A longitudinal evaluation of cardiovascular risk factors, treatment patterns, and outcomes in patients with documented cardiovascular disease treated with lipid lowering therapy in the United Kingdom
Notice bibliographique
Résumé
Abstract Background Over time, guidelines for dyslipidemia management in patients at high risk of atherosclerotic cardiovascular disease (CVD) changed with the goal of improving patient outcomes. Guidelines have been released by the European Joint Task Force in 2007, 2012 and 2016, European Society of Cardiology in 2011, 2016 and 2019, Joint British Societies in 2014, and National Institute for Health and Care Excellence in 2014. Purpose Evaluate cardiovascular risk factors, treatment patterns, and cardiovascular outcomes over time related to dyslipidemia management. Methods Ten prevalent cohorts of patients with documented CVD receiving lipid-lowering therapy (LLT) were created using Clinical Research Practice Datalink (CPRD) records as of January 1, each year from 2008 through 2017. For each cohort, we identified CVD risk factors and LLT, and estimated the 1-year composite rate of fatal and nonfatal myocardial infarction (MI), ischemic stroke (IS), or revascularization. Patient follow-up was censored at the earliest of one year, end of data, or the outcome of interest. Patients in each cohort were required to be ≥18 years old, have ≥1 years of available medical history, and have received ≥2 LLT prescriptions in the prior year. Documented CVD was defined as MI, IS, angina, revascularization, transient ischemic attack, carotid stenosis, abdominal aortic aneurysm, or peripheral arterial disease. Patients could be in multiple cohorts. Results Annual patient counts ranged from 170,501 to 179,137 through 2013 and declined to 94,418 by 2017 (due to fewer patients in the overall CPRD data). Comparing 2008, 2011 (when ESC guidelines were revised) and 2017 showed the following for CVD risk factors: mean age was 71.6, 72.3, and 72.5 years; males were 59.9%, 61.1%, and 63.1%; current smoking was 15.1%, 15.2%, and 13.9%; type 2 diabetes was 18.4%, 20.2%, and 22.4%; stage 3–5 chronic kidney disease was 22.4%, 25.1%, and 22.8%; history of MI was 22.5%, 23.9%, and 27.4%; history of IS was 5.5%, 6.6%, and 7.9%; LDL <1.8 mmol/L was 27.8%, 29.2% and 37.2%; and LDL <1.4 mmol/L was 9.9%, 10.1%, and 15.6%. In terms of treatment, high intensity statin use increased from 12.9% to 15.7% to 30.8%; atorvastatin 40–80 mg use increased from 12.9% to 15.5% to 30.5%; while simvastatin 20–40 mg use decreased from 55.4% to 58.8% to 36.7%. The 1-year cardiovascular event rate declined from 2.54 to 2.35 to 1.96 events per 100 person-years (Figure). Conclusions After 2011 in the UK, there was an increased use of high intensity statins, a greater proportion of patients with LDL levels <1.8 and <1.4 mmol/L, and lower 1-year cardiovascular event rates. While improved CVD management likely contributed to the event rate decline, less than 40% of very high-risk patients achieved an LDL <1.8 mmol/L, and the proportion with LDL <1.4 mmol/L, as recommended by the 2019 ESC guidelines, was less than 20%. Clinicians should continue their efforts to reduce LDL in these patients. Figure 1 Funding Acknowledgement Type of funding source: Private company. Main funding source(s): Amgen
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,009 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».