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Record W4406224870 · doi:10.1002/alz.088510

Drug Substitution as a Potential Unintended Consequence of Antipsychotic Deprescribing in Long‐Term Care: A Retrospective Cohort Study in Ontario, Canada

2024· article· en· W4406224870 on OpenAlexaffabout
Julia Kirkham, Daniel A. Harris, Paul Nguyen, Susan E. Bronskill, Colleen J. Maxwell, Andrea Iaboni, Dallas Seitz

Bibliographic record

VenueAlzheimer s & Dementia · 2024
Typearticle
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsToronto Rehabilitation InstituteUniversity of WaterlooUniversity of TorontoUniversity Health NetworkQueen's UniversityUniversity of Calgary
Fundersnot available
KeywordsDeprescribingDrugAntipsychoticRetrospective cohort studyMedicineAntipsychotic drugPolypharmacyCohortLong-term carePsychiatryPharmacologyInternal medicineSchizophrenia (object-oriented programming)

Abstract

fetched live from OpenAlex

Abstract Background The overuse of antipsychotics in persons with dementia in long‐term care (LTC) has been a source of clinical concern, public attention, and policy intervention for over 30 years. Targeted quality improvement, broader awareness of risks, and other initiatives have resulted in substantial reductions in antipsychotic use in LTC settings in North America and elsewhere. Limited evidence suggests that reductions in antipsychotic use may be resulting in unintended consequences, such as substitution with alternate, but similarly harmful, psychotropic medications. Methods We used a retrospective, matched cohort study design using linked population‐based health care databases held at ICES. LTC residents 66 years or older with dementia who were prescribed an inappropriate (i.e., without an indication aligning with the definition of appropriate antipsychotic use in LTC, including schizophrenia, Huntington’s disorder, hallucinations, delusions, or end‐of‐life care) antipsychotic medication with at least 6‐months of continuous use were identified over a 10‐year period (2008‐18). Antipsychotic users who subsequently discontinued an antipsychotic medication were matched 1:1 to persistent users on key variables and followed for up to 1‐year following antipsychotic discontinuation for new prescriptions of one or more psychotropic medications and clinical outcomes. Results Among 26,092 LTC residents with dementia (mean age of 84 years) who were prescribed an inappropriate antipsychotic medication, 5,854 (22%) discontinued during the follow‐up period. After adjusting for key variables, new psychotropic medication prescription was not more common among antipsychotic discontinuers in the 6‐months following antipsychotic discontinuation compared to those who continued an antipsychotic medication (hazard ratio (HR) 0.90; 95% CI, 0.70‐1.15). Mortality was similar between the two groups (HR 1.01; 95% CI 0.90‐1.15) at up to 1‐year following antipsychotic discontinuation. Conclusion Antipsychotic discontinuation in this study was not associated with medication substitution. These results supports other studies indicating that antipsychotic discontinuation in dementia can be safe but has questionable effect on mortality. While medication use trends in LTC have shown increases in other psychotropic medication use alongside antipsychotic reductions, this study suggests that this may be driven by factors other than substitution, such as increasing complexity of LTC residents, including higher prevalence of mental health disorders other than dementia.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.174

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.006
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.318
Teacher spread0.294 · 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 designObservational
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 routes2
Has abstractyes

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