Characteristics of Computed Tomography for Identifying Patients at High Risk of Endogenous Endophthalmitis Due to Klebsiella pneumoniae-Related Pyogenic Liver Abscess

Endogenous endophthalmitis (EE) associated with Klebsiella pneumoniae (K. pneumoniae)-related pyogenic liver abscess (PLA) is one of the fatal complications of PLA and leads to loss of vision. Early diagnosis and treatment are important to save the patient's vision. We investigated the characteristics of computed tomography (CT) in EE associated with K. pneumoniae-related PLA for the identification of the predictors of EE, in order to facilitate early diagnosis. A total of 274 patients diagnosed with K. pneumoniae-related PLA, including 15 patients with EE, were identified between January 2005 and December 2019. The clinical (age, gender, and underlying disease) and radiologic (the location, size, and number of abscesses) features were reviewed. In addition, the involvement of the adjacent vessels, such as the hepatic vein and portal vein, was carefully reviewed. A comparative analysis was performed between the EE and non-EE groups. Uni- and multivariate logistic regression analyses were used to identify the predictors of EE. Diabetes mellitus (DM), the involvement of the left or both hepatic lobes, and the adjacent vessels on the CT were significantly more frequent than those in the non-EE group (p < 0.05 in all), and they were the significant predictors of EE in the logistic regression analyses. In patients with K. pneumoniae-related PLA, the CT findings, such as the locations of the abscess (i.e., left or both lobes) and the involvement of the adjacent vessels, should be considered in addition to the ocular symptoms for an early diagnosis of EE.

Automated summary

This study investigated the CT characteristics of endogenous endophthalmitis (EE) associated with Klebsiella pneumoniae (K. pneumoniae)-related pyogenic liver abscess (PLA). It found that diabetes mellitus (DM), involvement of the left or both hepatic lobes, and the adjacent vessels on CT were significant predictors of EE. These findings provide valuable information for early diagnosis of EE.