Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 52 min ago
Peer-reviewedCC BY 4.0Frontiers in Immunology

A predictive model based on maternal immune-inflammatory markers for ARDS identification in mechanically ventilated late-preterm and term neonates

  • Chao Zhang1
  • Hui Jing2,3
  • Dekai Xu4,5
  • Zhixing Gao2
  • Kangjin Diao2,3
  • Xinmiao Yang2,3
  • Yong Ji5
  • Huaiqing Yin3
  • Tongyan Han1
  • Shirun Wu3
5 affiliations
  1. 1Department of Pediatric, Peking University Third Hospital
  2. 2First Clinical Medical College of Shanxi Medical University
  3. 3Department of Neonatal Intensive Care, First Hospital of Shanxi Medical University
  4. 4Department of Pediatrics, Shanxi Medical University
  5. 5Department of Neonatal Intensive Care, Shanxi Children's Hospital (Maternal and Child Health Hospital & Obstetrics and Gynecology Hospital)
Read full textPDFDOICite

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.

Methods: 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.

Results: 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.

Conclusions: 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.

Related

  1. Reply-Letter to the editor. Nutritional Goals in Mechanically Ventilated Children: Impact of a Standardized Enteral Protocol in a Tertiary Pediatric Intensive Care Unit
    Arthur Gaudaire, Cyril Ceci, Héléna Huguet +7
    Clinical Nutrition ESPENPeer-reviewedCC BY 4.0Full textGeneral biologyEpidemiology & public healthHAL
  2. Nutritional Goals in Mechanically Ventilated Children: Impact of a Standardized Enteral Protocol in a Tertiary Pediatric Intensive Care Unit
    Cyril Ceci, Julien Baleine, Héléna Huguet +7
    Clinical Nutrition ESPENPeer-reviewedCC BY 4.0Full text2 citedGeneral biologyEpidemiology & public healthHAL
  3. Adverse events and associated factors during intra-hospital transport of mechanically ventilated intensive care patients
    Fabien Cambert, Gaëlle Sauvaget, Anne-Sylvie Scholastique +9
    Anaesthesia Critical Care & Pain MedicinePeer-reviewedCC BYFull textGeneral biologyHAL
  4. Standardized low-flow ventilation with PEEP maintenance during bronchoscopy in mechanically ventilated ICU patients: a pilot trial
    Jordan Uguet, Charles-Hervé Vacheron, Margot Bonnet +15
    Journal of Intensive CarePeer-reviewedCC BY-NC-NDGeneral biologyEpidemiology & public healthHAL
  5. Maternal Gait as a Potential Scaffold for Rhythm Processing: A Predictive Processing Network Model.
    Matin Yousefabadi, Jonathan Cannon
    Annals of the New York Academy of SciencesPeer-reviewedCC BY-NC-NDFull textNeuroscienceEurope PMC

Cite

BibTeXRIS
BibTeX
@article{zhang2026predictive,
  title = {{A predictive model based on maternal immune-inflammatory markers for ARDS identification in mechanically ventilated late-preterm and term neonates}},
  author = {Chao Zhang and Hui Jing and Dekai Xu and Zhixing Gao and Kangjin Diao and Xinmiao Yang and Yong Ji and Huaiqing Yin and Tongyan Han and Shirun Wu},
  journal = {Frontiers in Immunology},
  year = {2026},
  month = oct,
  doi = {10.3389/fimmu.2026.1889452},
  url = {https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889452/full},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - A predictive model based on maternal immune-inflammatory markers for ARDS identification in mechanically ventilated late-preterm and term neonates
AU  - Chao Zhang
AU  - Hui Jing
AU  - Dekai Xu
AU  - Zhixing Gao
AU  - Kangjin Diao
AU  - Xinmiao Yang
AU  - Yong Ji
AU  - Huaiqing Yin
AU  - Tongyan Han
AU  - Shirun Wu
PY  - 2026
DA  - 2026/10/06
JO  - Frontiers in Immunology
DO  - 10.3389/fimmu.2026.1889452
UR  - https://www.frontiersin.org/articles/10.3389/fimmu.2026.1889452/full
AB  - 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.  Methods: 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.  Results: 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.  Conclusions: 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.
SN  - 1664-3224
ER  -