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. 2022 Aug 9;22(1):306.
doi: 10.1186/s12890-022-02100-0.

Development and validation of a prognostic nomogram among patients with acute exacerbation of chronic obstructive pulmonary disease in intensive care unit

Jiang-Chen Peng #  1 , Wen-Wen Gong #  2 , Yan Wu  2 , Tian-Yi Yan  3 , Xiao-Yan Jiang  4   5
Affiliations

Development and validation of a prognostic nomogram among patients with acute exacerbation of chronic obstructive pulmonary disease in intensive care unit

Jiang-Chen Peng et al. BMC Pulm Med. .

Abstract

Background: Acute exacerbation of Chronic Obstructive Pulmonary Disease (AECOPD) contributes significantly to mortality among patients with COPD in Intensive care unit (ICU). This study aimed to develop a nomogram to predict 30-day mortality among AECOPD patients in ICU.

Methods: In this retrospective cohort study, we extracted AECOPD patients from Medical Information Mart for Intensive Care III (MIMIC-III) database. Multivariate logistic regression based on Akaike information criterion (AIC) was used to establish the nomogram. Internal validation was performed by a bootstrap resampling approach with 1000 replications. The discrimination and calibration of the nomogram were evaluated by Harrell's concordance index (C-index) and Hosmer-Lemeshow (HL) goodness-of-fit test. Decision curve analysis (DCA) was performed to evaluate its clinical application.

Results: A total of 494 patients were finally included in the study with a mean age of 70.8 years old. 417 (84.4%) patients were in the survivor group and 77 (15.6%) patients were in the non-survivor group. Multivariate logistic regression analysis based on AIC included age, pO2, neutrophil-to-lymphocyte ratio (NLR), prognostic nutritional index (PNI), invasive mechanical ventilation and vasopressor use to construct the nomogram. The adjusted C-index was 0.745 (0.712, 0.778) with good calibration (HL test, P = 0.147). The Kaplan-Meier survival curves revealed a significantly lower survival probability in the high-risk group than that in the low-risk group (P < 0.001). DCA showed that nomogram was clinically useful.

Conclusion: The nomogram developed in this study could help clinicians to stratify AECOPD patients and provide appropriate care in clinical setting.

Keywords: 30-day mortality; AECOPD; Intensive care unit; Nomogram; Predictive model.

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Conflict of interest statement

None of the authors has any potential conflicts of interest related to this article to declare and the results of this report have been produced, analyzed, and interpreted without any outside participation.

Figures

Fig. 1
Fig. 1
The flow chart of the included population
Fig. 2
Fig. 2
Nomogram to calculate risk score and predict 30-day survival probability in AECOPD patients. Scores were assigned for age, PO2, NLR level, PNI level, treatment of IMV and vasopressor by drawing a line upward from the corresponding values to the ‘score’ line. The sum of all these scores, plotted on the ‘Total score’ line, corresponds to predictions of 30-day survival probability. IMV invasive mechanical ventilation, NLR, neutrophil-to-lymphocyte ratio; PNI prognostic nutritional index; PO2 partial pressure of oxygen
Fig. 3
Fig. 3
The ROC curve (A) and calibration curve (B) of the nomogram in predicting 30-day mortality among AECOPD patients in ICU after 1000 bootstrap
Fig. 4
Fig. 4
The Kaplan–Meier survival curves classified by low-risk group and high-risk group
Fig. 5
Fig. 5
Decision curve analysis for 30-day survival. The x-axis showed the threshold probability. The y-axis represented net benefit. Black line meant that all patients were dead and gray line represented that none patients were dead. The red line displayed the benefit of the nomogram. The green line displayed the benefit of NLR. The blue line displayed the benefit of PLR. The lake blue line displayed the benefit of PNI. NLR neutrophil-to-lymphocyte ratio; PLR platelet-to-lymphocyte ratio; PNI prognostic nutritional index
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