MétaCan
Menu
Back to cohort
Record W2974964653 · doi:10.1177/1747493019871915

Special topic section: linkages among cerebrovascular, cardiovascular, and cognitive disorders: Preventing dementia by preventing stroke: The Berlin Manifesto

2019· article· en· W2974964653 on OpenAlexaff
Vladimir Hachinski, Karl M. Einhäupl, Detlev Ganten, Suvarna Alladi, Carol Brayne, Blossom C. M. Stephan, Melanie D. Sweeney, Berislav V. Zloković, Yasser Iturria‐Medina, Costantino Iadecola, Nozomi Nishimura, Chris B. Schaffer, Shawn N. Whitehead, Sandra E. Black, Leif Østergaard, Joanna M. Wardlaw, Steven M. Greenberg, Leif Friberg, Bo Norrving, Brian H. Rowe, Yves Joanette, Werner Hacke, Lewis H. Kuller, Martin Dichgans, Matthias Endres, Zaven S. Khachaturian

Bibliographic record

VenueInternational Journal of Stroke · 2019
Typearticle
Languageen
FieldNeuroscience
TopicNeurological Disease Mechanisms and Treatments
Canadian institutionsUniversity of AlbertaUniversity of TorontoHealth Sciences CentreMcGill UniversitySunnybrook Health Science CentreWestern University
FundersEngineering and Physical Sciences Research CouncilBritish Heart FoundationMedical Research CouncilNational Institute for Health and Care Research
KeywordsDementiaMedicineStroke (engine)Cerebral amyloid angiopathyVascular dementiaDiseasePopulationCognitive declineAtrial fibrillationNeurovascular bundleRisk factorIntensive care medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

The incidence of stroke and dementia are diverging across the world, rising for those in low-and middle-income countries and falling in those in high-income countries. This suggests that whatever factors cause these trends are potentially modifiable. At the population level, neurological disorders as a group account for the largest proportion of disability-adjusted life years globally (10%). Among neurological disorders, stroke (42%) and dementia (10%) dominate. Stroke and dementia confer risks for each other and share some of the same, largely modifiable, risk and protective factors. In principle, 90% of strokes and 35% of dementias have been estimated to be preventable. Because a stroke doubles the chance of developing dementia and stroke is more common than dementia, more than a third of dementias could be prevented by preventing stroke. Developments at the pathological, pathophysiological, and clinical level also point to new directions. Growing understanding of brain pathophysiology has unveiled the reciprocal interaction of cerebrovascular disease and neurodegeneration identifying new therapeutic targets to include protection of the endothelium, the blood-brain barrier, and other components of the neurovascular unit. In addition, targeting amyloid angiopathy aspects of inflammation and genetic manipulation hold new testable promise. In the meantime, accumulating evidence suggests that whole populations experiencing improved education, and lower vascular risk factor profiles (e.g., reduced prevalence of smoking) and vascular disease, including stroke, have better cognitive function and lower dementia rates. At the individual levels, trials have demonstrated that anticoagulation of atrial fibrillation can reduce the risk of dementia by 48% and that systolic blood pressure lower than 140 mmHg may be better for the brain. Based on these considerations, the World Stroke Organization has issued a proclamation, endorsed by all the major international organizations focused on global brain and cardiovascular health, calling for the joint prevention of stroke and dementia. This article summarizes the evidence for translation into action. © 2019 the Alzheimer's Association and the World Stroke Organisation. Published by Elsevier Inc. All rights reserved.

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)0.003
metaresearch head score (Gemma)0.006
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: Editorial
Teacher disagreement score0.039
Threshold uncertainty score0.130

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0030.001
Science and technology studies0.0010.001
Scholarly communication0.0050.003
Open science0.0030.002
Research integrity0.0110.006
Insufficient payload (model declined to judge)0.0390.019

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 head0.010
GPT teacher head0.235
Teacher spread0.225 · 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
GenreEditorial

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

Citations27
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of StrokeSame topicNeurological Disease Mechanisms and TreatmentsFrench-language works237,207