Oral care post stroke: a scoping review
Bibliographic record
Abstract
Health concerns post stroke may be the result of, or exacerbated by, neglected oral health care (OHC). However, OHC may be challenging post stroke due to hemiparesis, hemiplegia, a lack of coordination, and/or cognitive deficits. The objective of this study was to conduct a scoping review and summarise the current state of knowledge pertaining to OHC post stroke. A literature search was conducted using the multiple databases (MEDLINE, CINAHL, EMBASE, etc.). Combinations of multiple keywords were searched: oral, dental, health, care, hygiene, teeth, dentures, tooth brushing, stroke, cardiovascular health and cardiovascular disease. A grey literature search was also conducted. Articles included were those published in English between 1970 and July 2013, which focused on at least one aspect of OHC among a stroke population. For clinical trials, ≥50% of the sample must have sustained a stroke. In total, 60 articles met inclusion and focused on three primary area: (i) OHC Importance/Stroke Implications; (ii) Current Research; and (iii) Current Practice. It was found that OHC concerns are mainly related to mastication, dysphagia/nutrition, hygiene, prostheses and quality of life. Research indicates that there is limited specialised and individual care provided, and there are few assessment tools, guidelines and established protocols for oral health that are specific to the stroke population. Further, dental professionals' and nurses' knowledge of OHC is generally inadequate; hence, proper education for health professionals in acute and rehabilitation settings, patients, and caregivers has been discussed.
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 | 0.008 | 0.031 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.017 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".