Evidence map›Paper›PMID 40955061›Full record

ArticleCNS neuroscience & therapeutics2025

Metabolic Factors Related to Interpersonal Dysfunction in Acromegaly: A Nationwide Cross-Sectional Study in China.

Shashi Kiran Tagilapalli, Zongming Wang, Yuechu Lucinda Lu, Guofeng Zhang, Weijie Su, Zhentian Wu, Jiaming Wang, Qing Rao, Haijun Wang, Dongsheng He and 4 more

Abstract read
In one paragraph

Article in CNS neuroscience & therapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors.

Shashi Kiran TagilapalliCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID 0009-0006-1728-1795
Zongming WangDepartment of Neurosurgery, the Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Yuechu Lucinda LuMorrissey College of Arts and Sciences, Boston College, Boston, Massachusetts, USA.
Guofeng ZhangCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Weijie SuCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Zhentian WuDepartment of Statistics, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, China.
Jiaming WangCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Qing RaoZhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Haijun WangDepartment of Neurosurgery, the Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Dongsheng HeCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Yonggao MouDepartment of Neurosurgery, Sun Yat-Sen University Cancer Center, Guangzhou, China.
Shun YaoCenter for Pituitary Tumor Surgery, Department of Neurosurgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.ORCID 0000-0003-1727-4078
Yanmei TieDepartment of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
Wenli ChenDepartment of Neurosurgery, the Sixth Affiliated Hospital, Sun Yat-Sen University, Guangzhou, Guangdong, China.

Funding

Basic and Applied Basic Research Foundation of Guangdong Province 2024A1515011697Guangdong Medical Association Clinical Research Special Fund 2024HY-A6003Guangdong Province Key Technologies R&D 2023B0303020002National Natural Science Foundation of China 82203179
6 · The paper itself

Abstract

objectiveTo identify the clinical manifestations, metabolic factors, and comorbidities independently associated with interpersonal dysfunction in Chinese acromegaly patients.

methodsWe analyzed clinical, cognitive, and comorbidity data from 585 acromegaly patients across 112 tertiary hospitals in China (July 1995-December 2018). Interpersonal difficulties were quantified using the Inventory of Interpersonal Problems-Distress (IIP-D) and dichotomized into low (< 17) and high (≥ 17) groups. Group differences were tested with nonparametric tests. Supervised machine-learning models were developed to predict features associated with the high IIP-D group, with performance evaluated via five-fold cross-validation. The top-performing model was further validated on the held-out data set and the feature importance analysis identified the key predictors. Exploratory hierarchical clustering (Ward's method) was used to explore symptom groupings, though sampling adequacy was limited.

resultsPatients with high interpersonal distress exhibited significantly higher preoperative growth hormone (GH), frontal bossing, palpitations, and cognitive impairment (all p < 0.05). Among machine-learning models, extreme gradient boosting (XGBoost) demonstrated the highest performance, area under the curve (AUC = 0.868 in across-validation), and maintained strong accuracy in final testing (AUC = 0.873). Key independent predictors included frontal bossing, palpitations, cardiomyopathy, disease duration, preoperative GH, acral enlargement, arrhythmia, and atrial fibrillation.

conclusionPhysical disfigurement, palpitations, cardiac comorbidities, and elevated GH levels independently predict high IIP-D in acromegaly. Integrating systematic psychosocial screening into neuroendocrine care, alongside referral to psychoneuroendocrine teams, may help mitigate social disability and improve quality of life.

Indexed as

AcromegalyInterpersonal RelationsAdultAgedChinaComorbidityCross-Sectional StudiesFemaleHumansMachine LearningMaleMiddle Agedacromegalycardiovascular dysfunctionhigh growth hormone levelsinterpersonal problemsquality of life

Identifiers

PMID40955061
PMCPMC12436684

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.