Benzodiazepine Consumption, Functionality, Cognition, and Somnolence in Older Adults at a Tertiary Care Psychiatric Hospital in Mexico City
Bibliographic record
Abstract
BACKGROUND: The aging population in Mexico, particularly those aged 60 and above, faces challenges in healthcare, including potentially inappropriate prescriptions of benzodiazepines. Physiological changes in older adults make precise drug prescriptions crucial. OBJECTIVE: This study aims to evaluate and compare functionality, cognition, and daytime somnolence in older adults using benzodiazepines versus non-users. Additionally, it outlines the demographic and clinical characteristics of both groups. METHODS: A cross-sectional study enrolled 162 participants aged 60 and above, categorized as benzodiazepine consumers or non-consumers. Assessment tools included Lawton's Index, Montreal Cognitive Assessment, Epworth Sleepiness Scale, and Benzodiazepine Dependence Questionnaire. Statistical analysis employed t-tests and chi-square tests. RESULTS: Benzodiazepine users (n=81) exhibited lower cognitive scores, increased sleepiness, and reduced daily living activities compared to non-users (n=81). Demographically, BZD users had lower education levels. CONCLUSION: Benzodiazepine use in older adults is associated with cognitive decline, daytime somnolence, and functional limitations, emphasizing the need for cautious prescription practices and continual monitoring. This study contributes insights into the impact of benzodiazepines on the cognitive health of older adults in Mexico.
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 | 0.001 | 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".