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Record W2085175594 · doi:10.1097/hjh.0000000000000021

Pathophysiology of hypertension

2013· article· en· W2085175594 on OpenAlexaff
Alexandra Yannoutsos, Bernard Lévy, Jacques Blacher

Bibliographic record

VenueJournal of Hypertension · 2013
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsHotel Dieu Hospital
Fundersnot available
KeywordsMedicineArterial stiffnessPathophysiologyMicrocirculationEndothelial dysfunctionCardiologyPulse wave velocityVasodilationInternal medicineBlood pressurePathology

Abstract

fetched live from OpenAlex

Hypertension is a multifactorial systemic chronic disorder through functional and structural macrovascular and microvascular alterations. Macrovascular alterations are featured by arterial stiffening, disturbed wave reflection and altered central to peripheral pulse pressure amplification. Microvascular alterations, including altered wall-to-lumen ratio of larger arterioles, vasomotor tone abnormalities and network rarefaction, lead to disturbed tissue perfusion and susceptibility to ischemia. Central arterial stiffness and microvascular alterations are common denominators of organ damages. Vascular alterations are intercorrelated, amplifying the haemodynamic load and causing further damage in the arterial network. A plausible precursor role of vascular alterations in incident hypertension provides new insights for preventive and therapeutic strategies targeting macro and microvasculature. Cumulative metabolic burden and oxidative stress lead to chronic endothelial injury, promoting structural and functional vascular alterations, especially in the microvascular network. Pathophysiology of hypertension may then be revisited, based on both macrovascular and microvascular alterations, with a precursor role of endothelial dysfunction for the latter.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.030
GPT teacher head0.235
Teacher spread0.205 · 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

Citations119
Published2013
Admission routes1
Has abstractyes

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