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Record W2040079480 · doi:10.1586/ern.09.89

Prevention of dementia by antihypertensive drugs: how AT1-receptor-blockers and dihydropyridines better prevent dementia in hypertensive patients than thiazides and ACE-inhibitors

2009· review· en· W2040079480 on OpenAlexaff
Albert Fournier, Roxana Oprisiu-Fournier, Jean‐Marie Sérot, Olivier Godefroy, Jean‐Michel Achard, Sébastien Faure, Hakim Mazouz, M. Temmar, Adriana Albu, Régis Bordet, Olivier Hanon, François Gueyffier, Ji‐Guang Wang, Sandra E. Black, Naoyuki Sato

Bibliographic record

VenueExpert Review of Neurotherapeutics · 2009
Typereview
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsSunnybrook Health Science Centre
Fundersnot available
KeywordsDementiaMedicineCognitive declineStroke (engine)PharmacologyInternal medicineAlzheimer's diseaseDisease

Abstract

fetched live from OpenAlex

Our review of cohort studies and clinical trials evaluating antihypertensive drugs in the prevention of cognition decline and all dementia in patients with hypertension indicates that two antihypertensive drug classes have greater protective effects, independent of blood pressure decrease: dihydropyridine calcium-channel blockers as shown in the Syst-Eur trial and angiotensin-AT1 receptor blockers as found in the MOSES and ONTARGET trials. By contrast, diuretics and angiotensin-converting enzyme-inhibitors (ACEIs) prevent dementia only in patients with a stroke history, provided they are combined, and prevent stroke recurrence. A Japanese cohort study and a small trial in patients already suffering from Alzheimer's disease (AD) suggest, however, that the BBB-penetrating ACEI may slow down cognitive decline. Only cohort studies support the hypothesis that diuretics, (especially potassium-sparing diuretics), may decrease the risk of AD. beta-blockers worsen cognition decline, or are neutral, according to whether or not they cross the BBB. Centrally-acting sympatholytic agent have a negative impact on cognition as BBB-penetrating beta-blockers, probably by blunting the adrenergic pathways. The AD protective effect of DHP appears related to the blockade of neuronal calcium channels. The ambiguous effect of ACEI on cognitive decline and dementia prevention may be explained by the fact that brain ACE is not specific for angiotensin-I. Brain ACE also catabolizes cognition-enhancing brain peptides, amyloid peptides and converts toxic Abeta(42) into less toxic Abeta(40). Therefore, ACEIs may have short-term cognition-enhancing properties and may increase in the long term Abeta(42) brain burden and cognitive decline. The clinical relevance of this scenario, mainly observed in animals, cannot be excluded in man, since the ACE gene has been associated with AD via the human whole genome analysis. To support the hypothesized deleterious effect of ACEI on human AD, confirmation that the ACE gene polymorphism DD is associated with protection against AD is necessary, since this polymorphism increases ACE activity. Independently of their preventive impact on beta-amyloid degenerative neuropathological process by overexpressing insulin degrading enzyme which catabolyses amyloid, the angiotensin AT1-receptor-blockers may have greater cognition protective effects than ACEI (observed in the ONTARGET trial), as they share with ACEI cognition-enhancing effects directly linked with a common AT1-blunting effect. In addition, they increase angiotensin II and IV formation and therefore stimulate non-opposed AT2 and AT4 receptors, whose activation in cognitive processes is well established.

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)0.007
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0030.002
Science and technology studies0.0000.001
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.002
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 head0.031
GPT teacher head0.322
Teacher spread0.292 · 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 designNot applicable
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

Citations127
Published2009
Admission routes1
Has abstractyes

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