Antimicrobial prescription in severe COVID-19 and CAP: a matched case-control study.

BACKGROUND: In severe coronavirus diseases 2019 (COVID-19), a high and potentially excessive use of antimicrobials for suspected bacterial co-infection and intensive care unit (ICU)-acquired infections has been repeatedly reported. OBJECTIVES: To compare an ICU cohort of community-acquired pneumonia (CAP) with a cohort of severe COVID-19 pertaining to co-infections, ICU-acquired infections and associated antimicrobial consumption. METHODS: We retrospectively compared a cohort of CAP patients with a cohort of COVID-19 patients matched according to organ failure, ICU length of stay (LOS) and ventilation days. Patient data such as demographics, infection focus, probability and severity, ICU severity scores and ICU and in-hospital mortality, days of antimicrobial therapy (DOT) and number of antimicrobial prescriptions, using an incremental scale, were registered and analysed. The total number of cultures (sputum, urinary, blood cultures) was collected and corrected for ICU LOS. FINDINGS: CAP patients (n = 148) were matched to COVID-19 patients (n = 74). Significantly less sputum cultures (68.2% versus 18.9%, P < 0.05) and bronchoalveolar lavages (BAL) (73.7% versus 36.5%, P < 0.05) were performed in COVID-19 patients. Six (8.1%) COVID-19 patients were diagnosed with a co-infection. Respectively, 58 of 148 (39.2%) CAP and 38 of 74 (51.4%) COVID-19 patients (P = 0.09) developed ICU-acquired infections. Antimicrobial distribution, both in the number of prescriptions and DOT, was similar in both cohorts. CONCLUSIONS: We found a low rate of microbiologically confirmed bacterial co-infection and a high rate of ICU-acquired infections in COVID-19 patients. Infection probabilities, antimicrobial prescriptions and DOT were comparable with a matched CAP cohort.

Towards automated generation and execution of clinical guidelines: engine design and implementation through the ICU Modified Schofield use case.

As the complexity and amount of medical information keeps increasing, it is difficult to maintain the same quality of care. Therefore, clinical guidelines are used to structure best practices and care, but they also support physicians and nurses in the diagnostic and treatment process. Currently, no standardized format exists to represent these guidelines. Translating guidelines into a computer interpretable format can overcome problems in the physicians' workflow and improve clinician's uptake. An engine is proposed to automatically translate and execute clinical guidelines. These guidelines are represented as flowcharts, expressed in either (i) a computer interpretable guideline format or (ii) a UML diagram. A detailed overview of the architecture is presented and algorithms, aiming at grouping several components and distributing the guidelines, are proposed to optimize the execution of the guidelines. The Modified Schofield guideline for the calculation of the calorie need for burn patients was used for evaluation. Results show that the execution of guidelines using the engine is very efficient. Using optimization algorithms the execution times can be lowered.

Service-oriented subscription management of medical decision data in the intensive care unit.

OBJECTIVES: This paper addresses the design of a platform for the management of medical decision data in the ICU. Whenever new medical data from laboratories or monitors is available or at fixed times, the appropriate medical support services are activated and generate a medical alert or suggestion to the bedside terminal, the physician's PDA, smart phone or mailbox. Since future ICU systems will rely ever more on medical decision support, a generic and flexible subscription platform is of high importance. METHODS: Our platform is designed based on the principles of service-oriented architectures, and is fundamental for service deployment since the medical support services only need to implement their algorithm and can rely on the platform for general functionalities. A secure communication and execution environment are also provided. RESULTS: A prototype, where medical support services can be easily plugged in, has been implemented using Web service technology and is currently being evaluated by the Department of Intensive Care of the Ghent University Hospital. To illustrate the platform operation and performance, two prototype medical support services are used, showing that the extra response time introduced by the platform is less than 150 ms. CONCLUSIONS: The platform allows for easy integration with hospital information systems. The platform is generic and offers user-friendly patient/service subscription, transparent data and service resource management and priority-based filtering of messages. The performance has been evaluated and it was shown that the response time of platform components is negligible compared to the execution time of the medical support services.

Comparison of single and multiple agency clients in substance abuse treatment services.

BACKGROUND: Frequent and multiple service utilization among substance abusers is a well-known problem. However, little statistical evidence exists about overlapping agency populations. METHODS: This phenomenon was studied in a clear-cut region in Belgium, based on intake information concerning all clients who addressed a drug treatment center within a 6-month period (n=1,139). RESULTS: Multiple service utilization was rather common but not omnipresent during this particular registration period. Almost 15% of the clients were registered in more than one substance abuse treatment agency. Compared to single agency attendees, multiple agency clients appeared to be more often poly-substance abusers with a longer previous treatment history and greater problem severity. CONCLUSION: A continuous care perspective, interagency collaboration and a common tracking and documentation system are recommended to better address the needs of this specific subgroup of substance abusers. More research is needed to clarify whether these multiple service utilization patterns are caused by client-related, agency-related or other factors.

Design of a flexible platform for execution of medical decision support agents in the intensive care unit.

This paper addresses the design of a generic and scalable platform for the execution of medical decision support agents in the intensive care unit (ICU). As will be motivated, medical decision support agents can impose high computational load and in practical setups a large amount of such agents are typically running in parallel. Future ICU systems will rely on extensive medical decision support. However, in current systems only one workstation is typically dedicated for the execution of medical decision support agents. Therefore, we propose an architecture based on middleware technology to allow for easy distribution of the agents along multiple workstations. The architecture allows for easy integration with a general ICU data flow management architecture.

Implementation of a real-time electronic alert based on the RIFLE criteria for acute kidney injury in ICU patients.

Acute kidney injury (AKI) is very common among critically-ill patients and is correlated with significant morbidity and mortality. The RIFLE criteria (an acronym comprising Risk, Injury, Failure, Loss and End-stage kidney disease), were developed by a panel of experts aiming at standardizing the definition of AKI and to subdivide AKI into different categories of severity. However, although these criteria are clear and easy to understand, they are still complex and labour-intensive, and therefore mostly used in retrospective. The use of an electronic alert based on the RIFLE criteria, which warns the physician in real-time when kidney function is deteriorating can help to implement these criteria in daily clinical practice. In this paper we describe the successful implementation of such an alert system. Not only were there technological barriers to solve; also acceptance of the alert by the end user was of pivotal importance. Further research is currently performed to investigate whether the implementation of real-time electronic RIFLE alerts induce faster therapeutic intervention, and to evaluate the impact of a more timely intervention on improved preservation of kidney function and patients' outcome.