慢性阻塞性肺疾病患者合并贫血的危险因素分析及风险预测模型的构建

doi:10.19983/j.issn.2096-8493.2024003

结核与肺部疾病杂志 ›› 2024, Vol. 5 ›› Issue (1): 20-27.doi: 10.19983/j.issn.2096-8493.2024003

慢性阻塞性肺疾病患者合并贫血的危险因素分析及风险预测模型的构建

傅一婷¹, 刘蕾², 赵倩¹, 孟继娴¹, 甄紫伊¹, 王暘³, 李荣梅¹()

¹沈阳医学院公共卫生学院,沈阳 110034
²辽宁中医药大学护理学院,沈阳 116600
³沈阳医学院附属第二医院呼吸内科,沈阳 110035

收稿日期:2023-11-19 出版日期:2024-02-20 发布日期:2024-02-02
通信作者: 李荣梅,Email:lrm7696@163.com
基金资助:
辽宁省2022年社会科学规划基金(L22BCL047);沈阳医学院硕士研究生科技创新基金(Y20220513);2024年度辽宁省经济社会发展研究课题(2024lslybkt-032)

Analysis of risk factors and construction of risk prediction model for anemia in patients with chronic obstructive pulmonary disease

Fu Yiting¹, Liu Lei², Zhao Qian¹, Meng Jixian¹, Zhen Ziyi¹, Wang Yang³, Li Rongmei¹()

¹Department of Public Health, Shenyang Medical College, Shenyang 110034, China
²Department of Nursing, Liaoning University of Traditional Chinese Medicine, Shenyang 116600, China
³Department of Respiratory Medicine, the Second Affiliated Hospital of Shenyang Medical College, Shenyang 110035, China

Received:2023-11-19 Online:2024-02-20 Published:2024-02-02
Contact: Li Rongmei, Email: lrm7696@163.com
Supported by:
Social Science Planning Fund 2022 of Liaoning Province(L22BCL047);Shenyang Medical College Master’s Science and Technology Innovation Fund(Y20220513);2024 Research Project on Economic and Social Development of Liaoning Province(2024lslybkt-032)

摘要/Abstract

摘要：

目的: 探讨慢性阻塞性肺疾病(简称“慢阻肺”)患者合并贫血的危险因素,并构建列线图预测模型。方法: 回顾性选取2019年12月至2023年3月沈阳医学院附属第二医院呼吸内科收治的492例慢阻肺患者为研究对象,运用LASSO回归进行危险因素筛选,采用多因素logistic回归分析方法构建慢阻肺患者发生贫血的预测模型,并构建列线图预测模型。采用Bootstrap重抽样法对模型进行内部验证,利用校准曲线及其C指数评估模型的区分度,分别利用受试者工作特征(ROC)曲线的曲线下面积(AUC)和临床决策曲线(DCA)评价列线图预测模型的预测能力和临床适用性。结果: 492例慢阻肺患者中,19.51%(96/492)的患者存在贫血。LASSO回归分析筛选出9个候选预测因子,分别为性别、肌酐、低蛋白血症、糖尿病、高血压、新型冠状病毒感染、红细胞计数(RBC)、血红蛋白(Hb)、体质量指数(BMI)。将9个候选预测因子纳入logistic回归分析,结果显示,性别为女性(OR=3.353,95%CI:1.530~7.349)、肌酐水平升高(OR=1.024,95%CI:1.010~1.037)、Hb水平升高(OR=0.928,95%CI:0.905~0.951)、合并低蛋白血症(OR=6.239,95%CI:2.845~13.678)、合并糖尿病(OR=0.198,95%CI:0.056~0.703)均为慢阻肺发生贫血的独立影响因素。采用Bootstrap法构建的列线图预测模型显示,校准曲线拟合良好,其C指数为0.933(95%CI:0.910~1.848),提示模型区分度良好,AUC为0.933(95%CI:0.910~0.957),DCA曲线显示模型具有良好的正向净收益。结论: 构建的慢阻肺合并贫血列线图预测模型简便、准确,对于临床早期甄别贫血高危人群与个体化精准防治措施的制定具有一定价值。

关键词: 肺疾病, 慢性阻塞性, 贫血, 因素分析, 统计学, 预测, 列线图

Abstract:

Objective: To explore the risk factors of anemia in patients with chronic obstructive pulmonary disease (COPD), and construct a nomograph prediction model. Methods: COPD patients admitted to the Respiratory Department of the Second Affiliated Hospital of Shenyang Medical College from December 2019 to March 2023 were retrospectively selected as the study objects (492 patients). LASSO regression was used to screen risk factors, and logistic regression analysis was used to construct a prediction model of anemia in COPD patients, and a nomogram prediction model was constructed. The model was validated internally by Bootstrap resample method. The calibration curve and its C-index were used to evaluate the differentiation of the model. The area under receiver operating characteristic (ROC) curve and clinical decision curve (DCA) were used to evaluate the prediction ability and clinical applicability of the nomogram prediction model, respectively. Results: A total of 492 COPD patients were included, 19.51% (96/492) of them had anemia. Nine candidate predictors were identified by LASSO regression analysis: gender, creatinine, hypoproteinemia, diabetes, hypertension, COVID-19 infection, red blood cells (RBC), hemoglobin (Hb), body mass index (BMI). They were included in logistic regression analysis, and the results showed that gender being female (OR=3.353, 95%CI: 1.530-7.349), elevated creatinine levels (OR=1.024, 95%CI: 1.010-1.037), elevated Hb levels (OR=0.928, 95%CI: 0.905-0.951), hypoproteinemia (OR=6.239, 95%CI: 2.845-13.678), diabetes mellitus (OR=0.198, 95%CI: 0.056-0.703) were all independent influencing factors for anemia. Calibration curve of the nomogram prediction model showed good fitness, with a C-index of 0.933 (95%CI: 0.910-1.848), indicating that the model was well distinguished. The area under the curve was 0.933 (95%CI: 0.910-0.957), and DCA curve showed good clinical applicability of the model. Conclusion: The prediction model of COPD combined with anemia is simple and accurate, has certain value in early clinical screening of high-risk groups of anemia and the formulation of individualized precise prevention and treatment plans.

Key words: Pulmonary disease, chronic obstructive, Anemia, Factor analysis, statistical, Forecasting, Nomograms

中图分类号:

R563

傅一婷, 刘蕾, 赵倩, 孟继娴, 甄紫伊, 王暘, 李荣梅. 慢性阻塞性肺疾病患者合并贫血的危险因素分析及风险预测模型的构建[J]. 结核与肺部疾病杂志, 2024, 5(1): 20-27. doi: 10.19983/j.issn.2096-8493.2024003

Fu Yiting, Liu Lei, Zhao Qian, Meng Jixian, Zhen Ziyi, Wang Yang, Li Rongmei. Analysis of risk factors and construction of risk prediction model for anemia in patients with chronic obstructive pulmonary disease[J]. Journal of Tuberculosis and Lung Disease, 2024, 5(1): 20-27. doi: 10.19983/j.issn.2096-8493.2024003

图/表 8

表1

两组患者一般资料的比较

变量^a	贫血组(96例)	无贫血组(396例)	统计检验值	P值
性别[例(构成比,%)]			χ²=2.139	0.168
男性(1)	61(63.50)	219(55.30)
女性(0)	35(36.50)	177(44.70)
年龄(岁, $\bar{x} \pm s$)	80.24±8.25	74.47±9.94	t=-5.889	<0.001
体质量指数($\bar{x} \pm s$)	21.22±3.64	23.00±5.17	t=3.196	0.001
吸烟指数[支/年,M(Q₁,Q₃)]	360.00(0.00,800.00)	205.00(0.00,800.00)	Z=-0.815	0.415
病程[年,M(Q₁,Q₃)]	2.00(0.10,6.00)	3.00(0.10,7.00)	Z=-0.872	0.383
住院次数[次,M(Q₁,Q₃)]	3.00(2.00,7.00)	4.00(2.00,8.00)	Z=-1.372	0.170
红细胞计数(×10¹²/L, $\bar{x} \pm s$)	3.77±0.56	4.53±0.63	t=10.784	<0.001
血红蛋白(g/L, $\bar{x} \pm s$)	108.43±20.77	137.80±18.66	t=13.530	<0.001
红细胞体积分布宽度[%,M(Q₁,Q₃)]	13.70(13.00,15.00)	13.00(12.50,14.00)	Z=-5.311	<0.001
二氧化碳分压[mmHg,M(Q₁,Q₃)]	43.00(36.50,47.00)	45.00(40.00,50.00)	Z=-3.394	0.001
血氧分压[mmHg,M(Q₁,Q₃)]	72.00(63.50,85.00)	72.00(60.50,81.00)	Z=-0.694	0.488
血氧饱和度[%,M(Q₁,Q₃)]	93.00(91.00,97.00)	93.90(91.00,96.00)	Z=-0.903	0.367
白蛋白(g/L, $\bar{x} \pm s$)	37.03±5.37	40.69±4.33	t=6.201	<0.001
C反应蛋白[mg/L,M(Q₁,Q₃)]	28.65(8.50,60.74)	9.12(2.51,28.65)	Z=-4.872	<0.001
肌酐[μmol/L,M(Q₁,Q₃)]	72.70(68.95,102.00)	70.20(58.30,77.00)	Z=-4.667	<0.001
中性粒细胞与淋巴细胞比值[M(Q₁,Q₃)]	5.21(3.26,8.63)	3.58(2.33,5.21)	Z=-4.391	<0.001
糖尿病[例(构成比,%)]			χ²=6.711	0.009
无(0)	90(93.75)	330(83.33)
有(1)	6(6.25)	66(16.67)
冠心病[例(构成比,%)]			χ²=2.892	0.110
无(0)	38(39.58)	195(49.24)
有(1)	58(60.42)	201(50.76)
低氧血症[例(构成比,%)]			χ²=1.573	0.239
无(0)	66(68.75)	245(61.87)
有(1)	30(31.25)	151(38.13)
低蛋白血症[例(构成比,%)]			χ²=64.620	<0.001
无(0)	58(60.42)	365(92.17)
有(1)	38(39.58)	31(7.83)
高脂血症[例(构成比,%)]			χ²=3.039	0.094
无(0)	95(98.96)	376(94.95)
有(1)	1(1.04)	20(5.05)
新型冠状病毒感染[例(构成比,%)]			χ²=21.017	<0.001
无(0)	87(90.62)	392(98.99)
有(1)	9(9.38)	4(1.01)
高血压[例(构成比,%)]			χ²=10.380	0.001
无(0)	60(62.50)	175(44.19)
有(1)	36(37.50)	221(55.81)

表1

图1

图2

表2

图3

图4

图5

图6

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变量	β值	s $\bar{x}$值	Wald χ²值	P值	OR值	95%CI值
变量	β值	s $\bar{x}$值	Wald χ²值	P值	OR值	下限	上限
性别(女性)	1.210	0.400	9.133	0.003	3.353	1.530	7.349
肌酐(连续变量)	0.023	0.007	11.443	0.001	1.024	1.010	1.037
血红蛋白(连续变量)	-0.075	0.013	34.447	<0.001	0.928	0.905	0.951
低蛋白血症(是)	1.831	0.401	20.892	<0.001	6.239	2.845	13.678
糖尿病(是)	-1.620	0.647	6.275	0.012	0.198	0.056	0.703

慢性阻塞性肺疾病患者合并贫血的危险因素分析及风险预测模型的构建

Analysis of risk factors and construction of risk prediction model for anemia in patients with chronic obstructive pulmonary disease

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[3]	胡帅,李梦颖,车思雨,韩广庆,刘芯言,刘爱连,李智勇. 对CT值≤-560HU的肺部纯磨玻璃样结节中浸润性肺腺癌的研究[J]. 结核病与肺部健康杂志, 2018, 7(4): 236-240.