PDF(Pubmed)
Abstract：
UNASSIGNED: This study investigated potential predictive models associated with natural killer (NK) cell mitochondrial membrane potential (MMP or ΔΨm) in predicting death among critically ill patients with COVID-19.
UNASSIGNED: We included 97 patients with COVID-19 of different severities attending Peking Union Medical College Hospital from December 2022 to January 2023. Patients were divided into three groups according to oxygen and mechanical ventilation use during specimen collection and were followed for survival and death at 3 months. The lymphocyte subpopulation MMP was detected via flow cytometry. We constructed a joint diagnostic model by integrating identified key indicators and generating receiver operating curves (ROCs) and evaluated its predictive performance for mortality risk in critically ill patients.
UNASSIGNED: The NK-cell MMP median fluorescence intensity (MFI) was significantly lower in critically ill patients who died from COVID-19 (p<0.0001) and significantly and positively correlated with D-dimer content in critically ill patients (r=0.56, p=0.0023). The random forest model suggested that fibrinogen levels and NK-cell MMP MFI were the most important indicators. Integrating the above predictive models for the ROC yielded an area under the curve of 0.94.
UNASSIGNED: This study revealed the potential of combining NK-cell MMP with key clinical indicators (D-dimer and fibrinogen levels) to predict death among critically ill patients with COVID-19, which may help in early risk stratification of critically ill patients and improve patient care and clinical outcomes.
UNASSIGNED: We included 97 patients with COVID-19 of different severities attending Peking Union Medical College Hospital from December 2022 to January 2023. Patients were divided into three groups according to oxygen and mechanical ventilation use during specimen collection and were followed for survival and death at 3 months. The lymphocyte subpopulation MMP was detected via flow cytometry. We constructed a joint diagnostic model by integrating identified key indicators and generating receiver operating curves (ROCs) and evaluated its predictive performance for mortality risk in critically ill patients.
UNASSIGNED: The NK-cell MMP median fluorescence intensity (MFI) was significantly lower in critically ill patients who died from COVID-19 (p<0.0001) and significantly and positively correlated with D-dimer content in critically ill patients (r=0.56, p=0.0023). The random forest model suggested that fibrinogen levels and NK-cell MMP MFI were the most important indicators. Integrating the above predictive models for the ROC yielded an area under the curve of 0.94.
UNASSIGNED: This study revealed the potential of combining NK-cell MMP with key clinical indicators (D-dimer and fibrinogen levels) to predict death among critically ill patients with COVID-19, which may help in early risk stratification of critically ill patients and improve patient care and clinical outcomes.
摘要：
■这项研究调查了与自然杀伤（NK）细胞线粒体膜电位（MMP或ΔkWm）相关的潜在预测模型，以预测COVID-19重症患者的死亡。
■我们纳入了2022年12月至2023年1月在北京协和医院就诊的97名不同严重程度的COVID-19患者。根据标本收集期间的氧气和机械通气使用情况将患者分为三组，并在3个月时随访生存和死亡。通过流式细胞术检测淋巴细胞亚群MMP。我们通过整合确定的关键指标并生成受试者工作曲线（ROC）来构建联合诊断模型，并评估其对危重患者死亡风险的预测性能。
■COVID-19死亡的危重患者NK细胞MMP中位荧光强度(MFI)显著降低(p<0.0001)，与D-二聚体含量呈显著正相关(r=0.56，p=0.0023)。随机森林模型表明纤维蛋白原水平和NK细胞MMPMFI是最重要的指标。对ROC的上述预测模型进行积分得到0.94的曲线下面积。
这项研究揭示了将NK细胞MMP与关键临床指标（D-二聚体和纤维蛋白原水平）相结合来预测COVID-19危重患者死亡的潜力，这可能有助于对危重患者进行早期风险分层，并改善患者护理和临床预后。
■我们纳入了2022年12月至2023年1月在北京协和医院就诊的97名不同严重程度的COVID-19患者。根据标本收集期间的氧气和机械通气使用情况将患者分为三组，并在3个月时随访生存和死亡。通过流式细胞术检测淋巴细胞亚群MMP。我们通过整合确定的关键指标并生成受试者工作曲线（ROC）来构建联合诊断模型，并评估其对危重患者死亡风险的预测性能。
■COVID-19死亡的危重患者NK细胞MMP中位荧光强度(MFI)显著降低(p<0.0001)，与D-二聚体含量呈显著正相关(r=0.56，p=0.0023)。随机森林模型表明纤维蛋白原水平和NK细胞MMPMFI是最重要的指标。对ROC的上述预测模型进行积分得到0.94的曲线下面积。
这项研究揭示了将NK细胞MMP与关键临床指标（D-二聚体和纤维蛋白原水平）相结合来预测COVID-19危重患者死亡的潜力，这可能有助于对危重患者进行早期风险分层，并改善患者护理和临床预后。
