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register herePostpartum hemorrhage (PPH) is the primary cause of maternal mortality globally, with uterine atony being the predominant contributing factor. However, accurate prediction of PPH in the general population remains challenging due to a lack of reliable biomarkers.Using retrospective cohort data, we quantified 48 cytokines in plasma samples from 40 women diagnosed with PPH caused by uterine atony.

在此登记产后出血（PPH）是全球孕产妇死亡的主要原因，子宫收缩乏力是主要因素。然而，由于缺乏可靠的生物标志物，准确预测普通人群中的PPH仍然具有挑战性。使用回顾性队列数据，我们量化了40名被诊断患有子宫收缩乏力引起的PPH的女性血浆样本中的48种细胞因子。

We also analyzed previously reported hemogram and coagulation parameters related to inflammatory response. The least absolute shrinkage and selection operator (LASSO) and logistic regression were applied to develop predictive models. Established models were further evaluated and temporally validated in a prospective cohort.Fourteen factors showed significant differences between the two groups, among which IL2Rα, IL9, MIP1β, TNFβ, CTACK, prenatal Hb, Lymph%, PLR, and LnSII were selected by LASSO to construct predictive model A.

我们还分析了先前报道的与炎症反应相关的血象和凝血参数。应用最小绝对收缩和选择算子（LASSO）和逻辑回归来开发预测模型。建立的模型在前瞻性队列中进行了进一步评估和时间验证。14个因素显示两组之间存在显着差异，其中通过LASSO选择IL2Rα，IL9，MIP1β，TNFβ，CTACK，产前Hb，淋巴结%，PLR和LnSII来构建预测模型A。

Further, by logistic regression, model B was constructed using prenatal Hb, PLR, IL2Rα, and IL9. The area under the curve (AUC) values of model A in the training set, internal validation set, and temporal validation set were 0.846 (0.757-0.934), 0.846 (0.749-0.930), and 0.875 (0.789-0.961), respectively.

此外，通过逻辑回归，使用产前Hb，PLR，IL2Rα和IL9构建模型B。模型A在训练集，内部验证集和时间验证集中的曲线下面积（AUC）值分别为0.846（0.757-0.934），0.846（0.749-0.930）和0.875（0.789-0.961）。

And the corresponding AUC values for model 3 / 40 B were 0.805 (0.709-0.901), 0.805 (0.701-0.894), and 0.901 (0.824-0.979). Decision curve analysis results showed that both nomograms had a high net benefit for predicting atonic PPH.We identified novel biomarkers and developed predictive models for atonic PPH in women undergoing 'low-risk' vaginal delivery, providing immunological insights for further exploration of the mechanism underlying uterine atonic PPH..

模型3/40 B的相应AUC值分别为0.805（0.709-0.901），0.805（0.701-0.894）和0.901（0.824-0.979）。决策曲线分析结果表明，这两个列线图对于预测无张力PPH具有很高的净效益。我们确定了新的生物标志物，并开发了接受“低风险”阴道分娩的女性无张力PPH的预测模型，为进一步探索子宫无张力PPH的潜在机制提供了免疫学见解。。