Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用

刘欢; 黄晓玲; 代梦莹; 郭杰洁; 高峰

doi:10.12290/xhyxzz.2023-0055

Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用

doi: 10.12290/xhyxzz.2023-0055

刘欢^{1, 2},
黄晓玲^{1, 2},
代梦莹^{1, 2},
郭杰洁^{1, 2},
高峰^{1, 2, ,}

1.
新疆维吾尔自治区人民医院消化内科，乌鲁木齐 830000
2.
新疆消化系统疾病临床医学研究中心，乌鲁木齐 830000

详细信息

通讯作者:
高峰, E-mail: xjgf@sina.com

中图分类号: R511; R446
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出版历程
- 收稿日期: 2023-02-03
- 录用日期: 2023-04-03
- 刊出日期: 2023-09-30

Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis

LIU Huan^{1, 2},
HUANG Xiaoling^{1, 2},
DAI Mengying^{1, 2},
GUO Jiejie^{1, 2},
GAO feng^{1, 2
, ,}

1.
Department of Gastroenterology, People's Hospital of Xinjiang Uygur Autonomous Region, Urumqi 830000, China
2.
Xinjiang Digestive System Disease Clinical Medical Research Center, Urumqi 830000, China

More Information

Corresponding author: GAO Feng, E-mail: xjgf@sina.com

摘要

摘要: 目的分析Omicron BA.5.2变异株感染住院患者临床特征及炎症指标，筛选可能的预后诊断标志物。方法回顾性收集2022年8月1日—11月30日新疆维吾尔自治区人民医院收治的Omicron BA.5.2变异株感染住院患者临床资料，根据疾病严重程度将患者分为轻型、普通型、重型和危重型，比较4组临床资料差异，采用二元Logistic回归法分析与疾病严重程度相关的炎症指标，采用多因素Logistic回归法分析各指标与疾病预后的相关性，采用受试者工作特征(receiver operator characteristic, ROC)曲线分析各指标对疾病严重程度和预后的诊断价值。结果共纳入符合纳入和排除标准的3006例患者，其中男性1522例(50.63%)、女性1484例(49.37%)；平均年龄为(58.72±18.01)(14~96)岁；根据疾病严重程度分为轻型(40.98%，1232/3006)、普通型(52.56%，1580/3006)、重型(4.26%，128/3006)、危重型(2.20%，66/3006)；各组在合并基础疾病(心脏病、糖尿病、高血压、肾脏病、肺部疾病、恶性肿瘤、脑部疾病、病毒性肝炎和自身免疫性疾病)方面均具有显著性差异(P均＜0.01)；住院期间共死亡74例(2.43%)，其中危重型46例(63.01%)、重型19例(26.03%)、普通型7例(9.60%)、轻型2例(2.74%)，年龄≥70岁的死亡患者占比为75.68%(56/74)，所有死亡患者均为合并基础疾病人群；C-反应蛋白(C-reactive protein，CRP)、白蛋白是疾病严重程度的独立危险因素，且CRP与疾病严重程度呈显著正相关(P=0.002)，白蛋白水平与疾病严重程度呈显著负相关(P＜0.001)；CRP、全身炎症反应指数(systemic inflammatory response index，SIRI)、全身免疫炎症指数(systemic immune-inflammation index，SII)为疾病预后的独立危险因素，且CRP(P=0.027)、SIRI(P=0.025)与疾病预后呈显著正相关，SII与疾病预后呈显著负相关(P=0.021)；CRP、白细胞介素-6(interleukin-6，IL-6)、D-二聚体、中性粒细胞与淋巴细胞比值(neutrophil to lymphocyte ratio，NLR)对应的曲线下面积(area under the curve，AUC)均＞0.70，对疾病严重程度分型的诊断价值较高；CRP、IL-6、降钙素原(procalcitonin, PCT)、D-二聚体、肌钙蛋白T(troponin T，TnT)、肌钙蛋白Ⅰ(troponin Ⅰ, TnⅠ)、NLR、SII、血小板与淋巴细胞比值(platelet to lymphocyte ratio，PLR)、单核细胞与淋巴细胞比值(monocyte to lymphocyte ratio，MLR)对应的AUC均＞0.70，对死亡或存活的预后诊断价值较高。结论不同疾病严重程度的Omicron BA.5.2变异株感染住院患者临床特征比较具有显著差异，结合CRP、IL-6、PCT、D-二聚体、TnT、TnⅠ、NLR、SII、PLR、MLR的预测模型可早期识别Omicron BA.5.2变异株感染住院患者中的高危人群，及时进行早期诊断和治疗。
- 新型冠状病毒感染 /
- Omicron BA.5.2 /
- 炎症指标 /
- 临床特征 /
- 预后
Abstract: Objective To analyze the clinical characteristics and inflammatory indicators of hospitalized patients infected with Omicron BA.5.2 variant, and screen for possible prognostic diagnostic markers. Methods We retrospectively collected clinical data from hospitalized patients with Omicron BA.5.2 variant infection admitted to the People's Hospital of Xinjiang Uygur Autonomous Region from August 1 to November 30, 2022. The patients were divided into mild, common, severe, and critically ill patient groups based on the severity of the disease. The differences in clinical data between the four groups were compared, and binary logistic regression was used to analyze inflammation indicators related to the severity of the disease. Multiple logistic regression method and receiver operator characteristic (ROC) curve were used to analyze the correlation between various indicators and patient prognosis, as well as the evaluation value for disease severity and prognosis. Results A total of 3006 patients who met the inclusion and exclusion criteria were included, including 1522 males (50.63%) and 1484 females (49.37%), with an average age of (58.72±18.01)(14-96) years. According to the severity of the disease, they were classified into mild (40.98%, 1232/3006), ordinary (52.56%, 1580/3006), severe (4.26%, 128/3006), and critically severe (2.20%, 66/3006) groups.There were a significant differences(all P < 0.01) in the merging of underlying diseases including cardiac disease, diabetes, hypertension, kidney disease, lung disease, malignant tumor, brain disease, viral hepatitis and autoimmune disease among each group. During the hospitalization period, a total of 74 cases (2.43%) died, including 46 cases of severe illness (63.01%), 19 cases of severe illness (26.03%), 7 cases of ordinary illness (9.60%), and 2 cases of mild illness (2.74%). The proportion of death patients aged≥70 years old was 75.68%(56/74), and all deaths were among those with underlying diseases. C-reactive protein(CRP) and albumin levels were independent risk factors for disease severity, and CRP was significantly positively correlated with disease severity(P=0.002), while albumin levels were significantly negatively correlated with disease severity (P < 0.001). CRP, systemic inflammatory response index (SIRI), and systemic immune inflammation index (SII) were independent risk factors for disease prognosis, and CRP(P=0.027) and SIRI(P=0.025) were significantly positively correlated with disease prognosis, while SII was significantly negatively correlated with disease prognosis (P=0.021). CRP, interleukin-6 (IL-6), D-dimer, and neutrophil to lymphocyte ratio (NLR) had high diagnostic value for disease severity classification with the corresponding area under the aurve(AUC) > 7.0, while CRP, IL-6, procalcitonin (PCT), D-dimer, troponin T(TnT), troponin Ⅰ(TnⅠ), NLR, SII, platelet to lymphocyte ratio (PLR), the monocyte to lymphocyte ratio (MLR) had a high prognostic diagnostic value for death or survival with the corresponding AUC > 0.70. Conclusions There were significant differences in clinical characteristics among hospitalized patients infected with Omicron BA.5.2 variant strains with different disease severity. Combining CRP, IL-6, D-dimer, PCT, D-dimer, TnT, TnⅠ, NLR, SII, PLR, and MLR prediction models may enable early identification of high-risk populations among hospitalized patients infected with Omicron BA.5.2 variant strains, and provide timely diagnosis and treatment.
- coronavirus disease 2019 /
- Omicron BA.5.2 /
- inflammation index /
- clinical characteristics /
- prognosis
注释:

作者贡献：刘欢负责论文设计、数据统计及论文撰写；代梦莹负责收集、整理临床资料及患者随访；郭杰洁负责数据整理、统计、分析；黄晓玲、高峰负责论文设计、实施及修订。

利益冲突：所有作者均声明不存在利益冲突

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图 1 炎症指标预测Omicron BA.5.2感染住院患者疾病严重程度的受试者工作特征曲线

CRP、ESR、IL-6、PCT、TnT、Tn Ⅰ、dNLR、NLR、SII、SIRI、PLR、MLR：同表 1

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图 2 炎症指标预测Omicron BA.5.2感染住院患者疾病预后的受试者工作特征曲线

CRP、ESR、IL-6、PCT、dNLR、NLR、SII、SIRI、PLR、MLR：同表 1

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表 1 3006例Omicron BA.5.2感染住院患者一般资料比较

	轻型(n＝1232)	普通型(n＝1580)	重型(n＝128)	危重型(n＝66)	F/H值	P值
年龄(x±s, 岁)	52.76±17.45	61.60±17.11	72.27±14.76	74.70±14.23	110.939	＜0.001
住院天数(x±s, d)	8.83±7.34	12.44±7.81	13.68±8.75	14.07±7.84	11.486	＜0.001
入院前症状出现时间[M(P₂₅, P₇₅), d]	2.0(2.0, 3.0)	2.0(2.0, 3.0)	2.0(2.0, 3.0)	2.0(2.0, 3.0)	0.507	0.917
BMI(x±s, kg/m²)	23.86±3.40	24.14±3.16	23.86±2.28	24.08±2.27	1.819	0.141
入院氧分压(x±s, mm Hg)	86.93±21.66	87.20±23.49	82.72±28.48	85.66±31.93	1.531	0.204
血氧饱和度(x±s, %)	95.82±2.48	95.69±2.79	93.78±5.58	95.08±3.76	20.494	＜0.001
CRP[M(P₂₅, P₇₅), mg/L]	6.240(2.2, 18.8)	7.875(2.4, 24.5)	53.720(15.5, 100.8)	75.475(23.0, 171.2)	208.752	＜0.001
ESR(x±s, mm/h)	16.59±7.60	17.19±9.18	27.46±20.08	25.64±16.42	66.832	＜0.001
IL-6[M(P₂₅, P₇₅), ng/L]	9.650(4.7, 25.5)	10.475(5.0, 28.4)	38.430(13.2, 104.3)	76.080(30.3, 275.5)	156.806	＜0.001
PCT[M(P₂₅, P₇₅), μg/L]	0.080(0.0, 0.2)	0.090(0.1, 0.2)	0.240(0.1, 0.9)	0.530(0.2, 2.7)	110.902	＜0.001
白蛋白(x±s, g/L)	33.72±14.35	34.72±12.40	31.61±8.17	32.03±8.46	3.659	0.012
球蛋白(x±s, g/L)	28.04±3.95	28.62±3.82	29.96±4.91	28.88±4.45	11.904	＜0.001
D-二聚体[M(P₂₅, P₇₅), mg/L]	0.339(0.1, 0.8)	0.299(0.1, 0.8)	0.893(0.4, 2.2)	1.159(0.6, 5.8)	137.481	＜0.001
肌酐[M(P₂₅, P₇₅), μmol/L]	69.26(55.41, 96.45)	69.94(55.69，96.26)	81.4(55.45, 173.05)	69.90(55.30，91.90)	3.533	0.316
肌酸激酶[M(P₂₅, P₇₅), U/L]	69.000(44.0, 117.0)	70.000(44.0, 126.0)	76.000(45.5, 142.5)	106.000(64.8, 413.0)	22.08	＜0.001
TnT[M(P₂₅, P₇₅), μg/L]	0.015(0.0, 0.0)	0.014(0.0, 0.0)	0.033(0.0, 0.1)	0.065(0.0, 0.2)	82.581	＜0.001
TnⅠ[M(P₂₅, P₇₅), μg/L]	0.019(0.0, 0.1)	0.011(0.0, 0.0)	0.035(0.0, 0.2)	0.080(0.0, 0.5)	89.339	＜0.001
白细胞计数(x±s, 10⁹/L)	5.66±2.54	6.32±2.76	8.09±4.38	10.34±4.97	82.378	＜0.001
淋巴细胞计数(x±s, 10⁹/L)	1.38±0.67	1.32±0.68	0.80±0.50	0.81±0.66	41.036	＜0.001
单核细胞计数(x±s, 10⁹/L)	0.45±0.18	0.47±0.20	0.47±0.24	0.42±0.21	5.047	0.002
中性粒细胞计数(x±s, 10⁹/L)	3.64±2.08	4.20±2.22	4.85±2.86	5.60±2.90	32.765	＜0.001
血小板计数(x±s, 10⁹/L)	202.03±73.81	197.47±73.60	160.45±68.13	155.97±68.45	19.426	＜0.001
dNLR[M(P₂₅, P₇₅)]	1.670(1.1, 2.6)	2.090(1.3, 3.3)	3.460(0.8, 5.4)	2.090(0.5, 4.5)	58.486	＜0.001
NLR(x±s)	3.48±3.25	4.24±3.77	7.17±5.55	7.12±3.62	57.516	＜0.001
SII(x±s)	686.23±676.52	826.52±773.60	1088.07±966.25	1273.54±919.02	25.095	＜0.001
SIRI[M(P₂₅, P₇₅)]	1.010(0.5, 2.0)	1.340(0.7, 2.8)	2.555(1.3, 4.7)	2.640(1.9, 5.6)	151.871	＜0.001
PLR(x±s)	174.67±97.85	180.33±105.17	234.66±136.72	239.75±123.91	19.793	＜0.001
MLR(x±s)	0.42±0.30	0.45±0.30	0.63±0.38	0.65±0.33	31.351	＜0.001
BMI：体质量指数；CRP：C-反应蛋白；ESR：红细胞沉降率；IL-6：白细胞介素-6；PCT：降钙素原；TnT：肌钙蛋白T；Tn Ⅰ：肌钙蛋白Ⅰ；NLR：中性粒细胞与淋巴细胞比值；dNLR：动态NLR；SII：全身免疫炎症指数；SIRI：全身炎症反应指数；PLR：血小板与淋巴细胞比值；MLR：单核细胞与淋巴细胞比值

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表 2 3006例Omicron BA.5.2住院患者疾病严重程度影响因素分析

指标	回归系数	标准误	Z值	χ²	P值	OR值	95% CI
年龄(岁)	0.020	0.015	1.288	1.659	0.198	1.020	0.990~1.051
住院天数(d)	0.988	0.788	1.254	1.573	0.210	2.686	0.573~12.579
血氧饱和度(%)	-0.020	0.034	-0.580	0.337	0.562	0.981	0.918~1.048
CRP(mg/L)	0.015	0.005	3.133	9.819	0.002	1.015	1.006~1.025
ESR(mm/h)	-0.012	0.010	-1.158	1.342	0.247	0.989	0.969~1.008
IL-6(ng/L)	0.000	0.001	0.851	0.723	0.395	1.000	0.999~1.002
PCT(μg/L)	0.094	0.110	0.859	0.738	0.390	1.099	0.886~1.362
白蛋白(g/L)	-0.191	0.042	-4.578	20.954	＜0.001	0.826	0.761~0.896
球蛋白(g/L)	0.076	0.043	1.779	3.163	0.075	1.079	0.992~1.173
D-二聚体(mg/L)	-0.000	0.039	-0.007	0.000	0.995	1.000	0.926~1.080
肌酸激酶(U/L)	0.000	0.000	0.842	0.709	0.400	1.000	1.000~1.001
TnT(μg/L)	0.619	1.040	0.595	0.354	0.552	1.857	0.242~14.263
TnⅠ(μg/L)	-0.092	0.252	-0.366	0.134	0.715	0.912	0.557~1.494
dNLR	-0.031	0.032	-0.984	0.967	0.325	0.969	0.911~1.032
NLR	0.037	0.056	0.659	0.434	0.510	1.038	0.929~1.159
SII	0.000	0.000	0.465	0.216	0.642	1.000	0.999~1.001
SIRI	-0.340	0.185	-1.837	3.375	0.066	0.712	0.495~1.023
PLR	0.001	0.003	0.315	0.099	0.753	1.001	0.994~1.008
MLR	1.618	1.181	1.369	1.875	0.171	5.041	0.498~51.062
CRP、ESR、IL-6、PCT、TnT、Tn Ⅰ、dNLR、NLR、SII、SIRI、PLR、MLR：同表 1；McFadden R²=0.433；Cox & Snell R²=0.447；Nagelkerke R²=0.599

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表 3 3006例Omicron BA.5.2感染住院患者疾病预后影响因素分析

指标	回归系数	标准误	Z值	χ²	P值	OR值	95% CI
年龄(岁)	0.025	0.021	1.220	1.488	0.223	1.026	0.985~1.068
住院天数(d)	-0.990	1.114	-0.889	0.790	0.374	0.372	0.042~3.295
血氧饱和度(%)	0.021	0.033	0.620	0.385	0.535	1.021	0.957~1.089
CRP(mg/L)	0.008	0.003	2.214	4.902	0.027	1.008	1.001~1.015
ESR(mm/h)	-0.010	0.011	-0.860	0.739	0.390	0.990	0.969~1.012
IL-6(ng/L)	0.000	0.000	0.927	0.860	0.354	1.000	1.000~1.001
PCT(μg/L)	-0.042	0.030	-1.419	2.013	0.156	0.959	0.904~1.016
白蛋白(g/L)	-0.069	0.047	-1.467	2.153	0.142	0.933	0.851~1.024
球蛋白(g/L)	-0.044	0.052	-0.850	0.723	0.395	0.957	0.864~1.059
D-二聚体(mg/L)	-0.034	0.046	-0.735	0.540	0.463	0.967	0.883~1.058
肌酸激酶(U/L)	0.001	0.000	1.658	2.748	0.097	1.001	1.000~1.001
TnT(μg/L)	0.053	1.267	0.042	0.002	0.967	1.055	0.088~12.622
TnⅠ(μg/L)	0.428	0.284	1.507	2.271	0.132	1.534	0.879~2.676
dNLR	-0.172	0.112	-1.539	2.369	0.124	0.842	0.676~1.048
NLR	0.075	0.059	1.275	1.625	0.202	1.078	0.960~1.211
SII	-0.001	0.001	-2.317	5.367	0.021	0.999	0.998~1.000
SIRI	0.375	0.168	2.237	5.003	0.025	1.455	1.047~2.021
PLR	0.006	0.004	1.389	1.929	0.165	1.006	0.998~1.014
MLR	-1.273	1.361	-0.935	0.874	0.350	0.280	0.019~4.036
CRP、ESR、IL-6、PCT、TnT、Tn Ⅰ、dNLR、NLR、SII、SIRI、PLR、MLR：同表 1；McFadden R²=0.391；Cox & Snell R²=0.273；Nagelkerke R²=0.490

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表 4 3006例Omicron BA.5.2感染住院患者疾病严重程度诊断预测价值

指标	AUC	95% CI	标准误	P值
年龄(岁)	0.648	0.533~0.762	0.058	0.012
住院天数(d)	0.493	0.372~0.613	0.061	0.906
血氧饱和度(%)	0.461	0.339~0.582	0.062	0.523
CRP(mg/L)	0.830	0.751~0.909	0.040	＜0.001
ESR(mm/h)	0.662	0.553~0.770	0.055	0.004
IL-6(ng/L)	0.757	0.660~0.853	0.049	＜0.001
PCT(μg/L)	0.691	0.584~0.799	0.055	＜0.001
白蛋白(g/L)	0.249	0.151~0.346	0.050	＜0.001
球蛋白(g/L)	0.613	0.494~0.732	0.061	0.063
D-二聚体(mg/L)	0.777	0.685~0.868	0.047	＜0.001
肌酸激酶(U/L)	0.529	0.409~0.649	0.061	0.634
TnT(μg/L)	0.692	0.589~0.795	0.053	＜0.001
TnⅠ(μg/L)	0.683	0.577~0.790	0.054	0.001
dNLR	0.511	0.376~0.646	0.069	0.875
NLR	0.706	0.592~0.821	0.058	＜0.001
SII	0.658	0.542~0.773	0.059	0.007
SIRI	0.636	0.523~0.749	0.058	0.019
PLR	0.643	0.524~0.761	0.060	0.018
MLR	0.643	0.526~0.760	0.060	0.016
CRP、ESR、IL-6、PCT、TnT、Tn Ⅰ、dNLR、NLR、SII、SIRI、PLR、MLR: 同表 1; AUC: 曲线下面积

下载: 导出CSV

表 5 3006例Omicron BA.5.2感染住院患者疾病预后预测价值

指标	AUC	95% CI	标准误	P值
年龄(岁)	0.590	0.409~0.770	0.092	0.330
住院天数(d)	0.267	0.098~0.435	0.086	0.007
血氧饱和度(%)	0.332	0.180~0.485	0.078	0.031
CRP(mg/L)	0.805	0.697~0.914	0.055	＜0.001
ESR(mm/h)	0.668	0.491~0.845	0.090	0.063
IL-6(ng/L)	0.836	0.724~0.949	0.057	＜0.001
PCT(μg/L)	0.770	0.624~0.916	0.075	＜0.001
白蛋白(g/L)	0.168	0.071~0.265	0.050	＜0.001
球蛋白(g/L)	0.509	0.318~0.699	0.097	0.928
D-二聚体(mg/L)	0.875	0.800~0.950	0.038	＜0.001
肌酸激酶(U/L)	0.612	0.426~0.798	0.095	0.239
TnT(μg/L)	0.760	0.624~0.897	0.070	＜0.001
TnⅠ(μg/L)	0.774	0.655~0.894	0.061	＜0.001
dNLR	0.463	0.264~0.662	0.102	0.715
NLR	0.767	0.624~0.909	0.073	＜0.001
SII	0.704	0.547~0.861	0.080	0.011
SIRI	0.662	0.506~0.818	0.080	0.042
PLR	0.741	0.564~0.917	0.090	0.007
MLR	0.784	0.636~0.933	0.076	＜0.001
CRP、ESR、IL-6、PCT、TnT、Tn Ⅰ、dNLR、NLR、SII、SIRI、PLR、MLR：同表 1

下载: 导出CSV

参考文献(22)

[1]	Qiu W, Shi Q, Chen F, et al. The derived neutrophil to lymphocyte ratio can be the predictor of prognosis for COVID-19 Omicron BA. 2 infected patients[J]. Front Immunol, 2022, 13: 1065345. doi: 10.3389/fimmu.2022.1065345
[2]	Ruan Q, Yang K, Wang W, et al. Clinical predictors of mortality due to COVID- 19 based on an analysis of data of 150 patients from wuhan, China[J]. Intensive Care Med, 2020, 46: 846-848. doi: 10.1007/s00134-020-05991-x
[3]	Citu C, Gorun F, Motoc A, et al. The predictive role of NLR, d-NLR, MLR, and SIRI in COVID-19 mortality[J]. Diagnostics (Basel Switzerland), 2022, 12: 122.
[4]	Ortega-Rojas S, Salazar-Talla L, Romero-Cerdán A, et al. The neutrophil-to-Lymphocyte ratio and the platelet-to Lymphocyte ratio as predictors of mortality in older adults hospitalized with COVID-19 in Peru[J]. Dis Markers, 2022, 2022: 2497202.
[5]	国家卫生健康委员会办公厅, 国家中医药管理局办公室. 新型冠状病毒肺炎诊疗方案(试行第九版)[EB/OL ]. (2022-03-14)[ 2023-02-03 ]. http://www.gov.cn/zhengce/zhengceku/2022-03/15/5679257/files/49854a49c7004f4ea9e622f3f2c568d8.pdf.
[6]	Robson F, Khan KS, Le TK, et al. Coronavirus RNA Proofreading: Molecular Basis and Therapeutic Targeting[J]. Mol Cell, 2020, 79: 710-727. doi: 10.1016/j.molcel.2020.07.027
[7]	Garland V, Kumar AB, Borum ML, et al. Gastrointestinal and Hepatic Manifestations of COVID-19: Evolving Recognition and Need for Increased Understanding in Vulnerable Populations[J]. J Natl Med Assoc, 2021, 113: 142-146.
[8]	Viana R, Moyo S, Amoako DG, et al. Rapid epidemic expansion of the SARS-CoV-2 Omicron variant in southern Africa[J]. Nature, 2022, 603: 679-686. doi: 10.1038/s41586-022-04411-y
[9]	Adam D. What scientists know about new, fast-spreading coronavirus variants[J]. Nature, 2021, 594: 19-20. doi: 10.1038/d41586-021-01390-4
[10]	Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China[J]. Lancet, 2020, 395: 497-506. doi: 10.1016/S0140-6736(20)30183-5
[11]	张炜宗, 袁红, 孙金栋, 等. 新型冠状病毒感染患者院内死亡危险因素的Meta分析[J]. 中国全科医学, 2023, 26: 607-620. https://www.cnki.com.cn/Article/CJFDTOTAL-QKYX202305013.htm
[12]	de Jong VMT, Rousset RZ, Antonio-Villa NE, et al. Bello-Chavolla OY, et al. Clinical prediction models for mortality in patients with COVID-19: external validation and individual participant data meta-analysis[J]. BMJ, 2022, 378: e069881.
[13]	Hu C, Liu Z, Jiang Y, et al. Early prediction of mortality risk among patients with severe COVID-19, using machine learning[J]. Int J Epidemiol, 2021, 49: 1918-1929. doi: 10.1093/ije/dyaa171
[14]	Tehrani S, Killander A, Åstrand P, et al. Risk factors for death in adult COVID-19 patients: Frailty predicts fatal outcome in older patients[J]. Int J Infect Dis, 2021, 102: 415-421. doi: 10.1016/j.ijid.2020.10.071
[15]	Goodarzi P, Mahdavi F, Mirzaei R, et al. Coronavirus disease 2019 (COVID-19): Immunological approaches and emerging pharmacologic treatments[J]. Int Immunopharmacol, 2020, 88: 106885. doi: 10.1016/j.intimp.2020.106885
[16]	Karampoor S, Hesamizadeh K, Maleki F, et al. A possible pathogenic correlation between neutrophil elastase (NE) enzyme and inflflammation in the pathogenesis of coronavirus disease 2019 (COVID-19)[J]. Int Immunopharmacol, 2021, 100: 108137. doi: 10.1016/j.intimp.2021.108137
[17]	Batabyal R, Freishtat N, Hill E, et al. Metabolic dysfunc-tion and immunometabolism in COVID-19 pathophysiology and therapeutics[J]. Int J Obes, 2021, 45: 1163-1169. doi: 10.1038/s41366-021-00804-7
[18]	Xiao F, Tang M, Zheng X, et al. Evidence for gastrointestinal infection of SARS-CoV-2[J]. Gastroenterology, 2020, 158: 1831-1833. e3. doi: 10.1053/j.gastro.2020.02.055
[19]	Tian Y, Rong L, Nian W, et al. Review article: gastrointestinal features in COVID-19 and the possibility of faecal transmission[J]. Aliment Pharmacol Ther, 2020, 51: 843-851. doi: 10.1111/apt.15731
[20]	Liu C, Li L, Song K, et al. A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study[J]. J Immunother Cancer, 2020, 8: e001314. doi: 10.1136/jitc-2020-001314
[21]	Cai J, Li H, Zhang C, et al. The neutrophil-to-Lymphocyte ratio determines clinical efficacy of corticosteroid therapy in patients with COVID-19[J]. Cell Metab, 2021, 33: 258-269. e3. doi: 10.1016/j.cmet.2021.01.002
[22]	Xia W, Tan Y, Hu S, et al. Predictive value of systemic immune-inflammation index and neutrophil-to-Lymphocyte ratio in patients with severe COVID-19[J]. Clin Appl Thromb Hemost, 2022, 28: 10760296221111391.

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Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用

doi: 10.12290/xhyxzz.2023-0055

通讯作者:
高峰, E-mail: xjgf@sina.com

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Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis

Corresponding author: GAO Feng, E-mail: xjgf@sina.com

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Omicron BA.5.2变异株感染住院患者临床特征及炎症指标对疾病预后的预测作用

doi: 10.12290/xhyxzz.2023-0055

通讯作者: 高峰, E-mail: xjgf@sina.com

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出版历程

Clinical Characteristics and Inflammatory Markers of Omicron BA.5.2 Variant Infection in Hospitalized Patients and Their Predictive Role in Disease Prognosis

Corresponding author: GAO Feng, E-mail: xjgf@sina.com

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出版历程

目录

通讯作者:
高峰, E-mail: xjgf@sina.com