{
  "abstract": "Suboptimal clinical response (SCR) after sleeve gastrectomy (SG) remains a major clinical challenge, yet reliable preoperative risk stratification is lacking. Therefore, we developed and externally validated an interpretable machine‐learning model for predicting SCR after SG using multicenter data from three tertiary hospitals in China. Overall, 1312 patients were included, comprising a derivation cohort (n = 1094) and two external validation cohorts (n = 84 and n = 134). SCR, defined as percentage of total weight loss < 25% at 1 year, occurred in 374 (34.2%), 34 (40.5%), and 45 (33.6%) patients, respectively. Among six machine‐learning algorithms, XGB achieved the best performance. The final model incorporated eight routinely available predictors. In internal validation, the model showed excellent discrimination, with an AUC of 0.821 (95% confidence interval [CI], 0.752–0.871), sensitivity of 0.803, and specificity of 0.714. External validation confirmed satisfactory discrimination (AUC 0.761; 95% CI, 0.688–0.823), good calibration, and clinical benefit. Notably, the XGB model significantly outperformed 10 clinicians across experience levels and remained superior in clinically challenging cases. SHAP analysis enhanced interpretability, with predictor importance ranked as BMI, age, fasting glucose, type 2 diabetes, vitamin B12, calcium, total cholesterol, and gamma‐glutamyl transferase. This interpretable XGB model may enable precise preoperative risk stratification and support personalized management for patients undergoing SG.",
  "abstract_shown": true,
  "affiliations": [
    "Department of General Surgery & Obesity and Metabolic Disease Center China‐Japan Friendship Hospital Beijing China",
    "School of Basic Medical Sciences Capital Medical University Beijing China",
    "Department of Education Beijing Luhe Hospital Capital Medical University Beijing China",
    "Department of General Surgery Cheeloo College of Medicine The Second Hospital of Shandong University, Shandong University Jinan Shandong China",
    "Department of General Surgery The Third Xiangya Hospital of Central South University Changsha Hunan China",
    "Department of Gastrointestinal Metabolic Surgery Zhengzhou Central Hospital, Zhengzhou University Zhengzhou Henan China",
    "Department of Gastrointestinal Surgery Jining No. 1 People's Hospital Jining Shandong China",
    "Department of Gastrointestinal Surgery The Second Affiliated Hospital of Wenzhou Medical University Wenzhou Zhejiang China",
    "Department of Endocrinology The Second Hospital of Hebei Medical University Shijiazhuang Hebei China",
    "Department of Oncology Sinopharm Tongmei General Hospital Datong Shanxi China",
    "National Cancer Center/National Clinical Research Center For Cancer/Cancer Hospital, Chinese Academy of Medical Science and Peking Union Medical College Beijing China"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 23,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Yuntao Nie",
      "orcid": "0000-0001-5430-7057"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "An Ping",
      "orcid": "0009-0006-4345-2834"
    },
    {
      "affs": [
        3
      ],
      "name": "Tianshi Wang"
    },
    {
      "affs": [
        4
      ],
      "name": "Haibo Tang"
    },
    {
      "affs": [
        0
      ],
      "name": "Yishan Huang"
    },
    {
      "affs": [
        0
      ],
      "name": "Zhe Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Pengpeng Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Siqi Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Genzheng Liu"
    },
    {
      "affs": [
        0
      ],
      "name": "Ximing Lin"
    },
    {
      "affs": [
        0
      ],
      "name": "Shuman Ran"
    },
    {
      "affs": [
        5
      ],
      "name": "Yan Liu"
    },
    {
      "affs": [
        6
      ],
      "name": "Ming Zhu"
    },
    {
      "affs": [
        7
      ],
      "name": "Jingwei Hu"
    },
    {
      "affs": [
        8
      ],
      "name": "Chunhui Li"
    },
    {
      "affs": [
        0
      ],
      "name": "Nianrong Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Baoyin Liu"
    },
    {
      "affs": [
        9
      ],
      "name": "Lei Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Biao Zhou"
    },
    {
      "affs": [
        10
      ],
      "name": "Ziru Tian"
    },
    {
      "affs": [
        4
      ],
      "name": "Shaihong Zhu"
    },
    {
      "affs": [
        3
      ],
      "name": "Yinlu Ding"
    },
    {
      "affs": [
        0
      ],
      "name": "Hua Meng",
      "orcid": "0000-0003-3286-9424"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/8f6cnf00hx79d.bib",
  "cited_by": 0,
  "doi": "10.1002/mco2.71110",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13732101/",
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  "landing_url": "https://doi.org/10.1002/mco2.71110",
  "language": "en",
  "licence": "CC-BY-4.0",
  "licence_label": "CC BY 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
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    [
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      "2746|Bariatric Surgery and Outcomes"
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  "pdf_url": "https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/mco2.71110",
  "pmcid": "PMC13732101",
  "pmid": "42985237",
  "published": "2026-11-03",
  "publisher": "Wiley",
  "ris": "https://research.draconitic.com/paper/8f6cnf00hx79d.ris",
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  "subjects": [
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  "title": "Development and Validation of an Interpretable Machine‐Learning Model for Predicting Suboptimal Clinical Response After Sleeve Gastrectomy: A Multicenter Study",
  "title_text": "Development and Validation of an Interpretable Machine‐Learning Model for Predicting Suboptimal Clinical Response After Sleeve Gastrectomy: A Multicenter Study",
  "type": "peer-reviewed",
  "updated_at": "2026-11-08T12:22:08Z",
  "url": "https://research.draconitic.com/paper/8f6cnf00hx79d",
  "venue": "MedComm",
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}