Demographic and clinical factors associated with recovery of poststroke dysphagia: A meta‐analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Poststroke dysphagia (PSD) recovery depends on various factors. We aimed to provide evidence concerning predictive variables for the recovery of PSD. METHODS: PubMed, Embase, Web of Science, China National Knowledge Infrastructure (CNKI), Wanfang Database, VIP database of Chinese periodicals, Chinese biomedical literature service system (SinoMed), and Cochrane Library databases were systematically searched up to September 21, 2022. According to the inclusion criteria, the literature searched in the database was screened. The methodological quality of included studies was assessed using the Newcastle-Ottawa Scale (NOS). Meta-analysis was performed to identify the factors prognostic for PSD. RESULTS: Twenty-eight studies were eligible, and pooled analyses were allowed for 12 potential prognostic factors. We identified older age, higher National Institutes of Health Stroke Scale (NIHSS) score, lower activities of daily living (ADL) score, lower body mass index (BMI), severe dysphagia on admission, aspiration, brainstem stroke, severe cognitive impairment, and bilateral hemispheric stroke were negative factors for the recovery of PSD, while early intervention and Modified Rankin Scale (mRS) = 0 before onset were protective factors for the recovery of PSD. There was no significant association between stroke type and prognosis of PSD. CONCLUSION: Prognostic factors of PSD summarized in this meta-analysis could be useful for developing reasonable treatment plan to better promote recovery of swallowing function after stroke.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it