{
  "abstract": "Purpose: To prospectively investigate the association between patent foramen ovale (PFO), detected via agitated saline contrast echocardiography (ASCE), and anxiety using a deep learning approach.\n\nMaterials and methods: This prospective study consecutively enrolled 161 participants between July 15, 2025 and October 31, 2025. Participants were stratified into ASCE-negative (n=58) and ASCE-positive (n=103) groups based on the examination results. All participants underwent ASCE and anxiety assessment using the Self-Rating Anxiety Scale (SAS). An artificial intelligence model was developed using a 10-fold cross-validation approach on the 103 ASCE-positive videos to predict anxiety scores. The primary endpoint was the association between PFO and anxiety, while the deep learning model was evaluated as a secondary/exploratory endpoint. Statistical analyses, including logistic regression, were performed with statistical significance set at p<0.05.\n\nResults: Compared to the ASCE-negative group, the ASCE-positive group exhibited significantly higher anxiety levels (SAS score: 45.0 vs. 38.0, p<0.001) and a higher prevalence of anxiety (32.0% vs. 5.2%, p<0.001). Logistic regression identified a strong association between ASCE-positive status and anxiety (adjusted odds ratio=8.64, p<0.001), with no clear dose-dependent relationship across shunt grades. The imaging-only deep learning model achieved a mean absolute error (MAE) of 5.76 ± 0.12 and an R² of 0.46 ± 0.03 across cross-validation folds. After incorporating clinical and sociodemographic confounders, the model’s performance improved to an MAE of 5.15 ± 0.10 and an R² of 0.59 ± 0.02.\n\nConclusion: This prospective study confirms a significant association between PFO and anxiety and demonstrates the feasibility of using ASCE-based deep learning models to predict anxiety risk, although clinical application requires external validation.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Cardiology, Dongguan People’s Hospital (The Tenth Affiliated Hospital of Southern Medical University) , ,",
    "School of Electronic Information and Artificial Intelligence, Shaanxi University of Science & Technology , ,",
    "Department of Neurology, Dongguan People’s Hospital (The Tenth Affiliated Hospital of Southern Medical University) , ,",
    "Department of Cardiovascular and Neurology, Dongguan Xiegang Hospital , ,",
    "Department of Cardiology, Puji Campus of Dongguan People’s Hospital , ,",
    "Division of Cardiology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong , ,",
    "Department of Thoracic Surgery, Dongguan People’s Hospital (The Tenth Affiliated Hospital of Southern Medical University) , ,",
    "Faculty of Electrical Engineering and Computer Science, Ningbo University , ,"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 22,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Minqi Liao"
    },
    {
      "affs": [
        1
      ],
      "name": "Changji Yang"
    },
    {
      "affs": [
        1
      ],
      "name": "Chengyu Hong"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiaoyu Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Zheng Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Shumin Ouyang"
    },
    {
      "affs": [
        1
      ],
      "name": "Xuande Zhang"
    },
    {
      "affs": [
        2
      ],
      "name": "Hanyu Weng"
    },
    {
      "affs": [
        0
      ],
      "name": "Ziying Cao"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhihao Wu"
    },
    {
      "affs": [
        0
      ],
      "name": "Jiahua Ye"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhichao Huang"
    },
    {
      "affs": [
        0
      ],
      "name": "Yanhua Yang"
    },
    {
      "affs": [
        0
      ],
      "name": "Kangmin Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Patience Ratidzo Ngombengombe"
    },
    {
      "affs": [
        3
      ],
      "name": "Jiongbin Lu"
    },
    {
      "affs": [
        3
      ],
      "name": "Zekui Wu"
    },
    {
      "affs": [
        4
      ],
      "name": "Zhanyang Wei"
    },
    {
      "affs": [
        5
      ],
      "name": "Mark T. K. Tam"
    },
    {
      "affs": [
        6
      ],
      "name": "Jianping Zhou"
    },
    {
      "affs": [
        7
      ],
      "name": "Xin Huang"
    },
    {
      "affs": [
        0
      ],
      "name": "Suxia Guo"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/c9yv0k3rwahaj.bib",
  "cited_by": 0,
  "doi": "10.3389/fpsyt.2026.1877855",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13661545/?tool=EBI",
  "id": "c9yv0k3rwahaj",
  "issns": [
    "1664-0640"
  ],
  "landing_url": "https://europepmc.org/article/PMC/PMC13661545",
  "language": "eng",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
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      "2740|Cardiovascular and Diving-Related Complications"
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  "openalex": "W7214954906",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13661545/pdf/?tool=EBI",
  "pmcid": "PMC13661545",
  "pmid": null,
  "published": "2026-09-30",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/c9yv0k3rwahaj.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:17:20Z",
      "native_id": "PMC:PMC13661545",
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      "first_seen": "2026-10-30T12:20:18Z",
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      "url": "https://www.frontiersin.org/articles/10.3389/fpsyt.2026.1877855/full"
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  "subjects": [
    {
      "field": "medicine",
      "origin": "issn:1664-0640",
      "subfield": "psychiatry"
    }
  ],
  "title": "Association between patent foramen ovale and anxiety: a prospective study with deep learning-assisted analysis of contrast echocardiography",
  "title_text": "Association between patent foramen ovale and anxiety: a prospective study with deep learning-assisted analysis of contrast echocardiography",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:20:18Z",
  "url": "https://research.draconitic.com/paper/c9yv0k3rwahaj",
  "venue": "Frontiers in psychiatry",
  "versions": []
}