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Record W4406030218 · doi:10.1002/alz.093091

Standardizing Care for Agitation in Alzheimer’ Dementia: Results from a Randomized Controlled Trial of an Integrated Care Pathway versus Usual Care ‐The StaN trial

2024· article· en· W4406030218 on OpenAlexaff
Sanjeev Kumar, Amer M. Burhan, Li Chu, Sarah Colman, Simon Davies, Peter Derkach, Sarah Elmi, Philip Gerretsen, Ariel Graff‐Guerrero, Maria Hussain, Zahinoor Ismail, Donna Kim, Linda Krisman, Clement Ma, Rola Moghabghab, Benoit H. Mulsant, Vasavan Nair, Bruce G. Pollock, Soham Rej, Aviva Rostas, David L. Streiner, Lisa Van Bussel, Tarek K. Rajji

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsOntario Shores Centre for Mental Health SciencesHotchkiss Brain InstituteMcGill UniversityUniversity of CalgaryMcMaster UniversityQueen's UniversityWest Park Healthcare CentrePublic Health OntarioToronto Dementia Research AllianceWestern UniversityUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsPolypharmacyDementiaRandomized controlled trialPsychomotor agitationMedicineRandomizationClinical endpointQuality of life (healthcare)Physical therapyPsychiatryInternal medicineDisease

Abstract

fetched live from OpenAlex

Abstract Background Adherence to treatment guidelines for agitation in dementia is suboptimal and inconsistent. We designed an Integrated Care Pathway (ICP) that standardized behavioral and pharmacological interventions for agitation in dementia, and evaluated it against treatment‐as‐usual (TAU). The two primary hypotheses were that, compared to TAU, the ICP would result in (1) lower agitation and (2) lower rates of polypharmacy at study end. Method The Standardizing Care for Neuropsychiatric Symptoms and Quality of Life in Dementia (StaN) trial (ClinicalTrials.gov # NCT03672201) was conducted at five academically affiliated inpatient units (Inpatient) and seven long‐term‐care homes (LTCHs). Participants with agitation related to Alzheimer’s dementia were randomized 1:1 to receive the ICP or TAU for 12 weeks. Primary outcomes were: (1) Cohen Mansfield Agitation Inventory (CMAI) completed at weeks 3, 8, and 12 (primary), and (2) polypharmacy defined as using more than one psychotropic medication assessed at weeks 1, 3, 4, 6, 8, 10, and 12 (primary) post‐randomization. Linear mixed effect models and generalized estimating equations were used to test our hypotheses controlling for age, gender, and stage of dementia. The study was powered for Inpatient and LTCH settings separately. Result 185 participants were randomized: 93 in Inpatient (46 ICP: 47 TAU; females = 32 (34.4%); mean (standard deviation [SD]) age = 75.0 (8.4) years), and 92 in LTCH (46 ICP: 46 TAU; women = 63 (68.5%); mean (SD) age = 85.9 (7.6) years). There were no significant time*group interactions for the CMAI scores for Inpatient (F4, 297.9 = 0.8, p = 0.53) or LTCH (F4, 297.3 = 1.1, p = 0.36) and no significant differences at week‐12 (Inpatient: ICP‐TAU adjusted difference = 0.025; 95% Confidence Interval (CI): ‐0.410, 0.460; LTCH: ICP‐TAU adjusted difference = ‐0.214; 95%CI: ‐0.699, 0.270). However, there were significant time*group interactions for polypharmacy for both Inpatient (χ27 = 18.6, p = 0.01) and LTCH (Χ27 = 22.9, p = 0.002). Differences were not significant at week‐12 (Inpatient: ICP‐TAU adjusted difference = 0.15; 95%CI: ‐0.11, 0.40; LTCH: ICP‐TAU adjusted difference = 0.33; 95%CI: ‐0.06, 0.72), the ICP group had lower rates of polypharmacy than TAU group at weeks 3, 4, and 6 on Inpatient, and week 3 in LTCH. Conclusion Standardizing care for agitation in dementia may result in less polypharmacy without affecting efficacy. Future studies should assess the ICP in broader community and outpatient settings.

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 imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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.

Opus teacher head0.038
GPT teacher head0.352
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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