Completeness of Neisseria meningitidis reporting in New York City, 1989-2010

A rare case of purulent meningitis caused by Capnocytophaga canimorsus in the Czech Republic - case report and review of the literature

Background

Invasive infections caused by Capnocytophaga canimorsus are rare. Immunocompromised patients, who report being bitten by or having a close contact with an animal, represent a high-risk group for this infection. There are only few dozens of infections by this bacteria manifesting as purulent meningitis reported worldwide. The reported case is a first reported case of purulent meningitis caused by by Capnocytophaga canimorsus in Czech Republic with only a limited risk factor history.

Case presentation

The patient, a 74 years old man, was referred to the infectious diseases department of a teaching hospital with clear signs of developing purulent meningitis. His anamnestic data did not show any unusual findings. He was treated for compensated diabetes mellitus type II. The blood cultures were negative and the etiological agent did not grow from the cerebrospinal fluid (CSF) on common media. Eventually, it was identified by detecting pan-bacterial DNA and DNA sequencing. Subsequently, the pathogen was confirmed by anaerobic cultivation from CSF. Only after then the patient recalled being bitten by his German shepherd puppy during play. The patient was successfully treated intravenously by ceftriaxone.

Conclusions

Purulent meningitis caused by Capnocytophaga spp. is a rare disease, but it needs to be considered in patients at risk with pre-existing conditions, who report close contact with or being bitten by an animal. It is important to test for this microbe in cases with negative microbiological results for the more common agents.

Mining co-occurrence and sequence patterns from cancer diagnoses in New York State

The goal of this study is to discover disease co-occurrence and sequence patterns from large scale cancer diagnosis histories in New York State. In particular, we want to identify disparities among different patient groups. Our study will provide essential knowledge for clinical researchers to further investigate comorbidities and disease progression for improving the management of multiple diseases. We used inpatient discharge and outpatient visit records from the New York State Statewide Planning and Research Cooperative System (SPARCS) from 2011-2015. We grouped each patient’s visit history to generate diagnosis sequences for seven most popular cancer types. We performed frequent disease co-occurrence mining using the Apriori algorithm, and frequent disease sequence patterns discovery using the cSPADE algorithm. Different types of cancer demonstrated distinct patterns. Disparities of both disease co-occurrence and sequence patterns were observed from patients within different age groups. There were also considerable disparities in disease co-occurrence patterns with respect to different claim types (i.e., inpatient, outpatient, emergency department and ambulatory surgery). Disparities regarding genders were mostly found where the cancer types were gender specific. Supports of most patterns were usually higher for males than for females. Compared with secondary diagnosis codes, primary diagnosis codes can convey more stable results. Two disease sequences consisting of the same diagnoses but in different orders were usually with different supports. Our results suggest that the methods adopted can generate potentially interesting and clinically meaningful disease co-occurrence and sequence patterns, and identify disparities among various patient groups. These patterns could imply comorbidities and disease progressions.