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Record W3112929373 · doi:10.1002/alz.042014

Angiotensin receptor blockers versus angiotensin‐converting enzyme inhibitors: Longitudinal associations with PET amyloid in the Alzheimer's Disease Neuroimaging Initiative

2020· article· en· W3112929373 on OpenAlexaff
Michael Ouk, Che‐Yuan Wu, Jennifer S. Rabin, Jodi D. Edwards, Joel Ramirez, Mario Masellis, Richard H. Swartz, Nathan Herrmann, Krista L. Lanctôt, Sandra E. Black, Walter Swardfager

Bibliographic record

VenueAlzheimer s & Dementia · 2020
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsToronto Rehabilitation InstituteSunnybrook Health Science CentreHeart and Stroke FoundationUniversity of OttawaHealth Sciences CentreSunnybrook HospitalUniversity of Toronto
Fundersnot available
KeywordsPrecuneusInternal medicineMedicineNeuroimagingAlzheimer's diseaseAngiotensin-converting enzymeCognitive declineAlzheimer's Disease Neuroimaging InitiativeDiseaseCognitionCardiologyPsychologyOncologyNeuroscienceDementiaPsychiatry

Abstract

fetched live from OpenAlex

Abstract Background Evidence suggests that Angiotensin II type‐1 Receptor Blockers (ARBs) and Angiotensin‐Converting Enzyme Inhibitors (ACE‐Is) may be differentially beneficial for cognition, but there is little clinical evidence supporting possible mechanisms. This study examines longitudinal associations between the use of ARBs and ACE‐Is with summary cortical and subregional brain amyloid‐β (Aβ). Method This study included participants with hypertension who were using an ACE‐I or ARB with available PET data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) 1, GO, and 2 databases (years 2010‐2018). Analyses were conducted in subgroups with normal cognition (NC) and with cognitive impairment (amnestic mild cognitive impairment or Alzheimer’s disease [AD/MCI]). The outcome was PET Aβ SUVR in a cortical summary region and subregions involved in early/late stages of Aβ accumulation. Linear mixed‐effects models with inverse probability of treatment weighting were used to compare rates of Aβ accumulation over 48 months between ARB and ACE‐I users. Models were adjusted for demographics, ApoE ε4 status, baseline MMSE, relevant comorbidities, and other concurrent antihypertensive use. Result In the NC group (n=124, age=74.8±5.6, 46.3% women), ARB vs. ACE‐I use was associated with a slower rate of Aβ accumulation in the cortex (β=‐0.138 [‐0.062, ‐0.223]), the inferior temporal lobe (β=‐0.165 [‐0.076, ‐0.255]), and precuneus (β=‐0.164 [‐0.075, ‐0.252]). In people with AD/MCI (n=246, age=74.5±7.3, 39.1% women), users of an ARB vs. an ACE‐I did not differ in the rate of Aβ accumulation in the cortex (β=0.019 [‐0.038, 0.075]), in the above regions (inferior temporal lobe β=‐0.027 [‐0.102, 0.048]; precuneus β=0.008 [‐0.051, 0.067]), or in areas associated with later Aβ accumulation (parietal lobes β=0.035 [‐0.027, 0.097]; frontal lobes β=0.014 [‐0.053, 0.081]). Conclusion In cognitively‐normal adults, ARB use was associated with a significantly slower rate of Aβ accumulation. This difference may be partially explained by preservation of Aβ‐clearing effects of the angiotensin‐converting enzyme by ARBs. In contrast, there were no significant differences in AD/MCI which could reflect both plateau effects, less impact on more advanced stages, or a relatively small sample size. Prospective analyses and clinical trial evidence are warranted to confirm the potential benefit of ARB use to slow Aβ accumulation and prevent cognitive impairment.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.071
GPT teacher head0.284
Teacher spread0.213 · 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 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
Published2020
Admission routes1
Has abstractyes

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