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Record W4415711891 · doi:10.1016/j.eclinm.2025.103595

Prescribing trends and time series analysis of blood pressure-lowering drugs among patients with dementia: a multinational database study

2025· article· en· W4415711891 on OpenAlexaff
Edmund Chi Lok Cheung, Yunzhang Wang, Lisa M. Kalisch Ellett, Matthew Adesuyan, Máté Szilcz, Sonia Shah, Nicole Pratt, Ruth Brauer, Yogini Jani, Robert Smith, Hao Luo, Jacqueline Kwan Yuk Yuen, Sara Hägg, Celine Sze Ling Chui

Bibliographic record

VenueEClinicalMedicine · 2025
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsUniversity of Waterloo
FundersInnovation and Technology Commission - Hong KongResearch Grants Council, University Grants CommitteePfizerMSD
KeywordsMultinational corporationInterrupted Time Series AnalysisMEDLINEInterrupted time seriesAlternative medicineResearch design

Abstract

fetched live from OpenAlex

Background: Hypertension is common among people living with dementia and blood pressure-lowering drug (BPLD) treatment in dementia patients may vary widely between individuals and countries/regions. This study aimed to describe and evaluate how prescribing trends of BPLD change before and after incident dementia diagnosis using electronic health record databases across four countries/regions. Methods: Electronic health records were collected from Hong Kong, United Kingdom, Sweden, and Australia for this study. Study dates were based on data availability from each database and ranged from January 1st, 2000 to December 31st, 2020. The target population were people diagnosed with dementia, with a prior diagnosis of hypertension and prescription of BPLD. Time series analysis, similar to interrupted time series, was conducted to evaluate the prescribing trends of BPLD three years before and after dementia diagnosis. The primary outcome of interest was the monthly proportion of patients prescribed with a BPLD. Findings: 31,873 patients from Hong Kong, 59,108 from the UK, 5034 from Sweden and 12,807 from Australia were included in this study. The mean age ranged from 78.3 years in Australia to 81.1 years in Hong Kong at time series entry. BPLD prescribing decreased in the three years before dementia diagnosis (negative pre-dementia slope) across all four databases. A significant immediate increase in antihypertensive prescribing was observed immediately after incident dementia diagnosis in Hong Kong (Estimate∗100: 4.66, 95% CI: 3.79-5.53), Sweden (Estimate∗100: 2.24, 95% CI: 1.60-2.88), and Australia (Estimate∗100: 1.58, 95% CI: 1.07-2.09), while there was no significant level change in the UK. BPLD prescribing declined in the three years after diagnosis for all databases. Interpretation: This is the largest multinational population-based study to date investigating prescribing trends of BPLD before and after dementia diagnosis. The time series analysis results suggested that there was increased vigilance of blood pressure control shortly after dementia diagnosis. Funding: This study was supported by the Hong Kong Research Grants Council General Research Fund, No. 17113720.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.084
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.016
GPT teacher head0.295
Teacher spread0.278 · 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 teacher head, 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
Published2025
Admission routes1
Has abstractyes

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