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      Non-adherence to anti-hypertensive medications in a low-resource country Nepal: a systematic review and meta-analysis

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          Abstract

          Background:

          Nepal is a low resource country with cardiovascular diseases being the number one cause of mortality. Despite hypertension being the single most important risk factor for cardiovascular diseases, non-adherence to anti-hypertensive medications has not been assessed systematically. So, this systematic review and meta-analysis aims to analyze the prevalence of non-adherence to anti-hypertensive medications in Nepal.

          Methodology:

          This systematic review and meta-analysis was piloted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. Electronic databases of Embase, PubMed, Scopus, Web of Science, Cochrane Library, Cinhal Plus, and Google Scholar were searched from inception till 1 February 2023. The random-effects model with 95% confidence interval (CI) was used to calculate the non-adherence rate.

          Results:

          Altogether, 14 studies with a total of 3276 hypertensive patients were included in the meta-analysis. The pooled prevalence of non-adherence to anti-hypertensive medications was 49% (95% CI: 0.37–0.62, I 2=98.41%, P<0.001). The non-adherence rate using Morisky Medication Adherence Scale (MMAS) was 55% (95% CI: 0.34–0.76, I 2=99.14%, P<0.001), and using Hill–Bone Compliance Scale, the non-adherence rate was 45% (95% CI: 0.37–0.54, I 2=84.36%, P<0.001). In subgroup analysis, the non-adherence was higher in rural areas 56% (95% CI: 0.51–0.61, I 2=0.0%, P=0.46) compared to urban areas 42% (95% CI: 0.31–0.54, I 2=96.90%, P<0.001). The trend of non-adherence was increasing after 2020. Additionally, forgetfulness, carelessness, cost of medications, number of comorbidities, and using an alternate form of medication were common factors associated with non-adherence.

          Conclusions:

          This meta-analysis showed that half of the hypertensive population of Nepal are non-adherent to their anti-hypertensive medications, thereby posing a significant long-term cardiovascular consequence among Nepali population.

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          Most cited references35

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          Quantifying heterogeneity in a meta-analysis.

          The extent of heterogeneity in a meta-analysis partly determines the difficulty in drawing overall conclusions. This extent may be measured by estimating a between-study variance, but interpretation is then specific to a particular treatment effect metric. A test for the existence of heterogeneity exists, but depends on the number of studies in the meta-analysis. We develop measures of the impact of heterogeneity on a meta-analysis, from mathematical criteria, that are independent of the number of studies and the treatment effect metric. We derive and propose three suitable statistics: H is the square root of the chi2 heterogeneity statistic divided by its degrees of freedom; R is the ratio of the standard error of the underlying mean from a random effects meta-analysis to the standard error of a fixed effect meta-analytic estimate, and I2 is a transformation of (H) that describes the proportion of total variation in study estimates that is due to heterogeneity. We discuss interpretation, interval estimates and other properties of these measures and examine them in five example data sets showing different amounts of heterogeneity. We conclude that H and I2, which can usually be calculated for published meta-analyses, are particularly useful summaries of the impact of heterogeneity. One or both should be presented in published meta-analyses in preference to the test for heterogeneity. Copyright 2002 John Wiley & Sons, Ltd.
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            Meta-analysis in clinical trials

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              AMSTAR 2: a critical appraisal tool for systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both

              The number of published systematic reviews of studies of healthcare interventions has increased rapidly and these are used extensively for clinical and policy decisions. Systematic reviews are subject to a range of biases and increasingly include non-randomised studies of interventions. It is important that users can distinguish high quality reviews. Many instruments have been designed to evaluate different aspects of reviews, but there are few comprehensive critical appraisal instruments. AMSTAR was developed to evaluate systematic reviews of randomised trials. In this paper, we report on the updating of AMSTAR and its adaptation to enable more detailed assessment of systematic reviews that include randomised or non-randomised studies of healthcare interventions, or both. With moves to base more decisions on real world observational evidence we believe that AMSTAR 2 will assist decision makers in the identification of high quality systematic reviews, including those based on non-randomised studies of healthcare interventions.
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                Author and article information

                Contributors
                Journal
                Ann Med Surg (Lond)
                Ann Med Surg (Lond)
                MS9
                Annals of Medicine and Surgery
                Lippincott Williams & Wilkins (Hagerstown, MD )
                2049-0801
                September 2023
                19 July 2023
                : 85
                : 9
                : 4520-4530
                Affiliations
                [a ]Maharajgunj Medical Campus, Institute of Medicine, Tribhuvan University
                [b ]Shree Birendra Hospital, Chhauni, Kathmandu
                [c ]KIST Medical College and Teaching Hospital, Lalitpur, Nepal
                [d ]M Abdur Rahim Medical College, Dinajpur, Bangladesh
                Author notes
                [* ]Corresponding author. Address: Maharajgunj Medical Campus, Institute of Medicine, Tribhuvan University, P. O. Box 1524, Kathmandu, Nepal. Tel.: +977 986 159 6266. E-mail: pashupatipokharel@ 123456iom.edu.np (P. Pokharel).
                Article
                AMSU-D-23-00814 00047
                10.1097/MS9.0000000000001088
                10473346
                37663734
                65fc9381-7e08-411d-9580-d318f6fe1260
                Copyright © 2023 The Author(s). Published by Wolters Kluwer Health, Inc.

                This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. http://creativecommons.org/licenses/by/4.0/

                History
                : 8 April 2023
                : 9 July 2023
                Categories
                Review Articles
                Custom metadata
                TRUE
                T

                cardiovascular consequences,hill-bone compliance scale,hypertension,low-resource setting,morisky medication adherence scale,nepal,non-adherence

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