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Record W3035483123 · doi:10.1186/s12877-020-01607-7

Safety of pharmacologic interventions for neuropsychiatric symptoms in dementia: a systematic review and network meta-analysis

2020· review· en· W3035483123 on OpenAlexafffund
Jennifer Watt, Zahra Goodarzi, Areti Angeliki Veroniki, Vera Nincic, Paul A. Khan, Marco Ghassemi, Yuan Thompson, Yonda Lai, Victoria Treister, Andrea C. Tricco, Sharon E. Straus

Bibliographic record

VenueBMC Geriatrics · 2020
Typereview
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsInstitute for Work & HealthAlberta Children's HospitalUniversity of TorontoUniversity of CalgarySt. Michael's Hospital
FundersAlberta Health Services
KeywordsMedicineDementiaMeta-analysisPsychological interventionRehabilitationSystematic reviewPhysical medicine and rehabilitationPhysical therapyMEDLINEPsychiatryGerontologyDiseaseInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Prescribing trends suggest that pharmacologic alternatives to antipsychotics are gaining in popularity, but randomized trial (RCT) data of their comparative safety is scarce. Our objective was to describe the comparative safety of pharmacologic interventions for treating neuropsychiatric symptoms in dementia. METHODS: We searched MEDLINE, EMBASE, CENTRAL, CINAHL, and PsycINFO, from inception to May 28, 2019, for studies of pharmacologic interventions used to treat neuropsychiatric symptoms in dementia. Dementia care partners selected fracture risk as our primary outcome. Pairs of reviewers, working independently, conducted all study screening, data abstraction, and risk of bias appraisal. We conducted Bayesian random-effects network meta-analyses (NMAs) using data from RCTs to derive odds ratios (ORs). In secondary analyses, we conducted frequentist random-effects NMAs using data from RCTs and Bayesian three-level hierarchical random-effects NMAs incorporating data from RCTs and non-randomized studies. RESULTS: Our systematic review included 209 randomized and non-randomized studies (889,378 persons with dementia). In NMAs of data from randomized trials, there were no increased odds of fracture associated with any intervention in primary analyses; however, data were sparse. We found increased odds of cerebrovascular events associated with antipsychotics (odds ratio [OR] 2.12, 95% credible interval [CrI] 1.29 to 3.62; number needed to harm [NNH] = 99) and increased odds of falls associated with dextromethorphan-quinidine (OR 4.16, 95% CrI 1.47 to 14.22; NNH = 55) compared to placebo in persons with dementia. In a subgroup of persons with Alzheimer disease, antipsychotics were associated with increased odds of fracture compared to anticonvulsants (OR 54.1, 95% CrI 1.15 to 38,300; NNH = 18). In older persons (mean age ≥ 80 years) with dementia, anticonvulsants were associated with increased odds of death compared to placebo (OR 8.36, 95% CrI 1.17 to 203.4; NNH = 35) and antipsychotics were associated with increased odds of death compared to antidepressants (OR 5.28, 95% CrI 1.06 to 3.51; NNH = 47). CONCLUSION: Although antipsychotics were associated with greater harm than antidepressants and anticonvulsants in subgroups of persons with dementia, medications used in lieu of antipsychotics for treating neuropsychiatric symptoms in dementia, such as anticonvulsants and dextromethorphan-quinidine, were also associated with harm. Decision-making concerning treatments prescribed in lieu of antipsychotics should include potential harms. PROSPERO REGISTRATION: CRD42017050130.

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)0.033
metaresearch head score (Gemma)0.083
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.979
Threshold uncertainty score0.175

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.083
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0210.042
Bibliometrics0.0120.010
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0030.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.144
GPT teacher head0.428
Teacher spread0.285 · 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.

Study designMeta-analysis
Domainnot available
GenreReview

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

Citations59
Published2020
Admission routes2
Has abstractyes

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