THE STORM (acute coronary Syndrome in paTients end Of life and Risk assesMent) study.

INTRODUCTION: Elderly patients with coexisting frailty and multiple comorbidities frequently present to the emergency department (ED). Because non-cardiovascular comorbidities and declining health status may affect their life expectancy, management of these patients should start in the ED. This study evaluated the role of Gold Standards Framework (GSF) criteria for identifying patients with acute coronary syndromes (ACS) approaching end of life. METHODS: All consecutive patients admitted to the ED and hospitalised with a diagnosis of ACS between May 2012 and July 2012 were included. According to GSF criteria, patients were labelled as positive GSF status when they met at least one general criterion and two heart disease criteria; furthermore, traditional cardiovascular risk scores (the Global Registry for Acute Coronary Events (GRACE) score and the Age, Creatinine and Ejection Fraction (ACEF) score) were calculated and WHOQOL-BREF was assessed. Mortality and repeat hospitalisation due to cardiovascular and non-cardiovascular causes were evaluated at 3-month and 12-month follow-up. RESULTS: From a total of 156 patients with ACS enrolled, 22 (14%) had a positive GSF. A positive GSF was associated with higher rate of non-cardiovascular events (22.7% vs 6.7%; p=0.03) at 3 months and higher rates of both cardiovascular and non-cardiovascular events (36% vs 16.4%; p=0.04 and 27.3% vs 6.7%; p=0.009, respectively) at 12 months. In multivariate analysis, an in-hospital GRACE score was a predictor of cardiovascular events, while a positive GSF independently predicted non-cardiovascular events. CONCLUSIONS: The GSF score independently predicts non-cardiovascular events in patients presenting with ACS and may be used along with traditional cardiovascular risk scores in choosing wisely the most appropriate treatment. The present results need to be externally validated on larger samples.

Supporting human interaction and human resources coordination in distributed clinical guidelines.

Clinical guidelines (GL) play an important role in medical practice: the one of optimizing the quality of patient care on the basis of the best and most recent evidence based medicine. In order to achieve this goal, the interaction between different actors, who cooperate in the execution of the same GL, is a crucial issue. As a matter of fact, in many cases (e.g. in chronic disease treatment) the GL execution requires that patient treatment is not performed/completed in the hospital, but is continued in different contexts (e.g. at home, or in the general practitioner's ambulatory), under the responsibility of different actors. In this situation, the correct interaction and communication between the actors themselves is critical for the quality of care, and human resources coordination is a key issue to be addressed by the managers of the involved healthcare service. In this paper we describe how computerized GL management can be extended in order to support such needs, and we illustrate our approach by means of a practical case study.

Applying artificial intelligence to clinical guidelines: the GLARE approach.

We present GLARE, a domain-independent system for acquiring, representing and executing clinical guidelines (GL). GLARE is characterized by the adoption of Artificial Intelligence (AI) techniques in the definition and implementation of the system. First of all, a high-level and user-friendly knowledge representation language has been designed. Second, a user-friendly acquisition tool, which provides expert physicians with various forms of help, has been implemented. Third, a tool for executing GL on a specific patient has been made available. At all the levels above, advanced AI techniques have been exploited, in order to enhance flexibility and user-friendliness and to provide decision support. Specifically, this chapter focuses on the methods we have developed in order to cope with (i) automatic resource-based adaptation of GL, (ii) representation and reasoning about temporal constraints in GL, (iii) decision making support, and (iv) model-based verification. We stress that, although we have devised such techniques within the GLARE project, they are mostly system-independent, so that they might be applied to other guideline management systems.

Extending temporal databases to deal with telic/atelic medical data.

OBJECTIVE: In this paper, we aim at defining a general-purpose data model and query language coping with both "telic" and "atelic" medical data. BACKGROUND: In the area of Medical Informatics, there is an increasing realization that temporal information plays a crucial role, so that suitable database models and query languages are needed to store and support it. However, despite the wide range of approaches in the area, in this paper we show that a relevant class of medical data cannot be properly dealt with. METHODOLOGY: We first show that data models based on the "point-based" semantics, which is (implicitly or explicitly) assumed by the totality of temporal database approaches, have several limitations when dealing with "telic" data. We then propose a new model (based on the "interval-based" semantics) to cope with such data, and extend the query language accordingly. RESULTS: We propose a new three-sorted model and a query language to properly deal with both "telic" and "atelic" medical data (as well as non-temporal data). Our query language is flexible, since it allows one to switch from "atelic" to "telic" data, and vice versa. CONCLUSION: In this paper, we demonstrate the feasibility of a database approach copying with both telic and atelic data as needed in several (medical) applications.

The GLARE approach to clinical guidelines: main features.

In this paper, we present GLARE, a domain-independent prototypical system for acquiring, representing and executing clinical guidelines. GLARE has been built within a 7-year project with Azienda Ospedaliera San Giovanni Battista in Turin (one of the largest hospitals in Italy) and has been successfully tested on clinical guidelines in different domains, including bladder cancer, reflux esophagitis, and heart failure. GLARE is characterized by the adoption of advanced Artificial Intelligence (AI) techniques, to support medical decision making and to manage temporal knowledge.

A context-adaptable approach to clinical guidelines.

One of the most relevant obstacles to the use and dissemination of clinical guidelines is the gap between the generality of guidelines (as defined, e.g., by physicians' committees) and the peculiarities of the specific context of application. In particular, general guidelines do not take into account the fact that the tools needed for laboratory and instrumental investigations might be unavailable at a given hospital. Moreover, computer-based guideline managers must also be integrated with the Hospital Information System (HIS), and usually different DBMS are adopted by different hospitals. The GLARE (Guideline Acquisition, Representation and Execution) system addresses these issues by providing a facility for automatic resource-based adaptation of guidelines to the specific context of application, and by providing a modular architecture in which only limited and well-localised changes are needed to integrate the system with the HIS at hand.

Supporting a distributed execution of clinical guidelines.

Clinical guidelines (GL) play an important role in medical practice: the one of optimizing the quality of patient care on the basis of evidence based medicine. In order to achieve this goal, the interaction between different agents, who cooperate in the execution of the same GL, is a crucial issue. As a matter of fact, in many cases (e.g. in chronic disorders) the GL execution requires that patient treatment is not performed/completed in the hospital, but is continued in different contexts (e.g. at home, or in the general practitioner's ambulatory), under the responsibility of different agents. In this situation, the correct interaction and communication between the agents themselves is critical for the quality of care, and human resources coordination is a key issue to be addressed by the managers of the involved healthcare services. In this paper we describe how GLARE (Guideline Acquisition, Representation, and Execution), a computerized GL management system, has been extended in order to support such a need. In particular, we have provided: (i) an extension to GL actions representation languages, (ii) proper scheduling and (iii) querying services. By means of these enhancements we aimed at guaranteeing (1) treatment continuity and (2) responsibility assignment support in the various steps of a coordinated and distributed patient care process. We illustrate our approach by means of a practical case study.

Adopting model checking techniques for clinical guidelines verification.

OBJECTIVES: Clinical guidelines (GLs) are assuming a major role in the medical area, in order to grant the quality of the medical assistance and to optimize medical treatments within healthcare organizations. The verification of properties of the GL (e.g., the verification of GL correctness with respect to several criteria) is a demanding task, which may be enhanced through the adoption of advanced Artificial Intelligence techniques. In this paper, we propose a general and flexible approach to address such a task. METHODS AND MATERIALS: Our approach to GL verification is based on the integration of a computerized GL management system with a model-checker. We propose a general methodology, and we instantiate it by loosely coupling GLARE, our system for acquiring, representing and executing GLs, with the model-checker SPIN. RESULTS: We have carried out an in-depth analysis of the types of properties that can be effectively verified using our approach, and we have completed an overview of the usefulness of the verification task at the different stages of the GL life-cycle. In particular, experimentation on a GL for ischemic stroke has shown that the automatic verification of properties in the model checking approach is able to discover inconsistencies in the GL that cannot be detected in advance by hand. CONCLUSION: Our approach thus represents a further step in the direction of general and flexible automated GL verification, which also meets usability requirements.

Clinical guidelines contextualization in GLARE.

The adaptation of clinical guidelines to specific contexts is a fundamental task to promote guideline dissemination and use. Several aspects of contextualization need to be faced, including the adaptation of guidelines to local resource availability and (for computer-based guideline approaches) to local software environment. We show how a computer-based approach can help in such a challenging task.

GLARE: a domain-independent system for acquiring, representing and executing clinical guidelines.

We briefly describe GLARE, a domain-independent system to acquire, represent and execute clinical guidelines, which as been developed since 1997 in a joint cooperation between Computer Sciences Departments and Az. Ospedaliera S. Giovanni Battista in Turin, one of the largest hospitals in Italy. A demo of the (prototypical) system is also available.

Supporting physicians in taking decisions in clinical guidelines: the GLARE "what if" facility.

GLARE (GuideLine Acquisition, Representation and Execution) is a domain-independent system for the acquisition, representation and execution of clinical guidelines. GLARE is unique in its approach to supporting the decision-making process of users/physicians faced with various alternatives in the guidelines. In many cases, the best alternative cannot be determined on the basis of "local information" alone (i.e., by considering just the selection criteria associated with the decision at hand), but must also take into account information stemming from relevant alternative pathways. Exploitation of "global information" available in the various pathways is made possible by GLARE through the "what if" facility, a form of hypothetical reasoning which allows users to gather relevant decision parameters (e.g., costs, resources, times) from selected parts of the guideline in a semi-automatic fashion. In particular, the extremely complex task of coping with temporal information involves the extension and adaptation of various techniques developed by the Artificial Intelligence (AI) community.

Temporal consistency checking in clinical guidelines acquisition and execution: the GLARE's approach.

GLARE (GuideLine Acquisition, Representation and Execution) is a domain-independent system for the acquisition, representation and execution of clinical guidelines. Temporal constraints play an important role within clinical guidelines (e.g. to specify therapies). The treatment of such constraints is one of the distinguishing features of GLARE. During acquisition, GLARE supports (i) the representation and (ii) the check of the consistency of the temporal constraints. Moreover, it (iii) automatically checks that the times of execution of specific actions respect the general temporal constraints described in the guideline. Such a treatment of temporal constraints involves the extension of various Artificial Intelligence techniques.

Nitric oxide level profile in human liver transplantation.

The aim of this study was to monitor nitric oxide blood levels at various times intraoperatively and following liver transplantation in humans. Nitric oxide production was assessed directly as circulating nitrosyl-hemoglobin adducts by electron paramagnetic resonance spectroscopy in 22 patients undergoing orthotopic liver transplantation. Two significant peaks in nitrosylhemoglobin levels were detected at 5 and 60 min after reperfusion (5.02 +/- 3.33 arbitrary units and 5.75 +/- 4.19, respectively, vs 3.33 +/- 2.28 under basal state; P < 0.05 for both comparisons). Postoperative nitrosyl-hemoglobin levels remained elevated, up to 5.42 +/- 0.89 arbitrary units (P < 0.05 vs basal values). Neither soluble intercellular adhesion molecule-1 or soluble endothelial-leukocyte adhesion molecule concentrations were altered intraoperatively. Only the former was significantly raised after transplantation. Neutrophil elastase levels showed an early increase and remained high throughout surgery, returning to basal values after transplantation. No correlations were found among studied parameters. These data suggest that nitric oxide may play a role in ischemia-reperfusion phases in human liver transplantation. Mechanisms other than leukocyte-endothelial adhesion and neutrophil activation seem to affect nitric oxide production under these conditions.