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Record W4406957472 · doi:10.1093/ehjci/jeae333.269

Left atrial stiffness and its association to left ventricular geometry in resistance trained athletes using anabolic-androgenic steroids

2025· article· en· W4406957472 on OpenAlexaff
Florence Place, Hillary M. Carpenter, Lyn Howard, J. D. Maxwell, J K K Shardey, B Morrison, N Chester, Robert Cooper, Ben N. Stansfield, Keith George, Peter Angell, David Oxborough

Bibliographic record

VenueEuropean Heart Journal - Cardiovascular Imaging · 2025
Typearticle
Languageen
FieldMedicine
TopicCardiovascular Effects of Exercise
Canadian institutionsTrinity Western University
Fundersnot available
KeywordsAnabolic-Androgenic SteroidsInternal medicineAnabolismMedicineCardiologyAthletesEndocrinologyPhysical therapy

Abstract

fetched live from OpenAlex

Abstract Background Anabolic-Androgenic Steroids (AAS) are commonly used in resistance trained (RT) individuals despite the negative impact on left ventricular (LV) structure and function. Purpose Due to the inter-dependence of the left atrium (LA) and the LV, alongside the importance of the atria contributing to LV filling and cardiac output, this study aimed to assess the relationship between LV geometry and LA stiffness in young RT users of AAS. Methods Utilising a cross-sectional design, male (n=99) and female (n=19) RT individuals aged 29±6yrs were grouped based on self-reported AAS user status: current (CU; n=70), past (PU; n=22) and non-users (NU; n=27). All participants underwent transthoracic echocardiography with strain imaging. Left ventricular geometry was defined based on LV mass index and relative wall thickness as per European Association of Cardiovascular Imaging guidelines. Left atrial stiffness index (LASi) was calculated as the ratio of E/E’ to LA reservoir strain (LARes) and concentricity as the ratio of LV mass to end-diastolic volume^0.67. Ejection Fraction (EF) was calculated using Simpsons biplane method. All data was presented as mean ± standard deviation with group differences assessed using a one-way ANOVA with post-hoc Bonferroni adjustment and Kruskal-Wallis test for non-normally distributed indices. A Fishers exact test was used to compare geometry between groups. Relationships between LASi and concentricity were assessed using multi linear regression Results Current users presented greater LV remodelling compared to PU and NU (eccentric hypertrophy (45%, 9% and 0%), concentric remodelling (2%, 0% and 0%) and concentric hypertrophy (8%, 0% and 0% respectively; p<0.001). EF was lower in those with concentric (52±9, p=.006) and eccentric (53±5, p<.001) hypertrophy than with normal geometry (58±5), but no difference between concentric and eccentric hypertrophy. LARes was lower in CU (32.0±7.5) compared to PU (39.1±8.3, p=.001) and NU (40.2±7.7, p<.001). E/E’ and LASi were higher in CU than PU (p=.006, p=.001) and NU (p<.001, p<.001; E/E’: 6.7±1.8, 5.9±1.5, and 5.7±1.4; LA stiffness index: 0.21±0.08, 0.16±0.05, and 0.15±0.05). Concentricity was higher in CU than PU (p<.001) and NU (p<.001; 8.3±2.2; 6.4±1.4 and 5.7±2.2 respectively). Controlling for user status, concentricity predicted LASi (R²=0.23, F(2,109)=16.1, p<.001) with a 0.1 increase in LASi for each 10g.ml^-0.667 increase in concentricity. Conclusions Although current users of AAS presented with more eccentric hypertrophy, those with increased concentricity and concentric hypertrophy had higher LA stiffness index. These data highlight 1) the potential greater negative functional impact of concentric compared to eccentric hypertrophy in young RT individuals using AAS, 2) the added value of LASi above conventional indices such as EF and 3) the possible reversible nature of LV and LA remodelling following cessation of AAS use.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.282
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
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 head0.014
GPT teacher head0.275
Teacher spread0.261 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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