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Record W4281488378 · doi:10.3389/fneur.2022.799723

Clinical Practice Guidelines for the Management of Behavioral and Psychological Symptoms of Dementia: A Systematic Review With AGREE II

2022· review· en· W4281488378 on OpenAlexaboutno aff
Huixuan Ma, Xinliang Lu, Aihong Zhou, Fen Wang, Xiumei Zuo, Minmin Zhan, Qi Zou, Shuting Gong, Yufei Chen, Jihui Lyu, Longfei Jia, Jianping Jia, Cuibai Wei

Bibliographic record

VenueFrontiers in Neurology · 2022
Typereview
Languageen
FieldMedicine
TopicClinical practice guidelines implementation
Canadian institutionsnot available
FundersBeijing Municipal Administration of HospitalsBeijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support
KeywordsMedicineNiceCLARITYDementiaClinical PracticeScope (computer science)Systematic reviewMEDLINEFamily medicineDiseasePathology

Abstract

fetched live from OpenAlex

Background: High-quality clinical practice guidelines (CPGs) are important for the effective treatment of behavioral and psychological symptoms of dementia (BPSD). However, recommendations provided by different quality guidelines may lead to varied clinical practice outcomes. Objective: To assess the quality of available CPGs for the management of BPSD and summarize the best recommendations for treating BPSD. Methods: This was a systematic review of CPGs for the management of BPSD with data obtained from electronic databases and evaluated using the Appraisal of Guidelines for Research and Evaluation II instrument, consisting of six domains: "Scope and purpose", "Stakeholder involvement", "Rigor of development", "Clarity of presentation", "Applicability", and "Editorial independence". The criteria for high-quality guidelines were set as: the score of high-quality guidelines in the "Rigor of development" domain should be ≥60% and as well as a score of >60% in at least three other domains. High-quality guidelines were selected for recommendation extraction, and the final recommendations were formed in combination with the latest meta-analysis and randomized clinical-trial results. Results: In term of median scores in each domain for the six included CPGs, "Scope and purpose" (87.5%) scored better than all others, whereas "Applicability" (46.5%) was the domain with the lowest score. Four CPGs (2015 APA, 2018 NICE, 2018 CANADA, 2020 EAN) met the criteria of high-quality guidelines and were used to extract recommendations. From these four CPGs, nine specific recommendations related to the management of BPSD were summarized, of which seven were related to pharmacological treatment and two to non-pharmacological treatment. These recommendations covered the applicability of antipsychotic drugs, medication recommendations, withdrawal times, and several suitable non-pharmacological therapies. Conclusion: The quality of CPGs for the management of BPSD requires improvement, especially for the "Applicability" domain. For psychotic-like symptoms in dementia, the use of antipsychotics should be based on the individual's risk-benefit ratio, and the use of atypical antipsychotics seems to be a better choice. Non-pharmacological treatments may be suitable for emotional symptoms and sleep disorders. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42020209204.

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)0.091
metaresearch head score (Gemma)0.264
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.091
Threshold uncertainty score0.483

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0910.264
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0120.019
Bibliometrics0.0260.019
Science and technology studies0.0020.002
Scholarly communication0.0050.006
Open science0.0050.005
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.419
GPT teacher head0.577
Teacher spread0.158 · 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 designSystematic review
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

Citations44
Published2022
Admission routes1
Has abstractyes

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