{
  "abstract": "BackgroundTo develop and conditionally evaluate a multimodal prediction model incorporating a static baseline CT digital-twin framework for documented 1-year asthma exacerbation risk.MethodsThis retrospective single-center study analyzed 505 adults with asthma. Baseline three-dimensional CT reconstruction supplied quantitative features; the static baseline CT digital-twin framework did not simulate physiology or update dynamically. A LASSO-selected 10-variable logistic score was evaluated using nested domain comparisons, calibration, Brier score, and 1,000 bootstrap refits conditional on the selected predictor set. An available-variable clinical comparator was evaluated with and without CT features.ResultsSeventy-two patients (14.3%) had a documented exacerbation. The final score had apparent AUC 0.880 (conditional bootstrap 95% CI, 0.836–0.917) and Brier score 0.086. Fixed-predictor bootstrap correction yielded AUC 0.856, calibration slope 0.875, intercept −0.182, and Brier score 0.094, without accounting for the original variable-selection step. CT increased AUC from 0.880 to 0.894 in the fully nested comparison (likelihood-ratio P = 0.070), and from 0.725 to 0.774 in the available-variable comparator (P < 0.001). These were apparent, exploratory comparisons, not external validation.ConclusionThe multimodal score showed conditional internal performance, with a modest CT increment in the fully nested comparison and a larger apparent increment in the restricted available-variable comparator. The CT contribution remains exploratory and comparator-dependent. External validation, full selection-aware validation, quantitative CT repeatability assessment, and prospective impact evaluation are required before clinical use.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Geriatric and Special Needs Medicine Integrated Ward, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China",
    "Department of Pulmonary and Critical Care Medicine, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China",
    "Department of Pulmonary and Critical Care Medicine, Wuzhong People's Hospital, Wuzhong, Ningxia, China",
    "Department of Radiology, General Hospital of Ningxia Medical University, Yinchuan, Ningxia, China",
    "Department of Clinical Medicine, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China",
    "Department of Medical Sciences, Medical Laboratory of Innovation and Education Co., Ltd., Changsha, Hunan, China"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 13,
  "authors": [
    {
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        0
      ],
      "name": "Mei Xie"
    },
    {
      "affs": [
        0
      ],
      "name": "Xiaofei Jin"
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    {
      "affs": [
        1
      ],
      "name": "Shaojin Wang"
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    {
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        2
      ],
      "name": "Hanchi Yu"
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    {
      "affs": [
        3
      ],
      "name": "Jindong Cheng"
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    {
      "affs": [
        1
      ],
      "name": "Shuni Wang"
    },
    {
      "affs": [
        1
      ],
      "name": "Yating Zhang"
    },
    {
      "affs": [
        1
      ],
      "name": "Xiaotong Guo"
    },
    {
      "affs": [
        1
      ],
      "name": "Jinxia Li"
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    {
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        0
      ],
      "name": "Hui Li"
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    {
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        4
      ],
      "name": "Hongyi Wang"
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    {
      "affs": [
        5
      ],
      "name": "Hongyi Wang"
    },
    {
      "affs": [
        1
      ],
      "name": "Xiaoyan Yang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/4c3ef4961efjn.bib",
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  "doi": "10.3389/fdgth.2026.1935315",
  "fulltext_url": "https://www.frontiersin.org/articles/10.3389/fdgth.2026.1935315/full",
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  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
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  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
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  "pdf_url": "https://www.frontiersin.org/journals/digital-health/articles/10.3389/fdgth.2026.1935315/pdf",
  "pmcid": null,
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  "published": "2026-10-26",
  "publisher": "Frontiers Media S.A.",
  "ris": "https://research.draconitic.com/paper/4c3ef4961efjn.ris",
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  "title": "Multimodal prediction of documented 1-year asthma exacerbation risk incorporating a static baseline CT digital-twin framework: a retrospective cohort study",
  "title_text": "Multimodal prediction of documented 1-year asthma exacerbation risk incorporating a static baseline CT digital-twin framework: a retrospective cohort study",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:47:29Z",
  "url": "https://research.draconitic.com/paper/4c3ef4961efjn",
  "venue": "Frontiers in Digital Health",
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