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.

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.