An international risk prediction algorithm for the onset of generalized anxiety and panic syndromes in general practice attendees: predictA.

BACKGROUND: There are no risk models for the prediction of anxiety that may help in prevention. We aimed to develop a risk algorithm for the onset of generalized anxiety and panic syndromes. METHOD: Family practice attendees were recruited between April 2003 and February 2005 and followed over 24 months in the UK, Spain, Portugal and Slovenia (Europe4 countries) and over 6 months in The Netherlands, Estonia and Chile. Our main outcome was generalized anxiety and panic syndromes as measured by the Patient Health Questionnaire. We entered 38 variables into a risk model using stepwise logistic regression in Europe4 data, corrected for over-fitting and tested it in The Netherlands, Estonia and Chile. RESULTS: There were 4905 attendees in Europe4, 1094 in Estonia, 1221 in The Netherlands and 2825 in Chile. In the algorithm four variables were fixed characteristics (sex, age, lifetime depression screen, family history of psychological difficulties); three current status (Short Form 12 physical health subscale and mental health subscale scores, and unsupported difficulties in paid and/or unpaid work); one concerned country; and one time of follow-up. The overall C-index in Europe4 was 0.752 [95% confidence interval (CI) 0.724-0.780]. The effect size for difference in predicted log odds between developing and not developing anxiety was 0.972 (95% CI 0.837-1.107). The validation of predictA resulted in C-indices of 0.731 (95% CI 0.654-0.809) in Estonia, 0.811 (95% CI 0.736-0.886) in The Netherlands and 0.707 (95% CI 0.671-0.742) in Chile. CONCLUSIONS: PredictA accurately predicts the risk of anxiety syndromes. The algorithm is strikingly similar to the predictD algorithm for major depression, suggesting considerable overlap in the concepts of anxiety and depression.

Development and validation of an international risk prediction algorithm for episodes of major depression in general practice attendees: the PredictD study.

CONTEXT: Strategies for prevention of depression are hindered by lack of evidence about the combined predictive effect of known risk factors. OBJECTIVES: To develop a risk algorithm for onset of major depression. DESIGN: Cohort of adult general practice attendees followed up at 6 and 12 months. We measured 39 known risk factors to construct a risk model for onset of major depression using stepwise logistic regression. We corrected the model for overfitting and tested it in an external population. SETTING: General practices in 6 European countries and in Chile. PARTICIPANTS: In Europe and Chile, 10 045 attendees were recruited April 2003 to February 2005. The algorithm was developed in 5216 European attendees who were not depressed at recruitment and had follow-up data on depression status. It was tested in 1732 patients in Chile who were not depressed at recruitment. Main Outcome Measure DSM-IV major depression. RESULTS: Sixty-six percent of people approached participated, of whom 89.5% participated again at 6 months and 85.9%, at 12 months. Nine of the 10 factors in the risk algorithm were age, sex, educational level achieved, results of lifetime screen for depression, family history of psychological difficulties, physical health and mental health subscale scores on the Short Form 12, unsupported difficulties in paid or unpaid work, and experiences of discrimination. Country was the tenth factor. The algorithm's average C index across countries was 0.790 (95% confidence interval [CI], 0.767-0.813). Effect size for difference in predicted log odds of depression between European attendees who became depressed and those who did not was 1.28 (95% CI, 1.17-1.40). Application of the algorithm in Chilean attendees resulted in a C index of 0.710 (95% CI, 0.670-0.749). CONCLUSION: This first risk algorithm for onset of major depression functions as well as similar risk algorithms for cardiovascular events and may be useful in prevention of depression.

Prevalence of common mental disorders in general practice attendees across Europe.

BACKGROUND: There is evidence that the prevalence of common mental disorders varies across Europe. AIMS: To compare prevalence of common mental disorders in general practice attendees in six European countries. METHOD: Unselected attendees to general practices in the UK, Spain, Portugal, Slovenia, Estonia and The Netherlands were assessed for major depression, panic syndrome and other anxiety syndrome. Prevalence of DSM-IV major depression, other anxiety syndrome and panic syndrome was compared between the UK and other countries after taking account of differences in demographic factors and practice consultation rates. RESULTS: Prevalence was estimated in 2,344 men and 4,865 women. The highest prevalence for all disorders occurred in the UK and Spain, and lowest in Slovenia and The Netherlands. Men aged 30-50 and women aged 18-30 had the highest prevalence of major depression; men aged 40-60 had the highest prevalence of anxiety, and men and women aged 40-50 had the highest prevalence of panic syndrome. Demographic factors accounted for the variance between the UK and Spain but otherwise had little impact on the significance of observed country differences. CONCLUSIONS: These results add to the evidence for real differences between European countries in prevalence of psychological disorders and show that the burden of care on general practitioners varies markedly between countries.

Thermal conductivity of the porcine heart tissue.

The porcine heart was used as a model for studying the thermal changes in myocardium at cooling and re-warming during open heart surgery. A section of the heart septum was excised and tissue was cut into two similar square slices. The same shape of the tissue, cut from the surface from the upper lateral wall of the left ventricle, covered with epicardium and fat, was taken for another measurement. A thin (<0.5 mm) square thermal source of the same length of the side as the tissue samples was put between the two slices of tissue. This set was placed in the middle of two identical copper cylinders (2r=50 mm, height=55 mm) used to keep the outer side of the specimen at controlled room temperature. Thermal conductivity of the heart tissue was determined at controlled thermal power, and known difference of the temperature at the edge of the tissue and at the middle of the heater, when steady state was reached. Thermal conductivity calculated from the temperature difference and the geometry of heater and samples was 0.75 W/m.K for septal heart tissue, and 0.60 W/m.K for the lateral wall ventricle tissue with epicardium and fat.