Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jun 4:18:7183-7194.
doi: 10.2147/JIR.S522306. eCollection 2025.

Construction and Validation of a Nomogram Model for Predicting the Risk of Neonatal Sepsis Complicated by Purulent Meningitis

Jingyue Li  1 , Chunlan Song  1 , Tiewei Li  2 , Wanyu Jia  1 , Zhuo Qian  1 , Yiming Peng  1 , Yixin Xu  1 , Zhipeng Jin  1
Affiliations

Construction and Validation of a Nomogram Model for Predicting the Risk of Neonatal Sepsis Complicated by Purulent Meningitis

Jingyue Li et al. J Inflamm Res. .

Abstract

Background: Neonatal purulent meningitis (NPM) is a severe infection with high morbidity and mortality. NPM is a common complication in cases of neonatal sepsis (NS). This study aims to develop and validate a risk prediction model for NS complicated by NPM.

Methods: A retrospective study of 535 neonates diagnosed with sepsis at the Affiliated Children's Hospital of Zhengzhou University between January 2016 and October 2024 was conducted. The primary outcome was the presence of NPM. Multivariate logistic regression was used to identify predictive factors, and a nomogram model was created using R software.

Results: Multivariate analysis identified fever, seizures, tachycardia, and decreased levels of alkaline phosphatase (ALP) and total bilirubin (TBIL) as independent risk factors for NS complicated by NPM (P < 0.05). The area under the receiver operating characteristic curve (ROC) for the training set was 0.765 (95% CI: 0.711-0.819), and 0.713 (95% CI: 0.625-0.800) for the validation set. The Hosmer-Lemeshow test confirmed good model fit (χ² = 8.963, P = 0.345). Calibration and decision curve analysis showed high predictive performance and clinical applicability.

Conclusion: The nomogram developed in this study demonstrates promising predictive ability and clinical value for NS complicated by NPM.

Keywords: NPM; NS; neonatal purulent meningitis; neonatal sepsis; nomogram; prediction model.

PubMed Disclaimer

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
Nomogram prediction model for the risk of NS complicated by NPM. The corresponding scores are obtained based on the variables, and the total score is calculated by summing the individual scores. The total score corresponds to the risk axis, which allows the determination of the risk of NS complicated by NPM.
Figure 2
Figure 2
ROC curve of the nomogram prediction model. The AUC values for predicting the occurrence of NPM in neonatal sepsis (NS) in the training set (A) and validation set (B) are 0.765 and 0.713, respectively, indicating good discriminatory ability of the model.
Figure 3
Figure 3
Calibration curve of the nomogram prediction model. The x-axis represents the predicted probability, while the y-axis represents the actual probability. The closer the calibration curve is to the ideal curve, the better the model’s calibration. In this study, the calibration curves for both the training set (A) and validation set (B) of the nomogram model are close to the ideal curve, indicating that the model has good predictive performance.
Figure 4
Figure 4
Decision curve analysis of the nomogram prediction model. The black line (labeled “None”) represents no intervention for all NS patients, with a net benefit of 0. The gray line (labeled “All”) indicates interventions for all NS patients, reflecting the standardized net benefit under this strategy. The red line (labeled “Nomogram model”) demonstrates the standardized net benefit of the nomogram model in predicting the risk of NPM in NS patients. In both the training set (A) and validation set (B), the red line remains above the black and gray lines across most risk thresholds, indicating that the predictive model possesses high clinical applicability.
See this image and copyright information in PMC

Similar articles

See all similar articles

References

    1. Kohli-Lynch M, Russell NJ, Seale AC, et al. Neurodevelopmental Impairment in children after group B streptococcal disease worldwide: systematic review and meta-analyses. Clin Infect Dis. 2017;65(suppl_2):S190–S199. doi:10.1093/cid/cix663 - DOI - PMC - PubMed
    1. Liu L, Oza S, Hogan D, et al. Global, regional, and national causes of under-5 mortality in 2000-15: an updated systematic analysis with implications for the sustainable development goals. Lancet. 2016;388(10063):3027–3035. doi:10.1016/s0140-6736(16)31593-8 - DOI - PMC - PubMed
    1. Wondimu MN, Toni AT, Zamanuel TG. Magnitude of neonatal meningitis and associated factors among newborns with neonatal sepsis admitted to the university of Gondar comprehensive specialized hospital, North Gondar, Ethiopia. PLoS One. 2023;18(9):e0290639. doi:10.1371/journal.pone.0290639 - DOI - PMC - PubMed
    1. Ahmed S, Akhtar S, Sultan A, Rehman AU. Frequency, risk factors, and outcome of neonatal meningitis in sepsis. Pak J Med Sci. 2024;40(9):1964–1968. doi:10.12669/pjms.40.9.8890 - DOI - PMC - PubMed
    1. Pishori T, Furia FF, Manji K. A cross-sectional study of clinical features of bacterial meningitis among neonates presumed to have sepsis in a tertiary hospital, Dar es Salaam, Tanzania. Pan Afr Med J. 2023;46:123. doi:10.11604/pamj.2023.46.123.32787 - DOI - PMC - PubMed

LinkOut - more resources