Comparison of computed tomography findings between bacteremic and non-bacteremic acute pyelonephritis due to Escherichia coli.
World J Radiol
; 8(4): 403-9, 2016 Apr 28.
Article
em En
| MEDLINE
| ID: mdl-27158427
AIM: To identify computed tomography (CT) findings that are associated with the presence of bacteremia in patients with acute pyelonephritis (APN) due to Escherichia coli (E. coli). METHODS: The clinical data and contrast-enhanced CT findings of 128 patients who were diagnosed with APN due to E. coli and showed renal abnormality on contrast-enhanced CT between January 2003 and November 2013 were retrospectively reviewed. The patients were divided into two groups according to the presence of bacteremia: The bacteremia group and the non-bacteremia group. The abnormality on contrast-enhanced CT were categorized into 5 renal and 4 extrarenal CT findings and compared between the two groups using the χ (2) test and multivariate logistic regression. RESULTS: Among the 128 patients, 34 patients (26.6%) were classified into the bacteremia group and 94 patients (73.4%) into the non-bacteremia group. There was no statistically significant difference in gender between the two groups (P = 0.09), but the age of the patients in the bacteremia group was higher than that of the patients in the non-bacteremia group (P < 0.01). Compared to the non-bacteremia group, 1 renal CT finding such as urothelial thickening and 3 extrarenal CT findings such as diffuse peritoneal thickening, cystitis and pulmonary congestion were more frequently observed in the bacteremia group with statistical significance. The logistic regression analysis revealed that CT findings, including urothelial thickening, diffuse peritoneal thickening, cystitis and pulmonary congestion were suggested as the predictive CT findings of bacteremic APN. CONCLUSION: On CT, urothelial thickening, diffuse peritoneal thickening, cystitis, and pulmonary congestion are more frequently observed in patients with bacteremic APN due to E. coli.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Idioma:
En
Ano de publicação:
2016
Tipo de documento:
Article