Identifying Clinical and Immunological Predictors of Severe Pertussis in Children

Despite the implementation of widespread vaccination programs, pertussis, also known as whooping cough, continues to pose a significant health threat, particularly to infants and young children. A recent study conducted at Tianjin Second People’s Hospital has identified critical clinical and immunological predictors of severe pertussis, offering a novel nomogram-based prediction model that could enhance early identification and management of high-risk pediatric cases.

**Background and Study Overview** Pertussis, caused by the bacterium *Bordetella pertussis*, is a leading cause of vaccine-preventable deaths globally, particularly affecting children under five years old. According to the World Health Organization (WHO), millions of pertussis cases and hundreds of thousands of related deaths occur annually, particularly in regions with low vaccination coverage (WHO, 2023). Recent trends indicated a resurgence of pertussis cases, exacerbated by waning immunity from acellular vaccines introduced in the 1990s (Xie et al., 2025).

The retrospective case analysis, conducted from January to December 2023, involved 249 children diagnosed with pertussis at the Department of Infection in Tianjin. The cohort included 209 cases classified as common and 40 as severe, based on established diagnostic criteria (Tan & Gerbie, 2013). The researchers aimed to determine the clinical and immunological risk factors that contribute to severe pertussis, with an emphasis on developing a predictive model to streamline clinical decision-making.

**Key Findings** The study revealed significant demographic and clinical differences between the severe and common pertussis groups. Children with severe pertussis were more likely to be premature, have incomplete vaccination histories, and exhibit elevated white blood cell counts (WBC > 30 × 10⁹/L) compared to their counterparts. Moreover, severe cases were associated with longer hospital stays and higher rates of pneumonia (Zhang et al., 2022).

Immunologically, children with severe pertussis demonstrated altered levels of humoral and cellular immune markers. Specifically, they exhibited significantly lower levels of immunoglobulins (IgA and IgG) and complement C3, alongside higher counts of lymphocytes, including CD3⁺, CD4⁺, and CD19⁺ cells (Hashimoto et al., 2005). These findings underscore the complex immunological landscape of severe pertussis, indicating both humoral deficiencies and heightened cellular responses.

Utilizing Lasso regression and multivariate logistic regression analyses, the researchers identified several independent risk factors for severe pertussis: premature birth, incomplete vaccination, elevated WBC counts, and altered lymphocyte profiles. The resulting nomogram prediction model demonstrated excellent performance, achieving a C-index of 0.899, indicating strong discriminative ability (AUC = 0.899) (Dyer, 2025).

**Clinical Implications** The development of this nomogram offers a practical tool for clinicians, facilitating early identification of high-risk children and potentially improving clinical outcomes through timely interventions. Decision curve analysis indicated that the model provides substantial clinical utility, allowing for better-informed treatment decisions compared to traditional methods (Guarnieri et al., 2022).

The findings of this study highlight the urgent need for continued vigilance in pertussis management, particularly in vulnerable populations. Enhanced understanding of the immunological factors associated with severe disease could guide future vaccination strategies and inform public health policies aimed at reducing pertussis morbidity and mortality (Kim et al., 2024).

**Conclusion** In summary, the research conducted at Tianjin Second People’s Hospital significantly advances the understanding of severe pertussis in children, identifying critical clinical and immunological predictors and providing a robust predictive model that can be utilized in clinical practice. Future research efforts should focus on validating these findings in larger, multi-center studies to further refine the nomogram's applicability across diverse populations and settings.