Chronic Q fever diagnosis—consensus guideline versus expert opinion

Chronic Q fever, caused by Coxiella burnetii, has high mortality and morbidity rates if left untreated. Controversy about the diagnosis of this complex disease has emerged recently. We applied the guideline from the Dutch Q Fe­ver Consensus Group and a set of diagnostic criteria pro­posed by Didier Raoult to all 284 chronic Q fever patients included in the Dutch National Chronic Q Fever Database during 2006–2012. Of the patients who had proven cas­es of chronic Q fever by the Dutch guideline, 46 (30.5%) would not have received a diagnosis by the alternative cri­teria designed by Raoult, and 14 (4.9%) would have been considered to have possible chronic Q fever. Six patients with proven chronic Q fever died of related causes. Until results from future studies are available, by which current guidelines can be modified, we believe that the Dutch lit­erature-based consensus guideline is more sensitive and easier to use in clinical practice

A Probabilistic and Decision-Theoretic Approach to the Management of Infectious Disease at the ICU

The medical community is presently in a state of transition from a situation dominated by the paper medical record to a future situation where all patient data will be available online by an electronic clinical information system. In data-intensive clinical environments, such as intensive care units (ICUs), clinical patient data are already fully managed by such systems in a number of hospitals. However, providing facilities for storing and retrieving patient data to clinicians is not enough; clinical information systems should also offer facilities to assist clinicians in dealing with hard clinical problems. Extending an information system's capabilities by integrating it with a decision-support system may be a solution. In this paper, we describe the development of a probabilistic and decision-theoretic system that aims to assist clinicians in diagnosing and treating patients with pneumonia in the intensive-care unit. Its underlying probabilistic-network model includes tempo..

Improving Antibiotic Therapy of Ventilator Associated Pneumonia using a Probabilistic Approach

PTA is a decision-theoretic expert system that aims to assist clinicians in diagnosing and treating patients with pneumonia at the intensive care unit. The underlying probabilistic network model includes knowledge for diagnosing pneumonia on the basis of the likelihood of tracheobronchial-tree colonisation by pathogens, and symptoms and signs actually present in the patient. Optimal antibiotic therapy is selected by balancing the expected efficacy of treatment, which is related to the likelihood of pathogen-specific pneumonias, against costs and side effects of treatment. In this article, the structure of the system and results of a preliminary evaluation are described