Psychosocial factors predict medical outcome following a first XXXX . Working Group on Cardiac Rehabilitation of the Swiss Society of Cardiology.

@entity1 @entity583 @entity1188 @entity453
BACKGROUND: The aim of this study was to identify psychosocial variables that, in addition to known medical factors, predict the long-term outcome after a first @entity583 . @entity1 AND METHODS: The study population consisted of 222 @entity1 aged 30-60 years who entered an inpatient rehabilitation program a mean of 7 weeks after a first @entity583 . Medical data and completed questionnaires for psychosocial variables were obtained from the @entity1 and their family physicians at entry to the rehabilitation center and 1 year later. Further data, including answers to a detailed questionnaire, were collected at the beginning of rehabilitation and after one year; this follow-up was 99% complete. RESULTS: The 1-year mortality was 2.2%, the reinfarction rate 1.8%, hospital readmissions for cardiac reasons occurred in 25%, and 13% of the @entity1 underwent a subsequent revascularization procedure. At baseline and after 1 year, respectively, 84 and 83% of the @entity1 were asymptomatic. A poor medical outcome, defined as death, reinfarction, severe symptoms or poor exercise capacity, was seen in 9% of the @entity1 . The most important physiological predictors for an unfavourable medical outcome, found in bivariate and multivariate analyses, were age, severity of @entity1188 , and major coronary risk factors. In addition, some of the psychosocial variables were significantly related to a poor medical outcome: lack of a stable partnership, high work load, poor general well-being with multiple chronic non-specific health complaints, and a low external locus of control (failure to identify disease-promoting factors within own surroundings or lifestyle). CONCLUSIONS: The medical course of @entity453 was predicted not only by medical variables but also by psychological and social variables. As well as being addressed directly, these factors may help to identify @entity1 who need to be followed more closely, so that medical complications can be reduced by treating early signs of disease progression more aggressively.
