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Record W4403823659 · doi:10.1093/eurpub/ckae144.1951

BE-SAFE: Intervention to reduce benzodiazepine and sedative hypnotics in elderly with sleep problems

2024· article· en· W4403823659 on OpenAlexaffabout
Vagioula Tsoutsi, Carole E. Aubert, Laura Fernandez Maldonado, Adam Wichniak, Thomas Agoritsas, E Callegari, Jean Macq, Dimitris Dikeos, Nicolas Rodondi, Anne Spinewine

Bibliographic record

VenueEuropean Journal of Public Health · 2024
Typearticle
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsMcMaster UniversityImpact
Fundersnot available
KeywordsBenzodiazepineSedativeSleep (system call)MedicineSedative/hypnoticIntervention (counseling)PsychiatryInternal medicineComputer science

Abstract

fetched live from OpenAlex

Abstract Introduction Benzodiazepine and sedative hypnotics (BSH) may have significant adverse effects and associated costs, especially in older adults: increased risk of falls, fractures, hospitalisations, impaired functioning, delirium, cognitive impairment and mortality. Addressing BSH overuse is therefore an urgent priority to improve patient safety in Europe. Objectives To present the 5-year research project BE-SAFE, funded by the European Commission (HORIZON Europe) and by the Swiss State Secretariat for Education, Research, and Innovation. BE-SAFE aims to improve patient safety by addressing knowledge and practice gaps related to the reduction of BSH used by older adults for sleep problems. Methods BE-SAFE involves seven inter-related work packages and six European countries (Belgium, Greece, Norway, Poland, Spain and Switzerland) as well as experts from Canada; it proposes an interdisciplinary and inter-sectorial approach with experts in guidelines, implementation, dissemination, case studies, geriatrics and sleep. BE-SAFE will develop an intervention comprising trustworthy clinical guidelines, implementation recommendations and patient-centred material. This intervention will be tested in a cluster randomized controlled trial; 470 patients (65 years old and above) and 62 prescribing physicians in hospital and outpatient settings. Results BE-SAFE is expected to result in reduction of BSH use. Its toolkit, encompassing setting-specific implementation recommendations, will enable healthcare professionals (HCPs) to identify, evaluate and prevent risks of BSH use. The BE-SAFE approach could also be expanded to cover reduction of use of other medications. Conclusions Through BE-SAFE, patient safety is expected to improve; BE-SAFE project will reach a wide-ranging audience, including general population, informal carers, older adults, HCPs, healthcare system leaders and decision makers. Authors acknowledge the significant input of J. Grimshaw and W. Levinson, Canada. Key messages • Deprescription of benzodiazepine and sedative hypnotics, especially in older adults, is a priority due to their side effects, particularly in this age group. • The European project BE-SAFE aspires to create easy-to-use guidelines to this aim, improving thus patient safety and healthcare.

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)0.003
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: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.054
GPT teacher head0.337
Teacher spread0.283 · 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 designNon-randomized 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 routes2
Has abstractyes

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