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目的基于腹腔压力(IAP)、电阻抗断层成像(EIT)参数构建重症肺炎机械通气(MV)患者撤机结局的列线图模型，并验证其预测价值。方法前瞻性纳入重症肺炎患者110例，均行有创MV。撤机后48h评估患者结局，收集患者撤机结局相关资料，通过自主呼吸试验(SBT)30min后撤机前测量IAP和EIT参数全肺非均质指数(GI)、可用通气面积(SAV)。采用单因素和多因素二元Logistic回归分析撤机成功的影响因素；基于影响因素构建列线图模型，并绘制受试者工作特性曲线(ROC)评估模型的预测能力，用Bootstrap自助抽样法(重复抽样2000次)进行内部验证，并绘制校准曲线评估模型的校准度，决策曲线分析评估模型的临床应用价值。结果110例患者撤机成功86例、撤机失败24例。IAP升高(OR=2.36，95% CI：1.19～5.00)、GI升高(OR=2.35，95% CI：1.19～5.18)是重症肺炎有创MV患者撤机失败的独立危险因素(P均<0.05)，SAV升高(OR=0.43，95% CI：0.21～0.81)是其独立保护因素(P<0.05)。基于以上影响因素构建列线图模型，绘制ROC曲线，SAV与GI合并作为基于EIT的联合预测方案1，IAP、SAV、GI、联合预测方案1、列线图模型预测撤机成功的曲线下面积(AUC)分别为0.812(95% CI：0.704～0.906)、0.743(95% CI：0.604～0.862)、0.794(95% CI：0.690～0.888)、0.848(95% CI：0.756～0.927)、0.876(95% CI：0.798～0.940)。内部验证结果显示，校正后列线图模型预测撤机成功的AUC为0.856，提示模型无明显过拟合。在模型校准度方面，Hosmer-Lemeshow检验显示，χ2=1.846，P=0.247(>0.05)，提示模型拟合程度良好。该模型Brier分数为0.121，曲线贴近理想线，模型无明显校准偏移，即模型预测的撤机成功概率能准确反映患者的真实撤机风险。临床决策曲线分析显示，当阈值概率为0.10～0.65时，该预测模型的净获益曲线位于无干预和全干预参考线之上，表明其具有良好的临床实用性。结论IAP升高、GI升高是重症肺炎有创MV患者撤机失败的独立危险因素，SAV升高是其独立保护因素；基于以上因素构建的列线图模型具有良好的区分度、校准度和临床实用价值。
Abstract：Objective：To construct a nomogram model for predicting weaning outcomes in patients with severe pneumonia receiving invasive mechanical ventilation (MV) based on intra-abdominal pressure (IAP) and electrical impedance tomography (EIT) parameters， and to verify its predictive performance.Methods：A total of 110 patients with severe pneumonia undergoing invasive MV were prospectively enrolled. Clinical data related to weaning outcomes were collected， and patient outcomes were assessed within 48 hours after extubation. IAP together with EIT parameters including global inhomogeneity index (GI) and sum of available ventilation (SAV) were measured 30 minutes before planned weaning after passing a spontaneous breathing trial (SBT). Univariate and multivariate binary Logistic regression analyses were performed to identify independent influencing factors for successful weaning. A nomogram was developed based on the screened predictors. The receiver operating characteristic (ROC) curve was plotted to evaluate the model’s discrimination ability. Bootstrap resampling with 2，000 iterations was adopted for internal validation. Calibration curves were drawn to assess model calibration， and decision curve analysis was conducted to evaluate clinical utility. Spearman’s rank correlation test was used to analyze correlations between variables.Results：Among the 110 enrolled patients， 86 achieved successful weaning and 24 experienced weaning failure. Elevated IAP OR=2.36，95% CI：1.19～5.00 and elevated GI OR=2.35，95% CI：1.19～5.18 were independent risk factors for weaning failure in patients with severe pneumonia on invasive MV (both P<0.05)， whereas increased SAV OR=0.43，95% CI：0.21～0.81 was an independent protective factor (P<0.05). A nomogram was established incorporating the above predictors. ROC curve analysis revealed the area under the curve (AUC) of IAP， SAV， GI， the combined EIT marker panel (SAV + GI， Panel 1)， and the nomogram for predicting weaning success were 0.812（95% CI：0.704～0.906），0.743（95% CI：0.604～0.862），0.794（95% CI：0.690～0.888），0.848（95% CI：0.756～0.927）， and 0.876（95% CI：0.798～0.940）， respectively. Internal validation yielded a bias-corrected AUC of 0.856 for the nomogram， indicating no obvious overfitting. The Hosmer-Lemeshow test demonstrated favorable model calibration χ=1.846，P=0.247>0.05. The Brier score of the model was 0.121， and the calibration curve closely overlapped the ideal reference line without significant calibration drift， suggesting that the predicted probability of successful weaning accurately reflected the actual weaning risk of individual patients. Decision curve analysis showed that the net benefit curve of the nomogram lay above the treat-none and treat-all reference lines within a threshold probability range of 0.10–0.65， confirming satisfactory clinical practicability.Conclusions：Higher IAP and higher GI are independent risk factors for weaning failure， while higher SAV serves as an independent protective factor in patients with severe pneumonia receiving invasive MV. The nomogram constructed from these three indicators exhibits favorable discrimination， good calibration and promising clinical application value.
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基本信息:
中图分类号:R563.1
引用信息:
[1]袁文博,郭淳,王若熹,等.基于腹腔压力、电阻抗断层成像参数的重症肺炎机械通气患者撤机结局列线图模型构建与验证[J].山东医药().
基金信息:
河南省科技攻关计划（232102310063）
2026-08-05
2026-08-05
2026-08-05