Summary
Background
In patients with coronary artery disease (CAD), non-optimal use of evidence-based medications is associated with an increased risk of adverse outcome.
Aims
To assess the prevalence and correlates of non-optimal secondary medical prevention in patients with stable CAD.
Methods
We included 4184 consecutive outpatients with stable CAD. Treatment at inclusion was classified as optimal/non-optimal regarding the four major classes of secondary prevention drugs: antithrombotics; statins; angiotensin-converting enzyme (ACE) inhibitors or angiotensin II receptor blockers (ARBs); and beta-blockers. For each treatment, the prescription was considered non-optimal if the drug was missing despite a class IA indication according to international guidelines. To assess the information globally, non-optimal secondary prevention was defined as at least one major treatment missing.
Results
The proportions of patients with non-optimal treatment were 0.7%, 7.8%, 12.9% and 10.3% for antithrombotics, statins, ACE inhibitors/ARBs and beta-blockers, respectively. Non-optimal secondary medical prevention was observed in 16.8% of cases. By multivariable analysis, the correlates of non-optimal secondary medical prevention were long time interval since last coronary event ( P < 0.0001), older age ( P < 0.0001), diabetes mellitus ( P < 0.0001), hypertension ( P < 0.0001), no history of myocardial infarction ( P = 0.001), no history of coronary revascularization ( P = 0.013) and low glomerular filtration rate ( P = 0.042).
Conclusions
Although most patients with stable CAD are receiving evidence-based medications according to guidelines, there remain subgroups at higher risk of non-optimal treatment. In particular, it might be feasible to improve prevention by focusing on patients in whom a long time has elapsed since the last coronary event.
Résumé
Contexte
En cas de maladie coronaire, l’utilisation non optimale des thérapeutiques de prévention secondaire est associée à une augmentation du risque d’événements cliniques.
Objectif
Analyser la prévalence et les déterminants d’une prévention secondaire non optimale en cas de maladie coronaire stable.
Méthodes
Nous avons inclus 4184 patients ambulatoires présentant une maladie coronaire stable. Le traitement à l’inclusion a été défini comme optimal/non optimal pour les 4 grandes classes thérapeutiques de prévention secondaire : antithrombotiques, statines, inhibiteurs de l’enzyme de conversion (IEC) ou antagonistes du récepteur de l’angiotensine II (ARAII), et ß-bloquants. Pour chaque traitement, la prescription a été considérée comme non optimale si la thérapeutique était manquante en dépit d’une indication de classe IA dans les recommandations internationales. Pour analyser l’information globalement, une prévention secondaire non optimale a été définie comme ≥ 1 traitement majeur manquant.
Résultats
Le pourcentage de patients avec un traitement non optimal était de 0,7 %, 7,8 %, 12,9 % et 10,3 % pour les antithrombotiques, statines, IEC/ARAII et ß-bloquants, respectivement. Une prévention secondaire non optimale a été observée dans 16,8 % des cas. En analyse multivariée, les facteurs associés à une prévention secondaire non optimale étaient un délai long depuis le dernier événement coronarien ( p < 0,0001), l’âge ( p < 0,0001), un diabète ( p < 0,0001), une hypertension artérielle ( p < 0,0001), l’absence d’antécédent d’infarctus ( p = 0,001) ou de revascularisation myocardique ( p = 0,013) et une clairance de la créatinine diminuée ( p = 0,042).
Conclusion
Bien que la plupart des patients avec maladie coronaire stable reçoivent un traitement de prévention secondaire en accord avec les recommandations, certains sous-groupes demeurent à risque de traitement non optimal. La prévention pourrait en particulier être améliorée en ciblant les patients qui ont un délai long depuis le dernier événement coronarien.
Introduction
The appropriate use of evidence-based secondary prevention treatments is of greatest importance for the management of patients with stable coronary artery disease (CAD) . Observational studies have associated non-optimal secondary medical prevention with an increased risk of adverse clinical outcomes, including all-cause mortality and cardiovascular mortality . There is, however, relatively little contemporary information on the long-term use of evidence-based medications in patients with stable CAD. In addition, although several studies have suggested that factors such as age, race/ethnicity or practice site may be involved , the determinants of non-optimal secondary medical prevention in patients with stable CAD (i.e. at a distance from any acute event) are not well known. Such information could be of importance, as it might help to identify the subgroup(s) who may benefit the most from targeted interventions to improve prevention. The present study was therefore designed with two specific aims: to assess the prevalence of non-optimal secondary medical prevention in a recent cohort of outpatients with stable CAD; and to analyse the correlates of non-optimal prevention.
Methods
Study population
The CORONOR (Suivi d’une cohorte de patients COROnariens stables en région NORd-pas-de-Calais) study was a multicentre study that enrolled 4184 consecutive outpatients with stable CAD between February 2010 and April 2011 . Patients were enrolled by 50 cardiologists from the Region Nord Pas-de-Calais in France. Participating physicians were selected on the basis of geographic distribution, to provide a representative sample of current cardiology practice in university, non-university and private centres in the area. Patients were considered eligible if they had evidence of CAD defined by the presence of at least one of the following: previous myocardial infarction (MI) (> 1 year ago); previous coronary revascularization (> 1 year ago); and obstruction of ≥ 50% of the luminal diameter of at least one native vessel on coronary angiography. The sole exclusion criterion was hospitalisation for MI or coronary revascularization within the last year. To ensure the population was representative of the spectrum of patients with stable CAD, individuals with other cardiovascular or non-cardiovascular illnesses or co-morbidities were included.
Data collection
At the initial visit, the attending physicians prospectively completed the case record forms, which contained information regarding demographic and clinical details of the patients, including the usual cardiovascular risk factors and treatments. During the outpatient visit, the investigators reviewed the current drug treatment and entered all prescribed drugs in the case record form. If any change was needed at the time of the outpatient visit, it was taken into account for the present analysis.
Use of major secondary prevention therapies
For each patient, the treatment at inclusion was classified as optimal/non-optimal regarding the four major classes of secondary prevention drugs, according to the international guidelines available at the time of inclusion . Optimal antithrombotic therapy was defined as the prescription of aspirin or clopidogrel or a vitamin K antagonist. Optimal statin treatment was defined as the prescription of a statin for all patients. Optimal renin-angiotensin system antagonist treatment was defined as the prescription of an angiotensin-converting enzyme (ACE) inhibitor or an angiotensin II receptor blocker (ARB) in the subgroup ( n = 3335) with a class IA indication for ACE inhibitors (i.e. patients with a left ventricular ejection fraction [LVEF] ≤ 40%, diabetes mellitus or hypertension). Optimal beta-blocker treatment was defined as the prescription of a beta-blocker in the subgroup ( n = 378) with a class IA indication for beta-blockers (i.e. patients with an LVEF ≤ 40%). To assess the information globally, the number of major treatments missing (as defined above) was calculated. Non-optimal secondary medical prevention was defined as at least one major treatment missing.
Statistical analysis
Continuous variables are described as means ± standard deviations or as medians with 25th and 75th percentiles. Categorical variables are presented as absolute numbers and percentages. The last coronary event was defined as the most recent MI or coronary revascularization. For patients with no history of MI or coronary revascularization ( n = 212), the date of CAD diagnosis was used instead of the last coronary event. We analysed the correlates of non-optimal secondary medical prevention. Univariate analysis was performed using the Chi 2 test or Fisher’s test for categorical variables, and Student’s unpaired t test for continuous variables, as appropriate. Multivariable analysis was performed using logistic regression. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were calculated. Variables with a P value < 0.05 in univariate analysis were entered into the final multivariable model. Colinearity was excluded by means of a correlation matrix between candidate predictors. All statistical analyses were performed with STATA ® 9.2 software (STATA Corporation, College Station, TX, USA). Statistical significance was assumed at a P value < 0.05.
Results
The baseline characteristics of the patients included in the CORONOR study have been reported previously . As shown in Table 1 , the mean age was 66.9 ± 11.6 years and 22.3% were women. Sixty-two percent of the patients had a history of MI; the median time between last MI and inclusion was 5 years (range, 1–34 years). Eighty-six percent of the patients had a history of coronary revascularization; the median time interval between the last revascularization and inclusion was 4 years (range, 1–33 years). The median time elapsed since last coronary event (MI or coronary revascularization) was 5 years (range, 1–33 years). Only 7.3% of the patients were symptomatic (angina) at inclusion. Overall, there was a wide prescription of secondary prevention medications (antithrombotics, 99.3%; statins, 92.2%; ACE inhibitors/ARBs, 81.9%; beta-blockers, 79.4%).
| Age (years) | 66.9 ± 11.6 |
| Women | 22.3 |
| Diabetes mellitus | 31.0 |
| History of hypertension | 60.2 |
| History of myocardial infarction | 62.4 |
| Multivessel coronary artery disease | 57.8 |
| History of coronary revascularization | 85.9 |
| History of coronary stent implantation | 68.9 |
| History of CABG | 21.3 |
| History of hospitalization for decompensated HF | 7.5 |
| Left ventricular ejection fraction (%) | 57.5 ± 10.8 |
| Estimated GFR (mL/min/1.73 m 2 ) | 79 [63–93] |
| Treatment at inclusion | |
| Aspirin | 77.0 |
| Clopidogrel | 40.2 |
| Vitamin K antagonist | 11.1 |
| Any antithrombotic drug | 99.3 |
| ACE inhibitor | 59.3 |
| ARB | 24.0 |
| ACE inhibitor or ARB | 81.9 |
| Beta-blocker | 79.4 |
| Statin | 92.2 |
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