Predictors and Outcomes of Dysphagia Screening After Acute Ischemic Stroke
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Guidelines advocate screening all acute stroke patients for dysphagia. However, limited data are available regarding how many and which patients are screened and how failing a swallowing screen affects patient outcomes. We sought to evaluate predictors of receiving dysphagia screening after acute ischemic stroke and outcomes after failing a screening test. METHODS: We used the Ontario Stroke Registry from April 1, 2010, to March 31, 2013, to identify patients hospitalized with acute ischemic stroke and determine predictors of documented dysphagia screening and outcomes after failing the screening test, including pneumonia, disability, and death. RESULTS: Among 7171 patients, 6677 patients were eligible to receive dysphagia screening within 72 hours, yet 1280 (19.2%) patients did not undergo documented screening. Patients with mild strokes were significantly less likely than those with more severe strokes to have documented screening (adjusted odds ratio, 0.51; 95% confidence interval [CI], 0.41-0.64). Failing dysphagia screening was associated with poor outcomes, including pneumonia (adjusted odds ratio, 4.71; 95% CI, 3.43-6.47), severe disability (adjusted odds ratio, 5.19; 95% CI, 4.48-6.02), discharge to long-term care (adjusted odds ratio, 2.79; 95% CI, 2.11-3.79), and 1-year mortality (adjusted hazard ratio, 2.42; 95% CI, 2.09-2.80). Associations were maintained in patients with mild strokes. CONCLUSIONS: One in 5 patients with acute ischemic stroke did not have documented dysphagia screening, and patients with mild strokes were substantially less likely to have documented screening. Failing dysphagia screening was associated with poor outcomes, including in patients with mild strokes, highlighting the importance of dysphagia screening for all patients with acute ischemic stroke.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".