Drugs Aging DOI 10.1007/s40266-014-0189-x
ORIGINAL RESEARCH ARTICLE
Secondary Prevention Medication After Myocardial Infarction: Persistence in Elderly People over the Course of 1 Year Saba Al-Khadra • Christa Meisinger • Ute Amann • Rolf Holle • Bernhard Kuch Hildegard Seidl • Inge Kirchberger
•
Ó Springer International Publishing Switzerland 2014
Abstract Aims Persistent use of guideline-recommended drugs after acute myocardial infarction (AMI) is frequently reported to be inadequate in the elderly and scarce knowledge exists about factors that influence persistence in outpatient care. Our aim was to evaluate drug use and its predictors in survivors of AMI above 64 years from hospital discharge to 1-year post-AMI. Methods In a single-centre randomised controlled trial, discharge medication of 259 patients with AMI was obtained from medical records at hospital stay. Follow-up drug use and use of the healthcare system were selfreported to study nurses over 1 year in 3-month intervals. Electronic supplementary material The online version of this article (doi:10.1007/s40266-014-0189-x) contains supplementary material, which is available to authorized users. S. Al-Khadra C. Meisinger U. Amann I. Kirchberger (&) Central Hospital of Augsburg, MONICA/KORA Myocardial Infarction Registry, Augsburg, Germany e-mail: [email protected] S. Al-Khadra C. Meisinger U. Amann I. Kirchberger Helmholtz Zentrum Mu¨nchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology II, Neuherberg, Germany R. Holle H. Seidl Helmholtz Zentrum Mu¨nchen, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Neuherberg, Germany B. Kuch Department of Internal Medicine/Cardiology, Hospital of No¨rdlingen, No¨rdlingen, Germany B. Kuch Department of Internal Medicine I, Cardiology, Central Hospital of Augsburg, Augsburg, Germany
Predictors for persistence were modelled with multivariate logistic regression analysis considering demographics, comorbidities and treatment characteristics. Results At discharge, 99.2 % of the patients used antiplatelets, 86.5 % beta blockers, 95.0 % statins and 90.4 % angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. Use of the combination of all four drug classes decreased from discharge to 1 year post-AMI from 74.1 to 37.8 % and was significantly reduced by age C75 years (odds ratio [OR] 0.49; 95 % confidence interval [CI] 0.29–0.85) and ten or more visits with general practitioners (GPs) over 1 year (OR 0.29; 95 % CI 0.17–0.51). Persistence from month 3 to 12 was significantly associated with drug use at discharge for the single drug classes, but not for the drug combination. Conclusion Older age and frequent GP visits are associated with decreased use of the guideline-recommended drug combination after AMI. Further research is needed to specify underlying reasons and develop measures to improve persistence.
Key Points Anti-platelets, beta blockers, statins and angiotensinconverting enzyme inhibitors/angiotensin receptor blockers were prescribed to 74.1 % of elderly patients with myocardial infarction at hospital discharge, but their use significantly decreased to 37.8 % during 1 year follow-up. Patients who were 75 years or older or had ten or more visits with a general practitioner were less likely to receive all four secondary prevention drugs 1 year after myocardial infarction.
S. Al-Khadra et al.
1 Introduction Acute myocardial infarction (AMI) is one of the leading causes of death in developed countries [1, 2]. Although prognosis has improved over the last decades, survivors of AMI still have a high risk of cardiovascular death [3]. Secondary prevention programmes commonly include lifestyle changes and pharmacological treatment. The continuous use of medication has been shown to strongly reduce risk of all-cause mortality [4–6], hospital readmission and healthcare costs [6–8]. Accordingly, guidelines for clinical practice support the long-term use of at least four drug classes [9–12]: anti-platelets, including acetylsalicylic acid (ASA; aspirin) and thienopyridines, beta blockers (BBs), statins and angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin-receptor blockers (ARBs). A recently published worldwide multi-centre study [13] in patients with coronary heart disease demonstrated that the use of anti-platelets (96 %), BBs (79 %), statins (97 %) and ACEIs/ARBs (77 %) has increased compared with previous European surveys [14]. However, 1 year after discharge, significantly fewer BBs, ASA, statins and ACEIs were prescribed by doctors or used by the patients with AMI compared with at discharge [15, 16]. So far, only a few studies have examined factors associated with persistence or adherence to guideline recommendations on medication in patients following AMI. A recently published study revealed that socio-demographic characteristics including age and sex were the most important factors influencing drug prescription in outpatient care [17]. High-risk patients, who are expected to benefit most from optimal drug treatment, only rarely receive recommended medication [18]. Studies focusing on patients aged C65 years and on determinants of continuous use and guideline adherence at least 1 year after AMI are rare. We present data from a randomised controlled trial in elderly patients with AMI with a follow-up of 1 year. The objectives were to describe 1-year medication profiles and change in prescription patterns. Furthermore, we aimed to identify predictors of persistence to guideline-recommended drugs post-AMI regarding the single drug classes and the drug combination.
2 Methods 2.1 Study Design The KORINNA study (KORonarINfarkt Nachbehandlung im Alter) is a randomised controlled trial that included patients aged C65 years who were discharged after first or recurrent AMI from the Central Hospital of Augsburg
between September 2008 and May 2010. Patients assigned to the intervention group received nurse-based case management for 1 year, including home visits and telephone calls, whereas the control group received usual care. Details on the intervention programme and the outcome measures have been reported elsewhere [19, 20]. The outcome of this analysis was the use of guideline-recommended secondary prevention medication post-AMI for the entire patient sample. Outcome variables were drugs recommended at discharge and drug intake at months 3, 6, 9 and 12 after discharge. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the ethics committee. 2.2 Study Population In order to study changes in medication over the course of 1 year, the current analysis is based on patients with complete medication profiles, i.e. information on used secondary prevention drugs are available at discharge, and months 3, 6, 9 and 12 post-AMI. Consequently, only patients who were still alive and participating in the study at month 12 were included in this analysis. Thus, 259 of an initial 340 patients were subjects of analysis (76.2 %). Excluded patients (n = 81) were those who did not fulfil inclusion criteria (n = 2), withdrew consent (n = 35) or died during the study course (n = 39). One patient was lost to follow-up and four patients did not have complete medication profiles available. Compared with the sample with complete medication data, excluded patients were older, had significantly more often chronic kidney disease, were more often assigned to higher New York Heart Association (NYHA) classes and had received revascularization procedures significantly less often. No statistically significant differences were found between the complete medication sample and excluded patients concerning guideline-recommended medication at discharge. 2.3 Data Collection After subjects gave written informed consent, a first nursebased interview was conducted during the index hospital stay. Collected data covered age, sex, place of residence, education and smoking behaviour. Patients’ self-reports on the following variables were confirmed where possible from hospitals’ medical patient records: history of hyperlipidemia, hypertension, heart failure, AMI, angina pectoris (AP), and body mass index (BMI). History of stroke was self-reported only. Subjects with an estimated glomerular filtration rate (eGFR) below 60 mL/min/1.73 m2 of body surface area were classified as having chronic kidney disease. The eGFR was estimated with the abbreviated
Secondary Prevention Medication After Myocardial Infarction
Modification of Diet in Renal Disease (MDRD) equation [21], given by: eGFR = 175 9 standardised serum creatinine-1.154 9 age-0.203 9 1.212 (if Black) 9 0.742 (if female), where serum creatinine is expressed in mg/dL. Creatinine levels were routinely measured at index hospital stay. Treatment at the index hospital stay included reperfusion therapy, stent implantation, permanent pacemaker, and bypass surgery. Further clinical data were assessed according to the standards applied at the KORA Myocardial Infarction Registry, Augsburg, which have been reported elsewhere [22]. NYHA functional classification and presence of diabetes mellitus or depression were recorded by the study physician at the baseline examination. Depression was assessed using the Geriatric Depression Scale (GDS)-15. Scores above ten points were considered framing depression [23]. Information on discharge medication (without doses) was selected from hospital discharge letters. Doctors’ visits with general practitioners (GPs) and specialists/ internists over the course of 1 year were recorded simultaneously with medication profiles from nurse-led interviews at months 3, 6, 9 and 12 post-AMI. Thereby, medication profiles were accurately recorded, including the identification number for pharmaceutical products (for Germany), the size of the drug box, the tablet-taking regime and the date of first intake. To obtain this information precisely in the telephone interviews, patients were encouraged to read out the information from all used drug packages. In case of home visits, patients were requested to provide the study nurses with the medication packages currently being used. For this analysis, we focused on medication recommended for secondary prevention of AMI. Outcome measures were medication persistence [24], i.e. reported use by patients during the telephone calls or home visits. Discontinuation of therapy was assumed, if drug use was interrupted over 90 days (3 months) [25, 26], that is discontinuation at one of the four interview time points. We analysed drugs recommended by European and international guidelines with respect to pharmacological treatment after AMI [9–12]: anti-platelets, BBs, statins and ACEIs or ARBs. Use of diuretics and calcium channel blockers (CCBs) was additionally included in the descriptive analysis. Classification of drugs was performed by a pharmacist according to the international Anatomical Therapeutic Chemical (ATC) code [27]. Codes were ‘B01AC’ for anti-platelets, ‘C07’ for BBs, ‘C10AA’ and ‘C10BA02’ for statins, ‘C09A’ and ‘C09B’ for ACEIs, ‘C09C’ and ‘C09D’ for ARBs, ‘C03’, ‘C07B’, ‘C07C’, ‘C08G’, ‘C09BA’ and ‘C09DA’ for diuretics and ‘C08’ for CCBs. We further categorized patients in users of only ACEIs, users of only ARBs or users of ACEIs and/or ARBs (ACEI/ARB).
2.4 Statistics Basic patient characteristics were described using univariate analysis. Multivariate logistic regression analysis was performed to determine which factors contribute to medication persistence (‘continuous use’) from discharge to 1 year post-AMI for single drug classes and the drug combination (Model 1). Model 2 analysed factors associated with persistence in the outpatient care (from month 3 on), treating discharge medication as an explanatory factor. Models for anti-platelets were performed with exact logistic regression due to imbalanced data with regard to use or nonuse of medication. Covariates and possible confounders identified by univariate analysis (p \ 0.20) were tested for an impact on medication use. Odds ratios (ORs) were presented with their 95 % confidence intervals (CIs). The multivariate analysis included as explanatory variables age, sex, study arm, place of residence, history of AP, history of stroke, history of AMI, a composite of NYHA class II, III and IV versus class I, diagnosis of ST segment elevation myocardial infarction (STEMI) versus non-ST segment elevation myocardial infarction (NSTEMI), ten or more GP visits over the course of 1 year, visits with a specialist in the first 3 months post-AMI, chronic kidney disease, stent implantation, permanent pacemaker, hyperlipidemia, obesity (BMI C30 kg/m2) and diabetes mellitus. Model parameters were selected dependent on relevance and plausibility according to clinical experience and literature search and were added by forward variable selection. In order to control for possible effects of the intervention, the study arm was included as a covariable and forced to stay in the models. All variables were coded binary. Statistically significant interactions between any of the variables were not found. Computation of variation inflation factors was used to exclude obvious collinearity between independent variables in the model [28]. For each model, cstatistics were presented to indicate whether the model randomly (c = 0.5) or perfectly (c = 1.0) discriminated the response. In order to test the change of persistence to the drug combination within the study course of 1 year, marginal models were established. First, a crude model containing only the time variable as independent variable was calculated. Afterwards, sex, age, study arm, history of AP and ten or more GP visits were included in the model as additional covariables. As sensitivity analyses, the regression models were recalculated using log binomial regression statistics. In addition, logistic regression analyses were performed for the number of patients at risk at each measure point. All tests were two-tailed, and the level of significance was set to 5 %. Data were analysed using SAS 9.2 statistical software (SAS institute Inc., Cary, NC, USA).
S. Al-Khadra et al.
3 Results
p = 0.005) and ten or more GP visits per year (estimate 0.53, 95 % CI -0.89 to -0.18, p = 0.003).
3.1 Sample Characteristics 3.3 Changes in Medication Profiles within 1 Year The total sample characteristics are presented in Table 1 and additionally stratified by patients with (37.8 %) and without (62.2 %) continuous use of the drug combination. The median age of the sample was 74 years, and 63.7 % were men. Hypertension was the most commonly reported clinical parameter (91.1 %), followed by hyperlipidemia (64.5 %). The most common co-morbidities were chronic kidney disease (39.4 %) and diabetes mellitus (29.7 %), 3.9 % had a GDS score of ten or above, which indicates clinically relevant depression. The median number of drugs was seven at discharge, and the median number of GP visits was ten per year.
The highest individual discontinuation was seen for CCBs, ACEIs and the guideline-recommended drug combination until month 3 as well as until month 12 (Table 3). Until month 3, new onsets were highest for BBs, ACEI/ARB, diuretics and for the drug combination. This changed from month 3 to month 12, where the highest percentage of new onsets was seen for statins and ACEI/ARB. Altogether, ‘switching’ was common, as evidenced by high rates of withdrawals and new onsets. A total of 77.1 % of the patients who were discharged with all four drug classes actually used them at month 3; 78.9 % had no change of the drug combination from month 3 to 12.
3.2 Drug Use at Discharge and in the Course of 1 Year 3.4 Predictors for Persistent Drug Use over 1 Year Drug use differed between the single drug classes (Table 2). At discharge, 99.2 % of the patients used antiplatelets, of them 94.6 % ASA and 84.4 % thienopyridines, 86.5 % BBs, 95.0 % statins, 82.6 % ACEIs, 7.7 % ARBs and 90.4 % ACEI/ARB. Moreover, 63.3 % used diuretics and 18.5 % CCBs. The guideline-recommended combination of anti-platelets, BBs, statins and ACEI/ARB was prescribed to 74.1 % at discharge. At 1 year after AMI, the use of anti-platelets (-5.0 %), statins (-6.2 %) and ACEIs (-14.6 %) decreased. In contrast, use of BBs (?1.1 %) and ARBs (?10.8 %) increased. Use of diuretics increased from 63.3 to 74.1 %. The use of all four guideline-recommended drugs decreased from 74.1 to 63.7 %, and 37.8% used the combination continuously at discharge, month 3, 6, 9 and 12. Continuous use from month 3 to 12 was found for 47.9 % of the patients. In the unadjusted analysis, women were more likely to use diuretics, but significant results were only found for months 6 and 9. At month 3, patients aged C75 years were significantly less likely to use statins and ACEIs and more likely to use ARBs and diuretics than were patients aged \75 years. Regarding the continuous use over 1 year, older age was associated with underuse of anti-platelets and the drug combination. Trends for underuse were shown for statins, ACEIs, and ACEI/ARB. Results of the marginal effects model showed a significant change in the use of the drug combination over 1 year (crude model: estimate -0.04, 95 % CI -0.06 to -0.01, p = 0.003). After adjustment for sex, age, study arm, history of AP and ten or more GP visits per year, a significant change over time was still found (estimate -0.04, 95 % CI -0.06 to -0.01, p = 0.004). Significant covariables were history of AP (estimate -0.54, 95% CI -0.92 to -0.17,
The assignment to intervention or control group was considered in the analyses on predictors of medication persistence over 1 year after AMI. However, the assignment to intervention or control group was not significantly associated with medication persistence to any drug class over 1 year in either the univariate or the multivariate analysis (data not shown). After adjustment for age, sex and study arm, persistent use of anti-platelets was more likely after stent implantation (Table 4, Model 1). Persistent use of ACEIs was less likely if patients had a history of AP and ten or more GP visits per year. The effect of a high number of GP visits could also be found for users of ACEI/ARB. For the drug combination, persistent use was less likely for patients aged C75 years or with ten or more GP visits per year. Trends for a higher likelihood of persistence to ACEIs could be shown for patients living in the city versus rural areas and for obese patients regarding use of ACEI/ ARB. 3.5 Persistence in Outpatient Care A model that evaluated persistence in outpatient care revealed that discharge medication was a strong predictor for renewed prescription of single drug classes in the primary care setting (Table 4, Model 2). However, this effect was not observed for the drug combination. Model 2 confirmed the predictors of model 1, but not the effect of ten or more GP visits per year for ACEI/ARB. Additionally, persistent use of BBs was less likely if the patient was a man and assigned to NYHA class II–IV compared with I, and persistent use of the drug combination was less likely for patients with a history of AP.
Secondary Prevention Medication After Myocardial Infarction Table 1 Socio-demographics and medical history of the study sample (n = 259), stratified by continuous use of the drug combination over the course of 1 year Total (n = 259)
Continuous use of the drug combination for 1 year post-AMI Yes (n = 98)
n
%
n
No (n = 161) %
n
%
Age (median, range)
74, 65–91
73, 65–90
Men
165
63.7
64
65.3
101
75, 65–91 62.7
City
139
53.7
55
56.1
84
52.2
Rural
120
46.3
43
43.9
77
47.8
Primary school
187
72.2
71
72.5
116
72.0
Secondary school
63
24.3
26
26.5
37
23.0
Other
2
0.8
1
1.0
1
0.6
Missing
7
2.7
0
0
7
4.4
Place of residence
Education
Smoking status Ever smoker
29
11.2
11
11.3
18
11.2
Ex smoker
115
44.4
51
52.0
64
39.7
Never smoker Missing
110 5
42.5 1.9
36 0
36.7 0
74 5
46.0 3.1
AMI
53
20.5
21
21.4
32
19.9
Angina pectoris
76
29.3
22
22.5
54
33.5
Stroke
22
8.5
10
10.2
12
7.5
Missing
1
0.4
0
0
1
0.6
Arterial hypertension
236
91.1
89
90.8
History of
Hyperlipidemia
147
91.3
167
64.5
63
64.3
104
64.6
62
23.9
23
23.5
39
24.2
I
129
49.8
57
58.2
72
44.7
II
71
27.4
24
24.5
47
29.2
III ? IV
59
22.8
17
17.3
42
26.1
99 160
38.2 61.8
39 59
39.8 60.2
60 101
37.3 62.7
Reperfusion therapy (PCI, bypass)
232
89.6
91
92.9
141
87.6
Stent implantation
185
71.4
72
73.5
113
70.2
Pacemaker
36
13.9
12
12.2
24
14.9
Coronary artery bypass surgery
39
15.1
12
12.2
27
16.8
BMI C30 kg/m2 NYHA classification
Infarction type STEMI NSTEMI
Diabetes mellitus
77
29.7
28
28.6
49
30.4
Chronic kidney disease
102
39.4
37
37.8
65
40.4
Depression (GDS score C10)
10
3.9
4
4.1
6
3.7
6
2.3
4
4.1
2
1.2
Missing Healthcare utilization (median, interquartile range) Number of drugs overall at discharge
7, 6–8
6,5–8
7, 6–9
Number of GP visits within 1 year post-AMI
10, 7–16
8.5, 7–13
11, 8–19
Number of specialist consultations within 1 year post-AMI
2, 0–3
2, 0–3
1, 0–3
AMI acute myocardial infarction, BMI body mass index, GDS Geriatric Depression Scale, GP general practitioner, NSTEMI non-ST-segment elevation myocardial infarction, NYHA New York Heart Association, PCI percutaneous coronary intervention, STEMI ST-segment elevation myocardial infarction
S. Al-Khadra et al. Table 2 Frequency of use of single drug classes and the drug combination (anti-platelets ? beta blockers ? statins ? ACEI/ARB) at discharge, months 3, 6, 9, and 12 and for continuous use (discharge, months 3, 6, 9 and 12), stratified by age and sex Discharge
Month 3
Month 6
Month 9
Month 12
Continuous use
237 (91.5)
Anti-platelets Total
257 (99.2)
248 (95.8)
254 (98.1)
251 (96.9)
244 (94.2)
Women
94 (100)
91 (96.8)
94 (100)
93 (98.9)
89 (94.7)
87 (92.6)
Men
163 (98.8)
157 (95.2)
160 (97.0)
158 (95.8)
155 (93.9)
150 (90.9)
p value
0.536
0.751
0.162
0.265
0.806
0.648
Age \75 years
130 (99.2)
128 (97.7)
130 (99.2)
128 (97.7)
126 (96.2)
125 (95.4)
Age C75 years p value
127 (99.2) 1.00
120 (93.8) 0.134
124 (96.9) 0.210
123 (96.1) 0.497
118 (92.2) 0.169
112 (87.5) 0.022
Beta blockers Total
224 (86.5)
232 (89.6)
228 (88.0)
233 (90.0)
227 (87.6)
187 (72.2)
Women
81 (86.2)
86 (91.5)
86 (91.5)
87 (92.6)
83 (88.3)
72 (76.6)
Men
143 (86.7)
146 (88.5)
142 (86.1)
146 (88.5)
144 (87.3)
115 (69.7)
p value
0.911
0.447
0.196
0.295
0.810
0.233
Age \75 years
113 (86.3)
117 (89.3)
115 (87.8)
119 (90.8)
115 (87.8)
97 (74.1)
Age C75 years
111 (86.7)
115 (89.8)
113 (88.3)
114 (89.1)
112 (87.5)
90 (70.3)
p value
0.914
0.889
0.902
0.634
0.944
0.503 205 (79.1)
Statins Total
246 (95.0)
236 (91.1)
234 (90.4)
234 (90.4)
230 (88.8)
Women
87 (92.6)
84 (89.4)
82 (87.2)
81 (86.2)
80 (85.1)
71 (75.5)
Men
159 (96.4)
152 (92.1)
152 (92.1)
153 (92.7)
150 (90.9)
134 (81.2)
p value
0.177
0.453
0.200
0.086
0.154
0.279
Age \75 years Age C75 years
126 (96.2) 120 (93.8)
125 (95.4) 111 (86.7)
121 (92.4) 113 (88.3)
122 (93.1) 112 (87.5)
119 (90.8) 111 (86.7)
110 (84.0) 95 (74.2)
p value
0.370
0.014
0.266
0.125
0.293
0.053
ACEIs Total
214 (82.6)
189 (73.0)
184 (71.0)
178 (68.7)
176 (68.0)
145 (56.0)
Women
77 (81.9)
63 (67.0)
61 (64.9)
60 (63.8)
60 (63.8)
49 (52.1)
Men
137 (83.0)
126 (76.4)
123 (74.6)
118 (71.5)
116 (70.3)
96 (58.2)
p value
0.820
0.104
0.100
0.200
0.283
0.345
Age \75 years
113 (86.3)
105 (80.2)
99 (75.6)
95 (72.5)
92 (70.2)
81 (61.8)
Age C75 years
101 (78.9)
84 (65.6)
85 (66.4)
83 (64.8)
84 (65.6)
64 (50.0)
p value
0.118
0.009
0.104
0.183
0.427
0.055
Total
20 (7.7)
39 (15.1)
39 (15.1)
46 (17.8)
48 (18.5)
16 (6.2)
Women
7 (7.5)
17 (18.1)
17 (18.1)
19 (20.1)
21 (22.3)
6 (6.4)
Men
13 (7.9)
22 (13.3)
22 (13.3)
27 (16.4)
27 (16.4)
10 (6.1)
p value
0.900
0.304
0.304
0.436
0.234
0.918
Age \75 years Age C75 years
8 (6.1) 12 (9.4)
14 (10.7) 25 (19.5)
18 (13.7) 21 (16.4)
23 (17.6) 23 (18.0)
24 (18.3) 24 (18.8)
7 (5.3) 9 (7.0)
p value
0.325
0.047
0.549
0.931
0.929
0.573
Total
234 (90.4)
228 (88.0)
223 (86.1)
224 (86.5)
224 (86.5)
187 (72.2)a
Women
84 (89.4)
80 (85.1)
78 (83.0)
79 (84.0)
81 (86.2)
65 (69.2)
ARBs
ACEI/ARB
Men
150 (90.9)
148 (89.7)
145 (87.9)
145 (87.9)
143 (86.7)
122 (73.9)
p value
0.685
0.274
0.273
0.385
0.911
0.408
Age \75 years
121 (92.4)
119 (90.8)
117 (89.3)
118 (90.1)
116 (88.6)
101 (77.1)
Age C75 years
113 (88.3)
109 (85.2)
106 (82.8)
106 (82.8)
108 (84.4)
86 (67.2)
p value
0.266
0.159
0.131
0.087
0.326
0.075
Secondary Prevention Medication After Myocardial Infarction Table 2 continued Discharge
Month 3
Month 6
Month 9
Month 12
Continuous use
Drug combination Total
192 (74.1)
180 (69.5)
176 (68.0)
175 (67.6)
165 (63.7)
98 (37.8)
Women
66 (70.2)
62 (66.0)
62 (66.0)
60 (63.8)
56 (59.6)
34 (36.2)
Men
126 (76.4)
118 (71.5)
114 (69.1)
115 (69.7)
109 (66.1)
64 (38.8)
p value
0.277
0.350
0.603
0.332
0.297
0.676 61 (46.6)
Age \75 years
100 (76.3)
98 (74.8)
96 (73.3)
96 (73.3)
89 (67.9)
Age C75 years
92 (71.9)
82 (64.1)
80 (62.5)
79 (61.7)
76 (59.4)
37 (28.9)
p value
0.412
0.060
0.063
0.047
0.152
0.003 133 (51.4)
Diuretics Total
164 (63.3)
194 (74.9)
195 (75.3)
193 (74.5)
192 (74.1)
Women
63 (67.0)
75 (79.8)
78 (83.0)
77 (81.9)
73 (77.7)
50 (53.2)
Men
101 (61.2)
119 (72.2)
117 (70.9)
116 (70.3)
119 (72.1)
83 (50.3)
p value Age \75 years
0.351 80 (61.1)
0.171 90 (68.7)
0.030 94 (71.8)
0.039 91 (69.5)
0.328 94 (71.8)
0.655 65 (49.6)
Age C75 years
84 (65.6)
104 (81.3)
101 (78.9)
102 (79.7)
98 (76.6)
68 (53.1)
p value
0.447
0.020
0.182
0.059
0.377
0.572
CCBs Total
48 (18.5)
42 (16.2)
40 (15.4)
46 (17.8)
46 (17.8)
23 (8.9)
Women
12 (12.8)
15 (16.0)
16 (17.0)
20 (21.3)
21 (22.3)
7 (7.5)
Men
36 (21.8)
27 (16.4)
24 (14.6)
26 (15.8)
25 (15.2)
16 (9.7)
p value
0.071
0.932
0.596
0.264
0.146
0.540
Age \75 years
22 (16.8)
22 (16.8)
23 (17.6)
24 (18.3)
25 (19.1)
12 (9.2)
Age C75 years
26 (20.3)
20 (15.6)
17 (13.3)
22 (17.2)
21 (16.4)
11 (8.6)
p value
0.466
0.799
0.341
0.811
0.573
0.873
Data are presented as n (%) Significant results (Chi-squared test) are highlighted in boldface type ACEIs angiotensin-converting enzyme inhibitors, ARBs angiotensin receptor blockers, CCBs calcium channel blockers a
Sum of continuous users of ACEIs and users of ARBs is not equal to users of ACEI/ARB, because 26 patients switched from ACEIs to ARBs or vice versa in the course of 1 year and were therefore not categorized as continuous users of ACEIs or ARBs
3.6 Sensitivity Analyses Log binomial analyses overall revealed results similar to those of the logistic regression analyses, with slightly higher relative risk estimates for the analysis on the drug combination (Electronic Supplementary Material [ESM] 1). Logistic regression analyses separately performed for the patients at risk at the respective measure points showed results largely similar to the complete-cases analyses (ESM 2).
4 Discussion We performed an analysis regarding persistence with medication out of data from the randomised controlled KORINNA study following elderly survivors of AMI. We found that use of a guideline-recommended drug class combination initiated at index hospital stay decreased in
the course of the 1-year follow-up. However, 79.0 % of subjects had no change in the drug combination from month 3 to month 12. The use of single drug classes was high at discharge compared with other European studies [6, 29, 30], and 74.1 % of the patients were discharged with the combination of anti-platelets, BBs, statins and ACEI/ ARB. In total, prescription rates were higher at month 12 than at discharge for ARBs, diuretics and slightly for BBs. Despite this, the guideline-recommended drug combination was only used in 37.8 % of the sample within 1 year postAMI. Strong predictors for reduced persistence with the drug combination were age C75 years and ten or more GP visits per year. In addition, a high number of GP visits was associated with a lower likelihood of persistence to ACEI/ ARB. Overall, the deviation from guideline-recommended drug therapy within 1 year found in our study might be explained by a specific adjustment of pharmacotherapy to the individual situation of the patient. The decrease in
S. Al-Khadra et al. Table 3 Individual changes of medication use from discharge to month 3 and from month 3 to month 12 for single drug classes and the drug combination (anti-platelets ? beta blockers ? statins ? ACEI/ARB) Discharge ? month 3 Pts with drug use at discharge No changea
Drugs withdrawn at month 3a
Month 3 ? month 12 No drug use at discharge New onset at month 3b
Anti-platelets
248 (96.5)
9 (3.5)
BBs
208 (92.9)
16 (7.1)
0
Statins
232 (94.3)
14 (5.7)
ACEIs
172 (80.4)
42 (19.6)
ARBs
18 (90.0)
2 (10.0)
21 (8.8)
No use
b
Pts with drug use at month 3
No drug use at month 3
No changec
New onset at month 12d
Drugs withdrawn at month 12c
No used
2 (100)
240 (96.8)
8 (3.2)
4 (36.4)
7 (63.6)
11 (31.4)
218 (94.0)
14 (6.0)
9 (33.3)
18 (66.7)
4 (30.8)
9 (69.2)
219 (92.8)
17 (7.2)
11 (47.8)
12 (52.2)
17 (37.8)
28 (62.2)
165 (87.3)
24 (12.7)
11 (15.7)
59 (84.3)
218 (91.2)
36 (92.3)
3 (7.7)
12 (5.5)
208 (94.5)
24 (68.6)
ACEI/ARB
211 (90.2)
23 (9.8)
17 (68.0)
8 (32.0)
212 (93.0)
16 (7.0)
12 (38.7)
19 (61.3)
Drug combination
148 (77.1)
44 (22.9)
32 (47.8)
35 (52.2)
142 (78.9)
38 (21.1)
23 (29.1)
56 (71.9)
Diuretics
151 (92.1)
13 (7.9)
43 (45.3)
52 (54.7)
179 (92.2)
15 (7.9)
13 (20.0)
52 (80.0)
29 (60.4)
19 (39.6)
13 (6.2)
198 (93.8)
32 (76.2)
10 (23.8)
14 (6.5)
203 (93.5)
CCBs
Data are presented as n (%) ACEIs angiotensin-converting enzyme inhibitors, ARBs angiotensin receptor blockers, BBs beta blockers, CCBs calcium channel blockers, pts patients a
Percentages refer to the pts with medication use at discharge
b
Percentages refer to the pts without medication use at discharge
c
Percentages refer to the pts with medication use at month 3
d
Percentages refer to the pts without medication use at month 3
ACEIs and increase in ARBs may reflect a change of medication due to side effects of ACEIs. Side effects or the need to reduce polypharmacy due to emerging multi-morbidity may account for the decrease in statin treatment, and the increasing use of diuretics might be associated with the development of heart failure symptoms. Higher age and frequent GP visits were found to be significantly related to a lower likelihood of receiving the drug combination, anti-platelets (age) and ACEI/ARB (GP visits) continuously and may be overall associated with a higher number of comorbidities [15, 31, 32] that necessitate treatment modification, i.e. to reduce polypharmacy. Our results are supported by Spencer et al. [33], who demonstrated that history of AP is associated with underuse of a combination of anti-platelets, BBs, statins and ACEIs at the time of hospitalisation. Despite inconsistent evidence on the extent of medication persistence or adherence in the elderly, real-world data from primary care often report older age, particularly age above 74 years, as a predictor for reduced patient compliance and physicians’ non-adherence to guideline recommendations in terms of secondary prevention of AMI [6, 17, 32, 34–36] and coronary artery disease in general [29, 37]. Use of guideline-recommended drugs after AMI clearly reduces mortality in elderly people [35, 38, 39]. The use of BBs for blood pressure control and ACEI/ARB postAMI has class I recommendations and level of evidence A, especially regarding use in high-risk patients, i.e. patients
with STEMI, heart failure with left ventricular ejection fraction (LVEF) \40 %, large infarctions, or no reperfusion therapy [12]. Indeed, guidelines suggest their persistent use [12]. However, consideration of contraindications such as severe hypotension, severe congestive heart failure, severe bradycardia, lung disease or peripheral arterial disease [40] may be more prominent in elderly. Furthermore, it would have been interesting to clarify whether depression that is associated with worse outcomes after AMI [41] is related to lower medication persistence in our study. However, due to the low number of patients with depression, no statistical analysis could be performed. More studies on this subject are particularly needed. The association between a high number of GP visits and lower persistence with the guideline recommendations regarding uses of the drug combination, ACEI and ACEI/ ARB has thus far not been properly investigated and may depend on different factors, e.g. health status, healthcare system and medical care structure as well as patient preferences. It is undeniable that early physicians’ contact after discharge and a minimum number of physicians’ visits are crucial for receiving optimal care [42]. Overall, a mean of seven GP visits per year was reported for people aged above 64 years [43], whereas studies with different patient characteristics and study settings reported a mean of ten physician contacts per year for patients post-AMI [39]. Interestingly, we have seen in our study that patients readmitted to hospital had a higher number of GP visits,
Secondary Prevention Medication After Myocardial Infarction Table 4 Multivariate logistic regression models with presentation of odds ratios for predictors of continuous use (discharge, months 3, 6, 9 and 12) of the single drug classes and the drug combination (antiplatelets ? beta blockers ? statins ? ACEI/ARB) (Model 1). All n = 259
models are adjusted for age, sex and study arm (intervention vs. control group). Model 2 calculated continuous use from month 3 postacute myocardial infarction and was adjusted further for use at discharge
Model 1 OR (95 % CI)
Model 2 p value
c-statistics
OR (95 % CI)
p value
b
Anti-platelets
b
Age C75 years
0.38 (0.12–1.10)
0.080
0.34 (0.09–1.04)
0.060
Men
0.68 (0.21–1.96)
0.598
0.79 (0.24–2.34)
0.839
Study arma
1.51 (0.52–4.73)
0.559
1.28 (0.43–4.09)
0.824
Stent implantation
3.68 (1.37–10.33)
0.008
3.12 (1.11–9.02)
0.030
Anti-platelets (discharge)
–
11.67 (0.83–b)
0.068
Beta blockers
0.59
0.70
Age C75 years
0.87 (0.49–1.53)
0.619
0.82 (0.42–1.60)
0.561
Men
0.63 (0.35–1.15)
0.135
0.45 (0.22–0.93)
0.031
Study arm
0.98 (0.56–1.71)
0.935
0.91 (0.47–1.76)
0.780
NYHA class I II–IV
1.00 0.61 (0.34–1.07)
0.085
1.00 0.30 (0.15–0.61)
ORIGINAL RESEARCH ARTICLE
Secondary Prevention Medication After Myocardial Infarction: Persistence in Elderly People over the Course of 1 Year Saba Al-Khadra • Christa Meisinger • Ute Amann • Rolf Holle • Bernhard Kuch Hildegard Seidl • Inge Kirchberger
•
Ó Springer International Publishing Switzerland 2014
Abstract Aims Persistent use of guideline-recommended drugs after acute myocardial infarction (AMI) is frequently reported to be inadequate in the elderly and scarce knowledge exists about factors that influence persistence in outpatient care. Our aim was to evaluate drug use and its predictors in survivors of AMI above 64 years from hospital discharge to 1-year post-AMI. Methods In a single-centre randomised controlled trial, discharge medication of 259 patients with AMI was obtained from medical records at hospital stay. Follow-up drug use and use of the healthcare system were selfreported to study nurses over 1 year in 3-month intervals. Electronic supplementary material The online version of this article (doi:10.1007/s40266-014-0189-x) contains supplementary material, which is available to authorized users. S. Al-Khadra C. Meisinger U. Amann I. Kirchberger (&) Central Hospital of Augsburg, MONICA/KORA Myocardial Infarction Registry, Augsburg, Germany e-mail: [email protected] S. Al-Khadra C. Meisinger U. Amann I. Kirchberger Helmholtz Zentrum Mu¨nchen, German Research Center for Environmental Health (GmbH), Institute of Epidemiology II, Neuherberg, Germany R. Holle H. Seidl Helmholtz Zentrum Mu¨nchen, German Research Center for Environmental Health (GmbH), Institute of Health Economics and Health Care Management, Neuherberg, Germany B. Kuch Department of Internal Medicine/Cardiology, Hospital of No¨rdlingen, No¨rdlingen, Germany B. Kuch Department of Internal Medicine I, Cardiology, Central Hospital of Augsburg, Augsburg, Germany
Predictors for persistence were modelled with multivariate logistic regression analysis considering demographics, comorbidities and treatment characteristics. Results At discharge, 99.2 % of the patients used antiplatelets, 86.5 % beta blockers, 95.0 % statins and 90.4 % angiotensin-converting enzyme inhibitors or angiotensin receptor blockers. Use of the combination of all four drug classes decreased from discharge to 1 year post-AMI from 74.1 to 37.8 % and was significantly reduced by age C75 years (odds ratio [OR] 0.49; 95 % confidence interval [CI] 0.29–0.85) and ten or more visits with general practitioners (GPs) over 1 year (OR 0.29; 95 % CI 0.17–0.51). Persistence from month 3 to 12 was significantly associated with drug use at discharge for the single drug classes, but not for the drug combination. Conclusion Older age and frequent GP visits are associated with decreased use of the guideline-recommended drug combination after AMI. Further research is needed to specify underlying reasons and develop measures to improve persistence.
Key Points Anti-platelets, beta blockers, statins and angiotensinconverting enzyme inhibitors/angiotensin receptor blockers were prescribed to 74.1 % of elderly patients with myocardial infarction at hospital discharge, but their use significantly decreased to 37.8 % during 1 year follow-up. Patients who were 75 years or older or had ten or more visits with a general practitioner were less likely to receive all four secondary prevention drugs 1 year after myocardial infarction.
S. Al-Khadra et al.
1 Introduction Acute myocardial infarction (AMI) is one of the leading causes of death in developed countries [1, 2]. Although prognosis has improved over the last decades, survivors of AMI still have a high risk of cardiovascular death [3]. Secondary prevention programmes commonly include lifestyle changes and pharmacological treatment. The continuous use of medication has been shown to strongly reduce risk of all-cause mortality [4–6], hospital readmission and healthcare costs [6–8]. Accordingly, guidelines for clinical practice support the long-term use of at least four drug classes [9–12]: anti-platelets, including acetylsalicylic acid (ASA; aspirin) and thienopyridines, beta blockers (BBs), statins and angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin-receptor blockers (ARBs). A recently published worldwide multi-centre study [13] in patients with coronary heart disease demonstrated that the use of anti-platelets (96 %), BBs (79 %), statins (97 %) and ACEIs/ARBs (77 %) has increased compared with previous European surveys [14]. However, 1 year after discharge, significantly fewer BBs, ASA, statins and ACEIs were prescribed by doctors or used by the patients with AMI compared with at discharge [15, 16]. So far, only a few studies have examined factors associated with persistence or adherence to guideline recommendations on medication in patients following AMI. A recently published study revealed that socio-demographic characteristics including age and sex were the most important factors influencing drug prescription in outpatient care [17]. High-risk patients, who are expected to benefit most from optimal drug treatment, only rarely receive recommended medication [18]. Studies focusing on patients aged C65 years and on determinants of continuous use and guideline adherence at least 1 year after AMI are rare. We present data from a randomised controlled trial in elderly patients with AMI with a follow-up of 1 year. The objectives were to describe 1-year medication profiles and change in prescription patterns. Furthermore, we aimed to identify predictors of persistence to guideline-recommended drugs post-AMI regarding the single drug classes and the drug combination.
2 Methods 2.1 Study Design The KORINNA study (KORonarINfarkt Nachbehandlung im Alter) is a randomised controlled trial that included patients aged C65 years who were discharged after first or recurrent AMI from the Central Hospital of Augsburg
between September 2008 and May 2010. Patients assigned to the intervention group received nurse-based case management for 1 year, including home visits and telephone calls, whereas the control group received usual care. Details on the intervention programme and the outcome measures have been reported elsewhere [19, 20]. The outcome of this analysis was the use of guideline-recommended secondary prevention medication post-AMI for the entire patient sample. Outcome variables were drugs recommended at discharge and drug intake at months 3, 6, 9 and 12 after discharge. The study protocol conforms to the ethical guidelines of the 1975 Declaration of Helsinki as reflected in a priori approval by the ethics committee. 2.2 Study Population In order to study changes in medication over the course of 1 year, the current analysis is based on patients with complete medication profiles, i.e. information on used secondary prevention drugs are available at discharge, and months 3, 6, 9 and 12 post-AMI. Consequently, only patients who were still alive and participating in the study at month 12 were included in this analysis. Thus, 259 of an initial 340 patients were subjects of analysis (76.2 %). Excluded patients (n = 81) were those who did not fulfil inclusion criteria (n = 2), withdrew consent (n = 35) or died during the study course (n = 39). One patient was lost to follow-up and four patients did not have complete medication profiles available. Compared with the sample with complete medication data, excluded patients were older, had significantly more often chronic kidney disease, were more often assigned to higher New York Heart Association (NYHA) classes and had received revascularization procedures significantly less often. No statistically significant differences were found between the complete medication sample and excluded patients concerning guideline-recommended medication at discharge. 2.3 Data Collection After subjects gave written informed consent, a first nursebased interview was conducted during the index hospital stay. Collected data covered age, sex, place of residence, education and smoking behaviour. Patients’ self-reports on the following variables were confirmed where possible from hospitals’ medical patient records: history of hyperlipidemia, hypertension, heart failure, AMI, angina pectoris (AP), and body mass index (BMI). History of stroke was self-reported only. Subjects with an estimated glomerular filtration rate (eGFR) below 60 mL/min/1.73 m2 of body surface area were classified as having chronic kidney disease. The eGFR was estimated with the abbreviated
Secondary Prevention Medication After Myocardial Infarction
Modification of Diet in Renal Disease (MDRD) equation [21], given by: eGFR = 175 9 standardised serum creatinine-1.154 9 age-0.203 9 1.212 (if Black) 9 0.742 (if female), where serum creatinine is expressed in mg/dL. Creatinine levels were routinely measured at index hospital stay. Treatment at the index hospital stay included reperfusion therapy, stent implantation, permanent pacemaker, and bypass surgery. Further clinical data were assessed according to the standards applied at the KORA Myocardial Infarction Registry, Augsburg, which have been reported elsewhere [22]. NYHA functional classification and presence of diabetes mellitus or depression were recorded by the study physician at the baseline examination. Depression was assessed using the Geriatric Depression Scale (GDS)-15. Scores above ten points were considered framing depression [23]. Information on discharge medication (without doses) was selected from hospital discharge letters. Doctors’ visits with general practitioners (GPs) and specialists/ internists over the course of 1 year were recorded simultaneously with medication profiles from nurse-led interviews at months 3, 6, 9 and 12 post-AMI. Thereby, medication profiles were accurately recorded, including the identification number for pharmaceutical products (for Germany), the size of the drug box, the tablet-taking regime and the date of first intake. To obtain this information precisely in the telephone interviews, patients were encouraged to read out the information from all used drug packages. In case of home visits, patients were requested to provide the study nurses with the medication packages currently being used. For this analysis, we focused on medication recommended for secondary prevention of AMI. Outcome measures were medication persistence [24], i.e. reported use by patients during the telephone calls or home visits. Discontinuation of therapy was assumed, if drug use was interrupted over 90 days (3 months) [25, 26], that is discontinuation at one of the four interview time points. We analysed drugs recommended by European and international guidelines with respect to pharmacological treatment after AMI [9–12]: anti-platelets, BBs, statins and ACEIs or ARBs. Use of diuretics and calcium channel blockers (CCBs) was additionally included in the descriptive analysis. Classification of drugs was performed by a pharmacist according to the international Anatomical Therapeutic Chemical (ATC) code [27]. Codes were ‘B01AC’ for anti-platelets, ‘C07’ for BBs, ‘C10AA’ and ‘C10BA02’ for statins, ‘C09A’ and ‘C09B’ for ACEIs, ‘C09C’ and ‘C09D’ for ARBs, ‘C03’, ‘C07B’, ‘C07C’, ‘C08G’, ‘C09BA’ and ‘C09DA’ for diuretics and ‘C08’ for CCBs. We further categorized patients in users of only ACEIs, users of only ARBs or users of ACEIs and/or ARBs (ACEI/ARB).
2.4 Statistics Basic patient characteristics were described using univariate analysis. Multivariate logistic regression analysis was performed to determine which factors contribute to medication persistence (‘continuous use’) from discharge to 1 year post-AMI for single drug classes and the drug combination (Model 1). Model 2 analysed factors associated with persistence in the outpatient care (from month 3 on), treating discharge medication as an explanatory factor. Models for anti-platelets were performed with exact logistic regression due to imbalanced data with regard to use or nonuse of medication. Covariates and possible confounders identified by univariate analysis (p \ 0.20) were tested for an impact on medication use. Odds ratios (ORs) were presented with their 95 % confidence intervals (CIs). The multivariate analysis included as explanatory variables age, sex, study arm, place of residence, history of AP, history of stroke, history of AMI, a composite of NYHA class II, III and IV versus class I, diagnosis of ST segment elevation myocardial infarction (STEMI) versus non-ST segment elevation myocardial infarction (NSTEMI), ten or more GP visits over the course of 1 year, visits with a specialist in the first 3 months post-AMI, chronic kidney disease, stent implantation, permanent pacemaker, hyperlipidemia, obesity (BMI C30 kg/m2) and diabetes mellitus. Model parameters were selected dependent on relevance and plausibility according to clinical experience and literature search and were added by forward variable selection. In order to control for possible effects of the intervention, the study arm was included as a covariable and forced to stay in the models. All variables were coded binary. Statistically significant interactions between any of the variables were not found. Computation of variation inflation factors was used to exclude obvious collinearity between independent variables in the model [28]. For each model, cstatistics were presented to indicate whether the model randomly (c = 0.5) or perfectly (c = 1.0) discriminated the response. In order to test the change of persistence to the drug combination within the study course of 1 year, marginal models were established. First, a crude model containing only the time variable as independent variable was calculated. Afterwards, sex, age, study arm, history of AP and ten or more GP visits were included in the model as additional covariables. As sensitivity analyses, the regression models were recalculated using log binomial regression statistics. In addition, logistic regression analyses were performed for the number of patients at risk at each measure point. All tests were two-tailed, and the level of significance was set to 5 %. Data were analysed using SAS 9.2 statistical software (SAS institute Inc., Cary, NC, USA).
S. Al-Khadra et al.
3 Results
p = 0.005) and ten or more GP visits per year (estimate 0.53, 95 % CI -0.89 to -0.18, p = 0.003).
3.1 Sample Characteristics 3.3 Changes in Medication Profiles within 1 Year The total sample characteristics are presented in Table 1 and additionally stratified by patients with (37.8 %) and without (62.2 %) continuous use of the drug combination. The median age of the sample was 74 years, and 63.7 % were men. Hypertension was the most commonly reported clinical parameter (91.1 %), followed by hyperlipidemia (64.5 %). The most common co-morbidities were chronic kidney disease (39.4 %) and diabetes mellitus (29.7 %), 3.9 % had a GDS score of ten or above, which indicates clinically relevant depression. The median number of drugs was seven at discharge, and the median number of GP visits was ten per year.
The highest individual discontinuation was seen for CCBs, ACEIs and the guideline-recommended drug combination until month 3 as well as until month 12 (Table 3). Until month 3, new onsets were highest for BBs, ACEI/ARB, diuretics and for the drug combination. This changed from month 3 to month 12, where the highest percentage of new onsets was seen for statins and ACEI/ARB. Altogether, ‘switching’ was common, as evidenced by high rates of withdrawals and new onsets. A total of 77.1 % of the patients who were discharged with all four drug classes actually used them at month 3; 78.9 % had no change of the drug combination from month 3 to 12.
3.2 Drug Use at Discharge and in the Course of 1 Year 3.4 Predictors for Persistent Drug Use over 1 Year Drug use differed between the single drug classes (Table 2). At discharge, 99.2 % of the patients used antiplatelets, of them 94.6 % ASA and 84.4 % thienopyridines, 86.5 % BBs, 95.0 % statins, 82.6 % ACEIs, 7.7 % ARBs and 90.4 % ACEI/ARB. Moreover, 63.3 % used diuretics and 18.5 % CCBs. The guideline-recommended combination of anti-platelets, BBs, statins and ACEI/ARB was prescribed to 74.1 % at discharge. At 1 year after AMI, the use of anti-platelets (-5.0 %), statins (-6.2 %) and ACEIs (-14.6 %) decreased. In contrast, use of BBs (?1.1 %) and ARBs (?10.8 %) increased. Use of diuretics increased from 63.3 to 74.1 %. The use of all four guideline-recommended drugs decreased from 74.1 to 63.7 %, and 37.8% used the combination continuously at discharge, month 3, 6, 9 and 12. Continuous use from month 3 to 12 was found for 47.9 % of the patients. In the unadjusted analysis, women were more likely to use diuretics, but significant results were only found for months 6 and 9. At month 3, patients aged C75 years were significantly less likely to use statins and ACEIs and more likely to use ARBs and diuretics than were patients aged \75 years. Regarding the continuous use over 1 year, older age was associated with underuse of anti-platelets and the drug combination. Trends for underuse were shown for statins, ACEIs, and ACEI/ARB. Results of the marginal effects model showed a significant change in the use of the drug combination over 1 year (crude model: estimate -0.04, 95 % CI -0.06 to -0.01, p = 0.003). After adjustment for sex, age, study arm, history of AP and ten or more GP visits per year, a significant change over time was still found (estimate -0.04, 95 % CI -0.06 to -0.01, p = 0.004). Significant covariables were history of AP (estimate -0.54, 95% CI -0.92 to -0.17,
The assignment to intervention or control group was considered in the analyses on predictors of medication persistence over 1 year after AMI. However, the assignment to intervention or control group was not significantly associated with medication persistence to any drug class over 1 year in either the univariate or the multivariate analysis (data not shown). After adjustment for age, sex and study arm, persistent use of anti-platelets was more likely after stent implantation (Table 4, Model 1). Persistent use of ACEIs was less likely if patients had a history of AP and ten or more GP visits per year. The effect of a high number of GP visits could also be found for users of ACEI/ARB. For the drug combination, persistent use was less likely for patients aged C75 years or with ten or more GP visits per year. Trends for a higher likelihood of persistence to ACEIs could be shown for patients living in the city versus rural areas and for obese patients regarding use of ACEI/ ARB. 3.5 Persistence in Outpatient Care A model that evaluated persistence in outpatient care revealed that discharge medication was a strong predictor for renewed prescription of single drug classes in the primary care setting (Table 4, Model 2). However, this effect was not observed for the drug combination. Model 2 confirmed the predictors of model 1, but not the effect of ten or more GP visits per year for ACEI/ARB. Additionally, persistent use of BBs was less likely if the patient was a man and assigned to NYHA class II–IV compared with I, and persistent use of the drug combination was less likely for patients with a history of AP.
Secondary Prevention Medication After Myocardial Infarction Table 1 Socio-demographics and medical history of the study sample (n = 259), stratified by continuous use of the drug combination over the course of 1 year Total (n = 259)
Continuous use of the drug combination for 1 year post-AMI Yes (n = 98)
n
%
n
No (n = 161) %
n
%
Age (median, range)
74, 65–91
73, 65–90
Men
165
63.7
64
65.3
101
75, 65–91 62.7
City
139
53.7
55
56.1
84
52.2
Rural
120
46.3
43
43.9
77
47.8
Primary school
187
72.2
71
72.5
116
72.0
Secondary school
63
24.3
26
26.5
37
23.0
Other
2
0.8
1
1.0
1
0.6
Missing
7
2.7
0
0
7
4.4
Place of residence
Education
Smoking status Ever smoker
29
11.2
11
11.3
18
11.2
Ex smoker
115
44.4
51
52.0
64
39.7
Never smoker Missing
110 5
42.5 1.9
36 0
36.7 0
74 5
46.0 3.1
AMI
53
20.5
21
21.4
32
19.9
Angina pectoris
76
29.3
22
22.5
54
33.5
Stroke
22
8.5
10
10.2
12
7.5
Missing
1
0.4
0
0
1
0.6
Arterial hypertension
236
91.1
89
90.8
History of
Hyperlipidemia
147
91.3
167
64.5
63
64.3
104
64.6
62
23.9
23
23.5
39
24.2
I
129
49.8
57
58.2
72
44.7
II
71
27.4
24
24.5
47
29.2
III ? IV
59
22.8
17
17.3
42
26.1
99 160
38.2 61.8
39 59
39.8 60.2
60 101
37.3 62.7
Reperfusion therapy (PCI, bypass)
232
89.6
91
92.9
141
87.6
Stent implantation
185
71.4
72
73.5
113
70.2
Pacemaker
36
13.9
12
12.2
24
14.9
Coronary artery bypass surgery
39
15.1
12
12.2
27
16.8
BMI C30 kg/m2 NYHA classification
Infarction type STEMI NSTEMI
Diabetes mellitus
77
29.7
28
28.6
49
30.4
Chronic kidney disease
102
39.4
37
37.8
65
40.4
Depression (GDS score C10)
10
3.9
4
4.1
6
3.7
6
2.3
4
4.1
2
1.2
Missing Healthcare utilization (median, interquartile range) Number of drugs overall at discharge
7, 6–8
6,5–8
7, 6–9
Number of GP visits within 1 year post-AMI
10, 7–16
8.5, 7–13
11, 8–19
Number of specialist consultations within 1 year post-AMI
2, 0–3
2, 0–3
1, 0–3
AMI acute myocardial infarction, BMI body mass index, GDS Geriatric Depression Scale, GP general practitioner, NSTEMI non-ST-segment elevation myocardial infarction, NYHA New York Heart Association, PCI percutaneous coronary intervention, STEMI ST-segment elevation myocardial infarction
S. Al-Khadra et al. Table 2 Frequency of use of single drug classes and the drug combination (anti-platelets ? beta blockers ? statins ? ACEI/ARB) at discharge, months 3, 6, 9, and 12 and for continuous use (discharge, months 3, 6, 9 and 12), stratified by age and sex Discharge
Month 3
Month 6
Month 9
Month 12
Continuous use
237 (91.5)
Anti-platelets Total
257 (99.2)
248 (95.8)
254 (98.1)
251 (96.9)
244 (94.2)
Women
94 (100)
91 (96.8)
94 (100)
93 (98.9)
89 (94.7)
87 (92.6)
Men
163 (98.8)
157 (95.2)
160 (97.0)
158 (95.8)
155 (93.9)
150 (90.9)
p value
0.536
0.751
0.162
0.265
0.806
0.648
Age \75 years
130 (99.2)
128 (97.7)
130 (99.2)
128 (97.7)
126 (96.2)
125 (95.4)
Age C75 years p value
127 (99.2) 1.00
120 (93.8) 0.134
124 (96.9) 0.210
123 (96.1) 0.497
118 (92.2) 0.169
112 (87.5) 0.022
Beta blockers Total
224 (86.5)
232 (89.6)
228 (88.0)
233 (90.0)
227 (87.6)
187 (72.2)
Women
81 (86.2)
86 (91.5)
86 (91.5)
87 (92.6)
83 (88.3)
72 (76.6)
Men
143 (86.7)
146 (88.5)
142 (86.1)
146 (88.5)
144 (87.3)
115 (69.7)
p value
0.911
0.447
0.196
0.295
0.810
0.233
Age \75 years
113 (86.3)
117 (89.3)
115 (87.8)
119 (90.8)
115 (87.8)
97 (74.1)
Age C75 years
111 (86.7)
115 (89.8)
113 (88.3)
114 (89.1)
112 (87.5)
90 (70.3)
p value
0.914
0.889
0.902
0.634
0.944
0.503 205 (79.1)
Statins Total
246 (95.0)
236 (91.1)
234 (90.4)
234 (90.4)
230 (88.8)
Women
87 (92.6)
84 (89.4)
82 (87.2)
81 (86.2)
80 (85.1)
71 (75.5)
Men
159 (96.4)
152 (92.1)
152 (92.1)
153 (92.7)
150 (90.9)
134 (81.2)
p value
0.177
0.453
0.200
0.086
0.154
0.279
Age \75 years Age C75 years
126 (96.2) 120 (93.8)
125 (95.4) 111 (86.7)
121 (92.4) 113 (88.3)
122 (93.1) 112 (87.5)
119 (90.8) 111 (86.7)
110 (84.0) 95 (74.2)
p value
0.370
0.014
0.266
0.125
0.293
0.053
ACEIs Total
214 (82.6)
189 (73.0)
184 (71.0)
178 (68.7)
176 (68.0)
145 (56.0)
Women
77 (81.9)
63 (67.0)
61 (64.9)
60 (63.8)
60 (63.8)
49 (52.1)
Men
137 (83.0)
126 (76.4)
123 (74.6)
118 (71.5)
116 (70.3)
96 (58.2)
p value
0.820
0.104
0.100
0.200
0.283
0.345
Age \75 years
113 (86.3)
105 (80.2)
99 (75.6)
95 (72.5)
92 (70.2)
81 (61.8)
Age C75 years
101 (78.9)
84 (65.6)
85 (66.4)
83 (64.8)
84 (65.6)
64 (50.0)
p value
0.118
0.009
0.104
0.183
0.427
0.055
Total
20 (7.7)
39 (15.1)
39 (15.1)
46 (17.8)
48 (18.5)
16 (6.2)
Women
7 (7.5)
17 (18.1)
17 (18.1)
19 (20.1)
21 (22.3)
6 (6.4)
Men
13 (7.9)
22 (13.3)
22 (13.3)
27 (16.4)
27 (16.4)
10 (6.1)
p value
0.900
0.304
0.304
0.436
0.234
0.918
Age \75 years Age C75 years
8 (6.1) 12 (9.4)
14 (10.7) 25 (19.5)
18 (13.7) 21 (16.4)
23 (17.6) 23 (18.0)
24 (18.3) 24 (18.8)
7 (5.3) 9 (7.0)
p value
0.325
0.047
0.549
0.931
0.929
0.573
Total
234 (90.4)
228 (88.0)
223 (86.1)
224 (86.5)
224 (86.5)
187 (72.2)a
Women
84 (89.4)
80 (85.1)
78 (83.0)
79 (84.0)
81 (86.2)
65 (69.2)
ARBs
ACEI/ARB
Men
150 (90.9)
148 (89.7)
145 (87.9)
145 (87.9)
143 (86.7)
122 (73.9)
p value
0.685
0.274
0.273
0.385
0.911
0.408
Age \75 years
121 (92.4)
119 (90.8)
117 (89.3)
118 (90.1)
116 (88.6)
101 (77.1)
Age C75 years
113 (88.3)
109 (85.2)
106 (82.8)
106 (82.8)
108 (84.4)
86 (67.2)
p value
0.266
0.159
0.131
0.087
0.326
0.075
Secondary Prevention Medication After Myocardial Infarction Table 2 continued Discharge
Month 3
Month 6
Month 9
Month 12
Continuous use
Drug combination Total
192 (74.1)
180 (69.5)
176 (68.0)
175 (67.6)
165 (63.7)
98 (37.8)
Women
66 (70.2)
62 (66.0)
62 (66.0)
60 (63.8)
56 (59.6)
34 (36.2)
Men
126 (76.4)
118 (71.5)
114 (69.1)
115 (69.7)
109 (66.1)
64 (38.8)
p value
0.277
0.350
0.603
0.332
0.297
0.676 61 (46.6)
Age \75 years
100 (76.3)
98 (74.8)
96 (73.3)
96 (73.3)
89 (67.9)
Age C75 years
92 (71.9)
82 (64.1)
80 (62.5)
79 (61.7)
76 (59.4)
37 (28.9)
p value
0.412
0.060
0.063
0.047
0.152
0.003 133 (51.4)
Diuretics Total
164 (63.3)
194 (74.9)
195 (75.3)
193 (74.5)
192 (74.1)
Women
63 (67.0)
75 (79.8)
78 (83.0)
77 (81.9)
73 (77.7)
50 (53.2)
Men
101 (61.2)
119 (72.2)
117 (70.9)
116 (70.3)
119 (72.1)
83 (50.3)
p value Age \75 years
0.351 80 (61.1)
0.171 90 (68.7)
0.030 94 (71.8)
0.039 91 (69.5)
0.328 94 (71.8)
0.655 65 (49.6)
Age C75 years
84 (65.6)
104 (81.3)
101 (78.9)
102 (79.7)
98 (76.6)
68 (53.1)
p value
0.447
0.020
0.182
0.059
0.377
0.572
CCBs Total
48 (18.5)
42 (16.2)
40 (15.4)
46 (17.8)
46 (17.8)
23 (8.9)
Women
12 (12.8)
15 (16.0)
16 (17.0)
20 (21.3)
21 (22.3)
7 (7.5)
Men
36 (21.8)
27 (16.4)
24 (14.6)
26 (15.8)
25 (15.2)
16 (9.7)
p value
0.071
0.932
0.596
0.264
0.146
0.540
Age \75 years
22 (16.8)
22 (16.8)
23 (17.6)
24 (18.3)
25 (19.1)
12 (9.2)
Age C75 years
26 (20.3)
20 (15.6)
17 (13.3)
22 (17.2)
21 (16.4)
11 (8.6)
p value
0.466
0.799
0.341
0.811
0.573
0.873
Data are presented as n (%) Significant results (Chi-squared test) are highlighted in boldface type ACEIs angiotensin-converting enzyme inhibitors, ARBs angiotensin receptor blockers, CCBs calcium channel blockers a
Sum of continuous users of ACEIs and users of ARBs is not equal to users of ACEI/ARB, because 26 patients switched from ACEIs to ARBs or vice versa in the course of 1 year and were therefore not categorized as continuous users of ACEIs or ARBs
3.6 Sensitivity Analyses Log binomial analyses overall revealed results similar to those of the logistic regression analyses, with slightly higher relative risk estimates for the analysis on the drug combination (Electronic Supplementary Material [ESM] 1). Logistic regression analyses separately performed for the patients at risk at the respective measure points showed results largely similar to the complete-cases analyses (ESM 2).
4 Discussion We performed an analysis regarding persistence with medication out of data from the randomised controlled KORINNA study following elderly survivors of AMI. We found that use of a guideline-recommended drug class combination initiated at index hospital stay decreased in
the course of the 1-year follow-up. However, 79.0 % of subjects had no change in the drug combination from month 3 to month 12. The use of single drug classes was high at discharge compared with other European studies [6, 29, 30], and 74.1 % of the patients were discharged with the combination of anti-platelets, BBs, statins and ACEI/ ARB. In total, prescription rates were higher at month 12 than at discharge for ARBs, diuretics and slightly for BBs. Despite this, the guideline-recommended drug combination was only used in 37.8 % of the sample within 1 year postAMI. Strong predictors for reduced persistence with the drug combination were age C75 years and ten or more GP visits per year. In addition, a high number of GP visits was associated with a lower likelihood of persistence to ACEI/ ARB. Overall, the deviation from guideline-recommended drug therapy within 1 year found in our study might be explained by a specific adjustment of pharmacotherapy to the individual situation of the patient. The decrease in
S. Al-Khadra et al. Table 3 Individual changes of medication use from discharge to month 3 and from month 3 to month 12 for single drug classes and the drug combination (anti-platelets ? beta blockers ? statins ? ACEI/ARB) Discharge ? month 3 Pts with drug use at discharge No changea
Drugs withdrawn at month 3a
Month 3 ? month 12 No drug use at discharge New onset at month 3b
Anti-platelets
248 (96.5)
9 (3.5)
BBs
208 (92.9)
16 (7.1)
0
Statins
232 (94.3)
14 (5.7)
ACEIs
172 (80.4)
42 (19.6)
ARBs
18 (90.0)
2 (10.0)
21 (8.8)
No use
b
Pts with drug use at month 3
No drug use at month 3
No changec
New onset at month 12d
Drugs withdrawn at month 12c
No used
2 (100)
240 (96.8)
8 (3.2)
4 (36.4)
7 (63.6)
11 (31.4)
218 (94.0)
14 (6.0)
9 (33.3)
18 (66.7)
4 (30.8)
9 (69.2)
219 (92.8)
17 (7.2)
11 (47.8)
12 (52.2)
17 (37.8)
28 (62.2)
165 (87.3)
24 (12.7)
11 (15.7)
59 (84.3)
218 (91.2)
36 (92.3)
3 (7.7)
12 (5.5)
208 (94.5)
24 (68.6)
ACEI/ARB
211 (90.2)
23 (9.8)
17 (68.0)
8 (32.0)
212 (93.0)
16 (7.0)
12 (38.7)
19 (61.3)
Drug combination
148 (77.1)
44 (22.9)
32 (47.8)
35 (52.2)
142 (78.9)
38 (21.1)
23 (29.1)
56 (71.9)
Diuretics
151 (92.1)
13 (7.9)
43 (45.3)
52 (54.7)
179 (92.2)
15 (7.9)
13 (20.0)
52 (80.0)
29 (60.4)
19 (39.6)
13 (6.2)
198 (93.8)
32 (76.2)
10 (23.8)
14 (6.5)
203 (93.5)
CCBs
Data are presented as n (%) ACEIs angiotensin-converting enzyme inhibitors, ARBs angiotensin receptor blockers, BBs beta blockers, CCBs calcium channel blockers, pts patients a
Percentages refer to the pts with medication use at discharge
b
Percentages refer to the pts without medication use at discharge
c
Percentages refer to the pts with medication use at month 3
d
Percentages refer to the pts without medication use at month 3
ACEIs and increase in ARBs may reflect a change of medication due to side effects of ACEIs. Side effects or the need to reduce polypharmacy due to emerging multi-morbidity may account for the decrease in statin treatment, and the increasing use of diuretics might be associated with the development of heart failure symptoms. Higher age and frequent GP visits were found to be significantly related to a lower likelihood of receiving the drug combination, anti-platelets (age) and ACEI/ARB (GP visits) continuously and may be overall associated with a higher number of comorbidities [15, 31, 32] that necessitate treatment modification, i.e. to reduce polypharmacy. Our results are supported by Spencer et al. [33], who demonstrated that history of AP is associated with underuse of a combination of anti-platelets, BBs, statins and ACEIs at the time of hospitalisation. Despite inconsistent evidence on the extent of medication persistence or adherence in the elderly, real-world data from primary care often report older age, particularly age above 74 years, as a predictor for reduced patient compliance and physicians’ non-adherence to guideline recommendations in terms of secondary prevention of AMI [6, 17, 32, 34–36] and coronary artery disease in general [29, 37]. Use of guideline-recommended drugs after AMI clearly reduces mortality in elderly people [35, 38, 39]. The use of BBs for blood pressure control and ACEI/ARB postAMI has class I recommendations and level of evidence A, especially regarding use in high-risk patients, i.e. patients
with STEMI, heart failure with left ventricular ejection fraction (LVEF) \40 %, large infarctions, or no reperfusion therapy [12]. Indeed, guidelines suggest their persistent use [12]. However, consideration of contraindications such as severe hypotension, severe congestive heart failure, severe bradycardia, lung disease or peripheral arterial disease [40] may be more prominent in elderly. Furthermore, it would have been interesting to clarify whether depression that is associated with worse outcomes after AMI [41] is related to lower medication persistence in our study. However, due to the low number of patients with depression, no statistical analysis could be performed. More studies on this subject are particularly needed. The association between a high number of GP visits and lower persistence with the guideline recommendations regarding uses of the drug combination, ACEI and ACEI/ ARB has thus far not been properly investigated and may depend on different factors, e.g. health status, healthcare system and medical care structure as well as patient preferences. It is undeniable that early physicians’ contact after discharge and a minimum number of physicians’ visits are crucial for receiving optimal care [42]. Overall, a mean of seven GP visits per year was reported for people aged above 64 years [43], whereas studies with different patient characteristics and study settings reported a mean of ten physician contacts per year for patients post-AMI [39]. Interestingly, we have seen in our study that patients readmitted to hospital had a higher number of GP visits,
Secondary Prevention Medication After Myocardial Infarction Table 4 Multivariate logistic regression models with presentation of odds ratios for predictors of continuous use (discharge, months 3, 6, 9 and 12) of the single drug classes and the drug combination (antiplatelets ? beta blockers ? statins ? ACEI/ARB) (Model 1). All n = 259
models are adjusted for age, sex and study arm (intervention vs. control group). Model 2 calculated continuous use from month 3 postacute myocardial infarction and was adjusted further for use at discharge
Model 1 OR (95 % CI)
Model 2 p value
c-statistics
OR (95 % CI)
p value
b
Anti-platelets
b
Age C75 years
0.38 (0.12–1.10)
0.080
0.34 (0.09–1.04)
0.060
Men
0.68 (0.21–1.96)
0.598
0.79 (0.24–2.34)
0.839
Study arma
1.51 (0.52–4.73)
0.559
1.28 (0.43–4.09)
0.824
Stent implantation
3.68 (1.37–10.33)
0.008
3.12 (1.11–9.02)
0.030
Anti-platelets (discharge)
–
11.67 (0.83–b)
0.068
Beta blockers
0.59
0.70
Age C75 years
0.87 (0.49–1.53)
0.619
0.82 (0.42–1.60)
0.561
Men
0.63 (0.35–1.15)
0.135
0.45 (0.22–0.93)
0.031
Study arm
0.98 (0.56–1.71)
0.935
0.91 (0.47–1.76)
0.780
NYHA class I II–IV
1.00 0.61 (0.34–1.07)
0.085
1.00 0.30 (0.15–0.61)
