was >7 days in 102 (49%) patients. Age > or =70 (odds ratio [OR], 2.2; 95% CI, 1.2 to 4.0), lack of improvement at 24 hours (OR, 2.5; 95% CI, 1.4 to 4.4), prestroke modified Rankin Scale > or =2 (OR, 2.4; 95% CI, 1.2 to 4.9), baseline National Institutes of Health Stroke Scale score > or =15 (OR, 9.4; 95% CI, 3.2 to 27.6), cortical involvement (OR, 2.2; 95% CI, 1.2 to 3.9), and new infarction on the control computed tomography (CT; OR, 2.8; 95% CI, 1.4 to 5.9) were independent predictors of longer stay. CONCLUSIONS: Lack of improvement at 24 hours after rtPA, cortical involvement, and new infarction on the 24-hour CT scan are relevant variables that can independently affect the LOS. These new variables may be useful for establishing policy in relation to the organization and planning of the health care system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.040 | 0.008 |
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".