Study identifies NMI as novel biomarker of severity in community-acquired pneumonia

CHINA: According to a study published in BMJ Open Respiratory Research, NMI (N-myc and STAT interactor) can serve as a novel predictive biomarker for 30-day mortality and ICU hospitalization and is a valuable indicator for initial risk categorization and precise clinical decision-making in community-acquired pneumonia.

Community-acquired pneumonia (CAP) is a respiratory illness that poses a substantial risk to human health and may be followed by acute and severe lung inflammation. Although previous research has indicated that moderate pneumonia has a fair prognosis, 21% of hospitalized CAP patients require admission to the intensive care unit (ICU). Recent studies have shown that a delay in the identification of severe CAP results in the improper therapeutic care of patients, increasing length of stay (LOS) and mortality. Therefore, it is critical to identify patients with severe CAP as soon as possible. A transcriptional regulator of several nuclear signaling pathways is N-myc and STAT interactor (NMI).

In order to determine whether the NMI may be utilized as a novel biomarker to stratify CAP severity and predict the prognosis of CAP, the authors of this study obtained blood samples and bronchoalveolar lavage fluid (BALF) from CAP patients. They also assessed NMI expression in these samples.

For this research, individuals with CAP underwent prospective observational analysis. From January 2019 through November 2020, the study was conducted at the Second Affiliated Hospital of Zhejiang University in Hangzhou, Zhejiang, China. Serum was taken from 394 adult CAP patients and 40 uninfected controls, whereas BALF was taken from 37 adult CAP patients and 23 uninfected controls.Upon arrival, 394 CAP patients had their serum NMI levels determined using an immunoassay. Patient outcomes were determined to be 30-day mortality and ICU hospitalization. Logistic regression analysis and the receiver operating characteristic curve were used to establish the predictive value of NMI for clinical outcomes. Cross-validation with bootstrap resampling was used to evaluate the internal validity.