Molecular Epidemiology, Clinical Course, and Implementation of Specific Hygiene Measures in Hospitalised Patients with Clostridioides difficile Infection in Brandenburg, Germany.
Esther E DirksJasminka A LukovićHeidrun Peltroche-LlacsahuangaAnke HerrmannAlexander MellmannMardjan ArvandPublished in: Microorganisms (2022)
(1) Background: Clostridioides difficile infections (CDI) have increased worldwide, and the disease is one of the most common healthcare-associated infections (HAI). This study aimed to evaluate the molecular epidemiology of C. difficile , the clinical outcome, and the time of initiation of specific hygiene measures in patients with CDI in a large tertiary-care hospital in Brandenburg. (2) Methods: Faecal samples and data from hospitalised patients diagnosed with CDI were analysed from October 2016 to October 2017. The pathogens were isolated, identified as toxigenic C. difficile , and subsequently subtyped using PCR ribotyping and whole genome sequencing (WGS). Data regarding specific hygiene measures for handling CDI patients were collected. (3) Results: 92.1% of cases could be classified as healthcare-associated (HA)-CDI. The recurrence rate within 30 and 90 days after CDI diagnosis was 15.7% and 18.6%, and the mortality rate was 21.4% and 41.4%, respectively. The most frequent ribotypes (RT) were RT027 (31.3%), RT014 (18.2%), and RT005 (14.1%). Analysis of WGS data using cgMLST showed that all RT027 isolates were closely related; they were assigned to two subclusters. Single-room isolation or barrier measures were implemented in 95.7% patients. (4) Conclusions: These data show that RT027 is regionally predominant, thus highlighting the importance of specific hygiene measures to prevent and control CDI and the need to improve molecular surveillance of C. difficile at the local and national level.
Keyphrases
- healthcare
- clostridium difficile
- end stage renal disease
- ejection fraction
- newly diagnosed
- chronic kidney disease
- prognostic factors
- electronic health record
- tertiary care
- emergency department
- public health
- peritoneal dialysis
- primary care
- cardiovascular disease
- coronary artery disease
- type diabetes
- social media
- machine learning
- patient reported
- oral health
- health insurance