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Multicenter Study
. 2025 Oct 7;30(1):931.
doi: 10.1186/s40001-025-03223-w.

An early predictive model for acute respiratory distress-syndrome related to pancreatitis in pregnancy: an 8-year multicenter analysis

Yu Wang  1 , Shu Zhou  2 , JinJin Zhang  1 , LiuRong Zhang  3 , Qi Yang  4 , YiDi He  4 , GengYun Sun  5
Affiliations
Multicenter Study

An early predictive model for acute respiratory distress-syndrome related to pancreatitis in pregnancy: an 8-year multicenter analysis

Yu Wang et al. Eur J Med Res. .

Abstract

Background: Acute respiratory distress syndrome (ARDS) related to acute pancreatitis in pregnancy (APIP) is associated with a higher risk of maternal and fetal death. This study aimed to explore early predictors and develop a predictive model for ARDS associated with APIP aligned with the updated global ARDS definition.

Methods: The APIP data of two hospitals over an 8-year period were retrospectively collected. The variables were analyzed using Least Absolute Shrinkage and Selection Operator regression, and binary logistic regression to build a predictive model, visualized with a nomogram. The performance of the predictive model was then evaluated.

Results: Of 6597 patients with acute pancreatitis, 103 pregnant patients were included, and 24 pregnant patients had ARDS. Lower oxygen saturation as measured by pulse oximetry to fraction of inspired oxygen (SpO2/FiO2) ratio, elevated heart rate (HR), and total cholesterol (TCH) were identified as independent risk factors for ARDS in APIP. Compared to previous scoring systems, the predictive model was more discriminating between APIP and ARDS, with an area under the receiver operating characteristic curve of 0.926 (95% CI 0.864-0.988). Notably, the new model performed best when the prediction cutoff was set at 0.205 (sensitivity = 0.823, specificity = 0.958). Calibration and decision curve analyses confirmed the strong clinical utility and accurate risk prediction.

Conclusion: A new accurate utility predictive model for ARDS related to APIP, including three simple variables (HR, TCH, and SpO2/FiO2), was constructed at admission. Elevated total cholesterol level was first identified as an independent risk factor for ARDS in patients with APIP.

Keywords: Acute pancreatitis in pregnancy; Acute respiratory distress-syndrome; Predictive model.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The present study was approved by the Ethics Committee of the First and the Second Affiliated Hospitals of Anhui Medical University (reference number PJ 2024–07-67 and YX2024-181). Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Nomogram of acute respiratory distress syndrome prediction model
Fig. 2
Fig. 2
The ROC curves in prediction of ARDS related to APIP. A ROC curves of present prediction model; B ROC curves of APACHE.II, Modified Marshall, Ranson, BISAP, SIRS and Nomogram
Fig. 3
Fig. 3
Gray zone analysis for prediction model. A ROC curve with gray zone annotation; B Predicted probability distribution with gray zone; C ARDS incidence rate by risk zone
Fig. 4
Fig. 4
Calibration curves and decision curve analysis of new predictive models. A Calibration curves of acute respiratory distress syndrome (ARDS) predictive model; B Decision curve analysis of acute respiratory distress syndrome (ARDS) predictive model
See this image and copyright information in PMC

References

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