Falls, medications and balance among residents in long-term care institutions
Bibliographic record
Abstract
The aim of this study was to investigate prevalence of falls, use of medications and balance among the residents in longterm care institutions. Methods. Every third resident from 8 long-term care institutions in Kaunas region was included in the study, totally 252 residents. Questionnaire interRAI LTCF (Long Term Care Facility) version 2006 (09) was used for the data collection. Results. More than one quarter (28.2%) of the residents fell down during the last 30 days. Most of the residents (38.1%) were prescribed with 2–3 medications. Benzodiazepines were one of the most frequently used medications (27.0%) in our study (respectively female 30.4% and male 21.3%). Falls possibility among residents was increased by unsteady gait (OR = 9.164, p = 0.001), dizziness (OR = 13.453, p = 0.015), and difficulties move self to stand position unassisted (OR = 13.453, p = 0.008). Conclusions. The findings support the view that falls could be avoided through rational use of drugs and appropriated management of balance in long term care institutions in Lithuania.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".