AUTHOR=Yang Fan , Dong Ruirui , Wang Yating , Guo Junshuang , Zang Qiuling , Wen Lijun , Huang Peipei , Qin Jinjin , Song Dandan , Ren Zhiping , Teng Junfang , Miao Wang TITLE=Prediction of pulmonary infection in patients with severe myelitis by NPAR combined with spinal cord lesion segments JOURNAL=Frontiers in Neurology VOLUME=15 YEAR=2024 URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2024.1364108 DOI=10.3389/fneur.2024.1364108 ISSN=1664-2295 ABSTRACT=Objectives

To investigate the risk factors of pulmonary infection in patients with severe myelitis and construct a prediction model.

Methods

The clinical data of 177 patients with severe myelitis at admission from the First Affiliated Hospital of Zhengzhou University from January 2020 to December 2022 were retrospectively analyzed. The predicting factors associated with pulmonary infection were screened by multivariate logistic regression analysis, and the nomogram model was constructed, and the predictive efficiency of the model was evaluated, which was verified by calibration curve, Hosmer–Lemeshow goodness-of-fit test and decision curve analysis.

Results

Of the 177 patients with severe myelitis, 38 (21.5%) had pulmonary infection. Multivariate logistic regression analysis showed that neutrophil percentage to albumin ratio (NPAR) (OR = 6.865, 95%CI:1.746–26.993, p = 0.006) and high cervical cord lesion (OR = 2.788, 95%CI:1.229–6.323, p = 0.014) were independent risk factors for pulmonary infection, and the combined nomogram could easily predict the occurrence of pulmonary infection, with a C-index of 0.766 (95% CI: 0.678–0.854). The calibration curve, Hosmer-Lemeshow goodness-of-fit test (χ2 = 9.539, p = 0.299) and decision curve analysis showed that the model had good consistency and clinical applicability.

Conclusion

The nomogram model constructed based on NPAR combined with high cervical cord lesion at admission has good clinical application value in predicting pulmonary infection in patients with severe myelitis, which is conducive to clinicians’ evaluation of patients.