Evidence map›Paper›PMID 39361379›Full record

ArticleInteractive journal of medical research2024

Analyzing Comorbidity Patterns in Patients With Thyroid Disease Using Large-Scale Electronic Medical Records: Network-Based Retrospective Observational Study.

Yanqun Huang, Siyuan Chen, Yongfeng Wang, Xiaohong Ou, Huanhuan Yan, Xin Gan, Zhixiao Wei

Abstract read
In one paragraph

Article in Interactive journal of medical research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yanqun HuangDepartment of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0001-8111-6352
Siyuan ChenDepartment of Nuclear Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0008-9898-2511
Yongfeng WangDepartment of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0007-1675-9598
Xiaohong OuDepartment of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0003-9310-6559
Huanhuan YanDepartment of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0005-4091-1858
Xin GanDepartment of Medical Equipment, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0009-0008-0215-2880
Zhixiao WeiDepartment of Nuclear Medicine, The First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China.ORCID https://orcid.org/0000-0003-3466-2902

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThyroid disease (TD) is a prominent endocrine disorder that raises global health concerns; however, its comorbidity patterns remain unclear.

objectiveThis study aims to apply a network-based method to comprehensively analyze the comorbidity patterns of TD using large-scale real-world health data.

methodsIn this retrospective observational study, we extracted the comorbidities of adult patients with TD from both private and public data sets. All comorbidities were identified using ICD-10 (International Classification of Diseases, 10th Revision) codes at the 3-digit level, and those with a prevalence greater than 2% were analyzed. Patients were categorized into several subgroups based on sex, age, and disease type. A phenotypic comorbidity network (PCN) was constructed, where comorbidities served as nodes and their significant correlations were represented as edges, encompassing all patients with TD and various subgroups. The associations and differences in comorbidities within the PCN of each subgroup were analyzed and compared. The PageRank algorithm was used to identify key comorbidities.

resultsThe final cohorts included 18,311 and 50,242 patients with TD in the private and public data sets, respectively. Patients with TD demonstrated complex comorbidity patterns, with coexistence relationships differing by sex, age, and type of TD. The number of comorbidities increased with age. The most prevalent TDs were nontoxic goiter, hypothyroidism, hyperthyroidism, and thyroid cancer, while hypertension, diabetes, and lipoprotein metabolism disorders had the highest prevalence and PageRank values among comorbidities. Males and patients with benign TD exhibited a greater number of comorbidities, increased disease diversity, and stronger comorbidity associations compared with females and patients with thyroid cancer.

conclusionsPatients with TD exhibited complex comorbidity patterns, particularly with cardiocerebrovascular diseases and diabetes. The associations among comorbidities varied across different TD subgroups. This study aims to enhance the understanding of comorbidity patterns in patients with TD and improve the integrated management of these individuals.

Indexed as

comorbidity patternselectronic medical recordsnetwork analysisprevalencethyroid disease

Identifiers

PMID39361379
PMCPMC11487213

What Socratic holds

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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 Socratic graph.