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. 2023 Sep 21:11:1194186.
doi: 10.3389/fped.2023.1194186. eCollection 2023.

Clinical features and risk factors analysis for poor outcomes of severe community-acquired pneumonia in children: a nomogram prediction model

Changjing Xu  1 , Xuemei Tao  1 , Junlong Zhu  2 , Chao Hou  3 , Yujie Liu  4 , Liya Fu  5 , Wanlong Zhu  5 , Xuping Yang  1 , Yilan Huang  1
Affiliations

Clinical features and risk factors analysis for poor outcomes of severe community-acquired pneumonia in children: a nomogram prediction model

Changjing Xu et al. Front Pediatr. .

Abstract

Background: Pneumonia remains the leading cause of death among children aged 1-59 months. The early prediction of poor outcomes (PO) is of critical concern. This study aimed to explore the risk factors relating to PO in severe community-acquired pneumonia (SCAP) and build a PO-predictive nomogram model for children with SCAP.

Methods: We retrospectively identified 300 Chinese pediatric patients diagnosed with SCAP who were hospitalized in the Affiliated Hospital of Southwest Medical University from August 1, 2018, to October 31, 2021. Children were divided into the PO and the non-PO groups. The occurrence of PO was designated as the dependent variable. Univariate and multivariate logistic regression analyses were used to identify the risk factors of PO. A nomogram model was constructed from the multivariate logistic regression analysis and internally validated for model discrimination and calibration. The performance of the nomogram was estimated using the concordance index (C-index).

Results: According to the efficacy evaluation criteria, 56 of 300 children demonstrated PO. The multivariate logistic regression analysis resulted in the following independent risk factors for PO: co-morbidity (OR: 8.032, 95% CI: 3.556-18.140, P < 0.0001), requiring invasive mechanical ventilation (IMV) (OR: 7.081, 95% CI: 2.250-22.282, P = 0.001), and ALB < 35 g/L (OR: 3.203, 95% CI: 1.151-8.912, P = 0.026). Results of the internal validation confirmed that the model provided good discrimination (concordance index [C-index], 0.876 [95% CI: 0.828-0.925]). The calibration plots in the nomogram model were of high quality.

Conclusion: The nomogram facilitated accurate prediction of PO in children diagnosed with SCAP and could be helpful for clinical decision-making.

Keywords: children; nomogram; predictive model; risk factor; severe community-acquired pneumonia.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
The nomogram for calculating the risk score and predicting the risk of PO in SCAP patients. To calculate total score and predicted probability of PO, points from individual variables are added and a vertical line is drawn from the total points line at the bottom downward to determine the predicted probability of PO due to SCAP. PO, poor outcome; SCAP, severe community-acquired pneumonia; pH, blood pH; AMS, altered mental status; ALB, albumin; IMV, invasive mechanical ventilation.
Figure 2
Figure 2
ROC curve and AUC of the nomogram, AUC = 0.876 (95% CI: 0.828–0.925).
Figure 3
Figure 3
The calibration plot of the nomogram. The horizontal axis indicates the risk of PO occurrence predicted by the nomogram, and the vertical axis represents the actual observed risk of PO occurrence.
See this image and copyright information in PMC

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