Predictors of Dysphagia Screening After Acute Ischemic Stroke (S31.002)
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence and predictors of dysphagia screening after acute ischemic stroke. BACKGROUND: Dysphagia is a devastating complication of acute ischemic stroke and can lead to malnutrition, aspiration pneumonia, and death. Guidelines state that all patients with acute stroke should have early screening for dysphagia, however previous research suggests only 60[percnt] of individuals are tested, and it is unclear what factors contribute to receiving dysphagia screening. DESIGN/METHODS: We used the Ontario Stroke Registry from 2010-2013 to identify patients who were admitted to regional stroke centres and received (‘Yes’) or did not receive (‘No’) a dysphagia screen, and compared their baseline characteristics with independent t-tests. Multivariable logistic regression with backward selection was used to identify predictors of receiving a dysphagia screen. RESULTS: Among 7175 patients with acute ischemic stroke, 5468 patients (76.1[percnt]) underwent dysphagia screening (‘Yes’ group), 1389 patients (26.4[percnt]) did not undergo screening (‘No’ group) and 318 patients (4.4[percnt]) were deemed ineligible (eg. intubated). The ‘No’ group had less severe strokes (NIH score 5.1 vs. 8.0). Factors increasing the odds of receiving a dysphagia test were: admission to stroke unit (adjusted odds ratio (aOR) 5.8, 95[percnt] confidence intervals (CI) 4.3-7.9), presenting with speech deficits (aOR 1.9, 95[percnt] CI 1.7-2.2), weakness (aOR 1.5, 95[percnt] CI 1.3-1.7), or dysphagia (aOR 2.4, 95[percnt] CI 1.9-3.2), and treatment with thrombolysis (aOR 1.9, 95[percnt] CI 1.5-2.4). Moderate stroke (aOR 1.7, 95[percnt] CI 1.4-2.0) had a higher odds ratio when compared to severe stroke (aOR 1.2, 95[percnt] CI 0.9-1.4). (p-value <0.001 for all comparisons). CONCLUSIONS: A significant portion of patients with acute ischemic stroke did not receive a swallowing test. Patients were more likely to receive testing if they had moderate rather than mild or severe strokes, presenting symptoms of speech deficits, weakness, or dysphagia, received thrombolytics, or were admitted to a stroke unit.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".