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Abstract 4370902: Sex Differences in Latent Profiles of Hypertension-Mediated Organ Damage: A UK Biobank Analysis

2025· article· en· W4415793495 on OpenAlexaff
Adriana Angarita Fonseca, Abhinav Sharma, Colin Berry, Amanpreet Kaur, Thomas A. Mavrakanas, Hassan Behlouli, Natasha Rajah, Louise Pilote

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Health and Risk Factors
Canadian institutionsToronto Metropolitan UniversityMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsArterial stiffnessBiobankSex characteristicsHyperintensityNeurocognitiveBrain sizeYoung adult

Abstract

fetched live from OpenAlex

Background: Hypertension-mediated organ damage (HMOD) can develop concurrently in the heart, the brain, the kidneys and the vasculature, yet most research still relies on counting the number of affected systems or recording the presence versus absence of multi-organ damage, approaches that overlook the complex, multisystem nature of HMOD. Objective: To identify HMOD profiles in adults with hypertension and to quantify sex-specific differences. Methods: We analyzed 4,787 UK Biobank participants with physician-diagnosed or self-reported hypertension (mean ± SD age 57.4 ± 6.8 years; 41.6 % women). Twenty-two continuous indicators, assessed at baseline or first follow-up and spanning cardiac structure and function, vascular stiffness, brain integrity (white-matter hyperintensity volume and fractional anisotropy), and renal function, were log-transformed and entered into latent profile analysis (LPA). Sex differences in profile membership were subsequently examined. Results: A four-profile solution (entropy = 0.86) best balanced statistical fit with clinical interpretability. The largest profile, comprising 38.0% participants, showed modest arterial stiffness and mild concentric left-ventricular remodeling with largely preserved cerebral and renal integrity; males were more common in this group (17% females vs 53.2% males, p < 0.001). A second profile (37.6%) was marked by heightened autonomic tone, micro-albuminuria and subtle micro-structural brain changes without overt cardiac dysfunction (65.4% females vs 17.6% males, p < 0.001). The third profile (22.1 %) combined QRS prolongation, elevated cystatin-C and albumin-creatinine ratio, and a higher burden of white-matter hyperintensities, indicating a cardio-neuro-renal stress pattern (15.3% females vs 27.1% males, p < 0.001). The smallest profile (2.2 %) exhibited pronounced ventricular dilatation, reduced ejection fraction, rapid ventricular rate and marked QRS widening, consistent with cardiac overload and dysfunction; (2.4 % females vs 2.0% males). Conclusion: LPA identifies four biologically coherent HMOD profiles. Most males fall into a mild vascular–cardiac strain profile, underscoring the need for optimized blood pressure control and arterial stiffness monitoring. Most females cluster in an autonomic–renal–cerebral stress profile with preserved cardiac function, indicating that early renal and neurovascular surveillance should be prioritized for them even when conventional cardiac indices appear normal.

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)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.002
Research integrity0.0000.000
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 head0.027
GPT teacher head0.268
Teacher spread0.241 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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