AUTHOR=Yu Tingting , Liu Haimei , Liu Ying , Jiang Jianxin 

TITLE=Inflammatory response biomarkers nomogram for predicting pneumonia in patients with spontaneous intracerebral hemorrhage

JOURNAL=Frontiers in Neurology

VOLUME=Volume 13 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/neurology/articles/10.3389/fneur.2022.1084616

DOI=10.3389/fneur.2022.1084616

ISSN=1664-2295

ABSTRACT=Background/ Objectives: Inflammatory response biomarkers have shown to be promising prognostic factors for improving the predictive accuracy in stroke-associated pneumonia (SAP) after ischemic stroke. The purpose of the study was to investigate the prognostic significance of admission inflammatory response biomarkers in SAP after spontaneous intracerebral hemorrhage (SICH) and establish a corresponding nomogram.
Methods: The data of 378 patients with SICH who underwent conservative treatment between January 2019 and December 2021 were selected from Taizhou People's Hospital. All eligible patients were separated into the training cohort (70%,265) and the validation cohort (30%,113) at random. In the training cohort, multivariate logistic regression analysis was used to establish an optimal nomogram including inflammatory response biomarkers and clinical risk factors. The area under the curve (AUC) of operating characteristics (ROC), calibration curve, and decision curve analysis (DCA) curves were used to evaluate the nomogram’s discriminating, calibration, and performance, respectively. Moreover, this model would be further validated in the validation cohort. 
Results: Logistic regression analysis indicated that the intraventricular hemorrhage
(IVH), hypertension, dysphagia,(Glasgow coma scale) GCS, NIHSS, SIRI, and PLR were correlated with SAP after SICH (P< 0.05). The nomogram was made up of all these significant statistically significant factors. The nomogram, based on the inflammatory markers, showed powerful prognostic ability, compared with conventional factors with AUCs of 0.886(95%CI:0.841 -0.921), and 0.848 (95%CI:0.799–0.899), respectively. The calibration curve proved the predicted risk yielded good homogeneity with the observation. In addition, the model has a significant net benefit for SAP according to the DCA. Meanwhile, the internal validation also demonstrated the reliability of the prediction nomogram.
Conclusion: Admission SIRI and PLR may serve as potential prognostic inflammatory biomarkers in patients with supratentorial SICH who underwent SAP. The nomogram covering SIRI, and PLR could more accurately predict SAP in patients with supratentorial SICH.