Predicting Mortality in AECOPD With Hypercapnic Respiratory Failure

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Investigators developed a nomogram for predicting mortality in patients presenting to the ED with AECOPD and hypercapnic respiratory failure.

Researchers have proposed a mortality risk assessment model based on clinical variables to predict in-hospital mortality among patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) with hypercapnic respiratory failure who present to the emergency department (ED). The research was recently published in BMC Pulmonary Medicine.

Predictors for establishing a nomogram for in-hospital mortality were identified based on a study of 601 patients using least absolute shrinkage and selection operator (LASSO) regression. The primary study endpoint was hospital mortality. The secondary endpoint was the need for invasive mechanical ventilation in the ED or admission to an intensive care unit (ICU).

All study participants presented to an ED in Zhejiang Province, China, between January 2018 and September 2020, and met the following inclusion criteria: (1) a primary diagnosis of AECOPD or “respiratory failure” and a secondary diagnosis of AECOPD; and (2) partial pressure of carbon dioxide (PCO2) arterial of at least 50 mm Hg. Of the 601 patients evaluated, 213 received noninvasive mechanical ventilation, 137 received invasive mechanical ventilation, 6 died in the ED, 172 were admitted to the ICU, and 19 died during hospitalization.

Per LASSO regression analysis, 7 variables were identified, including PCO2, respiratory rate, blood urea nitrogen, hemoglobin, lactic acid, platelet count, and platelet distribution width. A predictive model was created that used these 7 variables, along with the variable of concomitant pneumonia. Predictive ability was evaluated via use of the area under the receiver operating curve (AUC).

An AUC of 0.940 (95% CI, 0.895–0.985) was indicative of good discrimination by the nomogram for predicting risk for mortality among the patients. Further, the AUC for the internal validation model was 0.933 (95% CI, 0.870–0.975). For ICU admission and use of invasive mechanical ventilation, the AUCs of the nomogram were 0.7822 (95% CI, 0.7408–0.8237) and 0.8044 (95% CI, 0.7615–0.8473), respectively.

The investigators concluded that the proposed nomogram “can be conveniently used by ED staff to grade patients with AECOPD faster, and accurately,” thus allowing for more effective management of these patients in the ED as well as for enhanced quality of care.

Disclosure: None of the study authors have declared affiliations with biotech, pharmaceutical, and/or device companies.


Chen L, Chen L, Zheng H, Wu S, Wang S. Emergency admission parameters for predicting in-hospital mortality in patients with acute exacerbations of chronic obstructive pulmonary disease with hypercapnic respiratory failure. BMC Pulm Med. 2021;21(1):258. doi: 10.1186/s12890-021-01624-1