High nutrition risk is associated with higher risk of dysphagia in advanced age adults newly admitted to hospital
Bibliographic record
Abstract
AIM: To establish the prevalence of nutrition risk and associated risk factors among adults of advanced age newly admitted to hospital. METHODS: A cross-sectional study was undertaken in adults aged over 85 years admitted to one of two hospital wards in Auckland within the previous 5 days. An interviewer-administered questionnaire was used to establish participant's socio-demographic and health characteristics. Markers of body composition and muscle strength were collected. Nutrition risk was assessed using the Mini Nutritional Assessment-Short Form (MNA-SF), dysphagia risk using the 10-Item Eating Assessment Tool (EAT-10) and level of cognition using the Montreal Cognitive Assessment. RESULTS: A total of 88 participants with a mean age of 90.0 ± 3.7 years completed the assessments. A third (28.4%) of the participants were categorised by the MNA-SF as malnourished and 43.2% were classified at risk of malnutrition. A third (29.5%) were at risk of dysphagia as assessed by EAT-10. Malnourished participants were more likely to be at risk of dysphagia (P = 0.015). The MNA-SF score was positively correlated with body mass index (r = 0.484, P < 0.001) and grip strength (r = 0.250, P = 0.026) and negatively correlated with risk of dysphagia (r = -0.383, P < 0.001). CONCLUSIONS: Among newly hospitalised adults of advanced age, over two thirds were malnourished or at risk of malnutrition, and a third were at risk of dysphagia. Nutrition risk was positively correlated with low BMI and grip strength and negatively correlated with dysphagia risk. Findings highlight the importance of screening for dysphagia risk, especially in those identified to be malnourished or at nutrition risk.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".