目的评估基于Kaiser评分的MRI影像特征列线图模型术前预测肿块型乳腺癌脉管侵犯的价值。方法回顾性分析经手术病理证实的345例肿块型浸润性乳腺癌患者临床、病理、影像学和Kaiser评分资料,按照7∶3随机分为训练集(n=242)和验证集(n=103...目的评估基于Kaiser评分的MRI影像特征列线图模型术前预测肿块型乳腺癌脉管侵犯的价值。方法回顾性分析经手术病理证实的345例肿块型浸润性乳腺癌患者临床、病理、影像学和Kaiser评分资料,按照7∶3随机分为训练集(n=242)和验证集(n=103)。应用单因素和多因素Logistic回归模型分析肿块型乳腺癌脉管侵犯的独立危险因素并构建列线图预测模型,通过受试者工作特征(receiver operating characteristic,ROC)曲线、校准曲线和临床决策曲线评估模型效能。结果单因素Logistic回归分析发现,肿瘤最大直径、Kaiser评分、扩散加权成像信号、形状和相关受侵征象与肿块型乳腺癌脉管侵犯相关(均P<0.05);进一步的多因素Logistic回归分析显示,Kaiser评分≥6分、扩散加权成像高信号、形状不规则和存在相关受侵征象是肿块型乳腺癌脉管侵犯的独立危险因素(均P<0.05)。Kaiser评分联合扩散加权成像信号、形状和相关侵犯征象构建的肿块型乳腺癌脉管侵犯列线图预测模型在训练集和验证集中的ROC曲线下面积(area under the ROC curve,AUC)分别为0.899(95%CI:0.859~0.939)和0.827(95%CI:0.744~0.909);训练集中特异性为0.845,敏感性为0.840;验证集中的特异性为0.787,敏感性为0.750;校准曲线和Hosmer-Lemeshow拟合优度检验结果表明列线图模型一致性较好;临床决策曲线结果显示列线图预测肿块型乳腺癌脉管侵犯可获得较高收益。结论本研究构建的基于Kaiser评分的MRI影像特征列线图模型有助于术前预测肿块型乳腺癌脉管侵犯,并且该模型具有较高的预测效能,可为临床术前评估肿块型乳腺癌脉管侵犯提供参考依据。展开更多
Objective:To analyze the existing risks in breast milk management at the neonatal department and provide corresponding countermeasures.Methods:22 risk events were identified in 7 risk links in the process of bottle-fe...Objective:To analyze the existing risks in breast milk management at the neonatal department and provide corresponding countermeasures.Methods:22 risk events were identified in 7 risk links in the process of bottle-feeding of breast milk.Hazard Vulnerability Analysis based on the Kaiser model was applied to investigate and evaluate the risk events.Results:High-risk events include breast milk quality inspection,hand hygiene during collection,disinfection of collectors,cold chain management,hand hygiene during the reception,breast milk closed-loop management,and post-collection disposal.Root cause analysis of high-risk events was conducted and breast milk management strategies outside the hospital and within the neonatal department were proposed.Conclusion:Hazard Vulnerability Analysis based on the Kaiser model can identify and assess neonatal breast milk management risks effectively,which helps improve the management of neonatal breast milk.It is conducive to the safe development and promotion of bottle feeding of breast milk for neonates,ensuring the quality of medical services and the safety of children.展开更多
文摘目的评估基于Kaiser评分的MRI影像特征列线图模型术前预测肿块型乳腺癌脉管侵犯的价值。方法回顾性分析经手术病理证实的345例肿块型浸润性乳腺癌患者临床、病理、影像学和Kaiser评分资料,按照7∶3随机分为训练集(n=242)和验证集(n=103)。应用单因素和多因素Logistic回归模型分析肿块型乳腺癌脉管侵犯的独立危险因素并构建列线图预测模型,通过受试者工作特征(receiver operating characteristic,ROC)曲线、校准曲线和临床决策曲线评估模型效能。结果单因素Logistic回归分析发现,肿瘤最大直径、Kaiser评分、扩散加权成像信号、形状和相关受侵征象与肿块型乳腺癌脉管侵犯相关(均P<0.05);进一步的多因素Logistic回归分析显示,Kaiser评分≥6分、扩散加权成像高信号、形状不规则和存在相关受侵征象是肿块型乳腺癌脉管侵犯的独立危险因素(均P<0.05)。Kaiser评分联合扩散加权成像信号、形状和相关侵犯征象构建的肿块型乳腺癌脉管侵犯列线图预测模型在训练集和验证集中的ROC曲线下面积(area under the ROC curve,AUC)分别为0.899(95%CI:0.859~0.939)和0.827(95%CI:0.744~0.909);训练集中特异性为0.845,敏感性为0.840;验证集中的特异性为0.787,敏感性为0.750;校准曲线和Hosmer-Lemeshow拟合优度检验结果表明列线图模型一致性较好;临床决策曲线结果显示列线图预测肿块型乳腺癌脉管侵犯可获得较高收益。结论本研究构建的基于Kaiser评分的MRI影像特征列线图模型有助于术前预测肿块型乳腺癌脉管侵犯,并且该模型具有较高的预测效能,可为临床术前评估肿块型乳腺癌脉管侵犯提供参考依据。
文摘Objective:To analyze the existing risks in breast milk management at the neonatal department and provide corresponding countermeasures.Methods:22 risk events were identified in 7 risk links in the process of bottle-feeding of breast milk.Hazard Vulnerability Analysis based on the Kaiser model was applied to investigate and evaluate the risk events.Results:High-risk events include breast milk quality inspection,hand hygiene during collection,disinfection of collectors,cold chain management,hand hygiene during the reception,breast milk closed-loop management,and post-collection disposal.Root cause analysis of high-risk events was conducted and breast milk management strategies outside the hospital and within the neonatal department were proposed.Conclusion:Hazard Vulnerability Analysis based on the Kaiser model can identify and assess neonatal breast milk management risks effectively,which helps improve the management of neonatal breast milk.It is conducive to the safe development and promotion of bottle feeding of breast milk for neonates,ensuring the quality of medical services and the safety of children.