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AGT AND AT1R GENE POLYMORPHISM IN HYPERTENSIVE HEART DISEASE

2002· article· en· W2441831827 on OpenAlexaff
Marco Mettimano, V. Romano-Spica, A. Ianni, Maria Lucia Specchia, Alessio Migneco, L Savi

Bibliographic record

VenueInternational Journal of Clinical Practice · 2002
Typearticle
Languageen
FieldMedicine
TopicRenin-Angiotensin System Studies
Canadian institutionsHypertension Canada
Fundersnot available
KeywordsMedicineLeft ventricular hypertrophyInternal medicineGenotypeAlleleMuscle hypertrophyRenin–angiotensin systemPolymorphism (computer science)PathophysiologyEssential hypertensionAngiotensin IICardiologyGeneReceptorEndocrinologyGeneticsBlood pressureBiology

Abstract

fetched live from OpenAlex

Left ventricular hypertrophy in patients with hypertension is a main clinical prognostic entity The aim of this study was to evaluate the association between mutations at genes of the renin-angiotensin system (RAS) and the development of left ventricular hypertrophy. Genetic polymorphism in angiotensinogen (AGT) and angiotensin Il-type 1 receptor (AT1R) genes was examined in a group of well-selected essential hypertensive caucasians with left ventricular involvement (n = 40) and a group of healthy unrelated caucasians (n = 150). Cardiac morphology and function were assessed by M-mode echocardiography. Molecular variants were analysed by amplified fragment length polymorphism. We observed a statistically significant difference both for AGT and AT1R genotype distribution in patients with left ventricular hypertrophy compared with controls (p<0.05). A 0.49 and 0.225 frequency was detected among cases for T and C mutant alleles at AGT and AT1R genes. Mutations in RAS genes are involved in the pathophysiology of target-organ damage in essential hypertension. Evaluation of molecular factors conferring a risk of developing heart involvement may lead to better identification of patient subgroups and more effective control of the clinical course.

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)0.001
metaresearch head score (Gemma)0.024
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.200
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.114
GPT teacher head0.442
Teacher spread0.327 · 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.

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

Citations17
Published2002
Admission routes1
Has abstractyes

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