276 SENSORY DEPRIVATION IN OLDER MEDICAL INPATIENTS: ARE WE AWARE ENOUGH?
Bibliographic record
Abstract
Abstract Background Visual and hearing impairment is common amongst older adults admitted to the acute hospital setting. Sensory deprivation can contribute to falls and incidence of delirium, particularly in those who have underlying cognitive impairment. Interventions which reduce sensory deprivation have been recommended to avoid these complication [1]. Methods Patients over 75 admitted to 11 medical wards in a University Teaching Hospital were assessed. Baseline demographics were collected. Documentation regarding hearing and visual impairment, delirium, completion of 4 AT, and underlying cognitive impairment was reviewed. Inpatient falls were documented. Results 100 older adults were included in the audit. (Mean age: 83.5 years). 73% of patients had a visual impairment and 23% had a hearing impairment. 67% had access to their glasses and only 27% of patients had access to their hearing aids. Documentation of sensory disability in either medical or nursing notes was 19%. 29% of patients had documented delirium during their inpatient stay. 4AT was performed on 76% of admitted older adults in the selected wards. Conclusion Visual and hearing impairment is common amongst older admitted medical inpatients. Despite this, there can be a lack of access to glasses and hearing aids. There is a paucity of documentation regarding sensory deprivation, therefore interventions targeting this risk factor for delirium may not be allocated to the cohort most at risk. We recommend strategies highlighting awareness of sensory deprivation in older adults admitted to hospital. Reference 1. Surkan MJ and Gibson W. Interventions to mobilize elderly patients and reduce length of hospital stay. Canadian Journal of Cardiology. 2018 34(7), pp. 881–888.
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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 | 0.001 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".