The PREvention Program for Alzheimer’s RElated Delirium (PREPARED) cluster randomized trial: a study protocol
Bibliographic record
Abstract
BACKGROUND: Delirium is a significant cause of morbidity and mortality among older people admitted to both acute and long-term care facilities (LTCFs). Multicomponent interventions have been shown to reduce delirium incidence in the acute care setting (30-73%) by acting on modifiable risk factors. Little work, however, has focused on using this approach to reduce delirium incidence in LTCFs. METHODS: The objective is to assess the effectiveness of the multicomponent PREPARED Trial intervention in reducing the following primary outcomes: incidence, severity, duration, and frequency of delirium episodes in cognitively impaired residents. This 4-year, parallel-design, cluster randomized study will involve nursing staff and residents in 45-50 LTCFs in Montreal, Canada. Participating public and private LTCFs (clusters) that provide 24-h nursing care will be assigned to either the PREPARED Trial intervention or the control (usual care) arm of the study using a covariate constrained randomization procedure. Approximately 400-600 LTC residents aged 65 and older with dementia and/or cognitive impairment will be enrolled in the study and followed for 18 weeks. Residents must be at risk of delirium, delirium-free at baseline and have resided at the facility for at least 2 weeks. Residents who are unable to communicate verbally, have a history of specific psychiatric conditions, or are receiving end-of-life care will be excluded. The PREPARED Trial intervention consists of four main components: a decision tree, an instruction manual, a training package, and a toolkit. Primary study outcomes will be assessed weekly. Functional autonomy and cognitive levels will be assessed at the beginning and end of follow-up, while information pertaining to modifiable delirium risk factors, medical consultations, and facility transfers will be collected retrospectively for the duration of the follow-up period. Primary outcomes will be reported at the level of intervention assignment. All researchers analyzing the data will be blinded to group allocation. DISCUSSION: This large-scale intervention study will contribute significantly to the development of evidence-based clinical guidelines for delirium prevention in this frail elderly population, as it will be the first to evaluate the efficacy of a multicomponent delirium prevention program translated into LTC clinical practice on a large scale. TRIAL REGISTRATION: NCT03718156 , ClinicalTrials.gov .
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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 | 0.019 | 0.018 |
| Meta-epidemiology (narrow) | 0.006 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.050 | 0.009 |
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".