{
  "abstract": "Routine laboratory measurements may capture nutritional, inflammatory, and organ-function vulnerability in patients with gastrointestinal cancer. We developed nested logistic regression models using INSPIRE v1.4.2 and evaluated a portable model in MIMIC-IV v3.1. The original INSPIRE cohort comprised 11,471 operations among 10,728 patients, with 893 deaths within 365 days. Patients were allocated to development and held-out test sets. For 365-day mortality, area under the receiver operating characteristic curve (AUROC) was 0.783 (95% CI 0.752-0.811) for clinical variables, 0.843 (95% CI 0.820-0.868) after adding laboratory variables, and 0.856 (95% CI 0.834-0.879) for the full perioperative model. Patient-level full-pipeline bootstrap analysis yielded an optimism-corrected AUROC of 0.837. External AUROC was 0.676 (95% CI 0.663-0.688) for 365-day mortality and 0.724 (95% CI 0.692-0.754) for recorded hospital death after harmonizing CRP units. Calibration drift was substantial, and hospital-death discrimination was sensitive to laboratory timing. Corrected operation-linked risk tertiles showed graded mortality and lower albumin and hemoglobin levels in higher-risk groups. Perioperative nutrition-related laboratory profiles provided additional discrimination for 365-day mortality beyond clinical variables, although limited external performance and calibration drift warrant further validation before clinical use.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Gastroenterology, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University , ,",
    "Department of Intensive Care Unit, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University , ,",
    "Department of Gastrointestinal Surgery, The Affiliated Huaian No. 1 People’s Hospital of Nanjing Medical University , ,"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 7,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Menghui Zhang"
    },
    {
      "affs": [
        1
      ],
      "name": "Liangliang Hui"
    },
    {
      "affs": [
        0
      ],
      "name": "Jialing Zhang"
    },
    {
      "affs": [
        0
      ],
      "name": "Chengran Wang"
    },
    {
      "affs": [
        0
      ],
      "name": "Fan Xu"
    },
    {
      "affs": [
        2
      ],
      "name": "Guoquan Tao"
    },
    {
      "affs": [
        0
      ],
      "name": "Honggang Wang"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/dv07tm2f4tp3f.bib",
  "cited_by": 0,
  "doi": "10.3389/fnut.2026.1927720",
  "fulltext_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13716669/?tool=EBI",
  "id": "dv07tm2f4tp3f",
  "issns": [
    "2296-861X"
  ],
  "landing_url": "https://europepmc.org/article/PMC/PMC13716669",
  "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": [
    [
      "heading",
      "Original Research"
    ],
    [
      "openalex",
      "2730|Inflammatory Biomarkers in Disease Prognosis"
    ]
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  "openalex": "W7222018101",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13716669/pdf/?tool=EBI",
  "pmcid": "PMC13716669",
  "pmid": "42959099",
  "published": "2026-10-15",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/dv07tm2f4tp3f.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T00:20:37Z",
      "native_id": "PMC:PMC13716669",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13716669"
    },
    {
      "first_seen": "2026-10-31T12:21:46Z",
      "native_id": "MED:42959099",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42959099"
    },
    {
      "first_seen": "2026-11-01T12:23:55Z",
      "native_id": "PMC13716669",
      "source": "pmc",
      "url": "https://doi.org/10.3389/fnut.2026.1927720"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2730|Inflammatory Biomarkers in Disease Prognosis",
      "subfield": "oncology"
    }
  ],
  "title": "Perioperative nutrition-related laboratory profiles predict outcomes after digestive procedures in patients with gastrointestinal cancer",
  "title_text": "Perioperative nutrition-related laboratory profiles predict outcomes after digestive procedures in patients with gastrointestinal cancer",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T12:21:09Z",
  "url": "https://research.draconitic.com/paper/dv07tm2f4tp3f",
  "venue": "Frontiers in nutrition",
  "versions": []
}