早期预测新型冠状病毒肺炎患者病情严重程度列线图的建立及应用
Establishment of a nomogram for early prediction of the severity of patients with coronavirus disease 2019 and its application

陈清 ¹ 胡雨峰 ² 林素涵 ¹ 陈玉熹 ¹ 潘景业 ² ^*

文摘	目的建立早期预测新型冠状病毒肺炎患者病情严重程度的列线图,以指导临床治疗。方法选择2020年1月17日至2020年2月14日温州市中心医院收治的116例新型冠状病毒肺炎患者,根据临床表现,将116例患者分为轻型组(4例)、普通型组(90例)、重型组(18例)和危重型组(4例)。记录所有患者的住院时间和并发症,比较4组患者的一般资料及临床指标。通过多因素Logistic回归分析得到影响新型冠状病毒肺炎患者预后的危险因素,并用R语言软件建立可视化的回归列线图,最后采用受试者工作特征(ROC)曲线检测该列线图的效能。结果轻型组、普通型组、重型组和危重型组新型冠状病毒肺炎患者年龄[(39 ± 11)、(43 ± 12)、(53 ± 13)、(60 ± 8)岁,F = 5.815,P = 0.001]、C反应蛋白质[1.7(0.6,7.1)、7.9(2.9,21.6)、28.4(13.9,42.5)、61.7(44.7,79.8)mg/ L,H = 8.424,P <0.001]、红细胞比容[(36 ± 5)%、(41 ± 4)%、(39 ± 4)%、(37 ± 5)%,F = 4.344,P = 0.006]、血小板计数[318.0(251.0,409.0)× 10~9/ L、180.5(140.0,225.5)× 10~9/ L、162.0(130.0,222.8)× 10~9/ L、108.5(82.0,103.0)× 10~9/ L,H = 7.225,P <0.001]、天冬氨酸氨基转移酶[16.0(15.5,19.5)、23.0(19.0,31.0)、34.5(26.3,55.0)、39.5(29.0,82.3)U/ L, H = 6.159,P = 0.001]、白蛋白[(44 ± 6)、(43 ± 16)、(39 ± 3)、(33 ± 4)g/ L,F = 9.508,P <0.001]和乳酸脱氢酶[142.5(107.8,189.3)、198.0(159.5,238.0)、295.0(251.0,323.0)、369.5(295.2,436.3)U/ L, H = 14.225,P <0.001]水平比较,差异均有统计学意义。将年龄、C反应蛋白质、红细胞比容、血小板计数、天冬氨酸氨基转移酶、白蛋白和乳酸脱氢酶纳入多因素Logistic回归分析,结果显示,白蛋白[比值比(OR)= 0.756,95%置信区间(CI)(0.581,0.982),P = 0.036]和乳酸脱氢酶[OR = 1.019,95%CI(1.007,1.032),P = 0.002]为影响新型冠状病毒肺炎患者预后的危险因素。通过R语言软件得到可靠直观的列线图。ROC曲线分析结果显示,该列线图对重型及危重型患者[曲线下面积(AUC)= 0.903,95%CI(0.831,0.975),P <0.001]、单独预测危重型患者[AUC = 0.974,95%CI(0.932,1.000),P <0.001]、单独预测重型患者[AUC = 0.848,95%CI(0.759,0.937),P <0.001]均具有优秀的预测能力。结论该列线图可以早期并有效预测新型冠状病毒肺炎患者严重程度,可能成为指导临床治疗的一项实用工具。
其他语种文摘	Objective To establish a nomogram for early prediction of the severity of patients with coronavirus disease 2019(COVID-19)to guide clinical treatment.Methods From January 17 to February 14, 2020, 116 patients with COVID-19 admitted to Wenzhou Central Hospital were selected.According to their clinical manifestations, 116 patients were divided into a mild group(n = 4), a common group(n = 90), a severe group(n = 18)and a critical group(n = 4).The hospitalization time and complications of all patients were recorded, and the general data and clinical indicators were compared among the 4 groups.Risk factors for the prognosis of patients with COVID-19 were obtained by multivariate Logistic regression analysis.Then a visual regression nomogram was established using R language software.Finally, efficacy of the nomogram was detected by a receiver operating characteristic(ROC)curve.Results The age [(39 ± 11),(43 ± 12),(53 ± 13),(60 ± 8)years;F = 5.815, P = 0.001], C-reactive protein [1.7(0.6, 7.1), 7.9(2.9, 21.6), 28.4(13.9, 42.5), 61.7(44.7, 79.8)mg/ L;H = 8.424, P <0.001], hematocrit [(36 ± 5)%,(41 ± 4)%,(39 ± 4)%,(37 ± 5)%;F = 4.344, P = 0.006], platelet count [318.0(251.0, 409.0)× 10~9/ L, 180.5(140.0, 225.5)× 10~9/ L, 162.0(130.0, 222.8)× 10~9/ L, 108.5(82.0, 103.0)× 10~9/ L;H = 7.225, P <0.001], aspartate aminotransferase [16.0(15.5, 19.5), 23.0(19.0, 31.0), 34.5(26.3, 55.0), 39.5(29.0, 82.3)U/ L;H = 6.159, P = 0.001], albumin [(44 ± 6),(43 ± 16),(39 ± 3),(33 ± 4)g/ L;F = 9.508, P <0.001], and lactate dehydrogenase [142.5(107.8, 189.3), 198.0(159.5, 238.0), 295.0(251.0, 323.0), 369.5(295.2, 436.3)U/ L;H = 14.225, P <0.001] of patients with COVID-19 in the 4 groups were statistically significantly different.Then the age, C-reactive protein, hematocrit, platelet count, aspartate aminotransferase, albumin, and lactate dehydrogenase were incorporated into multivariate Logistic regression analysis.It showed that the albumin [odds ratio(OR)= 0.756, 95% confidence interval(CI)(0.581, 0.982), P = 0.036] and lactate dehydrogenase [OR = 1.019, 95%CI(1.007, 1.032), P = 0.002] were risk factors for the prognosis of patients with COVID-19.In the meantime, a reliable and intuitive nomogram was obtained by R language software.ROC curve analysis showed that this nomogram had excellent predictive ability for severe and critical patients [area under the curve(AUC)= 0.903, 95%CI(0.831, 0.975), P <0.001], for critical patients alone [AUC = 0.974, 95%CI(0.932, 1.000), P <0.001] and for severe patients alone [AUC = 0.848, 95%CI(0.759, 0.937), P <0.001].Conclusion This nomogram can predict the severity of patients with COVID-19 early and effectively, and may be a practical tool to guide clinical treatment.
来源	中华危重症医学杂志(电子版) ,2020,13(4):258-263 【扩展库】
DOI	10.3877/cma.j.issn.1674-6880.2020.04.004
关键词	新型冠状病毒肺炎 ; 列线图 ; 预后
地址	1. 温州市中心医院急诊科, 浙江, 温州, 325000 2. 温州医科大学附属第一医院重症监护室, 浙江, 温州, 325000
语种	中文
文献类型	研究性论文
ISSN	1674-6880
学科	内科学
基金	浙江省医学创新学科建设计划项目
文献收藏号	CSCD:6823281