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Gaist D, García Rodríguez LA, Hallas J, Hald SM, Möller S, Høyer BB, Selim M, Goldstein LB. Association of Statin Use With Risk of Stroke Recurrence After Intracerebral Hemorrhage. Neurology 2023; 101:e1793-e1806. [PMID: 37648526 PMCID: PMC10634647 DOI: 10.1212/wnl.0000000000207792] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 07/12/2023] [Indexed: 09/01/2023] Open
Abstract
BACKGROUND AND OBJECTIVES Survivors of spontaneous intracerebral hemorrhage (ICH) may have indications for statin therapy. The effect of statins on the risk of subsequent hemorrhagic and ischemic stroke (IS) in this setting is uncertain. We sought to determine the risk of any stroke (ischemic stroke, IS or recurrent ICH), IS, and recurrent ICH associated with statin use among ICH survivors. METHODS Using the Danish Stroke Registry, we identified all patients admitted to a hospital in Denmark (population 5.8 million) with a first-ever ICH between January 2003 and December 2021 who were aged 50 years or older and survived >30 days. Patients were followed up until August 2022. Within this cohort, we conducted 3 nested case-control analyses for any stroke, IS, and recurrent ICH. We matched controls for age, sex, time since first-ever ICH, and history of prior IS. The primary exposure was statin use before or on the date of subsequent stroke or the equivalent date in matched controls. Using conditional logistic regression, we calculated adjusted odds ratios (aORs) and corresponding 95% confidence intervals (CIs) for any stroke, IS, and recurrent ICH associated with statin exposure. RESULTS We identified 1,959 patients with any stroke (women 45.3%; mean [SD] age, 72.6 [9.7] years) who were matched to 7,400 controls; 1,073 patients with IS (women 42.0%; mean [SD] age, 72.4 [10.0] years) who were matched to 4,035 controls and 984 patients with recurrent ICH (women 48.7%; mean [SD] age, 72.7 [9.2] years) who were matched to 3,755 controls. Statin exposure was associated with a lower risk of both any stroke (cases 38.6%, controls 41.1%; aOR 0.88; 95% CI 0.78-0.99) and IS (cases 39.8%, controls 41.8%, aOR 0.79; 95% CI 0.67-0.92), but was not associated with recurrent ICH risk (cases 39.1%, controls 40.8%, aOR 1.05; 95% CI 0.88-1.24). DISCUSSION Exposure to statins was not associated with an increased risk of recurrent ICH but was associated with a lower risk of any stroke, largely due to a lower risk of IS. Confirmation of these findings in randomized trials is needed. CLASSIFICATION OF EVIDENCE This study provides Class III evidence that statin use in patients with ICH is associated with a lower risk of any stroke and IS and not with increased risk of recurrent ICH.
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Affiliation(s)
- David Gaist
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington.
| | - Luis Alberto García Rodríguez
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Jesper Hallas
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Stine Munk Hald
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Sören Möller
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Birgit Bjerre Høyer
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Magdy Selim
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
| | - Larry B Goldstein
- From the Research Unit for Neurology (D.G., S.M.H.), Odense University Hospital; University of Southern Denmark, Odense, Denmark; Centro Español Investigación Farmacoepidemiológica (L.A.G.R.), Madrid, Spain; Department of Clinical Pharmacology (J.H.), Pharmacy and Environmental Medicine, University of Southern Denmark; Open Patient Data Explorative Network (OPEN) (S.M.), Odense University Hospital; Odense Patient Data Explorative Network (OPEN) (B.B.H.), Odense University Hospital, Denmark; Beth Israel Deaconess Medical Center (M.S.), Harvard Medical School; and Department of Neurology and Kentucky Neuroscience Institute (L.B.G.), University of Kentucky, Lexington
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Adherence to Treatment Regimen and its Related Factors in Patients Undergoing Coronary Artery Revascularization in the City of Zanjan in 2017. PREVENTIVE CARE IN NURSING AND MIDWIFERY JOURNAL 2020. [DOI: 10.52547/pcnm.10.3.42] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Jang DE, Zuñiga JA. Factors associated with medication persistence among ischemic stroke patients: a systematic review. Neurol Res 2020; 42:537-546. [PMID: 32321382 DOI: 10.1080/01616412.2020.1754640] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
OBJECTIVE An investigation of the prevalence of medication persistence and associated factors in order to inform effective strategies for improving medication persistence. METHODS A systematic review of the literature from 2010 to the present was performed, using the PRISMA protocol. Primary and empirical observational studies of adult ischemic stroke or transient ischemic attack patients were included. PubMed, CINAHL, Web of Science, Cochrane Library, and PsycInfo databases were searched using the key terms stroke, ischemic stroke, medication persistence, medication adherence, and patient compliance. RESULTS Of four hundred twenty-eight journal articles retrieved, a final 18 articles were included. Short-term medication persistence was 46.2-96.7%, and long-term medication persistence was 41.7-93.0%. Identified hospital-related factors for medication persistence were stroke unit care, in-hospital medical complications, and early follow-up visit. Demographic factors for medication persistence were older age, and high/adequate financial status; disease-related factors were disease history, stroke subtype, and symptom severity. Age less than 75, female sex, comorbidity, antiplatelet medication switch, and polypharmacy were identified as factors of medication nonpersistence. CONCLUSIONS Stroke patients' medication persistence decreases over time, and persistence on antiplatelets, anticoagulants, and statin was poor. Several factors were associated with medication persistence, and these factors should be considered in future secondary preventative strategies.
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Affiliation(s)
- Dong Eun Jang
- School of Nursing, The University of Texas at Austin , Austin, TX, USA
| | - Julie Ann Zuñiga
- School of Nursing, The University of Texas at Austin , Austin, TX, USA
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Riis AH, Erichsen R, Ostenfeld EB, Højskov CS, Thorlacius‐Ussing O, Stender MT, Lash TL, Møller HJ. Validating registry data on statins prescriptions by blood measurements. Pharmacoepidemiol Drug Saf 2019; 28:609-615. [DOI: 10.1002/pds.4700] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 09/07/2018] [Accepted: 10/17/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Anders H. Riis
- Department of Clinical EpidemiologyAarhus University Hospital Aarhus Denmark
| | - Rune Erichsen
- Department of Clinical EpidemiologyAarhus University Hospital Aarhus Denmark
| | - Eva B. Ostenfeld
- Department of Clinical EpidemiologyAarhus University Hospital Aarhus Denmark
| | - Carsten S. Højskov
- Department of Clinical BiochemistryAarhus University Hospital Aarhus Denmark
| | - Ole Thorlacius‐Ussing
- Department of Gastrointestinal SurgeryAalborg University Hospital Aalborg Denmark
- Institute of Clinical MedicineAalborg University Aalborg Denmark
- The Danish Colorectal Cancer Group Denmark
| | - Mogens Tornby Stender
- Department of Gastrointestinal SurgeryAalborg University Hospital Aalborg Denmark
- Institute of Clinical MedicineAalborg University Aalborg Denmark
| | - Timothy L. Lash
- Department of Clinical EpidemiologyAarhus University Hospital Aarhus Denmark
- Department of Epidemiology, Rollins School of Public HealthEmory University Atlanta Georgia USA
- Winship Cancer InstituteEmory University Atlanta Georgia USA
| | - Holger Jon Møller
- Department of Clinical BiochemistryAarhus University Hospital Aarhus Denmark
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Wawruch M, Zatko D, Wimmer G, Luha J, Wimmerova S, Kukumberg P, Murin J, Hloska A, Tesar T, Shah R. Non-persistence with antiplatelet therapy in elderly patients after a transient ischemic attack. Aging Clin Exp Res 2017; 29:1121-1127. [PMID: 28284002 DOI: 10.1007/s40520-017-0745-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 02/21/2017] [Indexed: 01/21/2023]
Abstract
BACKGROUND Antiplatelet therapy following a transient ischemic attack (TIA) constitutes an important secondary prevention measure. AIMS The study was aimed at evaluating the development of non-persistence with antiplatelet therapy in elderly patients after a TIA and identifying patient-related characteristics associated with the probability of non-persistence during the follow-up period. METHODS The study cohort (n = 854) was selected from the database of the largest health insurance provider of the Slovak Republic. It included patients aged ≥65 years, in whom antiplatelet medication was initiated following a TIA diagnosis during the period between 1 January 2010 and 31 December 2010. Each patient was followed for a period of 3 years from the date of the first antiplatelet medication prescription associated with TIA diagnosis. Patients in whom there was a treatment gap of at least 6 months without antiplatelet medication prescription were defined as "non-persistent". The factors predicting non-persistence were identified in the Cox proportional hazards model. RESULTS At the end of the follow-up period, 345 (40.4%) patients were non-persistent with antiplatelet medication. Protective factors decreasing a patient´s likelihood of becoming non-persistent were age ≥75 years [hazard ratio (HR) = 0.75], polypharmacy (concurrent use of ≥6 drugs) (HR = 0.79), arterial hypertension (HR = 0.68), diabetes mellitus (HR = 0.74), hypercholesterolemia (HR = 0.75), and antiplatelet medication switching during the follow-up period (HR = 0.73). CONCLUSIONS It is concluded that following a TIA, elderly patients aged <75 years or those with normal serum cholesterol levels, without certain comorbid conditions and polypharmacy may benefit from special counselling to encourage persistence with secondary preventive medication.
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Affiliation(s)
- Martin Wawruch
- Institute of Pharmacology and Clinical Pharmacology, Faculty of Medicine, Comenius University, Sasinkova 4, 811 08, Bratislava, Slovakia.
| | - Dusan Zatko
- General Health Insurance Company, Panónska cesta 2, 851 04, Bratislava, Slovakia
| | - Gejza Wimmer
- Institute of Pharmacology and Clinical Pharmacology, Faculty of Medicine, Comenius University, Sasinkova 4, 811 08, Bratislava, Slovakia
| | - Jan Luha
- Institute of Medical Biology, Genetics and Clinical Genetics, Faculty of Medicine, Comenius University, Sasinkova 4, 811 08, Bratislava, Slovakia
| | - Sona Wimmerova
- Department of Biophysics, Informatics and Biostatistics, Faculty of Public Health, Slovak Medical University, Limbová 12, 833 03, Bratislava, Slovakia
| | - Peter Kukumberg
- 2nd Department of Neurology, Faculty of Medicine, Comenius University, Limbová 5, 833 05, Bratislava, Slovakia
| | - Jan Murin
- 1st Department of Internal Medicine, Faculty of Medicine, Comenius University, Mickiewiczova 13, 813 69, Bratislava, Slovakia
| | - Adam Hloska
- Department of Pharmacology, Jessenius Faculty of Medicine in Martin, Comenius University, Mala Hora 11161, 036 01, Martin, Slovakia
| | - Tomas Tesar
- Department of Organisation and Management of Pharmacy, Faculty of Pharmacy, Comenius University, Kalinciakova 8, 832 32, Bratislava, Slovakia
| | - Rashmi Shah
- Rashmi Shah, Pharmaceutical Consultant, 8 Birchdale, Gerrards Cross, Bucks, SL9 7JA, UK
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Tanskanen A, Taipale H, Koponen M, Tolppanen AM, Hartikainen S, Ahonen R, Tiihonen J. Drug exposure in register-based research-An expert-opinion based evaluation of methods. PLoS One 2017; 12:e0184070. [PMID: 28886089 PMCID: PMC5590868 DOI: 10.1371/journal.pone.0184070] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Accepted: 08/17/2017] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND In register-based pharmacoepidemiological studies, construction of drug exposure periods from drug purchases is a major methodological challenge. Various methods have been applied but their validity is rarely evaluated. Our objective was to conduct an expert-opinion based evaluation of the correctness of drug use periods produced by different methods. METHODS Drug use periods were calculated with three fixed methods: time windows, assumption of one Defined Daily Dose (DDD) per day and one tablet per day, and with PRE2DUP that is based on modelling of individual drug purchasing behavior. Expert-opinion based evaluation was conducted with 200 randomly selected purchase histories of warfarin, bisoprolol, simvastatin, risperidone and mirtazapine in the MEDALZ-2005 cohort (28,093 persons with Alzheimer's disease). Two experts reviewed purchase histories and judged which methods had joined correct purchases and gave correct duration for each of 1000 drug exposure periods. RESULTS The evaluated correctness of drug use periods was 70-94% for PRE2DUP, and depending on grace periods and time window lengths 0-73% for tablet methods, 0-41% for DDD methods and 0-11% for time window methods. The highest rate of evaluated correct solutions for each method class were observed for 1 tablet per day with 180 days grace period (TAB_1_180, 43-73%), and 1 DDD per day with 180 days grace period (1-41%). Time window methods produced at maximum only 11% correct solutions. The best performing fixed method TAB_1_180 reached highest correctness for simvastatin 73% (95% CI 65-81%) whereas 89% (95% CI 84-94%) of PRE2DUP periods were judged as correct. CONCLUSIONS This study shows inaccuracy of fixed methods and the urgent need for new data-driven methods. In the expert-opinion based evaluation, the lowest error rates were observed with data-driven method PRE2DUP.
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Affiliation(s)
- Antti Tanskanen
- Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
- National Institute for Health and Welfare, Helsinki, Finland
- University of Eastern Finland, Department of Forensic Psychiatry, Niuvanniemi Hospital, Kuopio, Finland
| | - Heidi Taipale
- Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
- University of Eastern Finland, Department of Forensic Psychiatry, Niuvanniemi Hospital, Kuopio, Finland
- Kuopio Research Centre of Geriatric Care, University of Eastern Finland, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Marjaana Koponen
- Kuopio Research Centre of Geriatric Care, University of Eastern Finland, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Anna-Maija Tolppanen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Research Centre for Comparative Effectiveness and Patient Safety (RECEPS), University of Eastern Finland, Kuopio, Finland
| | - Sirpa Hartikainen
- Kuopio Research Centre of Geriatric Care, University of Eastern Finland, Kuopio, Finland
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Kuopio University Hospital, Psychiatry, Kuopio, Finland
| | - Riitta Ahonen
- School of Pharmacy, University of Eastern Finland, Kuopio, Finland
| | - Jari Tiihonen
- Karolinska Institutet, Department of Clinical Neuroscience, Stockholm, Sweden
- University of Eastern Finland, Department of Forensic Psychiatry, Niuvanniemi Hospital, Kuopio, Finland
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Secondary CV Prevention in South America in a Community Setting: The PURE Study. Glob Heart 2016; 12:305-313. [PMID: 27773540 DOI: 10.1016/j.gheart.2016.06.001] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2016] [Revised: 06/11/2016] [Accepted: 06/15/2016] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Despite the availability of evidence-based therapies, there is no information on the use of medications for the secondary prevention of cardiovascular disease in urban and rural community settings in South America. OBJECTIVES This study sought to assess the use, and its predictors, of effective secondary prevention therapies in individuals with a history of coronary heart disease (CHD) or stroke. METHODS In the PURE (Prospective Urban Rural Epidemiological) study, we enrolled 24,713 individuals from South America ages 35 to 70 years from 97 rural and urban communities in Argentina, Brazil, Chile, and Colombia. We assessed the use of proven therapies with standardized questionnaires. We report estimates of drug use at national, community, and individual levels and the independent predictors of their utilization through a multivariable analysis model. RESULTS Of 24,713 individuals, 910 had a self-reported CHD event (at a median of 5 years earlier) and 407 had stroke (6 years earlier). The proportions of individuals with CHD who received antiplatelet medications (30.1%), beta-blockers (34.2%), angiotensin-converting enzyme inhibitors, or angiotensin-receptor blockers (36.0%), or statins (18.0%) were low; with even lower proportions among stroke patients (antiplatelets 24.3%, angiotensin-converting enzyme inhibitors/angiotensin-receptor blockers 37.6%, statins 9.8%). A substantial proportion of patients did not receive any proven therapy (CHD 31%, stroke 54%). A minority of patients received either all 4 (4.1%) or 3 proven therapies (3.3%). Male sex, age >60 years, better education, more wealth, urban location, diabetes, and obesity were associated with higher rates of medication use. In a multivariable model, markers of wealth had the largest impact in secondary prevention. CONCLUSIONS There are large gaps in the use of proven medications for secondary prevention of cardiovascular disease in South America. Strategies to improve the sustained use of these medications will likely reduce cardiovascular disease burden substantially.
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Al AlShaikh S, Quinn T, Dunn W, Walters M, Dawson J. Predictive factors of non-adherence to secondary preventative medication after stroke or transient ischaemic attack: A systematic review and meta-analyses. Eur Stroke J 2016; 1:65-75. [PMID: 29900404 PMCID: PMC5992740 DOI: 10.1177/2396987316647187] [Citation(s) in RCA: 61] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2016] [Accepted: 04/06/2016] [Indexed: 11/30/2022] Open
Abstract
Purpose Non-adherence to secondary preventative medications after stroke is
relatively common and associated with poorer outcomes. Non-adherence can be
due to a number of patient, disease, medication or institutional factors.
The aim of this review was to identify factors associated with non-adherence
after stroke. Method We performed a systematic review and meta-analysis of studies reporting
factors associated with medication adherence after stroke. We searched
MEDLINE, EMBASE, CINAHL, PsycINFO, CENTRAL and Web of Knowledge. We followed
PRISMA guidance. We assessed risk of bias of included studies using a
pre-specified tool based on Cochrane guidance and the Newcastle–Ottawa
scales. Where data allowed, we evaluated summary prevalence of non-adherence
and association of factors commonly reported with medication adherence in
included studies using random-effects model meta-analysis. Findings From 12,237 titles, we included 29 studies in our review. These included
69,137 patients. The majority of included studies (27/29) were considered to
be at high risk of bias mainly due to performance bias. Non-adherence rate
to secondary preventative medication reported by included studies was 30.9%
(95% CI 26.8%–35.3%). Although many factors were reported as related to
adherence in individual studies, on meta-analysis, absent history of atrial
fibrillation (OR 1.02, 95% CI 0.72–1.5), disability (OR 1.27, 95% CI
0.93–1.72), polypharmacy (OR 1.29, 95% CI 0.9–1.9) and age (OR 1.04, 95% CI
0.96–1.14) were not associated with adherence. Discussion This review identified many factors related to adherence to preventative
medications after stroke of which many are modifiable. Commonly reported
factors included concerns about treatment, lack of support with medication
intake, polypharmacy, increased disability and having more severe
stroke. Conclusion Understanding factors associated with medication taking could inform
strategies to improve adherence. Further research should assess whether
interventions to promote adherence also improve outcomes.
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Affiliation(s)
- Sukainah Al AlShaikh
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Terry Quinn
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - William Dunn
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Matthew Walters
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Jesse Dawson
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
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Ostergaard K, Pottegård A, Hallas J, Bak S, dePont Christensen R, Gaist D. Discontinuation of antiplatelet treatment and risk of recurrent stroke and all-cause death: a cohort study. Neuroepidemiology 2014; 43:57-64. [PMID: 25323533 DOI: 10.1159/000365732] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2014] [Accepted: 07/02/2014] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND We wished to examine the impact of antiplatelet drug discontinuation on recurrent stroke and all-cause mortality. METHODS We identified a cohort of incident ischaemic stroke patients in a Danish stroke registry, 2007-2011. Using population-based registries we assessed subjects' drug use and followed them up for stroke recurrence, or all-cause death. Person-time was classified by antiplatelet drug use into current use, recent use (≤150 days after last use), and non-use (>150 days after last use). Lipid-lowering drug (LLD) use was classified by the same rules. We used Cox proportional hazard models to calculate the adjusted hazard ratio (HR) and corresponding 95% confidence intervals (CIs) for the risk of recurrent stroke or death associated with discontinuation of antiplatelet or LLD drugs. RESULTS Among 4,670 stroke patients followed up for up a median of 1.5 years, 237 experienced a second stroke and 600 died. Compared with current antiplatelet drug use, both recent use (1.3 (0.8-2.0)), and non-use (1.3 (0.8-1.9)) were associated with increased recurrent stroke risk. The corresponding HRs of death were 1.9 (1.4-2.5) for recent and 1.8 (1.4-2.3) for non-use of antiplatelet drugs. Recent statin use was associated with markedly increased risk of death (2.1 (1.7-2.6)), and only marginally with recurrent stroke (1.2 (0.9-1.6)). CONCLUSIONS Antiplatelet drug discontinuation may be associated with an increased recurrent stroke risk. Our results on death risk indicate that non-pharmacological biases, such as 'sick stopper', may threaten the validity of this risk estimate.
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