The Incidence, Co-occurrence, and Predictors of Dysphagia, Dysarthria, and Aphasia after Acute Ischemic Stroke
Bibliographic record
Abstract
Background- Dysphagia, dysarthria and aphasia are frequent sequelae of stroke. We sought to identify their frequency, co-occurrence, and predictors of them after acute ischemic stroke. Methods- First, we used the Registry of the Canadian Stroke Network’s (RCSN) database (2003–2008) from one stroke centre to identify a random sample of 250 patients with acute ischemic stroke confirmed by magnetic resonance imaging (MRI). We conducted a medical chart review to derive frequency estimates for the presence of dysphagia, dysarthria and aphasia and identified clinical predictors of them from the RCSN database. Second, we conducted a systematic review to identify neuroanatomical predictors of dysphagia after acute ischemic stroke. We searched 14 databases, 17 journals, three conference proceedings and the grey literature using the Cochrance Stroke Group search strategy. We pooled individual level data for the dysphagia outcome, calculating relative risks according to neuroanatomical lesion sites. Finally, from the medical chart review, we evaluated MRI scans for patients with acute lesions within 14 days of stroke onset, deriving clinical and neuroanatomical predictors of the three impairments, using logistic regression. Results – First, incidence estimates for dysphagia, dysarthria, and aphasia were 44% (95% CI, 38-51), 42% (95% CI, 35-48) and 30% (95% CI, 25-37), respectively. The highest clinical predictors were non-alert level of consciousness for dysphagia (OR 2.6, CI 1.03-6.5), symptoms of weakness for dysarthria (OR 5.3, CI 2.4-12.0), and right-sided symptoms for aphasia (OR 7.1, CI 3.1-16.6). Second, for our systematic review, we reviewed 964 abstracts, accepting 84 for full review. Seventeen met our inclusion criteria, providing individual results for 656 patients. Predictors of dysphagia included pontine (RR 3.7, 95% CI 1.5-7.7), medial medullary (RR 6.9, 95% CI 3.4-10.9) and lateral medullary (RR 9.6, 95% CI 5.9-12.8) lesions. Finally, 160 patients met our eligibility criteria for MRI analysis. Strongest predictors included medullary lesions (OR 6.2, 95% CI 1.5 – 25.8) for dysphagia, pontine lesions (OR 7.8, 95% CI 2.7 – 22.9) for dysarthria, and insular lesions (OR 34.4, 95% CI 4.2 – 283.4) for aphasia. Conclusions- We computed the frequency of dysphagia, dysarthria, and aphasia, identifying clinical and whole brain neuroanatomical predictors of their presence.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".