Predictive Framework for Recurrence Risk in Klebsiella pneumoniae Liver Abscess

Overview

This study developed and validated a predictive model specifically for recurrence risk in patients with pyogenic liver abscess caused by Klebsiella pneumoniae (KPLA). The model integrates independent risk factors such as SOFA score and septic shock, providing a quantitative tool to improve clinical decision-making and patient management.

Background

Pyogenic liver abscess (PLA) is a serious infectious disease with increasing incidence worldwide, especially in Asia where Klebsiella pneumoniae is the predominant pathogen. Recurrence of KPLA poses significant clinical challenges, including prolonged hospitalization and severe complications like sepsis. Existing predictive models have focused on mortality or treatment failure rather than recurrence, and often include non-KP cases, limiting their applicability. There is a critical need for a reliable, KP-specific predictive tool to identify patients at high risk of recurrence and guide early intervention.

Data Highlights

A retrospective cohort of 486 patients diagnosed with KPLA between 2015 and 2024 was analyzed. Inclusion criteria required confirmed PLA diagnosis with positive KP cultures. Recurrence was defined by clinical, radiological, and laboratory criteria after one year of follow-up. Independent risk factors identified included SOFA score and septic shock, which were incorporated into a nomogram-based predictive model to stratify recurrence risk.

Key Findings

• Klebsiella pneumoniae is the leading cause of PLA in the Asia-Pacific region, accounting for 42–78.2% of cases.
• Type 2 diabetes mellitus and cerebral infarction are associated with increased recurrence risk in KPLA patients.
• Sepsis and low albumin levels correlate with poor prognosis but differ from recurrence predictors.
• SOFA score and septic shock were identified as independent risk factors specifically predicting KPLA recurrence.
• The developed nomogram model quantitatively integrates these risk factors, enhancing accuracy over subjective clinical assessments.
• The model facilitates stratified risk management and targeted preventive interventions for high-risk patients.

Clinical Implications

Clinicians can utilize the validated nomogram to objectively assess recurrence risk in KPLA patients, enabling early identification of high-risk individuals. This supports tailored follow-up strategies and optimized resource allocation, potentially reducing recurrence rates and improving long-term outcomes. The model’s focus on KP-specific factors enhances its relevance in endemic regions.

Conclusion

This study successfully developed a KP-specific predictive framework for recurrence risk in pyogenic liver abscess, addressing a critical gap in clinical management. The model provides a robust, quantitative tool to guide individualized patient care and improve prognosis.

References

1. Rossi et al. 2021 -- Predictive model for pyogenic liver abscess outcomes
2. Li et al. 2022 -- Risk score for sepsis in KPLA patients
3. Affiliated Hospital of Chengde Medical University Ethics Committee 2024 -- Study approval CYFYLL2022507