目的：建立并验证慢性阻塞性肺疾病急性加重(AECOPD)合并高碳酸血症呼吸衰竭患者死亡风险的模型。方法：回顾性分析徐州医科大学附属医院2015年3月到2021年5月因AECOPD伴动脉血二氧化碳分压(PaCO₂)≥70 mmHg住院的50岁以上患者621例的资料。入院时评估患者的人口统计学特征、生命体征和精神状态，收集患者的实验室检查和主要合并症资料。使用最小绝对值收敛和选择算子(LASSO)建立住院患者死亡率列线图的预测因子。通过受试者工作特征(ROC)曲线下面积(AUC)评估列线图的预测效能。采用自助法(Bootstrap Method)进行内部验证。运用决策曲线分析法(DCA)对模型的临床效用进行评价。此外，还将列线图与CURB65、CRB65、BAP65及NEWS等预后模型进行比较。结果：621例患者中，有39例(6.28%)在住院期间死亡。LASSO回归分析确定了7个变量，包括呼吸频率、PaCO₂、血乳酸含量、血尿素氮、血红蛋白、血小板分布宽度和血小板计数。采用这7个变量建立预测模型。列线图具有良好的死亡率校准和鉴别能力(AUC=0.940；95%CI为0.895~0.985)，高于其他模型。DCA显示该列线图具有较高临床应用价值。结论：本研究构建的列线图对AECOPD合并高碳酸血症患者院内死亡风险具有较好的预测价值，可供临床参考。

[1] WEDZICHA J A E,MIRAVITLLES M,HURST J R,et al.Management of COPD exacerbations:a European Respiratory Society/American Thoracic Society guideline[J].Eur Respir J,2017,49(3):1600791.
[2] CHANG C L,SULLIVAN G D,KARALUS N C,et al.Predicting early mortality in acute exacerbation of chronic obstructive pulmonary disease using the CURB65 score[J].Respirology,2011,16(1):146-151.
[3] EDWARDS L,PERRIN K,WIJESINGHE M,et al.The value of the CRB65 score to predict mortality in exacerbations of COPD requiring hospital admission[J].Respirology,2011,16(4):625-629.
[4] MATKOVIC Z,HUERTA A,SOLER N,et al.Predictors of adverse outcome in patients hospitalised for exacerbation of chronic obstructive pulmonary disease[J].Respiration,2012,84(1):17-26.
[5] BROWN H,DODIC S,GOH S S,et al.Factors associated with hospital mortality in critically ill patients with exacerbation of COPD[J].Int J Chron Obstruct Pulmon Dis,2018,13:2361-2366.
[6] VOGELMEIER C F,CRINER G J,MARTINEZ F J,et al.Global strategy for the diagnosis,management,and prevention of chronic obstructive lung disease 2017 Report:GOLD Executive Summary[J].Arch Bronconeumol,2017,53(3):128-149.
[7] PORNSURIYASAK P,SUWATANAPONGCHED T,KLAEWSONGKRAM J,et al.Acute respiratory failure secondary to eosinophilic pneumonia following influenza vaccination in an elderly man with chronic obstructive pulmonary disease[J].Int J Infect Dis,2014,26:14-16.
[8] NEGEWO N A,GIBSON P G,MCDONALD V M.COPD and its comorbidities:impact,measurement and mechanisms[J].Respirology,2015,20(8):1160-1171.
[9] BAGDONAS E,RAUDONIUTE J,BRUZAUSKAITE I,et al.Novel aspects of pathogenesis and regeneration mechanisms in COPD[J].Int J Chron Obstruct Pulmon Dis,2015,10:995-1013.
[10] AHMADI Z,BORNEFALK-HERMANSSON A,FRANKLIN K A,et al.Hypo-and hypercapnia predict mortality in oxygen-dependent chronic obstructive pulmonary disease:a population-based prospective study[J].Respir Res,2014,15:30.
[11] MARTINEZ F J,RABE K F,FERGUSON G T,et al.Reduced all-cause mortality in the ethos trial of budesonide/glycopyrrolate/formoterol for chronic obstructive pulmonary disease.A randomized,double-blind,multicenter,parallel-group study[J].Am J Respir Crit Care Med,2021,203(5):553-564.
[12] DUFFY S P,CRINER G J.Chronic obstructive pulmonary disease:evaluation and management[J].Med Clin North Am,2019,103(3):453-461.
[13] FAZLEEN A,WILKINSON T.Early COPD:current evidence for diagnosis and management[J].Ther Adv Respir Dis,2020,14:1753466620942128.
[14] GOKALP H,DE FOLTER J,VERMA V,et al.Integrated telehealth and telecare for monitoring frail elderly with chronic disease[J].Telemed J E Health,2018,24(12):940-957.
[15] WEST J B.Causes of and compensations for hypoxemia and hypercapnia[J].Compr Physiol,2011,1(3):1541-1553.
[16] BRAUNLICH J,KOHLER M,WIRTZ H.Nasal highflow improves ventilation in patients with COPD[J].Int J Chron Obstruct Pulmon Dis,2016,11:1077-1085.
[17] MUSORO J Z,ZWINDERMAN A H,PUHAN M A,et al.Validation of prediction models based on lasso regression with multiply imputed data[J].BMC Med Res Methodol,2014,14:116.
[18] VIJAYAKUMAR B,CAO M,MACKILLOP L,et al.A challenging case of hypercapnic respiratory failure during pregnancy[J].Obstet Med,2021,14(2):121-124.
[19] MARTINEZ-URBISTONDO D,ALEGRE F,CARMONA-TORRE F,et al.Mortality prediction in patients undergoing non-invasive ventilation in intermediate care[J].PLoS One,2015,10(10):e0139702.