Search

Background: Critically ill patients undergo extensive physiological alterations that will have impact on antibiotic pharmacokinetics. Up to 60% of intensive care unit (ICU) patients meet the pharmacodynamic targets of beta-lactam antibiotics, with only 30% in fluoroquinolones. Not reaching these targets might increase the chance of therapeutic failure, resulting in increased mortality and morbidity, and antibiotic resistance. The DOLPHIN trial was designed to demonstrate the added value of therapeutic drug monitoring (TDM) of beta-lactam and fluoroquinolones in critically ill patients in the ICU. Methods: A multi-centre, randomised controlled trial (RCT) was designed to assess the efficacy and cost-effectiveness of model-based TDM of beta-lactam and fluoroquinolones. Four hundred fifty patients will be included within 24 months after start of inclusion. Eligible patients will be randomly allocated to either study group: the intervention group (active TDM) or the control group (non-TDM). In the intervention group dose adjustment of the study antibiotics (cefotaxime, ceftazidime, ceftriaxone, cefuroxime, amoxicillin, amoxicillin with clavulanic acid, flucloxacillin, piperacillin with tazobactam, meropenem, and ciprofloxacin) on day 1, 3, and 5 is performed based upon TDM with a Bayesian model. The primary outcome will be ICU length of stay. Other outcomes amongst all survival, disease severity, safety, quality of life after ICU discharge, and cost effectiveness will be included. Discussion: No trial has investigated the effect of early TDM of beta-lactam and fluoroquinolones on clinical outcome in critically ill patients. The findings from the DOLPHIN trial will possibly lead to new insights in clinical management of critically ill patients receiving antibiotics. In short, to TDM or not to TDM? Trial registration: EudraCT number: 2017-004677-14. Sponsor protocol name: DOLPHIN. Registered 6 March 2018. Protocol Version 6, Protocol date: 27 November 2019.

This paper explores the significance of narrative in collaborative reasoning using a qualitative case study of two teams of intelligence analysts who took part in an exercise using an online collaborative platform. Digital ethnographic methods were used to analyze the chat transcripts of analysts as they reasoned with evidence provided in a difficult, fictional intelligence-type problem and produced a final intelligence report. These chat transcripts provided a powerful "microscope" into the reasoning processes and interactions involved in complex, collaborative reasoning. We found that Individuals and teams used narrative to solve the kinds of complex problems organizations and intelligence agencies face daily. We observed that team members generated what we term "micro-narratives", which provided a means for testing, assessing and weighing alternative hypotheses through mental simulation in the context of collaborative reasoning. The creation of micro-narratives assisted in the teams' reasoning with evidence, an integral part of collaborative reasoning and intelligence analysis. Micro-narratives were combined into, and compared with, an ideal or 'virtual' narrative which informed the judgements the team came to in their final intelligence report. The case study developed in this paper provides evidence that narrative thought processes play an important role in complex collaborative problem-solving, reasoning with evidence and problem-solving. This is contrary to a widespread perception that narrative thinking is fundamentally distinct from formal, logical reasoning.

PURPOSE:To investigate the factors influencing EORTC QLQ-C30-derived EORTC QLU-C10D utility values across five cancer types (non-Hodgkin lymphoma, multiple myeloma, colorectal, thyroid, and prostate cancer) and a general population sample. METHODS:Data from the Dutch population-based patient-reported outcomes following initial treatment and long-term evaluation of survivorship (PROFILES) registry collected between 2009 and 2012 were used. EORTC QLQ-C30 data were used to estimate utility values by applying the EORTC QLU-C10D instrument using Australian utility weights. Regression analyses were conducted, within and across cancer type, to examine the factors influencing utility values, including patient- and cancer-specific factors, as well as the EORTC QLQ-C30 scale/item scores. RESULTS:The mean utility value for the total cancer sample was 0.791 (SD 0.201), significantly lower than that from the general population (0.865, SD 0.165). Multiple myeloma patients had the lowest utility value at 0.663 (SD 0.244). Physical functioning, pain and nausea and vomiting were the health-related quality of life (HRQoL) domains with the greatest impact on utility values; cognitive functioning and dyspnea had the lowest impact. Of the demographic and clinical factors, unemployment for reasons other than retirement, age older than 75 years, number of comorbidities, and experience of symptoms all had a statistically significant negative impact on utility values. CONCLUSIONS:This study is one of the first to apply the EORTC QLU-C10D to a heterogeneous group of cancer patients. Results can be used to more efficiently target care towards factors influencing HRQoL. Furthermore, it enhances our understanding of how the EORTC QLU-C10D performs across cancer types, supporting its use in cost-utility analyses.

Argument mapping is a way of diagramming the logical structure of an argument to explicitly and concisely represent reasoning. The use of argument mapping in critical thinking instruction has increased dramatically in recent decades. A brief history of argument mapping is provided at the end of this paper.