Observed communication skills: how do they relate to the consultation content? A nation-wide study of graduate medical students seeing a standardized patient for a first-time consultation in a general practice setting

<p>Abstract</p> <p>Background</p> <p>In this study, we wanted to investigate the relationship between background variables, communication skills, and the bio-psychosocial content of a medical consultation in a general practice setting with a standardized patient.</p> <p>Methods</p> <p>Final-year medical school students (N = 111) carried out a consultation with an actor playing the role of a patient with a specific somatic complaint, psychosocial stressors, and concerns about cancer. Based on videotapes, communication skills and consultation content were scored separately.</p> <p>Results</p> <p>The mean level of overall communication skills had a significant impact upon the counts of psychosocial issues, the patient's concerns about cancer, and the information and planning parts of the consultation content being addressed. Gender and age had no influence upon the relationship between communication skills and consultation content.</p> <p>Conclusion</p> <p>Communication skills seem to be important for final-year students' competence in addressing sensitive psychosocial issues and patients' concerns as well as informing and planning with patients being representative for a fairly complex case in general practice. This result should be considered in the design and incorporation of communication skills training as part of the curriculum of medical schools.</p

Conceptualization of category-oriented likelihood ratio: a useful tool for clinical diagnostic reasoning

<p>Abstract</p> <p>Background</p> <p>In the diagnostic reasoning process medical students and novice physicians need to be made aware of the diagnostic values of the clinical findings (including history, signs, and symptoms) to make an appropriate diagnostic decision. Diagnostic reasoning has been understood in light of two paradigms on clinical reasoning: <it>problem solving </it>and <it>decision making</it>. They advocate the reasoning strategies used by expert physicians and the statistical models of reasoning, respectively. Evidence-based medicine (EBM) applies <it>decision theory </it>to the clinical diagnosis, which can be a challenging topic in medical education.</p> <p>This theoretical article tries to compare evidence-based diagnosis with expert-based strategies in clinical diagnosis and also defines a novel concept <it>of category-oriented likelihood ratio (LR) </it>to propose a new model combining both aforementioned methods.</p> <p>Discussion</p> <p>Evidence-based medicine advocates the use of quantitative evidence to estimate the probability of diseases more accurately and objectively; however, the published evidence for a given diagnosis cannot practically be utilized in primary care, especially if the patient is complaining of a nonspecific problem such as abdominal pain that could have a long list of differential diagnoses. In this case, expert physicians examine the key clinical findings that could differentiate between broader categories of diseases such as organic and non-organic disease categories to shorten the list of differential diagnoses. To approach nonspecific problems, not only do the experts revise the probability estimate of specific diseases, but also they revise the probability estimate of the <it>categories of diseases </it>by using the available clinical findings.</p> <p>Summary</p> <p>To make this approach analytical and objective, we need to know how much more likely it is for a key clinical finding to be present in patients with one of the diseases of a specific category versus those with a disease not included in that category. In this paper, we call this value <it>category-oriented LR</it>.</p

Hypothermia in a surgical intensive care unit

BACKGROUND: Inadvertent hypothermia is not uncommon in the immediate postoperative period and it is associated with impairment and abnormalities in various organs and systems that can lead to adverse outcomes. The aim of this study was to estimate the prevalence, the predictive factors and outcome of core hypothermia on admission to a surgical ICU. METHODS: All consecutive 185 adult patients who underwent scheduled or emergency noncardiac surgery admitted to a surgical ICU between April and July 2004 were admitted to the study. Tympanic membrane core temperature (Tc) was measured before surgery, on arrival at ICU and every two hours until 6 hours after admission. The following variables were also recorded: age, sex, body weight and height, ASA physical status, type of surgery, magnitude of surgical procedure, anesthesia technique, amount of intravenous fluids administered during anesthesia, use of temperature monitoring and warming techniques, duration of the anesthesia, ICU length of stay, hospital length of stay and SAPS II score. Patients were classified as either hypothermic (Tc ≤ 35°C) or normothermic (Tc> 35°C). Univariate analysis and multiple regression binary logistic with an odds ratio (OR) and its 95% Confidence Interval (95%CI) were used to compare the two groups of patients and assess the relationship between each clinical predictor and hypothermia. Outcome measured as ICU length of stay and mortality was also assessed. RESULTS: Prevalence of hypothermia on ICU admission was 57.8%. In univariate analysis temperature monitoring, use of warming techniques and higher previous body temperature were significant protective factors against core hypothermia. In this analysis independent predictors of hypothermia on admission to ICU were: magnitude of surgery, use of general anesthesia or combined epidural and general anesthesia, total intravenous crystalloids administrated and total packed erythrocytes administrated, anesthesia longer than 3 hours and SAPS II scores. In multiple logistic regression analysis significant predictors of hypothermia on admission to the ICU were magnitude of surgery (OR 3.9, 95% CI, 1.4–10.6, p = 0.008 for major surgery; OR 3.6, 95% CI, 1.5–9.0, p = 0.005 for medium surgery), intravenous administration of crystalloids (in litres) (OR 1.4, 95% CI, 1.1–1.7, p = 0.012) and SAPS score (OR 1.0, 95% CI 1.0–1.7, p = 0.014); higher previous temperature in ward was a significant protective factor (OR 0.3, 95% CI 0.1–0.7, p = 0.003). Hypothermia was neither a risk factor for hospital mortality nor a predictive factor for staying longer in ICU. CONCLUSION: The prevalence of patient hypothermia on ICU arrival was high. Hypothermia at time of admission to the ICU was not an independent factor for mortality or for staying longer in ICU