Bibliographic record
Abstract
Each year, hundreds of thousands of Canadians experience critical illness and are admitted to intensive care units (ICUs), most of whom are older adults. While admitted to ICUs, many patients receive medications such as benzodiazepines, non-benzodiazepine sedative-hypnotics, or antipsychotics for sedation-agitation management. As patients transition out of the ICU, newly initiated sedatives are sometimes continued on hospital discharge. However, sedatives are often unnecessary and considered potentially inappropriate medications for community-dwelling older adults due to their association with serious adverse events. This thesis sought to assess, among sedative-naïve older adults hospitalized with critical illness, the incidence, trends, risk factors, and adverse events associated with new sedative prescriptions post-hospital discharge. This thesis contains three observational studies conducted using population-based administrative data for Ontario, Canada (2003 to 2019). Study one found that more than 5% of patients filled sedative prescriptions within seven days post-discharge, with an increased rate for those with ICU admission compared to those hospitalized without ICU. More than half of these new users filled persistent prescriptions within the six months post-discharge. Overall, the proportion of patients who filled sedative prescriptions post-discharge significantly decreased since 2003, with a dramatic reduction in benzodiazepines, especially among those with ICU admission. However, non-benzodiazepine sedative-hypnotic prescriptions have increased since 2003. Study two found that the factors strongly associated with sedative prescriptions post-discharge among ICU survivors were transfer to long-term care, geriatric or psychiatric consultation, invasive mechanical ventilation, and ICU length of stay. The proportion of ICU survivors who filled sedative prescriptions post-discharge varied widely across hospitals, suggesting potentially modifiable prescription practices. Study three found that among ICU survivors, new sedative prescriptions were associated with increased hazards of fall or fracture, return to the emergency department, rehospitalization, and death within 30 days post-discharge. The hazard of each adverse event varied by sedative class. Collectively, these results suggest that careful medication review before and after discharge with consideration of the risk-benefit of the class prescribed if sedative pharmacotherapy is indicated will likely be impactful to ICU survivors and the healthcare system, given the number of patients receiving such medications, and the safety implications for these older patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".