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Hsieh MT, Hsieh CY, Yang TH, Sung SF, Hsieh YC, Lee CW, Lin CJ, Chen YW, Lin KH, Sung PS, Tang CW, Chu HJ, Tsai KC, Chou CL, Lin CH, Wei CY, Chen TY, Yan SY, Chen PL, Hsiao CY, Chan L, Huang YC, Liu HM, Tang SC, Lee IH, Lien LM, Chiou HY, Lee JT, Jeng JS. Associations of diabetes status and glucose measures with outcomes after endovascular therapy in patients with acute ischemic stroke: an analysis of the nationwide TREAT-AIS registry. Front Neurol 2024; 15:1351150. [PMID: 38813247 PMCID: PMC11135283 DOI: 10.3389/fneur.2024.1351150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 04/03/2024] [Indexed: 05/31/2024] Open
Abstract
Background Hyperglycemia affects the outcomes of endovascular therapy (EVT) for acute ischemic stroke (AIS). This study compares the predictive ability of diabetes status and glucose measures on EVT outcomes using nationwide registry data. Methods The study included 1,097 AIS patients who underwent EVT from the Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke. The variables analyzed included diabetes status, admission glucose, glycated hemoglobin (HbA1c), admission glucose-to-HbA1c ratio (GAR), and outcomes such as 90-day poor functional outcome (modified Rankin Scale score ≥ 2) and symptomatic intracranial hemorrhage (SICH). Multivariable analyses investigated the independent effects of diabetes status and glucose measures on outcomes. A receiver operating characteristic (ROC) analysis was performed to compare their predictive abilities. Results The multivariable analysis showed that individuals with known diabetes had a higher likelihood of poor functional outcomes (odds ratios [ORs] 2.10 to 2.58) and SICH (ORs 3.28 to 4.30) compared to those without diabetes. Higher quartiles of admission glucose and GAR were associated with poor functional outcomes and SICH. Higher quartiles of HbA1c were significantly associated with poor functional outcomes. However, patients in the second HbA1c quartile (5.6-5.8%) showed a non-significant tendency toward good functional outcomes compared to those in the lowest quartile (<5.6%). The ROC analysis indicated that diabetes status and admission glucose had higher predictive abilities for poor functional outcomes, while admission glucose and GAR were better predictors for SICH. Conclusion In AIS patients undergoing EVT, diabetes status, admission glucose, and GAR were associated with 90-day poor functional outcomes and SICH. Admission glucose was likely the most suitable glucose measure for predicting outcomes after EVT.
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Affiliation(s)
- Meng-Tsang Hsieh
- Stroke Center and Department of Neurology, Chi-Mei Medical Center, Tainan, Taiwan
- Stroke Center and Department of Neurology, E-Da Hospital, Kaohsiung, Taiwan
| | - Cheng-Yang Hsieh
- Department of Neurology, Tainan Sin Lau Hospital, Tainan, Taiwan
| | - Tzu-Hsien Yang
- Department of Radiology, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan
| | - Sheng-Feng Sung
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan
| | - Yi-Chen Hsieh
- Program in Medical Neuroscience, Taipei Medical University, Taipei, Taiwan
| | - Chung-Wei Lee
- Department of Medical Imaging, National Taiwan University Hospital, Taipei, Taiwan
| | - Chun-Jen Lin
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Yu-Wei Chen
- Department of Neurology, Landseed International Hospital, Taoyuan, Taiwan
| | - Kuan-Hung Lin
- Department of Neurology, Chi Mei Medical Center, Tainan, Taiwan
| | - Pi-Shan Sung
- Department of Neurology, National Cheng Kung University Hospital, Tainan, Taiwan
| | - Chih-Wei Tang
- Department of Neurology, Far Eastern Memorial Hospital, New Taipei City, Taiwan
| | - Hai-Jui Chu
- Department of Neurology, En Chu Kong Hospital, New Taipei City, Taiwan
| | - Kun-Chang Tsai
- Department of Neurology, National Taiwan University Hospital, Hsinchu, Taiwan
| | - Chao-Liang Chou
- Department of Neurology, Mackay Memorial Hospital, Taipei, Taiwan
| | - Ching-Huang Lin
- Department of Neurology, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Cheng-Yu Wei
- Department of Neurology, Chang Bing Show Chwan Memorial Hospital, Changhwa County, Taiwan
| | - Te-Yuan Chen
- Department of Neurosurgery, E-Da Hospital, I-Shou University, Kaohsiung, Taiwan
| | - Shang-Yih Yan
- Department of Neurology, Tri Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Po-Lin Chen
- Department of Neurology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Chen-Yu Hsiao
- Department of Diagnostic Radiology, Shin Kong WHS Memorial Hospital, Taipei, Taiwan
| | - Lung Chan
- Department of Neurology, Taipei Medical University–Shuang Ho Hospital, New Taipei City, Taiwan
| | - Yen-Chu Huang
- Department of Neurology, Chang Gung University College of Medicine, Chang Gung Memorial Hospital, Chiayi, Taiwan
| | - Hon-Man Liu
- Department of Medical Imaging, Fu Jen Catholic University Hospital, New Taipei City, Taiwan
| | - Sung-Chun Tang
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - I-Hui Lee
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Li-Ming Lien
- Department of Neurology, Shin Kong WHS Memorial Hospital, Taipei, Taiwan
| | - Hung-Yi Chiou
- School of Public Health, College of Public Health, Taipei Medical University, Taipei, Taiwan
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli County, Taiwan
| | - Jiunn-Tay Lee
- Department of Neurology, Tri Service General Hospital, National Defense Medical Center, Taipei, Taiwan
- Institute of Population Health Sciences, National Health Research Institutes, Miaoli County, Taiwan
| | - Jiann-Shing Jeng
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
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Sadiq E, von Klemperer A, Woodiwiss A, Norton G, Modi G. Stroke as the index presentation of traditional cardiovascular risk factors and Human Immunodeficiency Virus in a South African population. J Stroke Cerebrovasc Dis 2024; 33:107529. [PMID: 38103446 DOI: 10.1016/j.jstrokecerebrovasdis.2023.107529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Revised: 12/05/2023] [Accepted: 12/08/2023] [Indexed: 12/19/2023] Open
Abstract
OBJECTIVES We sought to identify what proportion of each cardiovascular risk factor and Human Immunodeficiency Virus (HIV) was first diagnosed at the time of stroke, compared to those that were diagnosed prior to the event, and to explore if this had any impact on the severity of stroke. METHODS Adult patients presenting with a new stroke to a quaternary hospital in Johannesburg between 2014 and 2017 were prospectively recruited. Patients were investigated for undiagnosed traditional cardiovascular risk factors (hypertension, diabetes mellitus, dyslipidaemia, atrial fibrillation, obesity and smoking), as well as HIV infection. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS). RESULTS 346 patients were included. Stroke was the index presentation for at least one risk factor in 199 (57.5 %) patients. Dyslipidaemia was newly diagnosed in 76.0 % of all dyslipidaemics (95 out of 125). Newly-diagnosed dyslipidaemia was associated with a more severe neurological deficit (Median NIHSS of 12 (8-16) vs 7 (4-12), p=0.0007) and younger age on presentation (53 (44-63) years vs 62 (51-71) years, p=0.02) as compared to previously-diagnosed dyslipidaemia. CONCLUSIONS More than half of patients had previously undiagnosed modifiable risk factors at the time of their stroke. Dyslipidaemia was undiagnosed in a very high proportion, and this was associated with a higher stroke severity and younger age of presentation.
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Affiliation(s)
- Eitzaz Sadiq
- Division of Neurology, Department of Neurosciences, School of Clinical Medicine and Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg 2193, South Africa.
| | - Alexander von Klemperer
- Division of Neurology, Department of Neurosciences, School of Clinical Medicine and Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg 2193, South Africa
| | - Angela Woodiwiss
- Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Gavin Norton
- Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
| | - Girish Modi
- Division of Neurology, Department of Neurosciences, School of Clinical Medicine and Cardiovascular Pathophysiology and Genomics Research Unit, School of Physiology, Faculty of Health Sciences, University of the Witwatersrand, 7 York Road, Parktown, Johannesburg 2193, South Africa
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Kim J, Kim JY, Kang J, Kim BJ, Han MK, Lee JY, Park TH, Lee KJ, Kim JT, Choi KH, Park JM, Kang K, Lee SJ, Kim JG, Cha JK, Kim DH, Lee K, Lee J, Hong KS, Cho YJ, Park HK, Lee BC, Yu KH, Oh MS, Kim DE, Ryu WS, Choi JC, Kwon JH, Kim WJ, Shin DI, Yum KS, Sohn SI, Hong JH, Lee SH, Lee JS, Lee J, Gorelick PB, Bae HJ. Improvement in Delivery of Ischemic Stroke Treatments but Stagnation of Clinical Outcomes in Young Adults in South Korea. Stroke 2023; 54:3002-3011. [PMID: 37942640 DOI: 10.1161/strokeaha.123.044619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 10/12/2023] [Indexed: 11/10/2023]
Abstract
BACKGROUND There is limited information on the delivery of acute stroke therapies and secondary preventive measures and clinical outcomes over time in young adults with acute ischemic stroke. This study investigated whether advances in these treatments improved outcomes in this population. METHODS Using a prospective multicenter stroke registry in Korea, young adults (aged 18-50 years) with acute ischemic stroke hospitalized between 2008 and 2019 were identified. The observation period was divided into 4 epochs: 2008 to 2010, 2011 to 2013, 2014 to 2016, and 2017 to 2019. Secular trends for patient characteristics, treatments, and outcomes were analyzed. RESULTS A total of 7050 eligible patients (mean age, 43.1; men, 71.9%) were registered. The mean age decreased from 43.6 to 42.9 years (Ptrend=0.01). Current smoking decreased, whereas obesity increased. Other risk factors remained unchanged. Intravenous thrombolysis and mechanical thrombectomy rates increased over time from 2008 to 2010 to 2017 to 2019 (9.5%-13.8% and 3.2%-9.2%, respectively; Ptrend<0.01). Door-to-needle time improved (Ptrend <.001), but onset-to-door and door-to-puncture times remained constant. Secondary prevention, including dual antiplatelets for noncardioembolic minor stroke (26.7%-47.0%), direct oral anticoagulants for atrial fibrillation (0.0%-56.2%), and statins for large artery atherosclerosis (76.1%-95.3%) increased (Ptrend<0.01). Outcome data were available from 2011. One-year mortality (2.5% in 2011-2013 and 2.3% in 2017-2019) and 3-month modified Rankin Scale scores 0 to 1 (68.3%-69.1%) and 0 to 2 (87.6%-86.2%) remained unchanged. The 1-year stroke recurrence rate increased (4.1%-5.5%; Ptrend=0.04), although the difference was not significant after adjusting for sex and age. CONCLUSIONS Improvements in the delivery of acute stroke treatments did not necessarily lead to better outcomes in young adults with acute ischemic stroke over the past decade, indicating a need for further progress.
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Affiliation(s)
- Jonguk Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Jun Yup Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Jihoon Kang
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Beom Joon Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Moon-Ku Han
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Jeong-Yoon Lee
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
| | - Tai Hwan Park
- Department of Neurology, Seoul Medical Center, Korea (T.H.P.)
| | - Keon-Joo Lee
- Korea University Guro Hospital, Seoul, Korea (K.-J.L.)
| | - Joon-Tae Kim
- Department of Neurology, Chonnam National University Hospital, Gwangju, Korea (J.-T.K., K.-H.C.)
| | - Kang-Ho Choi
- Department of Neurology, Chonnam National University Hospital, Gwangju, Korea (J.-T.K., K.-H.C.)
| | - Jong-Moo Park
- Department of Neurology, Uijeongbu Eulji Medical Center, Eulji University, Korea (J.-M.P.)
| | - Kyusik Kang
- Department of Neurology, Nowon Eulji Medical Center, Department of Neurology, Eulji University School of Medicine, Seoul, Korea (K.K.)
| | - Soo Joo Lee
- Eulji University Hospital, Daejeon, Korea (S.J.L., J.G.K.)
| | - Jae Guk Kim
- Eulji University Hospital, Daejeon, Korea (S.J.L., J.G.K.)
| | - Jae-Kwan Cha
- Department of Neurology, Dong-A University Hospital, Busan, Korea (J.-K.C., D.-H.K.)
| | - Dae-Hyun Kim
- Department of Neurology, Dong-A University Hospital, Busan, Korea (J.-K.C., D.-H.K.)
| | - Kyungbok Lee
- Department of Neurology, Soonchunhyang University Hospital, Seoul, Korea (K.L.)
| | - Jun Lee
- Department of Neurology, Yeungnam University Medical Center, Daegu, Korea (J.L.)
| | - Keun-Sik Hong
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea (K.-S.H., Y.-J.C., H.-K.P.)
| | - Yong-Jin Cho
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea (K.-S.H., Y.-J.C., H.-K.P.)
| | - Hong-Kyun Park
- Department of Neurology, Inje University Ilsan Paik Hospital, Goyang, Korea (K.-S.H., Y.-J.C., H.-K.P.)
| | - Byung-Chul Lee
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea (B.-C.L., K.-H.Y., M.-S.O.)
| | - Kyung-Ho Yu
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea (B.-C.L., K.-H.Y., M.-S.O.)
| | - Mi-Sun Oh
- Department of Neurology, Hallym University Sacred Heart Hospital, Anyang, Korea (B.-C.L., K.-H.Y., M.-S.O.)
| | - Dong-Eog Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea (D.-E.K., W.-S.R.)
| | - Wi-Sun Ryu
- Department of Neurology, Dongguk University Ilsan Hospital, Goyang, Korea (D.-E.K., W.-S.R.)
| | - Jay Chol Choi
- Department of Neurology, Jeju National University Hospital, Korea (J.C.C.)
| | - Jee-Hyun Kwon
- Department of Neurology, Ulsan University Hospital, Korea (J.-H.W., W.-J.K.)
| | - Wook-Joo Kim
- Department of Neurology, Ulsan University Hospital, Korea (J.-H.W., W.-J.K.)
| | - Dong-Ick Shin
- Department of Neurology, Chungbuk National University and Hospital, Cheongju, Korea (D.-I.S., K.S.Y.)
| | - Kyu Sun Yum
- Department of Neurology, Chungbuk National University and Hospital, Cheongju, Korea (D.-I.S., K.S.Y.)
| | - Sung Il Sohn
- Department of Neurology, Keimyung University Dongsan Hospital, Daegu, Korea (S.I.S., J.H.)
| | - Jeong-Ho Hong
- Department of Neurology, Keimyung University Dongsan Hospital, Daegu, Korea (S.I.S., J.H.)
| | - Sang-Hwa Lee
- Department of Neurology, Hallym University Chuncheon Sacred Heart Hospital, Chuncheon, Korea (S.-H.L.)
| | - Ji Sung Lee
- Clinical Research Center, Asan Medical Center, Seoul, Korea (J.S.L.)
| | - Juneyoung Lee
- Department of Biostatistics, Korea University, Seoul, Korea (J.L.)
| | - Philip B Gorelick
- Davee Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL (P.B.G)
| | - Hee-Joon Bae
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Korea (J. Kim , J.Y.K., J.K., B.J.K., M.-K.H., J.-Y.L., H.-J.B.)
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Bawand R, Ghiasian M, Khazaei M, Samadyan M, Moradi A. Effects of blood pressure unawareness and poor adherence to antihypertensive drugs on outcomes of cerebrovascular accidents among patients with their first-ever stroke. J Hypertens 2023; 41:459-469. [PMID: 36728239 DOI: 10.1097/hjh.0000000000003358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
AIMS Our main target was to investigate the relationship of blood pressure (BP) unawareness and poor antihypertensive drug adherence with the clinical outcomes of the stroke including hospitalization time, degree of disability, and mortality rate. METHODS AND RESULTS In this cross-sectional study, we evaluated 530 eligible patients (male = 313; female = 217), aged 18 years and older who had a proven diagnosis of nontraumatic first-ever stroke and were referred to the Shahid Beheshti Hospital of Hamadan, Iran, during the period from March 2019 to September 2021. The prevalence of BP unawareness was 19.6%, and 31.8% of antihypertensive drug users (14.3% of all studied population) had poor drug adherence, in which, older age, male gender, marriage, rural residence, and smoking were associated with the lack of appropriate drug adherence. There was no significant difference between patients with diverse stroke types (ischemic or hemorrhagic) from the points of BP awareness and adherence to antihypertensive drugs; nevertheless, patients with a positive history of cardiac diseases had a significantly higher awareness of their BP status ( P = 0.037). BP unawareness was associated with poor clinical prognosis, and could significantly increase stroke mortality ( P = 0.001) and disability ( P < 0.001) rates as well as the duration of hospitalization ( P < 0.001). Moreover, those who survived the stroke (modified Rankin Scale < 6) had the highest odds to be aware of their BP status (adjusted odds ratio [AOR] = 2.380 [95% confidence interval [CI] = 1.39-4.07]). Additionally, nonsmokers (AOR = 7.740), urban residents (AOR = 3.314), and literate patients (AOR = 2.092) had the highest odds of having appropriate drug adherence. CONCLUSION Stroke mortality and morbidity rates can be significantly modified by persuading people to monitor their BP regularly and maximize antihypertensive medication adherence. In the meantime, increasing the literacy level in society and reducing the smoking rate can play important roles in achieving these goals.
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Affiliation(s)
| | | | | | | | - Abbas Moradi
- Department of Social Medicine, School of Medicine, Hamadan University of Medical Sciences, Hamadan, Iran
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Hsieh MT, Hsieh CY, Tsai TT, Sung SF. Validation of Stroke Risk Factors in Patients with Acute Ischemic Stroke, Transient Ischemic Attack, or Intracerebral Hemorrhage on Taiwan’s National Health Insurance Claims Data. Clin Epidemiol 2022; 14:327-335. [PMID: 35330593 PMCID: PMC8938165 DOI: 10.2147/clep.s353435] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 03/08/2022] [Indexed: 11/24/2022] Open
Abstract
Purpose Taiwan has changed the coding system to the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) coding since 2016. This study aimed to determine the optimal algorithms for identifying stroke risk factors in Taiwan’s National Health Insurance (NHI) claims data. Patients and Methods We retrospectively enrolled 4538 patients hospitalized for acute ischemic stroke (AIS), transient ischemic attack (TIA), or intracerebral hemorrhage (ICH) from two hospitals’ stroke registries, which were linked to NHI claims data. We developed several algorithms based on ICD-10-CM diagnosis codes and prescription claims data to identify hypertension, diabetes, hyperlipidemia, atrial fibrillation (AF), and ischemic heart disease (IHD) using registry data as the reference standard. The agreement of risk factor status between claims and registry data was quantified by calculating the kappa statistic. Results According to the registry data, the prevalence of hypertension, diabetes, hyperlipidemia, AF, and IHD among all patients was 77.5%, 41.5%, 47.9%, 12.1%, and 7.1%, respectively. In general, including diagnosis codes from prior inpatient or outpatient claims to those from the stroke hospitalization claims improved the agreement. Incorporating prescription data could improve the agreement for hypertension, diabetes, hyperlipidemia, and AF, but not for IHD. The kappa values of the optimal algorithms were 0.552 (95% confidence interval 0.524–0.580) for hypertension, 0.802 (0.784–0.820) for diabetes, 0.514 (0.490–0.539) for hyperlipidemia, 0.765 (0.734–0.795) for AF, and 0.518 (0.473–0.564) for IHD. Conclusion Algorithms using diagnosis codes alone are sufficient to identify hypertension, AF, and IHD whereas algorithms combining both diagnosis codes and prescription data are more suitable for identifying diabetes and hyperlipidemia. The study results may provide a reference for future studies using Taiwan’s NHI claims data.
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Affiliation(s)
- Meng-Tsang Hsieh
- Stroke Center and Department of Neurology, E-Da Hospital, Kaohsiung, Taiwan
- School of Medicine, College of Medicine, I-Shou University, Kaohsiung, Taiwan
- Institute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Cheng-Yang Hsieh
- Department of Neurology, Tainan Sin Lau Hospital, Tainan, Taiwan
- School of Pharmacy, Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Tzu-Tung Tsai
- Stroke Center and Department of Neurology, E-Da Hospital, Kaohsiung, Taiwan
| | - Sheng-Feng Sung
- Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chiayi City, Taiwan
- Department of Nursing, Min-Hwei Junior College of Health Care Management, Tainan, Taiwan
- Correspondence: Sheng-Feng Sung, Division of Neurology, Department of Internal Medicine, Ditmanson Medical Foundation Chia-Yi Christian Hospital, 539 Zhongxiao Road, East District, Chiayi City, 60002, Taiwan, Tel +886 5 276 5041 ext 7283, Fax +886 5 278 4257, Email
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Sieben A, A.W. van Onzenoort H, J.H.M. van Laarhoven K, Bredie SJ, van Dulmen S. Identification of Cardiovascular Patient Groups at Risk for Poor Medication Adherence: A Cluster Analysis. J Cardiovasc Nurs 2021; 36:489-497. [PMID: 32501862 PMCID: PMC8366598 DOI: 10.1097/jcn.0000000000000702] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
BACKGROUND Poor medication adherence limits the secondary prevention of cardiovascular diseases (CVDs) and leads to increased morbidity, mortality, and costs. Identifying groups of patients at risk of poor adherence behavior could enable an intervention to be developed and target patients appropriately. OBJECTIVE The first aim of this study was to identify homogeneous subgroups of cardiovascular outpatients based on their cardiovascular risk factors. Subsequently, differences in medication adherence between these groups were examined. METHODS In this retrospective, observational study, patients with an established CVD were included. Well-known cardiovascular risk factors such as smoking, diet, exercise, blood lipid levels, blood pressure, and body mass index were collected. To identify patient subgroups, a 2-step cluster analytic procedure was performed. Differences between the groups on medication adherence were determined on the outcome of the Modified Morisky Scale. Data collection took place between October 2011 and January 2013. RESULTS Cardiovascular risk factors of 530 patients were included in the cluster analysis. Three groups were identified. Compared with other clusters (clusters 1 and 2), cluster 3 contained significantly fewer patients who could be classified as highly adherent and more patients classified as medium adherent (23% and 57%, respectively; P = .024). This group was characterized by a younger age (53% were <55 years old) and using a relatively low number of different medications (41% used <4 different medications). Besides, in this subgroup the most smokers (37%), unhealthy alcohol users (27%), and patients with unhealthy eating habits (14%) were present. CONCLUSION This study showed that cardiovascular patients who are relatively young and have an unhealthy lifestyle are at risk for nonadherent behavior.
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Chatziefstratiou A, Giakoumidakis K, Fotos NV, Baltopoulos G, Brokalaki H. Scales for assessing medication adherence in patients with hypertension. ACTA ACUST UNITED AC 2019; 28:1388-1392. [PMID: 31778338 DOI: 10.12968/bjon.2019.28.21.1388] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
BACKGROUND the choice of the appropriate tool for assessing level of medication adherence is a significant barrier in scientific research. AIMS to translate into Greek and test the reliability of the Hill-Bone and A-14 scales among patients with hypertension. Also, to compare patients' responses in the Hill-Bone scale, A-14 scale and Morisky Medication Adherence Scale (MMAS). METHODS data collection occurred between February 2016 and March 2016 at a general hospital in Athens, Greece. The sample consisted of hypertensive patients (n=34) and non-hypertensive patients (n=34). FINDINGS the coefficient alpha in hypertensive patients was 0.76 for Hill-Bone, 0.64 for MMAS and 0.91 for the A-14 scale. In non-hypertensive patients, the Cronbach's alpha for MMAS was 0.81 and 0.78 for A-14. A statistically significant difference was found among the mean scores of the scales, whereas strong correlation was found only between two pairs of questions with similar meaning. CONCLUSION all tools are appropriate to assess the level of medication adherence in Greek hypertensive patients. However, careful translation of the scales is essential since items with the same meaning could be understudied in a different way.
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Affiliation(s)
| | - Konstantinos Giakoumidakis
- Associate Professor, Department of Nursing, School of Health Sciences and Welfare, University of West Attica, Greece
| | - Nikolaos V Fotos
- Assistant Professor, Faculty of Nursing, National and Kapodistrian University of Athens, Athens, Greece
| | - George Baltopoulos
- Emeritus Professor, Faculty of Nursing, National and Kapodistrian University of Athens, Athens, Greece
| | - Hero Brokalaki
- Emeritus Professor, Faculty of Nursing, National and Kapodistrian University of Athens, Athens, Greece
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