Development of a nomogram to estimate the risk of community-acquired pneumonia in adults with acute asthma exacerbations

Objective

The aim of this study is to investigate the clinical characteristics of acute asthma exacerbations (AEs) with community-acquired pneumonia (CAP) in adults and establish a CAP prediction model for hospitalized patients with AEs.

Methods

We retrospectively collected clinical data from 308 patients admitted to Beijing Luhe Hospital, Capital Medical University, for AEs from December 2017 to August 2021. The patients were divided into CAP and non-CAP groups based on whether they had CAP. We used the Lasso regression technique and multivariate logistic regression analysis to select optimal predictors. We then developed a predictive nomogram based on the optimal predictors. The bootstrap method was used for internal validation. We used the area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) to assess the nomogram's discrimination, accuracy, and clinical practicability.

Results

The prevalence of CAP was 21% (65/308) among 308 patients hospitalized for AEs. Independent predictors of CAP in patients hospitalized with an AE (P < 0.05) were C-reactive protein > 10 mg/L, fibrinogen > 4 g/L, leukocytes > 10 × 10⁹/L, fever, use of systemic corticosteroids before admission, and early-onset asthma. The AUC of the nomogram was 0.813 (95% CI: 0.753–0.872). The concordance index of internal validation was 0.794. The calibration curve was satisfactorily consistent with the diagonal line. The DCA indicated that the nomogram provided a higher clinical net benefit when the threshold probability of patients was 3% to 89%.

Conclusions

The nomogram performed well in predicting the risk of CAP in hospitalized patients with AEs, thereby providing rapid guidance for clinical decision-making.