慢性阻塞性肺疾病急性加重期患者合并应激性高血糖风险预测模型构建研究

doi:10.3761/j.issn.2096-7446.2024.12.001

摘要/Abstract

摘要： 目的探讨慢性阻塞性肺疾病急性加重期（acute-exacerbations of chronic obstructive pulmonary disease,AECOPD）患者发生应激性高血糖的影响因素,并构建风险预测列线图模型。方法回顾性选取2021年3月—2023年3月乌鲁木齐市某三级甲等医院急诊重症监护室收治的444例AECOPD患者作为调查对象。采用单因素分析和Logistic回归分析确定AECOPD发生应激性高血糖的危险因素,建立风险预测模型并绘制列线图。采用受试者工作特征曲线检测模型的预测效果,Hosmer-Lemeshow检验判断模型的拟合优度。结果 AECOPD患者应激性高血糖发生率为24.5%。Logistic回归分析结果显示,年龄、吸烟、脑血管疾病史、机械通气、入院时急性生理与慢性健康状况Ⅱ评分、血糖变异系数、C-反应蛋白是AECOPD患者发生应激性高血糖的独立影响因素（P<0.05）。基于Logistic回归建立个体化列线图预测模型,受试者操作特征曲线面积为0.823（95%CI：0.780~0.865）,Hosmer-Lemeshow检验P=0.354,最佳截断值为0.514,灵敏度为0.872,特异度为0.642。Bootstrap自助法进行内部验证的结果显示,C指数为0.817,提示模型预测效果良好。结论该研究构建的预测模型预测效果较好,可为临床有效评估AECOPD患者应激性高血糖发生风险提供参考依据。

关键词: 慢性阻塞性肺疾病急性加重期, 应激性高血糖, 影响因素分析, 列线图, 护理

Abstract: Objective To explore the influencing factors of stress hyperglycemia in patients with acute exacerbation of chronic obstructive pulmonary disease（AECOPD）,and to construct a risk prediction nomogram model. Methods A retrospective study was conducted among 444 AECOPD patients in the emergency intensive care of a tertiary class A hospital in Urumqi from March 2021 to March 2023,and the independent risk factors of stress hyperglycemia in AECOPD patients were explored through univariate analysis and Logistic regression analysis. A risk prediction model was established and incorporated into the nomogram. The prediction performance of the model was tested using the receiver operating characteristic curve（ROC）,and the Hosmer-Lemeshow test was used to determine the goodness of fit of the model. Results The incidence of stress hyperglycemia in AECOPD patients was 24.5%. Logistic regression analysis showed that age,smoking,history of cerebrovascular disease,mechanical ventilation,Acute Physiology and Chronic Health EvaluationⅡ score at admission,coefficient of variation of blood glucose and C-reactive protein were independent influencing factors for stress hyperglycemia in AECOPD patients（P<0.05）. The individual nomogram prediction model was established based on Logistic regression. The area under the receiver operating characteristic curve was 0.823（95%CI：0.780~0.865）,the Hosmer-Lemeshow test P=0.354,the best cutoff value was 0.514,the sensitivity was 0.872,and the specificity was 0.642. The Bootstrap method was used for internal validation,and the C-index was 0.817,indicating that the model had a good prediction effect. Conclusion The prediction model constructed in this study has a good prediction effect,which can provide a reference for effectively evaluating the risk of stress hyperglycemia in patients with AECOPD.

Key words: Acute Exacerbation of Chronic Obstructive Pulmonary Disease, Stress Hyperglycemia, Root Cause Analysis, Nomogram, Nurse Care

谢云, 罗莉, 王海燕. 慢性阻塞性肺疾病急性加重期患者合并应激性高血糖风险预测模型构建研究[J]. 中华急危重症护理杂志, 2024, 5(12): 1061-1067.

XIE Yun, LUO Li, WANG Haiyan. The development of a risk prediction model for stress hyperglycemia in patients with acute exacerbation of chronic obstructive pulmonary disease[J]. Chinese Journal of Emergency and Critical Care Nursing, 2024, 5(12): 1061-1067.

参考文献

[1] Yu X,Zhu GP,Cai TF,et al.Establishment of risk prediction model and risk score for in-hospital mortality in patients with AECOPD[J]. Clin Respir J,2020,14(11):1090-1098.
[2] Yang CJ,Liao WI,Tang ZC,et al.Glycated hemoglobin A1c-based adjusted glycemic variables in patients with diabetes presenting with acute exacerbation of chronic obstructive pulmonary disease[J]. Int J Chron Obstruct Pulmon Dis,2017,12:1923-1932.
[3] 乔梦圆,秦梦真,王海燕. ICU应激性高血糖患者危险因素模式的潜在类别及与预后的关系[J]. 护理学杂志,2023,38(18):33-37.
Qiao MY,Qin MZ,Wang HY.Latent class analysis patterns of risk factors for stress-induced hyperglycemia among ICU patients and their association with prognosis[J]. J Nurs Sci,2023, 38(18):33-37.
[4] Edriss H,Selvan K,Sigler M,et al.Glucose levels in patients with acute respiratory failure requiring mechanical ventilation[J]. J Intensive Care Med,2017,32(10):578-584.
[5] Wood DM,Brennan AL,Philips BJ,et al.Effect of hyperglycaemia on glucose concentration of human nasal secretions[J]. Clin Sci,2004,106(5):527-533.
[6] Baker EH,Janaway CH,Philips BJ,et al.Hyperglycaemia is associated with poor outcomes in patients admitted to hospital with acute exacerbations of chronic obstructive pulmonary disease[J]. Thorax,2006,61(4):284-289.
[7] Global strategy for the diagnosis,management and prevention of chronic obstructive pulmonary disease2021 report[EB/OL]. (2020-11-17)[2024-02-02]. https://goldcopd.org/gold-reports/.
[8] 王家良. 临床流行病学:临床科研设计、测量与评价[M]. 3版. 上海:上海科学技术出版社,2009:177.
Wang JL.Clinical epidemiology:design,measurement and evaluation of clinical scientific research[M]. 3rd ed. Shanghai:Shanghai Scientific & Technical Publishers,2009:177.
[9] Mifsud S,Schembri EL,Gruppetta M.Stress-induced hyperglycaemia[J]. Br J Hosp Med,2018,79(11):634-639.
[10] 马海平,黄炎. 重症患者应激性高血糖的护理研究进展[J]. 上海护理,2023,23(5):25-29.
Ma HP,Huang Y.Research progress on nursing care of stress hyperglycemia in critically ill patients[J]. Shanghai Nurs,2023,23(5):25-29.
[11] Islam EA,Limsuwat C,Nantsupawat T,et al.The association between glucose levels and hospital outcomes in patients with acute exacerbations of chronic obstructive pulmonary disease[J]. Ann Thorac Med,2015,10(2):94-99.
[12] Cai Y,Wang C,Di W,et al.Correlation between blood glucose variability and the risk of death in patients with severe acute stroke[J]. Rev Neurol,2020,176(7/8):582-586.
[13] Mi DH,Li ZX,Gu HQ,et al.Stress hyperglycemia is associated with in-hospital mortality in patients with diabetes and acute ischemic stroke[J]. CNS Neurosci Ther,2022,28(3):372-381.
[14] Magee MJ,Salindri AD,Kyaw NTT,et al.Stress hyperglycemia in patients with tuberculosis disease:epidemiology and clinical implications[J]. Curr Diab Rep,2018,18(9):71.
[15] Guo YZ,Wang GY,Jing J,et al.Stress hyperglycemia may have higher risk of stroke recurrence than previously diagnosed diabetes mellitus[J]. Aging,2021,13(6):9108-9118.
[16] McGraw M,White HD,Zolfaghari K,et al. Corticosteroid dosing and glucose levels in COPD patients are not associated with increased readmissions[J]. Chronic Obstr Pulm Dis,2021,8(1):117-123.
[17] 刘超. 增龄与2型糖尿病[J]. 重庆医科大学学报,2015,40(7):922-925.
Liu C.Aging and type 2 diabetes mellitus[J]. J Chongqing Med Univ,2015,40(7):922-925.
[18] 尹婧婧,张巍,张茗,等. 外周血嗜酸粒细胞与老年慢性阻塞性肺疾病急性加重患者临床特征及短期预后的关系研究[J]. 实用心脑肺血管病杂志,2023,31(5):45-49.
Yin JJ,Zhang W,Zhang M,et al.Relationship between peripheral blood eosinophil and clinical features and short-term prognosis in elderly patients with acute exacerbation of chronic obstructive pulmonary disease[J]. Pract J Card Cereb Pneumal Vasc Dis,2023,31(5):45-49.
[19] Wang D,Qiang DR,Xu WC,et al.Smoking causes the disorder of glucose metabolism under different levels of blood pressure in male occupational population[J]. J Clin Hypertens,2022,24(10):1276-1284.
[20] Tang ZQ,Xia NN,Yuan XL,et al.PRDX1 is involved in palmitate induced insulin resistance via regulating the activity of p38MAPK in HepG2 cells[J]. Biochem Biophys Res Commun,2015,465(4):670-677.
[21] 胡莹,耿力,袁颖,等. ICU应激性高血糖风险评估工具的构建[J]. 护理学杂志,2020,35(21):29-32.
Hu Y,Geng L,Yuan Y,et al.Development of a stress hyperglycemia risk assessment tool in ICU[J]. J Nurs Sci,2020,35(21):29-32.
[22] 乔梦圆,王海燕,秦梦真. 急诊重症监护室患者低血糖风险预测模型的构建及验证[J]. 中华护理杂志,2023,58(23):2835-2842.
Qiao MY,Wang HY,Qin MZ.Construction and evaluation of a risk prediction model of hypoglycemia risk in emergency intensive care unit patients[J]. Chin J Nurs,2023,58(23):2835-2842.
[23] 汪博,李亚娟,杜瑞妮,等. 血糖变异系数对肾移植预后的预测价值[J]. 重庆医学,2022,51(3):361-365.
Wang B,Li YJ,Du RN,et al.The predictive value of blood glucose variation coefficient for the prognosis of kidney transplantation[J]. Chongqing Med,2022,51(3):361-365.
[24] Kurisu K,Tsurutani Y,Inoue K,et al.Intra-individual association between C-reactive protein and insulin administration in postoperative lumbar spinal canal stenosis patients:a retrospective cohort study[J]. J Diabetes Investig,2020,11(4):980-984.