ISSN 1004-4140
CN 11-3017/P

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

贺燕林, 徐长荣, 乌力吉, 柴军

贺燕林, 徐长荣, 乌力吉, 等. 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[J]. CT理论与应用研究, 2023, 32(3): 331-338. DOI: 10.15953/j.ctta.2023.061.
引用本文: 贺燕林, 徐长荣, 乌力吉, 等. 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[J]. CT理论与应用研究, 2023, 32(3): 331-338. DOI: 10.15953/j.ctta.2023.061.
HE Y L, XU C R, WU L J, et al. Correlation of Lung Lesion Volume Measurement Using Artificial Intelligence and Prognosis of Patients with Severe Coronavirus Disease 2019 Infection[J]. CT Theory and Applications, 2023, 32(3): 331-338. DOI: 10.15953/j.ctta.2023.061. (in Chinese).
Citation: HE Y L, XU C R, WU L J, et al. Correlation of Lung Lesion Volume Measurement Using Artificial Intelligence and Prognosis of Patients with Severe Coronavirus Disease 2019 Infection[J]. CT Theory and Applications, 2023, 32(3): 331-338. DOI: 10.15953/j.ctta.2023.061. (in Chinese).

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

基金项目: 2022年度内蒙古自治区卫生健康科技计划项目(超高分辨率CT靶扫描技术联合低剂量对诊断亚实性肺结节的价值(202201015));内蒙古自治区人民医院院内基金项目(基于深度学习的病毒性肺炎不同临床转归胸部CT评价(2020YN08))。
详细信息
    作者简介:

    贺燕林: 女,硕士研究生,内蒙古自治区人民医院副主任医师,主要从事影像诊断工作,E-mail:708966749@qq.com

    通讯作者:

    柴军: 男,影像医学与核医学博士,内蒙古自治区人民医院主任医师,主要从事影像诊断及CT引导下肺结节穿刺术,E-mail:amaschai@126.com

  • 中图分类号: O  242;R  563.1

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

  • 摘要: 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。
    Abstract: 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.
  • 目前新型冠状病毒感染(COVID-19)变异毒株—奥密克戎(Omicron)已成为优势流行株[1],国内外证据显示奥密克戎变异株肺部致病力明显减弱,临床表现已由肺炎为主衍变为以上呼吸道感染为主,即轻型,而且轻型、中型患者预后良好,重型及危重型患者临床预后差[2],尤其是老年重型患者的死亡率较高[3],因此影响重型患者预后的因素值得关注。张炜宗等[4]的Meta分析显示影响COVID-19患者院内死亡因素有很多因素,而且COVID-19患者肺部病变体积被确定为危重症的独立预测因子[5]。人工智能(AI)不仅可以帮助放射科医生检测COVID-19患者肺部病变[6-7],还可以自动检测肺炎病变的数量、体积与病变体积占百分比[8]

    本研究通过AI定量重型COVID-19全肺病变体积(total lung lesion volume,TLLV)及全肺病变体积占比(percentage of total lung lesion volume,PTLLV),分析肺部病变体积及伴发基础疾病对重型COVID-19预后的影响。

    回顾性分析2022年12月8日至2023年1月31日内蒙古自治区人民医院确诊重型COVID-19患者147例,排除11例入院时在外院行CT检查或住院期间均行胸部普通X线检查进行诊断、复查患者及呼吸伪影较重无法准确测量患者。最终纳入136例住院且入院时行多层螺旋CT检查患者,男88例,年龄40~95岁,平均年龄(74.39±11.826)岁;女48例,年龄35~91岁,平均年龄(76.19±12.471)岁。诊断标准:新型冠状病毒感染诊疗方案(试行第十版)[1]发布重型诊断标准。

    包括年龄、性别、吸烟史、心血管疾病、低蛋白血症、2型糖尿病、脑卒中、恶性肿瘤、慢性肺部疾病、慢性肾脏疾病、慢性肝脏疾病。

    血常规:白细胞、中性粒细胞比值、淋巴细胞比值、血红蛋白、C反应蛋白。生化指标:白蛋白、丙氨酸转移酶、天门冬氨酸转移酶、乳酸脱氢酶、BUN、肌酐、总胆红素。凝血指标:凝血酶原时间、D-二聚体;降钙素原、N-端脑钠肽前体。检验指标的正常值源自《全国临床检验操作规程第4版》[9],核酸检测采集咽拭子或鼻拭子。

    采用64排及其以上多排螺旋CT(MSCT)扫描,仰卧位,从肺尖至肺底扫描,扫描时屏气。扫描条件:120 kV、80~100 mA、层厚5 mm、间隔5 mm,扫描完成后以层厚1.5 mm、间隔1.5 mm进行重建。肺窗:窗宽1500 HU、窗位 -600 HU,纵隔窗:窗宽400 HU、窗位40 HU。

    将数据传输到人工智能软件,由两位高年主治以上医生进行评估COVID-19肺部病变,即COVID-19肺部受累的特征性CT表现包括实变或胸膜下磨玻璃密度影,外周和下肺分布为主、铺路石症、晕症等[10],通过人工智能软件逐层测量得出全肺及各叶病灶体积(LV)及其占比等CT定量参数(图1),测量过程中如AI软件识别不准时,进行人工手动校正。

    图  1  AI定量病灶的分析图
    Figure  1.  Chart of quantitative lesions using AI

    将所有患者分为两类:好转、预后不良。预后不良:重型转为危重型放弃治疗或死亡;好转:根据新型冠状病毒感染诊疗方案(试行第十版)[1]住院患者达到出院标准及危重型诊断标准。

    所有数据采用SPSS 17.0软件进行处理,计量数据以$\, \bar{x}\pm s$表示,计量资料组间比较,采用独立样本t检验;计数资料以百分比表示,计数资料组间比较采用$\chi^{2}$检验,相关性分析采用logistic回归分析,P<0.05为差异有统计学意义。ROC曲线分析计算曲线下面积、最佳截止点、敏感性和特异性。

    所有纳入重症COVID-19患者各观察指标及不同预后两组研究对象观察指标的比较(表1表2),肺部病灶AI测量指标(图2图3)。

    表  1  重症COVID-19患者不同预后两组肺部病灶AI测量指标的比较($\bar{x}\pm s$
    Table  1.  Comparison of various indicators of lung lesions between two groups with patients with severe COVID-19 and different prognoses measured using AI
    AI测量指标所有纳入人群(n=136)预后好转(n=94)预后不良(n=42)tP
      右肺上叶LV/cm399.26±115.78482.30±102.082137.21±135.5342.3450.022*
      右肺上叶PLV/%14.22±17.01111.79±15.55119.65±18.9892.3510.022*
      右肺中叶LV/cm348.44±60.16738.57±70.51670.52±72.1372.5910.012*
      右肺中叶PLV/%16.22±18.50413.65±17.23821.97±20.1092.4680.015*
      右肺下叶LV/cm3187.30±139.077172.75±133.610219.87±147.050-0.338 0.736
      右肺下叶PLV/%42.76±163.24545.93±195.96935.66±23.6651.8420.068
      左肺上叶LV/cm384.79±99.04876.72±96.225102.84±104.0051.4270.156
      左肺上叶PLV/%11.86±15.07610.45±14.35415.02±16.3151.6450.102
      左肺下叶LV/cm3139.30±112.473123.59±104.904174.48±121.8892.4850.014*
      左肺下叶PTLV/%24.26±20.08021.36±19.27730.75±20.5522.5710.011*
      TLLV/cm3554.24±393.127486.90±359.175704.94±427.3123.0810.003*
      PTLLV/%18.11±14.44215.90±13.84423.04±14.7002.7240.007*
     注:*-P<0.05,统计学有显著性差异;LV为病灶体积,PLV为病灶体积占比。
    下载: 导出CSV 
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    表  2  重症COVID-19患者不同预后两组基础疾病及实验室检查的比较($\bar{x}\pm s$
    Table  2.  Comparison of observation indicators between two groups with patients with severe COVID-19 and different prognoses
    临床及实验室资料所有纳入人群(n=136)预后好转(n=94)预后不良(n=42)$t/\chi^{2}$P
     年龄/岁74.91±12.00673.66±11.44178.07±12.9151.9960.039*
     男性/例(%)88(64.71)60(63.83)28(66.67)0.1020.749
     吸烟/例(%)27(19.85)20(21.28)7(16.67)0.3880.534
     心血管疾病/例(%)98(72.06)66(70.21)32(76.19)0.5150.473
     低蛋白血症/例(%)78(57.35)48(51.06)30(71.43)4.9220.027*
     2型糖尿病/例(%)43(31.62)34(36.17)9(21.43)2.9180.088
     脑卒中/例(%)6(4.41)1(1.06)5(11.90)8.0900.004*
     恶性肿瘤/例(%)11(8.09)8(8.51)3(7.14)0.0730.787
     慢性肺部疾病/例(%)36(26.47)23(24.47)13(30.95)0.6720.428
     慢性肾脏疾病/例(%)22(16.18)12(12.77)10(23.81)2.6110.106
     慢性肝脏疾病/例(%)15(11.03)9(9.57)6(14.29)0.6570.418
     总胆红素/(µmol/L)11.87±9.4011.79±10.57912.03±6.0760.1370.891
     丙氨酸转移酶/(U/L)36.24±47.17334.36±43.25440.45±55.2900.6950.488
     天门冬氨酸转移酶/(U/L)40.18±42.56338.55±48.10243.84±26.4020.8230.412
     乳酸脱氢酶/(U/L)323.54±159.911305.05±149.402364.92±176.1542.0410.043*
     BUN/(mmol/L)8.47±6.6537.67±6.48710.25±6.7502.1170.036*
     肌酐/(µmol/L)99.10±136.866103.81±160.40588.57±56.150-0.5990.550
     凝血酶原时间/s13.23±2.60112.84±2.08814.09±3.3582.6400.009*
     白蛋白/(g/L)34.27±5.78735.32±5.46431.93±5.866-3.2690.001*
     降钙素原/(ng/mL)2.07±12.0581.65±10.3123.00±15.3700.6000.549
     血红蛋白/(mmol/L)131.99±23.442132.16±22.76131.62±25.193-0.1190.906
     白细胞/(109/L)7.40±4.3366.88±3.8398.58±5.1402.1490.033*
     淋巴细胞比值%15.33±9.41316.41±9.33112.90±9.249-2.0310.044*
     中性粒细胞比值%77.28±12.39775.55±11.68881.14±13.1922.4760.015*
     C反应蛋白/(mg/L)79.07±64.28271.59±64.53995.81±61.1732.0980.039*
     D-二聚体/(µg/mL)1.32±3.0620.96±1.9742.13±4.5902.0830.039*
     N-端脑钠肽前体/(pg/mL)3239.55±7118.4432797.38±7253.0594229.14±6787.3721.1120.269
     注:*-P<0.05,统计学有显著性差异。
    下载: 导出CSV 
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    图  2  男,79岁,重型COVID-19,预后不良,TLLV 1139.86 cm3,PTLLV 46.60%
    Figure  2.  Male, 79 years old with severe COVID-19 and poor prognosis,TLLV 1139.86 cm3,PTLLV 46.60%
    图  3  男68岁,重型COVID-19,预后好转,TLLV 517.38 cm3,PTLLV 12.96%
    Figure  3.  Male, 68 years old with severe COVID-19 and good prognosis, TLLV 517.38 cm3, PTLLV 12.96%

    本组136例重型COVID-19患者中,94例好转出院,42例预后不良,年龄、低蛋白血症、脑卒中、乳酸脱氢酶、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、右肺上叶LV、右肺上叶PLV、右肺中叶LV、右肺中叶PLV、左肺下叶LV、左肺下叶PLV、TLLV、PTLLV两组之间差异有显著意义。

    重型COVID-19患者不同预后两组肺病变体积及其占比、伴发疾病及其实验室检查相关性分析(表3)。本组重型COVID-19患者中,Logistic回归分析显示:年龄、PTLLV、TLLV、BUN、白蛋白、白细胞进入方程,与重型COVID-19患者预后显著相关;年龄、PTLLV、TLLV、BUN、白细胞OR>1,呈正相关,白蛋白OR<1,呈负相关。

    表  3  Logistic回归分析重型COVID-19患者预后与进入方程中的自变量及其参数的估计值
    Table  3.  Logistic regression analysis of prognosis and estimated values of independent variables and parameters in the entry equation for patients with severe COVID-19
    选入变量BS.E.WaldP0R
        年龄/岁0.0520.0206.7390.009*1.053**
        PTLLV/%0.0340.0155.0810.024*1.034**
        TLLV/cm30.0010.0016.4310.011*1.001**
        BUN/(mmol/L)0.0690.0314.9020.027*1.072**
        白蛋白/(g/L)-0.0820.0394.4750.034*0.922#
        白细胞/(109/L)0.1160.0485.7130.017*1.123**
     注:*-P<0.05,统计学有显著性差异。**-OR>1,呈正相关;# -OR<1,呈负相关。
    下载: 导出CSV 
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    ROC曲线分析显示:PTLLV、TLLV评估重型COVID-19患者预后有诊断意义(图4)。PTLLV、TLLV曲线下面积(AUC)分别为0.651和0.650,诊断敏感性分别为59.5% 和54.8%,特异性分别为76.6% 和76.6%,最佳截止点分别为19.38% 和647.93 cm3表4)。PTLLV、TLLV两者评估重型COVID-19患者预后的特异性相同,而PTLLV评估重型COVID-19患者预后的敏感性相对更高。

    表  4  PTLLV和TLLV评估重型COVID-19患者预后的ROC分析结果
    Table  4.  ROC analysis results of PTLLV and TLLV in the prognosis of patients with severe COVID-19
    预测值AUC最佳截止点敏感性/%特异性/%p
    PTLLV/%0.65119.3859.5076.600.005
    TLLV/cm30.650647.93 54.8076.600.005
    下载: 导出CSV 
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    图  4  PTLLV、TLLV评估重型COVID-19患者预后的ROC曲线图
    Figure  4.  ROC curve for evaluating the prognosis of patients with severe COVID-19 using PTLLV and TLLV

    重型COVID-19患者预后在不同年龄段中差异对比(表5)。两组预后有差别,说明年龄在重型新型冠状病毒感染患者预后中有差异。≥80岁重型COVID-19患者中,预后不良患者占43.86%。预后不良患者中59.52% 是≥80岁患者。

    表  5  重型COVID-19患者预后在不同年龄段中的卡方检验
    Table  5.  Chi-square test for the prognosis of patients with severe COVID-19 in different age groups
    年龄所有纳入人群(n=136)合计
    预后好转/例预后不良/例
    <60岁     10 4 14
    ≥60且<70岁  20 2 22
    ≥70岁且<80岁 32 11 43
    ≥80岁     32 25 57
    合计       94 42 136
    下载: 导出CSV 
    | 显示表格

    胸部CT是检测肺病变的有效成像方法[5],不仅可以诊断COVID-19肺炎还可以评估肺部病变的范围[11]。为了规范急性COVID-19肺部受累程度的主观评估,已有学者提出了一些不同的定量和半定量CT严重程度评分系统,他们的研究显示肺损伤比例较高与重症COVID-19相关[12-13]。也有研究者通过CT定量检测技术对COVID-19患者肺内病灶的总体容积、最大径、密度、分布范围,发现患者进展期、重症期病灶体积、最大密度和最大径均显著升高[14],在危重COVID-19患者中,观察到具有较大肺病灶体积者炎症反应生物标志物水平更高。肺病灶体积是危重症的独立预测因子,肺病灶体积等于或大于60% 的患者患危重症的风险增加了19.4倍[10]

    目前AI可以自动检测肺炎LV与PLV(图1),AI定量分析肺部病变体积方便快捷,本研究通过AI定量重型COVID-19患者TLLV及PTLLV,分析了其与重型COVID-19预后的关系。研究结果显示重型COVID-19不同预后两组比较PTLLV、TLLV差异有统计学意义,PTLLV、TLLV与重型COVID-19预后不良呈正相关,PTLLV、TLLV是重型COVID-19预后不良危险因素;ROC曲线分析显示:TLLV在647.93 cm3时,重型COVID-19预后不良的敏感性、特异性分别为54.8% 和76.6%,PTLLV在19.38%时,重型COVID-19预后不良的敏感性、特异性分别为59.5% 和76.6%。有研究显示在危重COVID-19患者中PTLLV为60%时,预后不良的敏感性、特异性分别为82.1% 和70.2%[10],可能他们的研究为危重型患者,肺部病变更重,而本研究为重型COVID-19患者肺部病变相对较危重型轻、PTLLV相对较小,而且病灶实性成分占比可能对重型COVID-19患者的预后也存在一定的影响。本研究没有阐述病灶实性成分占比对重型COVID-19预后的影响,有待于我们进一步研究。

    本研究中重型COVID-19患者都具有基础疾病,基础疾病可能使COVID-19患者更容易成为重型,但是不同预后两组之间对比除脑卒中以外,其余均没有统计学意义,COVID-19患者并发缺血性脑卒中的比例为1.6%~4.6%。与未感染者相比,COVID-19患者患缺血性脑卒中的风险增加3.6倍[15],重症COVID-19伴发脑卒中可能更易出现预后不良。

    本组研究对象中低蛋白血症患者57.35%,重症COVID-19不同预后两组比较显示:白蛋白、低蛋白血症差异有统计学意义,白蛋白与重型COVID-19预后不良呈负相关,白蛋白水平减低可以影响重型COVID-19预后,是重型COVID-19预后不良的危险因素。感染新冠病毒后的患者能量消耗增加,蛋白质分解加快,可以导致低蛋白血症,白蛋白水平的下降可以有效评估重型COVID-19患者病情[2]

    本研究重型COVID-19不同预后两组比较炎性指标中的白细胞计数、淋巴细胞比值、中性粒细胞比值、C反应蛋白等,肝功能指标中的乳酸脱氢酶,凝血功能异常中的凝血酶原时间延长、D-二聚体水平升高等指标,差异有统计学意义。重型COVID-19预后不良患者可能炎症爆发、肝功损伤、凝血系统的激活较预后良好者更明显。BUN是肾功能损伤的标志物,多见于各种类型肾功能衰竭,其水平升高多提示不良预后[16]。本研究显示BUN与重症COVID-19预后不良呈正相关,是预后不良的危险因素。

    老年患者大多数有基础疾病,当感染COVID-19时,容易导致病情加重,死亡率增加[17],本研究显示重症COVID-19不同预后两组比较年龄差异有统计学意义,而且年龄是重症COVID-19预后不良的危险因素。有研究认为新冠肺炎主要影响男性(58.1%),经常发生在中老年男性中,80岁以上人群的死亡率最高(8%~15%)[18],特别是重型COVID-19患者80岁以上死亡率更高。本组研究对象均为重型COVID-19患者,其中男性64.71%,≥80岁重型COVID-19患者中,预后不良患者占43.86%,而且预后不良患者中近一半以上都是≥80岁患者。重型COVID-19患者中男性占比更大原因可能与性激素有关[19-20],从免疫学角度来看,雌性比雄性更强,导致病原体清除速度更快[21]

    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。

  • 图  1   AI定量病灶的分析图

    Figure  1.   Chart of quantitative lesions using AI

    图  2   男,79岁,重型COVID-19,预后不良,TLLV 1139.86 cm3,PTLLV 46.60%

    Figure  2.   Male, 79 years old with severe COVID-19 and poor prognosis,TLLV 1139.86 cm3,PTLLV 46.60%

    图  3   男68岁,重型COVID-19,预后好转,TLLV 517.38 cm3,PTLLV 12.96%

    Figure  3.   Male, 68 years old with severe COVID-19 and good prognosis, TLLV 517.38 cm3, PTLLV 12.96%

    图  4   PTLLV、TLLV评估重型COVID-19患者预后的ROC曲线图

    Figure  4.   ROC curve for evaluating the prognosis of patients with severe COVID-19 using PTLLV and TLLV

    表  1   重症COVID-19患者不同预后两组肺部病灶AI测量指标的比较($\bar{x}\pm s$

    Table  1   Comparison of various indicators of lung lesions between two groups with patients with severe COVID-19 and different prognoses measured using AI

    AI测量指标所有纳入人群(n=136)预后好转(n=94)预后不良(n=42)tP
      右肺上叶LV/cm399.26±115.78482.30±102.082137.21±135.5342.3450.022*
      右肺上叶PLV/%14.22±17.01111.79±15.55119.65±18.9892.3510.022*
      右肺中叶LV/cm348.44±60.16738.57±70.51670.52±72.1372.5910.012*
      右肺中叶PLV/%16.22±18.50413.65±17.23821.97±20.1092.4680.015*
      右肺下叶LV/cm3187.30±139.077172.75±133.610219.87±147.050-0.338 0.736
      右肺下叶PLV/%42.76±163.24545.93±195.96935.66±23.6651.8420.068
      左肺上叶LV/cm384.79±99.04876.72±96.225102.84±104.0051.4270.156
      左肺上叶PLV/%11.86±15.07610.45±14.35415.02±16.3151.6450.102
      左肺下叶LV/cm3139.30±112.473123.59±104.904174.48±121.8892.4850.014*
      左肺下叶PTLV/%24.26±20.08021.36±19.27730.75±20.5522.5710.011*
      TLLV/cm3554.24±393.127486.90±359.175704.94±427.3123.0810.003*
      PTLLV/%18.11±14.44215.90±13.84423.04±14.7002.7240.007*
     注:*-P<0.05,统计学有显著性差异;LV为病灶体积,PLV为病灶体积占比。
    下载: 导出CSV

    表  2   重症COVID-19患者不同预后两组基础疾病及实验室检查的比较($\bar{x}\pm s$

    Table  2   Comparison of observation indicators between two groups with patients with severe COVID-19 and different prognoses

    临床及实验室资料所有纳入人群(n=136)预后好转(n=94)预后不良(n=42)$t/\chi^{2}$P
     年龄/岁74.91±12.00673.66±11.44178.07±12.9151.9960.039*
     男性/例(%)88(64.71)60(63.83)28(66.67)0.1020.749
     吸烟/例(%)27(19.85)20(21.28)7(16.67)0.3880.534
     心血管疾病/例(%)98(72.06)66(70.21)32(76.19)0.5150.473
     低蛋白血症/例(%)78(57.35)48(51.06)30(71.43)4.9220.027*
     2型糖尿病/例(%)43(31.62)34(36.17)9(21.43)2.9180.088
     脑卒中/例(%)6(4.41)1(1.06)5(11.90)8.0900.004*
     恶性肿瘤/例(%)11(8.09)8(8.51)3(7.14)0.0730.787
     慢性肺部疾病/例(%)36(26.47)23(24.47)13(30.95)0.6720.428
     慢性肾脏疾病/例(%)22(16.18)12(12.77)10(23.81)2.6110.106
     慢性肝脏疾病/例(%)15(11.03)9(9.57)6(14.29)0.6570.418
     总胆红素/(µmol/L)11.87±9.4011.79±10.57912.03±6.0760.1370.891
     丙氨酸转移酶/(U/L)36.24±47.17334.36±43.25440.45±55.2900.6950.488
     天门冬氨酸转移酶/(U/L)40.18±42.56338.55±48.10243.84±26.4020.8230.412
     乳酸脱氢酶/(U/L)323.54±159.911305.05±149.402364.92±176.1542.0410.043*
     BUN/(mmol/L)8.47±6.6537.67±6.48710.25±6.7502.1170.036*
     肌酐/(µmol/L)99.10±136.866103.81±160.40588.57±56.150-0.5990.550
     凝血酶原时间/s13.23±2.60112.84±2.08814.09±3.3582.6400.009*
     白蛋白/(g/L)34.27±5.78735.32±5.46431.93±5.866-3.2690.001*
     降钙素原/(ng/mL)2.07±12.0581.65±10.3123.00±15.3700.6000.549
     血红蛋白/(mmol/L)131.99±23.442132.16±22.76131.62±25.193-0.1190.906
     白细胞/(109/L)7.40±4.3366.88±3.8398.58±5.1402.1490.033*
     淋巴细胞比值%15.33±9.41316.41±9.33112.90±9.249-2.0310.044*
     中性粒细胞比值%77.28±12.39775.55±11.68881.14±13.1922.4760.015*
     C反应蛋白/(mg/L)79.07±64.28271.59±64.53995.81±61.1732.0980.039*
     D-二聚体/(µg/mL)1.32±3.0620.96±1.9742.13±4.5902.0830.039*
     N-端脑钠肽前体/(pg/mL)3239.55±7118.4432797.38±7253.0594229.14±6787.3721.1120.269
     注:*-P<0.05,统计学有显著性差异。
    下载: 导出CSV

    表  3   Logistic回归分析重型COVID-19患者预后与进入方程中的自变量及其参数的估计值

    Table  3   Logistic regression analysis of prognosis and estimated values of independent variables and parameters in the entry equation for patients with severe COVID-19

    选入变量BS.E.WaldP0R
        年龄/岁0.0520.0206.7390.009*1.053**
        PTLLV/%0.0340.0155.0810.024*1.034**
        TLLV/cm30.0010.0016.4310.011*1.001**
        BUN/(mmol/L)0.0690.0314.9020.027*1.072**
        白蛋白/(g/L)-0.0820.0394.4750.034*0.922#
        白细胞/(109/L)0.1160.0485.7130.017*1.123**
     注:*-P<0.05,统计学有显著性差异。**-OR>1,呈正相关;# -OR<1,呈负相关。
    下载: 导出CSV

    表  4   PTLLV和TLLV评估重型COVID-19患者预后的ROC分析结果

    Table  4   ROC analysis results of PTLLV and TLLV in the prognosis of patients with severe COVID-19

    预测值AUC最佳截止点敏感性/%特异性/%p
    PTLLV/%0.65119.3859.5076.600.005
    TLLV/cm30.650647.93 54.8076.600.005
    下载: 导出CSV

    表  5   重型COVID-19患者预后在不同年龄段中的卡方检验

    Table  5   Chi-square test for the prognosis of patients with severe COVID-19 in different age groups

    年龄所有纳入人群(n=136)合计
    预后好转/例预后不良/例
    <60岁     10 4 14
    ≥60且<70岁  20 2 22
    ≥70岁且<80岁 32 11 43
    ≥80岁     32 25 57
    合计       94 42 136
    下载: 导出CSV
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  • 收稿日期:  2023-03-14
  • 修回日期:  2023-04-03
  • 录用日期:  2023-04-05
  • 网络出版日期:  2023-04-26
  • 发布日期:  2023-05-30

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