人工智能定量肺部病变体积与重型新冠病毒感染患者预后的相关性分析

Correlation of Lung Lesion Volume Measurement Using Artificial Intelligence and Prognosis of Patients with Severe Coronavirus Disease 2019 Infection

目的:分析肺部病变体积及伴发基础疾病与重型新冠病毒感染(COVID-19)患者预后的相关性。方法:回顾2022年12月8日至2023年1月31日136例重型COVID-19患者,通过人工智能(AI)定量肺部病变体积、收集伴发基础疾病及实验室检查,分析其对重型COVID-19预后的影响。结果:重症COVID-19不同预后两组比较显示:年龄、低蛋白血症、脑卒中、乳酸脱氢酶、血尿素氮(BUN)、凝血酶原时间、白蛋白、白细胞、淋巴细胞比值、中性粒细胞比值、C反应蛋白、D-二聚体、全肺病灶体积(TLLV)和全肺病灶体积占比(PTLLV)两组之间差异有显著意义,年龄、PTLLV、TLLV、BUN、白细胞与预后不良呈正相关,白蛋白与预后不良呈负相关。结论:年龄越大、TLLV及PTLLV越大,重型COVID-19患者越容易出现预后不良,BUN、白细胞等指标增加以及白蛋白减少是重型COVID-19患者预后不良的危险因素。

Objective:To analyze the correlation between lung lesion volume and associated underlying diseases and prognosis of patients with severe coronavirus disease infection(COVID-19).Method:We reviewed 136 patients with severe COVID-19 in our hospital from December 8,2022 to January 31,2023.We measured the volume of lung lesions using artificial intelligence(AI),collected concomitant basic disease data and laboratory tests,and analyzed their impact on the prognosis of severe COVID-19.Results:The difference in the different prognoses of severe COVID-19,such as age,hypoproteinemia,stroke,lactate dehydrogenase,blood urea nitrogen(BUN),prothrombin time,albumin,leukocyte,lymphocyte ratio,neutrophil ratio,C-reactive protein,D-dimer,total lung lesion volume(TLLV),and percentage of total lung lesion volume(PTLLV),between the two groups was significant.Age,TLLV,PTLLV,BUN,and white blood cells were positively correlated with poor prognosis,while albumin was negatively correlated with poor prognosis.Conclusion:The older,the larger TLLV and PTLLV are,the more likely the patients with severe COVID-19 will have poor prognosis.The increase in indicators,such as BUN and white blood cells,and decrease in albumin are the risk factors for poor prognosis of the patients with severe COVID-19.