Using probabilistic patient flow modelling helps generate individualised intensive care unit operational predictions and improved understanding of current organisational behaviours.

PURPOSE: We sought a bespoke, stochastic model for our specific, and complex ICU to understand its organisational behaviour and how best to focus our resources in order to optimise our intensive care unit's function. METHODS: Using 12 months of ICU data from 2017, we simulated different referral rates to find the threshold between occupancy and failed admissions and unsafe days. We also modelled the outcomes of four change options. RESULTS: Ninety-two percent bed occupancy is our threshold between practical unit function and optimal resource use. All change options reduced occupancy, and less predictably unsafe days and failed admissions. They were ranked by magnitude and direction of change. CONCLUSIONS: This approach goes one step further from past models by examining efficiency limits first, and then allowing change options to be quantitatively compared. The model can be adapted by any intensive care unit in order to predict optimal strategies for improving ICU efficiency.

A Candida auris Outbreak and Its Control in an Intensive Care Setting.

BACKGROUND: Candida auris is an emerging and multidrug-resistant pathogen. Here we report the epidemiology of a hospital outbreak of C. auris colonization and infection. METHODS: After identification of a cluster of C. auris infections in the neurosciences intensive care unit (ICU) of the Oxford University Hospitals, United Kingdom, we instituted an intensive patient and environmental screening program and package of interventions. Multivariable logistic regression was used to identify predictors of C. auris colonization and infection. Isolates from patients and from the environment were analyzed by whole-genome sequencing. RESULTS: A total of 70 patients were identified as being colonized or infected with C. auris between February 2, 2015, and August 31, 2017; of these patients, 66 (94%) had been admitted to the neurosciences ICU before diagnosis. Invasive C. auris infections developed in 7 patients. When length of stay in the neurosciences ICU and patient vital signs and laboratory results were controlled for, the predictors of C. auris colonization or infection included the use of reusable skin-surface axillary temperature probes (multivariable odds ratio, 6.80; 95% confidence interval [CI], 2.96 to 15.63; P<0.001) and systemic fluconazole exposure (multivariable odds ratio, 10.34; 95% CI, 1.64 to 65.18; P=0.01). C. auris was rarely detected in the general environment. However, it was detected in isolates from reusable equipment, including multiple axillary skin-surface temperature probes. Despite a bundle of infection-control interventions, the incidence of new cases was reduced only after removal of the temperature probes. All outbreak sequences formed a single genetic cluster within the C. auris South African clade. The sequenced isolates from reusable equipment were genetically related to isolates from the patients. CONCLUSIONS: The transmission of C. auris in this hospital outbreak was found to be linked to reusable axillary temperature probes, indicating that this emerging pathogen can persist in the environment and be transmitted in health care settings. (Funded by the National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at Oxford University and others.).

Management of cerebral venous thrombosis in a patient with Lane-Hamilton syndrome and coeliac disease, epilepsy and cerebral calcification syndrome.

We describe a case of cerebral venous thrombosis presenting in a patient with Lane-Hamilton syndrome and coeliac disease epilepsy cerebral calcification syndrome. This is a first reported occurrence of this combination. Delayed anticoagulation with early external ventricular drain insertion for life-threatening raised intracranial pressure resulted in a successful outcome.