Ma Qingqing, Luo Guoju, Wang Fei, Li Haolong, Li Xiaomeng, Liu Yongmei, Li Zhan, Guo Ye, Li Yongzhe
Department of Clinical Laboratory, State Key Laboratory of Complex, Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, People's Republic of China.
Medical Laboratory Innovation Unit, Chinese Academy of Medical Sciences, Shenyang, People's Republic of China.
J Inflamm Res. 2024 Jul 5;17:4361-4372. doi: 10.2147/JIR.S458749. eCollection 2024.
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.
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.
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.
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.
本研究调查了与自然杀伤（NK）细胞线粒体膜电位（MMP或ΔΨm）相关的潜在预测模型，以预测新冠肺炎危重症患者的死亡情况。
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例不同严重程度的新冠肺炎患者。根据标本采集时的氧疗和机械通气使用情况将患者分为三组，并随访3个月的生存和死亡情况。通过流式细胞术检测淋巴细胞亚群的MMP。我们通过整合已确定的关键指标并生成受试者工作特征曲线（ROC）构建了联合诊断模型，并评估其对危重症患者死亡风险的预测性能。
死于新冠肺炎的危重症患者的NK细胞MMP中位荧光强度（MFI）显著降低（p<0.0001），且与危重症患者的D-二聚体含量显著正相关（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MMP MFI是最重要的指标。将上述预测模型整合到ROC中，曲线下面积为0.94。
本研究揭示了将NK细胞MMP与关键临床指标（D-二聚体和纤维蛋白原水平）相结合预测新冠肺炎危重症患者死亡的潜力，这可能有助于对危重症患者进行早期风险分层，并改善患者护理和临床结局。
