摘要
探讨各指标联合膈肌超声对重症肺炎患者撤机的指导价值,并构建撤机成功的预测模型。以2023—2024年住院期间确诊为重症肺炎且需机械通气的73例患者为研究对象,收集患者一般性资料,观察浅快呼吸指数(Rapid Shallow Breathing Index,RSBI)、降钙素原(Procalcitonin,PCT)、动脉血氧分压(Blood Oxygen Partial Pressure,PaO_(2))、呼吸速率(Respiratory Rate,RR)等临床指标。自主呼吸试验(Spontaneous Breathing Trial,SBT)30min时,通过超声评估膈肌功能,依据撤机结局分为撤机成功组与失败组。运用Logistic回归分析患者撤机的影响因素,进而构建撤机成功预测模型,并利用受测者工作特征曲线(Receiver Operating Characteristic,ROC)分析模型预测价值。结果表明:撤机成功组的膈肌增厚比(Diaphragmatic Thickening Ratio,DTR)与膈肌移动度(Diaphragmatic Excursion,DE)均高于失败组(P<0.05);RSBI、PCT、DTR、DE、机械通气时间(t)均为撤机的影响因素(P<0.05);Logistic回归拟合重症肺炎患者撤机预测模型为ln(P/(1-P))=16.107-0.28t-5.304R_(PCT)-0.258R_(RSBI)+5.132D_(DTR)+9.532D_(DE),该模型拟合优度检验χ^(2)=0.653,P>0.05;ROC曲线下面积为0.965(95%CI:0.925~1.000),敏感度与特异度分别为96.4%和86.7%,约登指数为0.831。证明多指标联合构建撤机成功预测模型对重症肺炎患者撤机具有指导意义,可为临床判断撤机时机提供可靠参考。
This study aims to analyze the predictive value of diaphragmatic ultrasound in combination with other clinical indicators for weaning from mechanical ventilation in patients with severe pneumonia,and to construct a predictive model for successful weaning.A prospective study was conducted on 73 patients diagnosed with severe pneumonia requiring mechanical ventilation from 2023 to 2024.General clinical data were collected,and clinical indicators such as the Rapid Shallow Breathing Index(RSBI),Procalcitonin(PCT),Blood Oxygen Partial Pressure(PaO_(2)),and respiratory rate were observed.Diaphragmatic function was assessed using ultrasound during a 30 minute Spontaneous Breathing Trial(SBT).Patients were divided into successful and failed weaning groups based on the outcome of the weaning.Logistic regression analysis was used to identify factors influencing weaning in patients with severe pneumonia and to construct a predictive model for the successful weaning.The predictive value of the model was analyzed using the Receiver Operating Characteristic(ROC)curve.The successful weaning group had significantly higher Diaphragmatic Thickening Ratio(DTR)and Diaphragmatic Excursion(DE)as compared to the failed weaning group,P<0.05.Mechanical ventilation duration,PCT,RSBI,DTR,and DE were identified as factors influencing weaning in patients with severe pneumonia(P<0.05).The logistic regression model for predicting weaning success was formulated as follows:ln(P/(1-P))=16.107-0.28t-5.304R_(PCT)-0.258R_(RSBI)+5.132D_(DTR)+9.532D_(DE).The model’s goodness-of-fit test showedχ^(2)=0.653,P>0.05.The Area Under the Curve(AUC)was 0.965(95%CI:0.925–1.000),with a sensitivity of 96.4%and specificity of 86.7%,and a Youden index of 0.831.The results demonstrated that this predictive model incorporating multiple indicators provides significant guidance for weaning in patients with severe pneumonia,and it can provide a reliable reference for clinical judgment on the timing of weaning from mechanical ventilation.
作者
于钦
胡占升
YU Qin;HU Zhansheng(The First Affiliated Hospital of Jinzhou Medical University,Jinzhou 121000,China)
出处
《宁波大学学报(理工版)》
2025年第5期113-120,共8页
Journal of Ningbo University(Natural Science and Engineering Edition)
基金
辽宁省教育厅基本科研项目(JYTMS20231728)。
关键词
重症肺炎
机械通气
膈肌超声
预测模型
severe pneumonia
mechanical ventilation
diaphragmatic ultrasound
predictive model
