Back

Are Statins Optimally Prescribed to Reduce Stroke Risk in Patients with Hypercholesterolaemia? A population-based Longitudinal Study Using Electronic Health Records in South London (2005-2021)

Delord, M.; Ashworth, M.; Douiri, A.

2025-03-11 epidemiology
10.1101/2025.03.10.25323670 medRxiv
Show abstract

BackgroundWe aim to evaluate the impact of statin prescription on stroke risk in patients with hypercholesterolaemia and to assess disparities in statin prescribing. MethodsWe analysed electronic health records from patients with hypercholesterolaemia, registered in 41 general practices in south London between 2005 and 2021. The cause-specific hazard ratio of statin prescription on stroke, adjusted for patients sociodemographic characteristics and stroke risk factors (smoking ever, hypertension, and diabetes), was estimated using a time-varying exposure Cox proportional hazards model stratified by history of heart diseases. The association between statin prescription and patients sociodemographic characteristics was evaluated using a logistic regression. ResultsOf the 849,968 registered patients, 166,124 (19.5%) had records of hypercholesterolaemia. Among them, 33.5% were prescribed statins, 2.6% had a record of stroke, and 50.6% were female, 31.7%, 16.2% and 8.9% had records of hypertension, diabetes and history of heart diseases respectively. In a Cox model stratified by history of heart diseases, statin prescription was associated with a reduced hazard of stroke (cause-specific hazard ratio: 0.74; 95% confidence interval (CI): 0.68-0.80, p<0.001), with follow-up administratively censored at 79 years (n=161,527; 97.2%). Statins were less likely prescribed to female patients and patients of Black ethnicity (odds-ratio: 0.70, 95% CI: 0.68-0.72, p<0.001 and odds-ratio: 0.82, 95% CI: 0.79-0.85, p<0.001, respectively). ConclusionsStatin therapy prescription is associated with reduced stroke risk in patients with hypercholesterolaemia, yet it was under-prescribed to women and patients of Black ethnicity, highlighting avoidable disparities in preventive care.

Published in BMC Medicine (predicted rank #4) · training set

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.