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Record W3216099710 · doi:10.1111/jch.14391

Impact of mean blood pressure and blood pressure variability after diagnosis of mild cognitive impairment and risk of dementia

2021· article· en· W3216099710 on OpenAlexaboutno aff
Adam de Havenon, Varsha Muddasani, Mohammad Anadani, Shyam Prabhakaran

Bibliographic record

VenueJournal of Clinical Hypertension · 2021
Typearticle
Languageen
FieldMedicine
TopicDementia and Cognitive Impairment Research
Canadian institutionsnot available
FundersNational Center for Advancing Translational SciencesNational Institute of Neurological Disorders and Stroke
KeywordsDementiaMedicineBlood pressureQuartileHazard ratioInternal medicineCardiologyConfidence intervalDisease

Abstract

fetched live from OpenAlex

Hypertension and increased blood pressure variability (BPV) are associated with the development of dementia. However, previous studies did not focus on the risk of dementia among participants with mild cognitive impairment (MCI) and controlled blood pressure level. To address this limitation, the authors performed a post-hoc analysis of SPRINT MIND participants diagnosed with MCI (mean Montreal Cognitive Assessment score at diagnosis 16.1±3.1). The primary outcome was subsequent diagnosis of probable dementia. The exposure was mean blood pressure and BPV following MCI diagnosis until the end of follow-up or a dementia event (mean follow-up 2.6±1.2 years). The primary outcome occurred in 76/516 (14.7%) patients. The mean blood pressure was not significantly higher in participants who developed dementia. In the lowest quartile of BPV (systolic standard deviation), the rate of dementia was 8.5% (11/129), while in the highest quartile it was 21.7% (28/129). The highest quartile of systolic BPV had an adjusted hazard ratio for dementia of 2.73 (95% CI, 1.31-5.69) and for diastolic BPV it was 2.62 (95% CI, 1.26-5.47). In SPRINT MIND participants, the authors found that increased BPV after MCI diagnosis was associated with incident probable dementia during subsequent follow-up.

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)0.003
metaresearch head score (Gemma)0.004
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 score0.050
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.033
GPT teacher head0.364
Teacher spread0.331 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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