Management of lipid-lowering therapy in patients with cardiovascular events in the UK: a retrospective cohort study.
BMJ open(2017)
Abstract
OBJECTIVES:To describe low-density lipoprotein (LDL) cholesterol management and lipid-lowering treatment patterns in patients with a cardiovascular (CV) event.
DESIGN:Retrospective cohort study using Clinical Practice Research Datalink records linked with Hospital Episode Statistics data.
SETTING:Routine clinical practice in the UK from 2006 to 2012.
PARTICIPANTS:Individuals ≥18 years were selected at their first CV-related hospitalisation (first event cohort) if they had received ≥2 lipid-lowering therapy prescriptions within 180 days beforehand. Patients were stratified into four mutually exclusive subgroups based on the presence or absence of vascular disease and of diabetes. Those with a second CV hospitalisation within 36 months were included in a separate cohort (second event cohort).
PRIMARY AND SECONDARY OUTCOME MEASURES:LDL levels in the year prior to the CV event and 12 months later as well as measures of adherence to lipid-lowering therapy during the 12 months after the CV hospitalisation.
RESULTS:There were 24 093 patients in the first event cohort, of whom 5274 were included in the second event cohort. Most received moderate intensity statins at baseline and 12 months. Among the four first event cohort subgroups at baseline, the proportions with an LDL of <1.8 mmol/L was similar between the two diabetic cohorts (36% to 38%) and were higher than those in the two non-diabetic cohorts (17% to 22%) and in the second event cohort (31%). An incremental 5% to 9% had an LDL below 1.8 mmol/L at 12 months, suggesting intensification of therapy. The proportion of adherent patients (medication possession ratio of≥0.8) was highest for statins, ranging from 68% to 72%. For ezetimibe, the range was 65% to 70%, and for fibrates, it was 48% to 62%.
CONCLUSIONS:Despite the existence of effective therapies for lowering cholesterol, patients do not reach achievable LDL targets.
MoreTranslated text
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined