Identifying excessive length of antibiotic treatment duration for hospital-acquired infections: a semi-automated approach to support antimicrobial stewardship.

BACKGROUND: Avoiding excessive antibiotic treatment duration is a fundamental goal in antimicrobial stewardship. Manual collection of data is a time-consuming process, but a semi-automated approach for data extraction has been shown feasible for community-acquired infections (CAI). Extraction of data however may be more challenging in hospital-acquired infections (HAI). The aim of this study is to explore whether semi-automated data extraction of treatment duration is also feasible and accurate for HAI. METHODS: Data from a university-affiliated hospital over the period 1-6-2020 until 1-6-2022 was used for this study. From the Electronic Health Record, raw data on prescriptions, registered indications and admissions was extracted and processed to define treatment courses. In addition, clinical notes including prescription instructions were obtained for the purpose of validation. The derived treatment course was compared to the registered indication and the actual length of treatment (LOT) in the clinical notes in a random sample of 5.7% of treatment courses, to assess the accuracy of the data for both CAI and HAI. RESULTS: Included were 10.564 treatment courses of which 73.1% were CAI and 26.8% HAI. The registered indication matched the diagnosis as recorded in the clinical notes in 79% of treatment courses (79.2% CAI, 78.5% HAI). Higher error rates were seen in urinary tract infections (UTIs) (29.0%) and respiratory tract infections (RTIs) (20.5%) compared to intra-abdominal infections (7.4%), or skin or soft tissue infections (11.1%), mainly due to incorrect specification of the type of UTI or RTI. The LOT was accurately extracted in 98.5% of courses (CAI 98.2%, HAI 99.3%) when compared to prescriptions in the EHR. In 21% of cases however the LOT did not match with the clinical notes, mainly if patients received treatment from other health care providers preceding or following the present course. CONCLUSION: Semi-automatic data extraction can yield reliable information about the indication and LOT in treatment courses of hospitalized patients, for both HAI and CAI. This can provide stewardship programs with a surveillance tool for all in-hospital treated infections, which can be used to achieve stewardship goals.

Community-acquired group B streptococcal meningitis in adults.

INTRODUCTION: Streptococcus agalactiae (group B streptococci; GBS) is an uncommon cause of bacterial meningitis in adults. METHODS: We reviewed literature published between 1975 and 2018. Studies were included if they reported age, sex and outcome of patients above 16 years of age with cerebrospinal fluid culture (CSF) positive for GBS. RESULTS: Sixty-seven articles describing 141 patients were included. Median age was 56 years (IQR 41-66); 52% were male. Fifty-three patients (38%) were immunocompromised and CSF leakage was reported in 9 (10%) of 88 immunocompetent patients. Sixty-two patients (44%) had extra-meningeal foci of infection, most commonly endocarditis, which occurred in 14 patients (12%). Twenty-eight patients (23%) were described as previously healthy. Forty-four (31%) of the 141 patients died, after a median duration of 5 days after admission. Death was associated with advanced age and an immunocompromised state. CONCLUSION: GBS meningitis in adults mainly occurs in those with underlying conditions such as immunocompromised state, CSF leakage, and endocarditis. These conditions should be actively sought for in adults with GBS meningitis.