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Left Ventricular Geometric Patterns After 1 Year of Antihypertensive Treatment

2005· article· en· W1996859776 on OpenAlexaff
Manuel Luque‐Ramírez, Nieves Martell, Isabel Egocheaga, Carmen Fernandez‐Pinilla, José Luis Zamorano, Carlos Almerı́a, Arturo Fernández‐Cruz, Carlos M. Ferrario

Bibliographic record

VenueJournal of Clinical Hypertension · 2005
Typearticle
Languageen
FieldMedicine
TopicBlood Pressure and Hypertension Studies
Canadian institutionsHypertension Canada
Fundersnot available
KeywordsMedicineLeft ventricular hypertrophyCardiologyInternal medicineBlood pressureMyocardial infarctionGeometric patternVentricular remodelingMuscle hypertrophyStroke (engine)Mass indexBody mass indexVentricular hypertrophyEssential hypertension

Abstract

fetched live from OpenAlex

Left ventricular hypertrophy increases the risk for cardiovascular target organ damage, myocardial infarction, and stroke. The authors assessed the patterns of ventricular adaptation in 107 essential hypertensives whose treatment had been withdrawn and its modification after 1 year of hypertension treatment. Blood pressure decreased from 158+/-17/96+/-12 mm Hg to 137+/-15/83+/-10 mm Hg (mean +/- SD; p<0.001); 45% of the patients (49 of 107) had their blood pressure controlled below 140 mm Hg and 90 mm Hg. Although a significant decrease of left ventricular mass index was found in the study, the percentage of patients with normal left ventricular geometry at the completion of the study increased by only 9% (27% to 36%, p>0.05). Left ventricular mass geometry improved in 31% of the patients, remained unaffected in 51%, and worsened in 18%. The data suggest that even while suboptimal antihypertensive treatment reduces left ventricular mass index, either left ventricular hypertrophy or concentric remodeling remains present in a significant number of patients at the end of a 1-year treatment period. The authors conclude that these patients should be considered as a subgroup at high risk and should be treated more aggressively.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.134
Threshold uncertainty score0.528

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.075
GPT teacher head0.355
Teacher spread0.280 · 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.

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

Citations3
Published2005
Admission routes1
Has abstractyes

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