Risk of pneumonia associated with incident benzodiazepine use among community-dwelling adults with Alzheimer disease
Bibliographic record
Abstract
BACKGROUND: Knowledge regarding whether benzodiazepines and similarly acting non-benzodiazepines (Z-drugs) are associated with an increased risk of pneumonia among older adults is lacking. We sought to investigate this association among community-dwelling adults with Alzheimer disease, a condition in which both sedative/hypnotic use and pneumonia are common. METHODS: We obtained data on all community-dwelling adults with a recent diagnosis of Alzheimer disease in Finland (2005-2011) from the Medication use and Alzheimer disease (MEDALZ) cohort, which incorporates national registry data on prescriptions, reimbursement, hospital discharges and causes of death. Incident users of benzodiazepines and Z-drugs were identified using a 1-year washout period and matched with nonusers using propensity scores. The association with hospital admission or death due to pneumonia was analyzed with the Cox proportional hazards model and adjusted for use of other psychotropic drugs in a time-dependent manner. RESULTS: Among 49 484 eligible participants with Alzheimer disease, 5232 taking benzodiazepines and 3269 taking Z-drugs were matched 1:1 with those not taking these drugs. Collectively, use of benzodiazepines and Z-drugs was associated with an increased risk of pneumonia (adjusted hazard ratio [HR] 1.22, 95% confidence interval [CI] 1.05-1.42). When analyzed separately, benzodiazepine use was significantly associated with an increased risk of pneumonia (adjusted HR 1.28, 95% CI 1.07-1.54), whereas Z-drug use was not (adjusted HR 1.10, 95% CI 0.84-1.44). The risk of pneumonia was greatest within the first 30 days of benzodiazepine use (HR 2.09, 95% CI 1.26-3.48). INTERPRETATION: Benzodiazepine use was associated with an increased risk of pneumonia among patients with Alzheimer disease. Risk of pneumonia should be considered when weighing the benefits and risks of benzodiazepines in this population.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".