Expert clinical reasoning and pain assessment in mechanically ventilated patients: A descriptive study.

BACKGROUND: Pain assessment in mechanically ventilated patients is challenging, because nurses need to decode pain behaviour, interpret pain scores, and make appropriate decisions. This clinical reasoning process is inherent to advanced nursing practice, but is poorly understood. A better understanding of this process could contribute to improved pain assessment and management. OBJECTIVE: This study aimed to describe the indicators that influence expert nurses' clinical reasoning when assessing pain in critically ill nonverbal patients. METHODS: This descriptive observational study was conducted in the adult intensive care unit (ICU) of a tertiary referral hospital in Western Switzerland. A purposive sample of expert nurses, caring for nonverbal ventilated patients who received sedation and analgesia, were invited to participate in the study. Data were collected in "real life" using recorded think-aloud combined with direct non-participant observation and brief interviews. Data were analysed using deductive and inductive content analyses using a theoretical framework related to clinical reasoning and pain. RESULTS: Seven expert nurses with an average of 7.85 (±3.1) years of critical care experience participated in the study. The patients had respiratory distress (n=2), cardiac arrest (n=2), sub-arachnoid bleeding (n=1), and multi-trauma (n=2). A total of 1344 quotes in five categories were identified. Patients' physiological stability was the principal indicator for making decision in relation to pain management. Results also showed that it is a permanent challenge for nurses to discriminate situations requiring sedation from situations requiring analgesia. Expert nurses mainly used working knowledge and patterns to anticipate and prevent pain. CONCLUSIONS: Patient's clinical condition is important for making decision about pain in critically ill nonverbal patients. The concept of pain cannot be assessed in isolation and its assessment should take the patient's clinical stability and sedation into account. Further research is warranted to confirm these results.

Digital evidence, 'absence' of data and ambiguous patterns of reasoning

In this paper we discuss the use of digital data by the Swiss Federal Criminal Court in a recent case of attempted homicide. We use this case to examine drawbacks for the defense when the presentation of scientific evidence is partial, especially when the only perspective mentioned is that of the prosecution. We tackle this discussion at two distinct levels. First, we pursue an essentially non-technical presentation of the topic by drawing parallels between the court's summing up of the case and flawed patterns of reasoning commonly seen in other forensic disciplines, such as DNA and particle traces (e.g., gunshot residues). Then, we propose a formal analysis of the case, using elements of probability and graphical probability models, to justify our main claim that the partial presentation of digital evidence poses a risk to the administration of justice in that it keeps vital information from the defense. We will argue that such practice constitutes a violation of general principles of forensic interpretation as established by forensic science literature and current recommendations by forensic science interest groups (e.g., the European Network of Forensic Science Institutes). Finally, we posit that argument construction and analysis using formal methods can help replace digital evidence appropriately into context and thus support a sound evaluation of the evidence.

Pharmacokinetics and pharmacogenomics of once-daily raltegravir and atazanavir in healthy volunteers.

Atazanavir inhibits UDP-glucuronyl-transferase-1A1 (UGT1A1), which metabolizes raltegravir, but the magnitude of steady-state inhibition and role of the UGT1A1 genotype are unknown. Sufficient inhibition could lead to reduced-dose and -cost raltegravir regimens. Nineteen healthy volunteers, age 24 to 51 years, took raltegravir 400 mg twice daily (arm A) and 400 mg plus atazanavir 400 mg once daily (arm B), separated by ?3 days, in a crossover design. After 1 week on each regimen, raltegravir and raltegravir-glucuronide plasma and urine concentrations were measured by liquid chromatography-tandem mass spectrometry in multiple samples obtained over 12 h (arm A) or 24 h (arm B) and analyzed by noncompartmental methods. UGT1A1 promoter variants were detected with a commercially available kit and published primers. The primary outcome was the ratio of plasma raltegravir C(tau), or concentration at the end of the dosing interval, for arm B (24 h) versus arm A (12 h). The arm B-to-arm A geometric mean ratios (95% confidence interval, P value) for plasma raltegravir C(tau), area under the concentration-time curve from 0 to 12 h (AUC(0-12)), and raltegravir-glucuronide/raltegravir AUC(0-12) were 0.38 (0.22 to 0.65, 0.001), 1.32 (0.62 to 2.81, 0.45), and 0.47 (0.38 to 0.59, <0.001), respectively. Nine volunteers were heterozygous and one was homozygous for a UGT1A1 reduction-of-function allele, but these were not associated with metabolite formation. Although atazanavir significantly reduced the formation of the glucuronide metabolite, its steady-state boosting of plasma raltegravir did not render the C(tau) with a once-daily raltegravir dose of 400 mg similar to the C(tau) with the standard twice-daily dose. UGT1A1 promoter variants did not significantly influence this interaction.

Programme de remédiation cognitive pour patients présentant une schizophrénie ou un trouble associé (Recos) : résultats préliminaires [Cognitive remediation program for individuals living with schizophrenia (Recos): preliminary results].

BACKGROUND: Nowadays, cognitive remediation is widely accepted as an effective treatment for patients with schizophrenia. In French-speaking countries, techniques used in cognitive remediation for patients with schizophrenia have been applied from those used for patients with cerebral injury. As cognitive impairment is a core feature of schizophrenia, the Département de psychiatrie du CHUV in Lausanne (DP-CHUV) intended to develop a cognitive remediation program for patients with a schizophrenia spectrum disease (Recos-Vianin, 2007). Numerous studies show that the specific cognitive deficits greatly differ from one patient to another. Consequently, Recos aims at providing individualized cognitive remediation therapy. In this feasibility trial, we measured the benefits of this individualized therapy for patients with schizophrenia. Before treatment, the patients were evaluated with a large battery of cognitive tests in order to determine which of the five specific training modules - Verbal memory, visuospatial memory and attention, working memory, selective attention, reasoning - could provide the best benefit depending on their deficit. OBJECTIVES: The study was designed to evaluate the benefits of the Recos program by comparing cognitive functioning before and after treatment. METHOD: Twenty-eight patients with schizophrenia spectrum disorders (schizophrenia [n=18], schizoaffective disorder [n=5], schizotypal disorder [n=4], schizophreniform disorder [n=1], DSM-IV-TR) participated in between one and three of the cognitive modules. The choice of the training module was based on the results of the cognitive tests obtained during the first evaluation. The patients participated in 20 training sessions per module (one session per week). At the end of the training period, the cognitive functioning of each patient was reevaluated by using the same neuropsychological battery. RESULTS: The results showed a greater improvement in the cognitive functions, which were specifically trained, compared to the cognitive functions, which were not trained. However, an improvement was also observed in both types of cognitive functions, suggesting an indirect cognitive gain. CONCLUSION: In our view, the great heterogeneity of the observed cognitive deficits in schizophrenia necessitates a detailed neuropsychological investigation as well as an individualized cognitive remediation therapy. These preliminary results need to be confirmed with a more extended sample of patients.

Validity of impedance-based equations for the prediction of total body water as measured by deuterium dilution in African women.

BACKGROUND: Little information is available on the validity of simple and indirect body-composition methods in non-Western populations. Equations for predicting body composition are population-specific, and body composition differs between blacks and whites. OBJECTIVE: We tested the hypothesis that the validity of equations for predicting total body water (TBW) from bioelectrical impedance analysis measurements is likely to depend on the racial background of the group from which the equations were derived. DESIGN: The hypothesis was tested by comparing, in 36 African women, TBW values measured by deuterium dilution with those predicted by 23 equations developed in white, African American, or African subjects. These cross-validations in our African sample were also compared, whenever possible, with results from other studies in black subjects. RESULTS: Errors in predicting TBW showed acceptable values (1.3-1.9 kg) in all cases, whereas a large range of bias (0.2-6.1 kg) was observed independently of the ethnic origin of the sample from which the equations were derived. Three equations (2 from whites and 1 from blacks) showed nonsignificant bias and could be used in Africans. In all other cases, we observed either an overestimation or underestimation of TBW with variable bias values, regardless of racial background, yielding no clear trend for validity as a function of ethnic origin. CONCLUSIONS: The findings of this cross-validation study emphasize the need for further fundamental research to explore the causes of the poor validity of TBW prediction equations across populations rather than the need to develop new prediction equations for use in Africa.

Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science

Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. Includes self-contained introductions to probability and decision theory. Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. Features implementation of the methodology with reference to commercial and academically available software. Presents standard networks and their extensions that can be easily implemented and that can assist in the reader's own analysis of real cases. Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

Epidémiologie clinique: définitions, utilités et raisons pour un développement en Suisse. [Clinical epidemiology: definitions, uses and reasons for development in Switzerland].

Clinical epidemiology is the most currently used name for a comparatively new branch of medicine covering a certain number of activities related to the practice of clinical medicine, but using epidemiological techniques and methods. Clinical epidemiology has only just begun to be known in Europe, whereas units are being increasingly developed and expanded in North America, particularly within the clinical departments of hospitals. The methods it offers are valid for both practicing physicians and hospital doctors (or those being trained in hospitals) and serve the purpose of promoting a better quality medical service, especially where a more adequate evaluation of the effectiveness of diagnostic methods, therapy and prognosis in medicine is concerned. Clinical epidemiology proposes a methodology of medical reasoning and of decision-making, as well as techniques intended to facilitate the indispensable task of keeping up with advances in medical knowledge.

A collaborative approach for incorporating forensic case data into crime investigation using criminal intelligence analysis and visualisation

There is an increasing awareness that the articulation of forensic science and criminal investigation is critical to the resolution of crimes. However, models and methods to support an effective collaboration between these partners are still poorly expressed or even lacking. Three propositions are borrowed from crime intelligence methods in order to bridge this gap: (a) the general intelligence process, (b) the analyses of investigative problems along principal perspectives: entities and their relationships, time and space, quantitative aspects and (c) visualisation methods as a mode of expression of a problem in these dimensions. Indeed, in a collaborative framework, different kinds of visualisations integrating forensic case data can play a central role for supporting decisions. Among them, link-charts are scrutinised for their abilities to structure and ease the analysis of a case by describing how relevant entities are connected. However, designing an informative chart that does not bias the reasoning process is not straightforward. Using visualisation as a catalyser for a collaborative approach integrating forensic data thus calls for better specifications.

Predicting smoking cessation and its relapse in HIV-infected patients: the Swiss HIV Cohort Study.

OBJECTIVES: The aim of the study was to assess whether prospective follow-up data within the Swiss HIV Cohort Study can be used to predict patients who stop smoking; or among smokers who stop, those who start smoking again. METHODS: We built prediction models first using clinical reasoning ('clinical models') and then by selecting from numerous candidate predictors using advanced statistical methods ('statistical models'). Our clinical models were based on literature that suggests that motivation drives smoking cessation, while dependence drives relapse in those attempting to stop. Our statistical models were based on automatic variable selection using additive logistic regression with component-wise gradient boosting. RESULTS: Of 4833 smokers, 26% stopped smoking, at least temporarily; because among those who stopped, 48% started smoking again. The predictive performance of our clinical and statistical models was modest. A basic clinical model for cessation, with patients classified into three motivational groups, was nearly as discriminatory as a constrained statistical model with just the most important predictors (the ratio of nonsmoking visits to total visits, alcohol or drug dependence, psychiatric comorbidities, recent hospitalization and age). A basic clinical model for relapse, based on the maximum number of cigarettes per day prior to stopping, was not as discriminatory as a constrained statistical model with just the ratio of nonsmoking visits to total visits. CONCLUSIONS: Predicting smoking cessation and relapse is difficult, so that simple models are nearly as discriminatory as complex ones. Patients with a history of attempting to stop and those known to have stopped recently are the best candidates for an intervention.

Adénopathies et fièvre chez une patiente VIH positive [Immunocompromised HIV patient with lymphadenopathy and fever].

The case of a immunocompromised HIV patient with fever and lymphadenopathy discussed in an anatomo-pathological round. This complex clinical case was used as an opportunity to discuss the broad differential diagnosis of fever in an immunocompromized individual with multiples lymphadenopathies. Clinical reasoning leading to the probable diagnosis based on clinical, biological and radiological informations is not only a difficult task for the speaker but also a rich source of learning opportunities for our medical community.

The likelihood approach to compare populations : a study on DNA evidence and pitfalls of intuitions

The paper follows on from earlier work [Taroni F and Aitken CGG. Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence. Science & Justice 1998; 38: 165-177]. Different explanations of the value of DNA evidence were presented to students from two schools of forensic science and to members of fifteen laboratories all around the world. The responses were divided into two groups; those which came from a school or laboratory identified as Bayesian and those which came from a school or laboratory identified as non-Bayesian. The paper analyses these responses using a likelihood approach. This approach is more consistent with a Bayesian analysis than one based on a frequentist approach, as was reported by Taroni F and Aitken CGG. [Probabilistic reasoning in the law, Part 1: assessment of probabilities and explanation of the value of DNA evidence] in Science & Justice 1998.

Age-specific incidence of all neoplasms after colorectal cancer.

PURPOSE: Patients diagnosed with a specific neoplasm tend to have a subsequent excess risk of the same neoplasm. The age incidence of a second neoplasm at the same site is approximately constant with age, and consequently the relative risk is greater at younger age. It is unclear whether such a line of reasoning can be extended from a specific neoplasm to the incidence of all neoplasms in subjects diagnosed with a defined neoplasm. METHODS: We considered the age-specific incidence of all non-hormone-related epithelial neoplasms after a first primary colorectal cancer (n = 9542) in the Vaud Cancer Registry data set. RESULTS: In subjects with a previous colorectal cancer, the incidence rate of all other epithelial non-hormone-related cancers was stable around 800 per 100,000 between age 30 and 60 years, and rose only about twofold to reach 1685 at age 70 to 79 years and 1826 per 100,000 at age 80 years or older. After excluding synchronous cancers, the rise was only about 1.5-fold, that is, from about 700 to 1000. In the general population, the incidence rate of all epithelial non-hormone-related cancers was 29 per 100,000 at age 30 to 39 years, and rose 30-fold to 883 per 100,000 at age 70 to 79 years. Excluding colorectal cancers, the rise of all non-hormone-related cancers was from 360 per 100,000 at age 40 to 49 years to 940 at age 70 to 79 years after colorectal cancer, and from 90 to 636 per 100,000 in the general population (i.e., 2.6- vs. 7.1-fold). CONCLUSIONS: The rise of incidence with age of all epithelial non-hormone-related second cancers after colorectal cancer is much smaller than in the general population. This can possibly be related to the occurrence of a single mutational event in a population of susceptible individuals, although alternative models are plausible within the complexity of the process of carcinogenesis.

Narrative Diagrammatik. Mit einer Modellanalyse: Die Diagrammatik des "Decameron"

Taking as a starting point the seeming inconsistency of late-medieval romances notoriously 'run wild' (verwildert), this article is concerned with the description of an abstract form of narrative coherence that is based on the notion of the diagrammatic. In a first section, this concept is illustrated in a simplified manner by an analysis of Boccaccio's Decameron based on two levels of spatial structure: that of the autograph Berlin manuscript (Codex Hamilton 90) and that of the recipient's mental visualisation of the relations between the frame and the tales of the work. It is argued that the connectivity of the work as a whole depends on the perception of those two spatial representations of the plot. A second section develops this concept in a more theoretical fashion, drawing on Charles Sanders Peirce's notion of diagrammatic reasoning as a way of perceiving relations through mental and material topological representations. Correspondingly, a view of narrative is proposed that does not depend on the traditional perspective of temporal sequence but emphasizes the spatial structure of literary narrative. It is argued that these conditions form the primary ontological mode of narrative, whereas the temporal development of a story is an aesthetic illusion that has been specifically stimulated by the narrative conventions of approximately the past three centuries and must thus be considered a secondary effect. To conclude, an interpretation in miniature of an aspect of Heinrich von Neustadt's Apollonius von Tyrland that seems to have 'run wild' is undertaken from a diagrammatic perspective.

A methodology to event reconstruction from trace images

The widespread use of digital imaging devices for surveillance (CCTV) and entertainment (e.g., mobile phones, compact cameras) has increased the number of images recorded and opportunities to consider the images as traces or documentation of criminal activity. The forensic science literature focuses almost exclusively on technical issues and evidence assessment [1]. Earlier steps in the investigation phase have been neglected and must be considered. This article is the first comprehensive description of a methodology to event reconstruction using images. This formal methodology was conceptualised from practical experiences and applied to different contexts and case studies to test and refine it. Based on this practical analysis, we propose a systematic approach that includes a preliminary analysis followed by four main steps. These steps form a sequence for which the results from each step rely on the previous step. However, the methodology is not linear, but it is a cyclic, iterative progression for obtaining knowledge about an event. The preliminary analysis is a pre-evaluation phase, wherein potential relevance of images is assessed. In the first step, images are detected and collected as pertinent trace material; the second step involves organising and assessing their quality and informative potential. The third step includes reconstruction using clues about space, time and actions. Finally, in the fourth step, the images are evaluated and selected as evidence. These steps are described and illustrated using practical examples. The paper outlines how images elicit information about persons, objects, space, time and actions throughout the investigation process to reconstruct an event step by step. We emphasise the hypothetico-deductive reasoning framework, which demonstrates the contribution of images to generating, refining or eliminating propositions or hypotheses. This methodology provides a sound basis for extending image use as evidence and, more generally, as clues in investigation and crime reconstruction processes.