Determinants and impact of multidrug antibiotic resistance in pathogens causing ventilator-associated-pneumonia

Introduction The idea that multidrug resistance (MDR) to antibiotics in pathogens causing ventilator-associated pneumonia (VAP) is an independent risk factor for adverse outcome is still debated. We aimed to identify the determinants of MDR versus non-MDR microbial aetiology in VAP and assessed whether MDR versus non-MDR VAP was independently associated with increased 30-day mortality. Methods We performed a retrospective analysis of a prospectively registered cohort of adult patients with microbiologically confirmed VAP, diagnosed at a university hospital intensive care unit during a three-year period. Determinants of MDR as compared with non-MDR microbial aetiology and impact of MDR versus non-MDR aetiology on mortality were investigated using multivariate logistic and competing risk regression analysis. Results MDR pathogens were involved in 52 of 192 episodes of VAP (27%): methicillin-resistant Staphylococcus aureus in 12 (6%), extended-spectrum beta-lactamase producing Enterobacteriaceae in 28 (15%), MDR Pseudomonas aeruginosa and other non-fermenting pathogens in 12 (6%). Multivariable logistic regression identified the Charlson index of comorbidity (odds ratio (OR) = 1.38, 95% confidence interval (CI) = 1.08 to 1.75, p = 0.01) and previous exposure to more than two different antibiotic classes (OR = 5.11, 95% CI = 1.38 to 18.89, p = 0.01) as predictors of MDR aetiology. Thirty-day mortality after VAP diagnosis caused by MDR versus non-MDR was 37% and 20% (p = 0.02), respectively. A multivariate competing risk regression analysis showed that renal replacement therapy before VAP (standardised hazard ratio (SHR) = 2.69, 95% CI = 1.47 to 4.94, p = 0.01), the Charlson index of comorbidity (SHR = 1.21, 95% CI = 1.03 to 1.41, p = 0.03) and septic shock on admission to the intensive care unit (SHR = 1.86, 95% CI = 1.03 to 3.35, p = 0.03), but not MDR aetiology of VAP, were independent predictors of mortality. Conclusions The risk of MDR pathogens causing VAP was mainly determined by comorbidity and prior exposure to more than two antibiotics. The increased mortality of VAP caused by MDR as compared with non-MDR pathogens was explained by more severe comorbidity and organ failure before VAP

Burnout in the ICU : potential consequences for staff and patient well-being

Peer reviewedAuthor versio

Outcome in patients perceived as receiving excessive care across different ethical climates : a prospective study in 68 intensive care units in Europe and the USA

Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0-1.00) and 85.9% (75.4-92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20-2.92) or receiving a written TLD (HR 2.32, CI 1.11-4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

An ontology-based nurse call management system (oNCS) with probabilistic priority assessment

<p>Abstract</p> <p>Background</p> <p>The current, place-oriented nurse call systems are very static. A patient can only make calls with a button which is fixed to a wall of a room. Moreover, the system does not take into account various factors specific to a situation. In the future, there will be an evolution to a mobile button for each patient so that they can walk around freely and still make calls. The system would become person-oriented and the available context information should be taken into account to assign the correct nurse to a call.</p> <p>The aim of this research is (1) the design of a software platform that supports the transition to mobile and wireless nurse call buttons in hospitals and residential care and (2) the design of a sophisticated nurse call algorithm. This algorithm dynamically adapts to the situation at hand by taking the profile information of staff members and patients into account. Additionally, the priority of a call probabilistically depends on the risk factors, assigned to a patient.</p> <p>Methods</p> <p>The <it>ontology-based Nurse Call System (oNCS) </it>was developed as an extension of a <it>Context-Aware Service Platform</it>. An ontology is used to manage the profile information. Rules implement the novel nurse call algorithm that takes all this information into account. Probabilistic reasoning algorithms are designed to determine the priority of a call based on the risk factors of the patient.</p> <p>Results</p> <p>The <it>oNCS </it>system is evaluated through a prototype implementation and simulations, based on a detailed dataset obtained from Ghent University Hospital. The arrival times of nurses at the location of a call, the workload distribution of calls amongst nurses and the assignment of priorities to calls are compared for the <it>oNCS </it><it>system </it>and the current, place-oriented nurse call system. Additionally, the performance of the system is discussed.</p> <p>Conclusions</p> <p>The execution time of the nurse call algorithm is on average 50.333 ms. Moreover, the <it>oNCS system </it>significantly improves the assignment of nurses to calls. Calls generally have a nurse present faster and the workload-distribution amongst the nurses improves.</p

Towards computerizing intensive care sedation guidelines: design of a rule-based architecture for automated execution of clinical guidelines

<p>Abstract</p> <p>Background</p> <p>Computerized ICUs rely on software services to convey the medical condition of their patients as well as assisting the staff in taking treatment decisions. Such services are useful for following clinical guidelines quickly and accurately. However, the development of services is often time-consuming and error-prone. Consequently, many care-related activities are still conducted based on manually constructed guidelines. These are often ambiguous, which leads to unnecessary variations in treatments and costs.</p> <p>The goal of this paper is to present a semi-automatic verification and translation framework capable of turning manually constructed diagrams into ready-to-use programs. This framework combines the strengths of the manual and service-oriented approaches while decreasing their disadvantages. The aim is to close the gap in communication between the IT and the medical domain. This leads to a less time-consuming and error-prone development phase and a shorter clinical evaluation phase.</p> <p>Methods</p> <p>A framework is proposed that semi-automatically translates a clinical guideline, expressed as an XML-based flow chart, into a Drools Rule Flow by employing semantic technologies such as ontologies and SWRL. An overview of the architecture is given and all the technology choices are thoroughly motivated. Finally, it is shown how this framework can be integrated into a service-oriented architecture (SOA).</p> <p>Results</p> <p>The applicability of the Drools Rule language to express clinical guidelines is evaluated by translating an example guideline, namely the sedation protocol used for the anaesthetization of patients, to a Drools Rule Flow and executing and deploying this Rule-based application as a part of a SOA. The results show that the performance of Drools is comparable to other technologies such as Web Services and increases with the number of decision nodes present in the Rule Flow. Most delays are introduced by loading the Rule Flows.</p> <p>Conclusions</p> <p>The framework is an effective solution for computerizing clinical guidelines as it allows for quick development, evaluation and human-readable visualization of the Rules and has a good performance. By monitoring the parameters of the patient to automatically detect exceptional situations and problems and by notifying the medical staff of tasks that need to be performed, the computerized sedation guideline improves the execution of the guideline.</p

Outcome in patients perceived as receiving excessive care across different ethical climates: a prospective study in 68 intensive care units in Europe and the USA

Purpose: Whether the quality of the ethical climate in the intensive care unit (ICU) improves the identification of patients receiving excessive care and affects patient outcomes is unknown. Methods: In this prospective observational study, perceptions of excessive care (PECs) by clinicians working in 68 ICUs in Europe and the USA were collected daily during a 28-day period. The quality of the ethical climate in the ICUs was assessed via a validated questionnaire. We compared the combined endpoint (death, not at home or poor quality of life at 1 year) of patients with PECs and the time from PECs until written treatment-limitation decisions (TLDs) and death across the four climates defined via cluster analysis. Results: Of the 4747 eligible clinicians, 2992 (63%) evaluated the ethical climate in their ICU. Of the 321 and 623 patients not admitted for monitoring only in ICUs with a good (n = 12, 18%) and poor (n = 24, 35%) climate, 36 (11%) and 74 (12%), respectively were identified with PECs by at least two clinicians. Of the 35 and 71 identified patients with an available combined endpoint, 100% (95% CI 90.0–1.00) and 85.9% (75.4–92.0) (P = 0.02) attained that endpoint. The risk of death (HR 1.88, 95% CI 1.20–2.92) or receiving a written TLD (HR 2.32, CI 1.11–4.85) in patients with PECs by at least two clinicians was higher in ICUs with a good climate than in those with a poor one. The differences between ICUs with an average climate, with (n = 12, 18%) or without (n = 20, 29%) nursing involvement at the end of life, and ICUs with a poor climate were less obvious but still in favour of the former. Conclusion: Enhancing the quality of the ethical climate in the ICU may improve both the identification of patients receiving excessive care and the decision-making process at the end of life

Ethical climate and intention to leave among critical care clinicians: an observational study in 68 intensive care units across Europe and the United States

Purpose: Apart from organizational issues, quality of inter-professional collaboration during ethical decision-making may affect the intention to leave one’s job. To determine whether ethical climate is associated with the intention to leave after adjustment for country, ICU and clinicians characteristics. Methods: Perceptions of the ethical climate among clinicians working in 68 adult ICUs in 12 European countries and the US were measured using a self-assessment questionnaire, together with job characteristics and intent to leave as a sub-analysis of the Dispropricus study. The validated ethical decision-making climate questionnaire included seven factors: not avoiding decision-making at end-of-life (EOL), mutual respect within the interdisciplinary team, open interdisciplinary reflection, ethical awareness, self-reflective physician leadership, active decision-making at end-of-life by physicians, and involvement of nurses in EOL. Hierarchical mixed effect models were used to assess associations between these factors, and the intent to leave in clinicians within I