The impact of hospitalization on oral health: a systematic review
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: Poor oral health of hospitalized patients is associated with an increased risk of hospital-acquired infections and reduced life quality. OBJECTIVES: To systematically review the evidence on oral health changes during hospitalization. DATA SOURCES: Cochrane library, Medline, OldMedline, Embase and CINAHL without language restrictions. STUDY ELIGIBILITY CRITERIA: Observational longitudinal studies. DATA APPRAISAL AND SYNTHESIS METHODS: Two independent reviewers screened studies for inclusion, assessed the risk of bias and extracted data. Risk of bias was assessed using the Newcastle-Ottawa assessment scale. A narrative synthesis was conducted. RESULTS: Five before and after studies were included. The data suggest a deterioration in oral health following hospitalization with an increase in dental plaque accumulation and gingival inflammation and a deterioration in mucosal health. LIMITATIONS: While before and after studies are at a general risk of bias, other specific study characteristics were judged to have a low risk of bias. However, methodological issues such as unvalidated outcome measures and the lack of assessor training limit the strength of the evidence. CONCLUSION: Hospitalization is associated with a deterioration in oral health, particularly in intubated patients.
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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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