{
  "abstract": "Objective: To develop and internally evaluate a model that uses maternal blood markers obtained before delivery to differentiate neonatal acute respiratory distress syndrome (ARDS) from other causes of respiratory distress in late-preterm and term neonates requiring mechanical ventilation.\n\nMethods: This retrospective study enrolled 227 mother-infant pairs from two tertiary hospitals between June 2024 and January 2026. Neonates born at 34–40 weeks’ gestation with ventilation-dependent respiratory distress were divided into a training cohort and an internal test cohort. Predictors were screened using elastic-net regression with 1,000 bootstrap resamples. Four feature sets and six algorithms were then compared by 20 repeats of stratified five-fold cross-validation, and a six-predictor random forest (RF) was ultimately selected. Discrimination, calibration and net benefit were assessed, with 500-resample bootstrap optimism correction and Shapley additive explanation (SHAP) interpretation.\n\nResults: Maternal systemic immune-inflammation index (SII) and related inflammatory ratios were higher, and antenatal infection was more frequent, in the ARDS group, whereas recorded antenatal corticosteroid (ACS) use was less frequent (P < 0.001). Six predictors were retained in the final model: SII, antenatal infection, maternal age, gestational hypothyroidism, gestational diabetes mellitus and ACS use. The principal internal performance estimate, the mean training-set cross-validated area under the curve (AUC) was 0.729 ± 0.080, the fixed-pipeline optimism-corrected AUC was 0.793 and the internal test-set AUC was 0.827 (95% CI, 0.712–0.923), with an average precision of 0.828 and a Brier score of 0.175. These three values are not interchangeable and are reported as one principal and two secondary estimates, and none represents fully independent performance. At the training-derived threshold of 0.424, sensitivity was 78.8% and specificity 77.8%. SHAP identified SII as the largest contributor, without implying a causal effect for any predictor. Logistic regression using the same six predictors reached a numerically higher internal test-set AUC (0.838 versus 0.827, ΔAUC = −0.011, P = 0.744) and a cross-validated AUC of 0.706 ± 0.082 versus 0.729 ± 0.080, the RF therefore conferred no discriminative advantage.\n\nConclusions: In mechanical ventilation needed neonates born at 34–40 weeks' gestation with respiratory distress, the six-predictor RF showed moderate discrimination, whereas evidence of adequate calibration was limited. The model remains preliminary and requires external validation, recalibration and prospective clinical-impact evaluation before clinical use.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Pediatric, Peking University Third Hospital",
    "First Clinical Medical College of Shanxi Medical University",
    "Department of Neonatal Intensive Care, First Hospital of Shanxi Medical University",
    "Department of Pediatrics, Shanxi Medical University",
    "Department of Neonatal Intensive Care, Shanxi Children's Hospital (Maternal and Child Health Hospital & Obstetrics and Gynecology Hospital)"
  ],
  "article_type": "research article",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Chao Zhang"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Hui Jing"
    },
    {
      "affs": [
        3,
        4
      ],
      "name": "Dekai Xu"
    },
    {
      "affs": [
        1
      ],
      "name": "Zhixing Gao"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Kangjin Diao"
    },
    {
      "affs": [
        1,
        2
      ],
      "name": "Xinmiao Yang"
    },
    {
      "affs": [
        4
      ],
      "name": "Yong Ji"
    },
    {
      "affs": [
        2
      ],
      "name": "Huaiqing Yin"
    },
    {
      "affs": [
        0
      ],
      "name": "Tongyan Han"
    },
    {
      "affs": [
        2
      ],
      "name": "Shirun Wu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/9cxfb96tfnhdr.bib",
  "cited_by": 0,
  "doi": "10.3389/fimmu.2026.1889452",
  "fulltext_url": "https://europepmc.org/articles/PMC13680245",
  "id": "9cxfb96tfnhdr",
  "issns": [
    "1664-3224"
  ],
  "landing_url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889452/full",
  "language": "eng",
  "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,
  "native_subjects": [
    [
      "openalex",
      "2740|Neonatal Respiratory Health Research"
    ]
  ],
  "openalex": "W7220682628",
  "pdf_url": "https://europepmc.org/articles/PMC13680245?pdf=render",
  "pmcid": "PMC13680245",
  "pmid": "42903227",
  "published": "2026-10-06",
  "publisher": "Frontiers Media SA",
  "ris": "https://research.draconitic.com/paper/9cxfb96tfnhdr.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:19:15Z",
      "native_id": "10.3389/fimmu.2026.1889452",
      "source": "crossref",
      "url": "https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889452/full"
    },
    {
      "first_seen": "2026-10-30T12:19:57Z",
      "native_id": "MED:42903227",
      "source": "europepmc",
      "url": "https://europepmc.org/article/MED/42903227"
    }
  ],
  "subjects": [
    {
      "field": "biology",
      "origin": "issn:1664-3224",
      "subfield": "immunology"
    }
  ],
  "title": "A predictive model based on maternal immune-inflammatory markers for ARDS identification in mechanically ventilated late-preterm and term neonates",
  "title_text": "A predictive model based on maternal immune-inflammatory markers for ARDS identification in mechanically ventilated late-preterm and term neonates",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:19:57Z",
  "url": "https://research.draconitic.com/paper/9cxfb96tfnhdr",
  "venue": "Frontiers in Immunology",
  "versions": []
}