慢性阻塞性肺疾病急性加重期预后的临床分析

doi:10.3877/cma.j.issn.1674-6902.2023.04.026

目的

分析慢性阻塞性肺病急性加重期(acute exacerbation of chronic obstructive pulmonary disease, AECOPD)预后影响因素，建立预测模型。

方法

选择2019年6月至2022年6月我院收治的AECOPD患者79例，将预后不良21例为观察组，58例为对照组，比较两组基础资料、实验室结果等指标，多因素Logistics回归分析。

结果

观察组中13例行有创机械通气，8例住院期间死亡；对照组经治疗后病情平稳，出院1个月后无再次急性发作。两组呼吸频率(25.57±2.40 vs. 23.27±3.89)、嗜酸性粒细胞(113.74±45.79 vs. 162.84±64.41)、血红蛋白(115.26±13.28 vs. 122.56±10.60)、尿素氮(9.91±1.27 vs. 8.67±2.32)、PaCO₂(67.19±11.66 vs. 60.01±12.77)、乳酸(2.74±0.74 vs. 2.20±0.65)，P<0.05。多因素Logistics回归发现呼吸频率(OR＝ 0.815，95%CI: 0.681~0.976)、尿素氮(OR＝0.725，95%CI: 0.539~0.977)、PaCO₂(OR＝0.945，95%CI: 0.903~0.988)、乳酸(OR＝ 0.380，95%CI: 0.176~0.821)是AECOPD不良预后的危险因素，嗜酸性粒细胞(OR＝1.013，95%CI: 1.002~1.024)、血红蛋白(OR＝1.061，95%CI: 1.009~1.116)是AECOPD预后不良的保护性因素。绘制列线图，预后不良相关因素C-index为0.902(95%CI: 0.856~0.949)，AUC为0.902(95%CI: 0.855~0.950)，平均绝对误差0.053。

结论

呼吸频率、嗜酸性粒细胞、血红蛋白、尿素氮、PaCO₂、乳酸等指标是AECOPD患者预后不良的影响因素，早期识别、早期救治重症患者具有临床意义。

关键词: 急性加重期，肺疾病，慢性阻塞性, 预后, 临床分析

表1 两组临床资料比较

临床资料	观察组(n＝21)	对照组(n＝58)	卡方/t值	P值
年龄	76.620±9.206	74.077±8.117	1.333	0.184
性别(男/女)	13/8	39/19	0.195	0.659
吸烟史	18(85.71%)	46(79.31%)	0.411	0.521
呼吸频率(次/min)	25.57±2.40	23.27±3.89	3.807	0.001
白细胞(×10⁹/L)	13.49±1.70	12.69±2.77	1.866	0.070
中性粒细胞(×10⁹/L)	8.06±1.06	7.56±1.28	1.988	0.057
嗜酸性粒细胞(×10⁶/L)	113.74±45.79	162.84±64.41	－3.385	0.001
红细胞(×10¹²/L)	4.89±0.49	4.74±0.70	1.329	0.193
血小板(×10⁹/L)	210.23±44.38	195.23±54.20	1.421	0.166
血红蛋白(g/L)	115.26±13.28	122.56±10.60	－2.452	0.023
谷草转氨酶(U/L)	36.82±6.70	34.37±8.32	1.538	0.135
谷丙转氨酶(U/L)	36.11±6.51	33.92±9.49	1.369	0.181
白蛋白(g/L)	37.90±4.20	39.35±4.53	－1.468	0.149
碱性磷酸酶(U/L)	85.40±23.68	77.97±27.67	1.327	0.196
血肌酐(μmol/L)	73.61±16.34	66.27±18.91	1.907	0.067
尿素氮(mmol/L)	9.91±1.27	8.67±2.32	2.401	0.017
钙(mmol/L)	2.46±0.12	2.51±0.17	－1.740	0.092
pH	7.39±0.03	7.40±0.03	－1.238	0.226
PaO₂(mmHg)	87.83±4.35	89.89±5.44	－1.986	0.057
PaCO₂(mmHg)	67.19±11.66	60.01±12.77	2.636	0.014
BE(mmol/L)	0.43±1.53	－0.02±1.65	1.280	0.212
乳酸(mmol/L)	2.74±0.74	2.20±0.65	3.214	0.004
FEV₁/FVC%	59.32±5.20	61.04±6.37	－1.395	0.174

表1 两组临床资料比较

临床资料	观察组(n＝21)	对照组(n＝58)	卡方/t值	P值
年龄	76.620±9.206	74.077±8.117	1.333	0.184
性别(男/女)	13/8	39/19	0.195	0.659
吸烟史	18(85.71%)	46(79.31%)	0.411	0.521
呼吸频率(次/min)	25.57±2.40	23.27±3.89	3.807	0.001
白细胞(×10⁹/L)	13.49±1.70	12.69±2.77	1.866	0.070
中性粒细胞(×10⁹/L)	8.06±1.06	7.56±1.28	1.988	0.057
嗜酸性粒细胞(×10⁶/L)	113.74±45.79	162.84±64.41	－3.385	0.001
红细胞(×10¹²/L)	4.89±0.49	4.74±0.70	1.329	0.193
血小板(×10⁹/L)	210.23±44.38	195.23±54.20	1.421	0.166
血红蛋白(g/L)	115.26±13.28	122.56±10.60	－2.452	0.023
谷草转氨酶(U/L)	36.82±6.70	34.37±8.32	1.538	0.135
谷丙转氨酶(U/L)	36.11±6.51	33.92±9.49	1.369	0.181
白蛋白(g/L)	37.90±4.20	39.35±4.53	－1.468	0.149
碱性磷酸酶(U/L)	85.40±23.68	77.97±27.67	1.327	0.196
血肌酐(μmol/L)	73.61±16.34	66.27±18.91	1.907	0.067
尿素氮(mmol/L)	9.91±1.27	8.67±2.32	2.401	0.017
钙(mmol/L)	2.46±0.12	2.51±0.17	－1.740	0.092
pH	7.39±0.03	7.40±0.03	－1.238	0.226
PaO₂(mmHg)	87.83±4.35	89.89±5.44	－1.986	0.057
PaCO₂(mmHg)	67.19±11.66	60.01±12.77	2.636	0.014
BE(mmol/L)	0.43±1.53	－0.02±1.65	1.280	0.212
乳酸(mmol/L)	2.74±0.74	2.20±0.65	3.214	0.004
FEV₁/FVC%	59.32±5.20	61.04±6.37	－1.395	0.174

表2 不良预后相关指标多元Logistics回归分析

相关因素	β	标准误差	Wald	P值	OR	95%置信区间
相关因素	β	标准误差	Wald	P值	OR	下限	上限
呼吸频率	－0.204	0.092	4.941	0.026	0.815	0.681	0.976
嗜酸性粒细胞	－0.130	0.005	5.805	0.016	1.013	1.002	1.024
血红蛋白	0.060	0.026	5.371	0.020	1.061	1.009	1.116
尿素氮	－0.321	0.152	4.469	0.035	0.725	0.539	0.977
PaCO₂	－0.057	0.023	6.162	0.013	0.945	0.903	0.988
乳酸	－0.967	0.393	6.058	0.014	0.380	0.176	0.821
常量	7.267	4.244	2.932	－	－	－	－

表2 不良预后相关指标多元Logistics回归分析

相关因素	β	标准误差	Wald	P值	OR	95%置信区间
相关因素	β	标准误差	Wald	P值	OR	下限	上限
呼吸频率	－0.204	0.092	4.941	0.026	0.815	0.681	0.976
嗜酸性粒细胞	－0.130	0.005	5.805	0.016	1.013	1.002	1.024
血红蛋白	0.060	0.026	5.371	0.020	1.061	1.009	1.116
尿素氮	－0.321	0.152	4.469	0.035	0.725	0.539	0.977
PaCO₂	－0.057	0.023	6.162	0.013	0.945	0.903	0.988
乳酸	－0.967	0.393	6.058	0.014	0.380	0.176	0.821
常量	7.267	4.244	2.932	－	－	－	－

图1 AECOPD患者预后不良模型列线图

图2 AECOPD患者预后不良模型决策曲线

1	Feng Zhouzhou, Zhang Lu, Yu Haichuan, et al. High-flow nasal cannula oxygen therapy versus non-invasive ventilation for AECOPD patients after extubation: A systematic review and Meta-analysis of randomized controlled trials[J]. Int J Chron Obstruct Pulmon Dis, 2022, 17: 1987-1999.
2	Xu Jie, Wang Xudong, Li Zhihai, et al. AECOPD research in the past ten years: a bibliographic analysis based on Web of Science[J]. Ann Palliat Med, 2021, 10(10): 10401-10413.
3	Chen Cai, Liu Xuejian, Wang Xianfeng, et al. Risk of temperature, humidity and concentrations of air pollutants on the hospitalization of AECOPD[J]. PLoS One, 2019, 14(11): e0225307.
4	Wang Ruiying, Zhaoyun, Xu Jianying, et al. Clinical features and three-year prognosis of AECOPD patients with different levels of blood eosinophils[J]. Heart Lung, 2022，56: 29-39.
5	中华医学会呼吸病学分会慢性阻塞性肺疾病学组，中国医师协会呼吸医师分会慢性阻塞性肺疾病工作委员会. 慢性阻塞性肺疾病诊治指南(2021年修订版)[J]. 中华结核和呼吸杂志，2021, 44(3): 170-205.
6	慢性阻塞性肺疾病急性加重抗感染治疗中国专家共识编写组. 慢性阻塞性肺疾病急性加重抗感染治疗中国专家共识[J]. 国际呼吸杂志，2019, 39(17): 1281-1296.
7	文富强，申永春. 基于线粒体动力学的慢性阻塞性肺疾病发病机制与保护策略[J]. 西南医科大学学报，2022, 45(5): 369-372.
8	任成山，王关嵩，钱桂生. 慢性阻塞性肺疾病的成因及其治疗的困惑与希望[J/CD]. 中华肺部疾病杂志(电子版), 2019, 12(2): 127-141.
9	Chang Chun, Zhu Hong, Shen Ning, et al. Bacterial infection, airway and systemic inflammation and clinical outcomes before and after treatment of AECOPD, a longitudinal and cross-sectional study[J]. COPD, 2015, 12(1): 19-30.
10	Choi Juwhan, Oh Jee Youn, Lee Young Seok, et al. The association between blood eosinophil percent and bacterial infection in acute exacerbation of chronic obstructive pulmonary disease[J]. Int J Chron Obstruct Pulmon Dis, 2019, 14: 953-959.
11	Kalemci Serdar, Bozdag Huriye Gülistan. Do blood eosinophil levels affect the prognosis of AECOPD patients? [J]. Heart Lung, 2022, 56: 182.
12	Ohnishi Hiroshi, Eitoku Masamitsu, Yokoyama Akihito. A systematic review and integrated analysis of biologics that target Type 2 inflammation to treat COPD with increased peripheral blood eosinophils[J]. Heliyon, 2022, 8(6): e09736.
13	Ren Jing, Sun Yong, Li Gang, et al. Tumor necrosis factor-α，interleukin-8 and eosinophil cationic protein as serum markers of glucocorticoid efficacy in the treatment of bronchial asthma[J]. Respir Physiol Neurobiol, 2018, 258: 86-90.
14	Antus Balazs, Barta Imre. Blood eosinophils and exhaled nitric oxide：Surrogate biomarkers of airway eosinophilia in stable COPD and exacerbation[J]. Biomedicines, 2022, 10(9): 2128.
15	Gong Yaya, Sun Hongyan. Stability of blood eosinophils in COPD with multiple acute exacerbations within 1 year and its relationship with prognosis[J]. Int J Chron Obstruct Pulmon Dis, 2022, 17: 3123-3128.
16	Han Huishan, Hu Siying, Du Juan. Predictive value of the hemoglobin-albumin-lymphocyte-platelet (HALP) index for ICU mortality in patients with acute exacerbations of chronic obstructive pulmonary disease (AECOPD)[J]. Intern Emerg Med, 2023, 18(1): 85-96.
17	Trudzinski FC, Jörres RA, Alter P, et al. Associations of oxygenated hemoglobin with disease burden and prognosis in stable COPD: Results from COSYCONET[J]. Sci Rep, 2020, 10(1): 10544.
18	Park Seon Cheol, Kim Young Sam, Kang Young Ae, et al. Hemoglobin and mortality in patients with COPD: a nationwide population-based cohort study[J]. Int J Chron Obstruct Pulmon Dis, 2018, 13: 1599-1605.
19	Pépin Jean-Louis, Degano Bruno, Tamisier Renaud, et al. Remote monitoring for prediction and management of acute exacerbations in chronic obstructive pulmonary disease (AECOPD)[J]. Life (Basel), 2022, 12(4): 499.
20	Naranjo-Hernández David, Talaminos-Barroso Alejandro, Reina-Tosina Javier, et al. Smart vest for respiratory rate monitoring of COPD patients based on non-contact capacitive sensing[J]. Sensors (Basel), 2018, 18(7): 2144.
21	Zhang Xiaodiao, Miao Xiaqi, Ding Keke, et al. The relationship of partial pressure of carbon dioxide (PaCO₂) with disease severity indicators such as BODE and GOLD in hospitalized COPD patients[J]. Int J Clin Pract, 2022, 2022: 4205079.
22	Csoma Balázs, Vulpi Maria Rosaria, Dragonieri Silvano, et al. Hypercapnia in COPD: Causes, Consequences, and Therapy[J]. J Clin Med, 2022, 11(11): 3180.
23	Storgaard Line Hust, Hockey Hans-Ulrich, Weinreich Ulla Møller. Development in PaCO₂ over 12 months in patients with COPD with persistent hypercapnic respiratory failure treated with high-flow nasal cannula-post-hoc analysis from a randomised controlled trial[J]. BMJ Open Respir Res, 2020, 7(1): e000712.
24	Rees Stephen E, Rychwicka-Kielek Beate A, Andersen Bjarne F, et al. Calculating acid-base and oxygenation status during COPD exacerbation using mathematically arterialised venous blood[J]. Clin Chem Lab Med, 2012, 50(12): 2149-2154.
25	Ba Abdoulaye, Delliaux Stephane, Bregeon Fabienne, et al. Post-exercise heart rate recovery in healthy, obeses, and COPD subjects: relationships with blood lactic acid and PaO₂ levels[J]. Clin Res Cardiol, 2009, 98(1): 52-58.
26	Pelaia Corrado, Pastori Daniele, Armentaro Giuseppe, et al. Predictors of renal function worsening in patients with chronic obstructive pulmonary disease (COPD): A multicenter observational study[J]. Nutrients, 2021, 13(8): 2811.
27	Akahane Jumpei, Ushiki Atsuhito, Kosaka Makoto, et al. Blood urea nitrogen-to-serum albumin ratio and A-DROP are useful in assessing the severity of Pneumocystis pneumonia in patients without human immunodeficiency virus infection[J]. J Infect Chemother, 2021, 27(5): 707-714.
28	Xia Bingtian, Song Bingxin, Zhang Jingcheng, et al. Prognostic value of blood urea nitrogen-to-serum albumin ratio for mortality of pneumonia in patients receiving glucocorticoids: Secondary analysis based on a retrospective cohort study[J]. J Infect Chemother, 2022, 28(6): 767-773.
29	John Michelle, Hussain Samia, Prayle Andrew, et al. Target renal damage: the microvascular associations of increased aortic stiffness in patients with COPD[J]. Respir Res, 2013, 14(1): 31.
30	Zhang Jiarui, Qin Yichun, Zhou Chen, et al. Elevated BUN upon admission as a predictor of in-hospital mortality among patients with acute exacerbation of COPD: A secondary analysis of multicenter cohort study[J]. Int J Chron Obstruct Pulmon Dis, 2023, 18: 1445-1455.

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Clinical analysis of prognosis in acute exacerbation of chronic obstructive pulmonary disease

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Clinical analysis of prognosis in acute exacerbation of chronic obstructive pulmonary disease