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Kengne AP, Brière JB, Gudiña IA, Jiang X, Kodjamanova P, Bennetts L, Khan ZM. The impact of non-pharmacological interventions on adherence to medication and persistence in dyslipidaemia and hypertension: a systematic review. Expert Rev Pharmacoecon Outcomes Res 2024; 24:807-816. [PMID: 38366854 DOI: 10.1080/14737167.2024.2319598] [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: 07/19/2023] [Accepted: 02/13/2024] [Indexed: 02/18/2024]
Abstract
INTRODUCTION Suboptimal medication adherence is common among patients with cardiovascular diseases. We sought evidence on non-pharmacological interventions used to support adherence for patients with hypertension and/or dyslipidemia. METHODS We searched MEDLINE, EMBASE, MEDLINE In-Process, ClinicalTrials.gov, EUCTR, and conference proceedings from July 2011 to July 2021 to identify trials evaluating effects of health education, phone reminders, or digital interventions on medication adherence or persistence of adult patients with hypertension and/or dyslipidemia. Risk of bias was assessed using the Cochrane Risk of Bias Assessment Tool v2. RESULTS Of 64 studies, 62 used health education approaches (e.g. educational interviews, motivational meetings, advice from physicians, and mobile health content), 16 phone reminders (e.g. text reminders, electronic pill-box linked reminders, bi-directional text messaging), and 10 digital applications as interventions (e.g., various self-management applications). All studies assessed medication adherence; only two persistence. Overall, 30 studies (83%) assessing health education approaches alone and 25 (78%) combined with other strategies, 12 (75%) phone reminders and eight studies (80%) digital applications combined with other strategies reported improved medication adherence. Two studies assessing health education approaches reported improved persistence. CONCLUSIONS Our findings indicate non-pharmacological interventions may positively impact adherence. Therefore, 'beyond the pill' approaches could play a role in preventing cardiovascular diseases.
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Affiliation(s)
| | | | | | - Xiaobin Jiang
- Health Economics and Market Access, Amaris Consulting, Shanghai, China
| | - Petya Kodjamanova
- Health Economics and Market Access, Amaris Consulting, Sofia, Bulgaria
| | - Liga Bennetts
- Health Economics and Market Access, Amaris Consulting, Montréal, Canada
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Ismail FF, Md Redzuan A, Wen CW. Patient-centered education in dyslipidemia management: a systematic review. ASIAN BIOMED 2022; 16:214-236. [PMID: 37551316 PMCID: PMC10321189 DOI: 10.2478/abm-2022-0026] [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] [Indexed: 08/09/2023]
Abstract
Background Dyslipidemia management is crucial to reduce mortality and morbidity from cardiovascular diseases (CVDs). Patients must be educated and empowered to enable them to manage their own diseases. Various methods of patient education, such as patient-centered education (PCE) or non-PCE (such as didactic education or any traditional form of education), have been implemented. Objective To review and determine the effectiveness of PCE for dyslipidemia management compared with usual care. The primary outcome chosen was cholesterol level. Other measures, such as psychosocial or cognitive, behavioral, and other relevant outcomes, were also extracted. Additionally, underlying theories and other contributing factors that may have led to the success of the intervention were also reviewed and discussed. Methods We conducted searches in PubMed, Cumulative Index to Nursing and Allied Health Literature (CINAHL), Scopus, and Google Scholar from inception until April 2021. All studies involving randomized controlled trials were included. Study quality was assessed using the Critical Appraisal Skills Program (CASP) checklist specifically for randomized controlled trials. Results The search identified 8,847 records. Of these, 20 studies were eligible for inclusion. Interventions using a PCE approach were largely successful. Contributing factors extracted from the included studies were underlying theories, instant reward system, dietary education, collaborative care, duration of intervention with systematic follow-ups, social support, adherence assessment method, and usage of e-health. Conclusions PCE is successful in achieving the desired outcomes in dyslipidemia management. Future studies may incorporate the elements of PCE to improve the management of dyslipidemia in hospital or community settings where appropriate.
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Affiliation(s)
- Farhana Fakhira Ismail
- Centre for Quality Management of Medicine, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur50300, Malaysia
- Department of Pharmacy Practice, Faculty of Pharmacy, Universiti Teknologi MARA, Puncak Alam, Selangor42300, Malaysia
| | - Adyani Md Redzuan
- Centre for Quality Management of Medicine, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur50300, Malaysia
| | - Chong Wei Wen
- Centre for Quality Management of Medicine, Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur50300, Malaysia
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Fagherazzi G, Zhang L, Aguayo G, Pastore J, Goetzinger C, Fischer A, Malisoux L, Samouda H, Bohn T, Ruiz-Castell M, Huiart L. Towards precision cardiometabolic prevention: results from a machine learning, semi-supervised clustering approach in the nationwide population-based ORISCAV-LUX 2 study. Sci Rep 2021; 11:16056. [PMID: 34362963 PMCID: PMC8346462 DOI: 10.1038/s41598-021-95487-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Accepted: 07/27/2021] [Indexed: 11/09/2022] Open
Abstract
Given the rapid increase in the incidence of cardiometabolic conditions, there is an urgent need for better approaches to prevent as many cases as possible and move from a one-size-fits-all approach to a precision cardiometabolic prevention strategy in the general population. We used data from ORISCAV-LUX 2, a nationwide, cross-sectional, population-based study. On the 1356 participants, we used a machine learning semi-supervised cluster method guided by body mass index (BMI) and glycated hemoglobin (HbA1c), and a set of 29 cardiometabolic variables, to identify subgroups of interest for cardiometabolic health. Cluster stability was assessed with the Jaccard similarity index. We have observed 4 clusters with a very high stability (ranging between 92 and 100%). Based on distinctive features that deviate from the overall population distribution, we have labeled Cluster 1 (N = 729, 53.76%) as "Healthy", Cluster 2 (N = 508, 37.46%) as "Family history-Overweight-High Cholesterol ", Cluster 3 (N = 91, 6.71%) as "Severe Obesity-Prediabetes-Inflammation" and Cluster 4 (N = 28, 2.06%) as "Diabetes-Hypertension-Poor CV Health". Our work provides an in-depth characterization and thus, a better understanding of cardiometabolic health in the general population. Our data suggest that such a clustering approach could now be used to define more targeted and tailored strategies for the prevention of cardiometabolic diseases at a population level. This study provides a first step towards precision cardiometabolic prevention and should be externally validated in other contexts.
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Affiliation(s)
- Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg. .,Center of Epidemiology and Population Health UMR 1018, Inserm, Gustave Roussy Institute, Paris South - Paris Saclay University, Villejuif, France.
| | - Lu Zhang
- Quantitative Biology Unit, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Gloria Aguayo
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Jessica Pastore
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Catherine Goetzinger
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.,University of Luxembourg, 2, avenue de l'Université, 4365, Esch-sur-Alzette, Luxembourg
| | - Aurélie Fischer
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Laurent Malisoux
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Hanen Samouda
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Torsten Bohn
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Maria Ruiz-Castell
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg
| | - Laetitia Huiart
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, 1A-B, rue Thomas Edison, 1445, Strassen, Luxembourg.,University of Luxembourg, 2, avenue de l'Université, 4365, Esch-sur-Alzette, Luxembourg
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Ni J, Hong H, Zhang Y, Tang S, Han Y, Fang Z, Zhang Y, Zhou N, Wang Q, Liu Y, Li Z, Wang Y, Dong M. Development of a non-invasive method for skin cholesterol detection: pre-clinical assessment in atherosclerosis screening. Biomed Eng Online 2021; 20:52. [PMID: 34074299 PMCID: PMC8170999 DOI: 10.1186/s12938-021-00889-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Accepted: 05/18/2021] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Establishing a high-accuracy and non-invasive method is essential for evaluating cardiovascular disease. Skin cholesterol is a novel marker for assessing the risk of atherosclerosis and can be used as an independent risk factor of early assessment of atherosclerotic risk. METHODS We propose a non-invasive skin cholesterol detection method based on absorption spectroscopy. Detection reagents specifically bind to skin cholesterol and react with indicator to produce colored products, the skin cholesterol content can be obtained through absorption spectrum information on colored products detected by non-invasive technology. Gas chromatography is used to measure cholesterol extracted from the skin to verify the accuracy and reliability of the non-invasive test method. A total of 342 subjects were divided into normal group (n = 115), disease group (n = 110) and risk group (n = 117). All subjects underwent non-invasive skin cholesterol test. The diagnostic accuracy of the measured value was analyzed by receiver-operating characteristic (ROC) curve. RESULTS The proposed method is able to identify porcine skin containing gradient concentration of cholesterol. The values measured by non-invasive detection method were significantly correlated with gas chromatography measured results (r = 0.9074, n = 73, p < 0.001). Bland-Altman bias was - 72.78 ± 20.03 with 95% limits of agreement - 112.05 to - 33.51, falling within the prespecified clinically non-significant range. We further evaluated the method of patients with atherosclerosis and risk population as well as normal group, patients and risk atherosclerosis group exhibited higher skin cholesterol content than normal group (all P < 0.001). The area under the ROC curve for distinguishing Normal/Disease group was 0.8642 (95% confidence interval, 0.8138 to 0.9146), meanwhile, the area under the ROC curve for distinguishing Normal/Risk group was 0.8534 (95% confidence interval, 0.8034 to 0.9034). CONCLUSIONS The method demonstrated its capability of detecting different concentration of skin cholesterol. This non-invasive skin cholesterol detection system may potentially be used as a risk assessment tool for atherosclerosis screening, especially for a large population.
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Affiliation(s)
- Jingshu Ni
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- University of Science and Technology of China, Hefei, 230026, China
| | - Haiou Hong
- Health Management Center, First Affiliated Hospital of University of Science and Technology of China, Hefei, China
| | - Yang Zhang
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- University of Science and Technology of China, Hefei, 230026, China
| | - Shiqi Tang
- Health Management Center, Renmin Hospital of WuHan University, Wuhan, 430060, China
| | - Yongsheng Han
- Department of Cardiovascular Medicine, First Affiliated Hospital of University of Science and Technology of China, Hefei, 230001, China
| | - Zhaohui Fang
- Department of Endocrinology, The First Affiliated Hospital of Anhui University of Traditional Chinese Medicine, Hefei, 230031, China
| | - Yuanzhi Zhang
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- Wanjiang Center for Development of Emerging Industrial Technology, Tongling, 244000, China
| | - Nan Zhou
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- Wanjiang Center for Development of Emerging Industrial Technology, Tongling, 244000, China
| | - Quanfu Wang
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- Wanjiang Center for Development of Emerging Industrial Technology, Tongling, 244000, China
| | - Yong Liu
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
- University of Science and Technology of China, Hefei, 230026, China
- Wanjiang Center for Development of Emerging Industrial Technology, Tongling, 244000, China
| | - Zhongsheng Li
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China
| | - YiKun Wang
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China.
- University of Science and Technology of China, Hefei, 230026, China.
| | - Meili Dong
- Anhui Provincial Engineering Technology Research Center for Biomedical Optical Instrument, Anhui Institute of Optics and Fine Mechanics, Hefei Institutes of Physical Science , Chinese Academy of Sciences, Hefei, 230031, China.
- University of Science and Technology of China, Hefei, 230026, China.
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Effectiveness of an Intervention Aimed at Improving Information for Patients with High Cardiovascular Risk: INFORISK Clinical Trial. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18073621. [PMID: 33807285 PMCID: PMC8036291 DOI: 10.3390/ijerph18073621] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 03/22/2021] [Accepted: 03/25/2021] [Indexed: 12/02/2022]
Abstract
Background: The concept of global cardiovascular risk is not usually well understood by patients in consultation. Methods: This was a multicenter, prospective, randomized, open clinical trial of one-year duration to evaluate the effectiveness in reducing global cardiovascular risk with an intervention aimed at high-risk patients to improve information on the cardiovascular risk compared to the usual care. The intervention was focused on providing information about cardiovascular risk in a more understandable way, explaining the best practices to reduce cardiovascular risk, and tailoring information to the individual. Results: Four-hundred and sixty-four subjects participated in the study; 59.3% were men, and the mean age was 61.0 (SD 8.0) years. Significant reductions in systolic blood pressure (SBP) (−3.12 mmHg), body mass index (BMI) (−0.34 kg/m2), abdominal circumference (−1.24 cm), and REGICOR cardiovascular risk (−0.63) were observed in the intervention group. Overall, no differences in cardiovascular risk score were observed between groups at the end of follow-up. Conclusions: Providing an easy-to-understand assessment of the cardiovascular risk motivated high-risk patients to adopt a healthier lifestyle and improved cardiovascular risk after one year in the intervention group. Clinicians should assess a patient’s baseline understanding of their CV risk using tools other than absolute risk before making treatment recommendations.
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