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Record W4415453766 · doi:10.1210/jendso/bvaf149.1570

SAT-088 Mental Health In Acromegaly: Insights From A North American Survey Of Individuals Living With Acromegaly.

2025· article· en· W4415453766 on OpenAlexaboutno aff
Lori Bulpett, Catherine Jonas, Jason A. Crompton, Rebecca Epstein, Christina Bott

Bibliographic record

VenueJournal of the Endocrine Society · 2025
Typearticle
Languageen
FieldMedicine
TopicPituitary Gland Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsMental healthAcromegalyAnxietyEmbarrassmentDepression (economics)Population

Abstract

fetched live from OpenAlex

Abstract Disclosure: L. Bulpett: Chiesi Global Rare Diseases. C. Jonas: Chiesi Global Rare Diseases. J. Crompton: Chiesi Global Rare Diseases. R.A. Epstein: Chiesi Global Rare Diseases. C. Bott: Chiesi Global Rare Diseases.. Introduction: Acromegaly is a rare endocrine disorder characterized by distinct physical changes and multiple comorbidities that may progress over time. While physical manifestations are well documented, mental health impacts remain underexplored. A survey-based approach was used to characterize the mental health challenges experienced by individuals living with acromegaly and identify potential support opportunities. Methods: An anonymous 15-question online survey in English and French was disseminated by 3 acromegaly patient advocacy groups in the US and Canada. Eligible respondents included adults (≥18 years) with a self-reported diagnosis of acromegaly. Questions addressed mental health symptoms, including frequency and impact across the acromegaly journey, and current and preferred sources of mental health support. Results: 261 of 358 individuals living with acromegaly responding were eligible and participated in the survey. Most respondents were white (87%), female (82%), and between the age of 46-60 years old (43%). The most constant or frequently reported mental health symptoms included cognitive fatigue (64%), chronic stress (59%), anxiety (59%), low self-esteem (56%), embarrassment (43%), and depression (43%). Self-esteem/body image, sleep/rest, and sexual relationships were the areas of life that mental health challenges had a major or severe impact in the majority of respondents. The diagnostic period was the most mentally challenging stage for individuals living with acromegaly, with 49% of individuals rating their mental health as poor or very poor. However, during post-treatment monitoring and management, only 30% of individuals rated their mental health as good or excellent. 78% of individuals living with acromegaly view mental health as a significant concern, and 91% believe that mental health is equally as important to address in acromegaly care as physical health. Over half of all respondents were not currently receiving mental health support, primarily due to a preference for self-management or a belief that providers may not understand their experience with rare disease. Among individuals who were receiving mental health support, most were self-motivated to do so, and care was often provided by professionals without rare disease expertise. Respondents expressed interest in in-person or virtual counselling and peer-support groups, particularly to improve self-esteem, body image, and overall enjoyment of life. Conclusions: These results add to the growing body of evidence that mental health challenges in individuals living with acromegaly are prevalent but often unaddressed, leading to negative impacts on the quality of life. Access to rare disease-informed mental health support remains an unmet need. Further research on proactive referral to mental health resources and adequate coverage and reimbursement of this support are warranted. Presentation: Saturday, July 12, 2025

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)0.000
metaresearch head score (Gemma)0.000
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 score0.004
Threshold uncertainty score0.894

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.010
GPT teacher head0.284
Teacher spread0.274 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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