Proteus empyema as a rare complication from an infected renal cyst, a case report.

BACKGROUND: The most commonly isolated organisms in a parapneumonic effusion include S. pneumoniae, H. influenzae, and S. aureus. If unusual organisms are isolated from the pleural space, further investigation is warranted to locate the primary source. We present a patient with an infected chronic renal cyst found to have an empyema secondary to Proteus mirabilis to highlight the importance of further diagnostic workup when encountering unusual organisms in the pleural space. CASE PRESENTATION: A 40-year-old African-American female, with a past medical history of asthma and sickle cell trait, presented with 5 weeks of upper respiratory tract symptoms and chest pain. A computed tomography angiogram (CTA) of the chest was negative for a pulmonary embolism but revealed a loculated left sided pleural effusion with associated left-lower lobe consolidation. She was started on empiric antibiotics, and a chest tube was inserted with drainage of frank pus. Fluid gram stain was positive for gram negative rods. Intrapleural fibrinolytics were administered for 72 h given the presence of loculations. With no improvement following fibrinolytics, she was taken to the operating room for large bore chest tube placement and left visceral pleura decortication. Pleural fluid cultures speciated to Proteus mirabilis, so further cross-sectional imaging of her abdomen/pelvis was pursued to evaluate for a primary source. A complex cystic lesion in the upper pole of the left kidney that communicated with the ipsilateral diaphragm was identified. Subsequent drainage and culture of the renal cyst was positive for Proteus mirabilis. Given clinical improvement following these interventions she was discharged with an extended course of antibiotics with plans for repeat imaging following completion of treatment. CONCLUSIONS: While cases of Proteus mirabilis empyema have previously been reported as a consequence of conditions such as pyelonephritis, we present, to our knowledge, the first case of a Proteus mirabilis empyema as a consequence of an infected renal cyst communicating with the pleural space. This study highlights that further evaluation with cross-sectional imaging is warranted when unusual organisms are found in the pleural space. Anatomic abnormalities that become apparent on imaging may help elucidate the source of infection.

Assessment of mutational load in biopsy tissue provides additional information about genomic instability to histological classifications of Barrett's esophagus.

PURPOSE: Progression of Barrett's esophagus (BE) to esophageal adenocarcinoma (EAC) is associated with accumulated genomic instability. Current risk stratification of BE for EAC relies on histological classification and grade of dysplasia. However, histology alone cannot assess the risk of patients with inconsistent or non-dysplastic BE histology. We, therefore, examined the presence and extent of genomic instability in advanced and less advanced BE histology using mutational load (ML). METHODS: ML summarized the presence and clonality of loss of heterozygosity (LOH) mutations and the emergence of new alleles, manifested as microsatellite instability (MSI) mutations, in ten genomic loci around tumor suppressor genes associated with EAC. The ML of 877 microdissected targets from BE biopsies was correlated to their histology. Histological targets were categorized into three levels: no ML, low ML, and high ML. RESULTS: Increasing ML correlated with increasingly severe histology. By contrast, proportions of targets that lacked mutations decreased with increasingly severe histology. A portion of targets with non-dysplastic and low-grade histology shared a similar ML as those with higher risk and EAC disease. The addition of MSI characterization to ML helped to differentiate the ML between advanced and less advanced histology. CONCLUSIONS: Given that EAC is associated with accumulated genomic instability, high ML in less severe histology may identify BE disease at greater risk of progression to EAC. ML may help to better manage BE in early histological stages and when histology alone provides insufficient information.