Use of Medications of Questionable Benefit at the End of Life in Nursing Home Residents with Advanced Dementia
Bibliographic record
Abstract
OBJECTIVES: To determine the prevalence of and resident characteristics associated with the prescription of medications of questionable benefit (MQBs) near the end of life in older adults with advanced dementia in nursing homes. DESIGN: Population-based, cross-sectional study using Resident Assessment Instrument Minimum Data Set 2.0 linked to health administrative data. SETTING: Ontario, Canada. PARTICIPANTS: All 9,298 nursing home residents with advanced dementia who died between June 1, 2010, and March 31, 2013; were aged 66 and older at time of death; and received at least one MQB in their last year of life. MEASUREMENTS: Prevalence of eight classes of MQBs (e.g., lipid-lowering agents, antidementia drugs) used in the last 120 days and last week of life. RESULTS: Of older nursing home residents with advanced dementia who received at least one MQB in the last year of life, 8,027 (86.3%) received them in the last 120 days and 4,180 (45.0%) in the last week of life. The most commonly prescribed MQB were antidementia (63.6%) and lipid-lowering agents (47.8%). Severe cognitive impairment (adjusted odds ratio (aOR) = 1.19, 95% confidence interval (CI) = 1.07-1.33, P = .002) and fewer signs and symptoms of health instability (aOR = 1.58, 95% CI = 1.44-1.74, P < .001) were associated with MQB use into the last week of life. Seeing a neurologist or psychiatrist was associated with less likelihood of MQB use in the last week of life. CONCLUSION: Many nursing home residents with advanced dementia are dispensed MQBs in the last week of life. Given that MQBs may cause more harm than benefit in this vulnerable population, it is important for physicians to actively reassess the role of all medications toward the end of life.
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 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".