Treatment of hypertension can modify the lipid profile and atherosclerosis induced by hyperlipidemia. MIn order to adequately address the treatment of hypertensive patients with dyslipidemia, we have to remember the importance of these two pathologies as risk factors for coronary heart disease. In addition to proven the two main factors [1], Systemic Arterial Hypertension and Dyslipidemia act synergistically, increasing cardiovascular risk [2]. Epidemiological studies [] have shown that the risk of cardiovascular mortality increases with cholesterol levels - in a year-old man, the risk is 0.
A frequent association of hypertriglyceridemia and hypoalphalipoproteinemia is also reported as elements of plurimetabolic syndrome described by Reaven, known as X Syndrome.
Another relevant data in the recognition of these patients is the presence of metabolic alterations of glucose intolerance and lipid alterations resulting from the treatment of hypertension, reflecting possible adverse effects of hypotensor agents [7,8] on insulin sensitivity; obesity and sedentary lifestyle, factors that can be modified, contribute to a condition conducive to atherogenesis.
As previously reported, lipid and glucose intolerance alterations are more common in treated hypertensive patients, possibly reflecting the adverse effects of hypotensive agents [9,10] on insulin sensitivity. The possible cause of this condition are diuretics and beta-blockers. Thiazides are those who have proven to perform a negative action in the lipid profile; act by increasing the action of lipoprotein lipase, which hydrolyzes triglycerides and VLDL-c lipoproteins, increasing the production of LDL-c and TC.
These changes are discrete and may return to normal with suspension of treatment. Act by inhibiting the activity of adenyl cyclase in fatty cells, reducing hydrolysis of fatty acids and triglycerides; TC elevation LDL-c and VLDL-c and triglycerides [12].
Calcium antagonists and angiotensin-converting enzyme inhibitors are the ones that best fit as a treatment option for dyslipemic hypertensive patients [8,14,15] Table 1. Hyperlipidemia Associations with Hypertension Medications. Dyslipidemia, Hypertension, Risk factors, Cardiovascular disease, Prevention, Atherosclerosis, Hypertriglyceridemia, Renal disease, Lipoprotein cholesterol, Blood pressure. Contact us at: cardio irispublishers.
Abstract Simultaneity of hypertension and hyperlipidemia as added risk factors for renal and cardiovascular disease cannot be approached without considering concomitant effect of some antihypertensive agents causing secondary hypercholesterolemia or hypertriglyceridemia.
Introduction MIn order to adequately address the treatment of hypertensive patients with dyslipidemia, we have to remember the importance of these two pathologies as risk factors for coronary heart disease.
Effects of Antihypertensive Medicines As previously reported, lipid and glucose intolerance alterations are more common in treated hypertensive patients, possibly reflecting the adverse effects of hypotensive agents [9,10] on insulin sensitivity.
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Show references Bloch M, et al. Antihypertensive drugs and lipids. Accessed March 6, Akhtar F, et al. The effect of thiazide diuretics on blood lipid profile in hypertensive adults: A meta-analysis of randomized controlled trials. Bonow RO, et al. Systemic hypertension: Management. Saunders Elsevier; Marketou M, et al. Differential metabolic effects of beta-blockers: An updated systematic review of nebivolol.
Current Hypertension Reports. Almeman AA, et al. Comparison of the effects of metoprolol and bisoprolol on lipid and glucose profiles in cardiovascular patients. Current Drug Safety. See also Medication-free hypertension control 6 surprising signs you may have obstructive sleep apnea After a flood, are food and medicines safe to use? Alcohol: Does it affect blood pressure? Beta blockers: How do they affect exercise? Blood pressure chart Blood pressure cuff: Does size matter?
A measure of variance, confidence interval, or P-value was provided. The age of study participants was equal to or greater than 18 years. There were no differences between comparison groups other than the specified intervention allocation. An intention to treat analysis ITT was performed. Studies were retrieved by systematically searching the PubMed and Embase databases. PubMed was selected because it is an open-source database for clinical trials. Embase was selected because it is a biomedical and pharmacological database of published literature designed to support information managers and pharmacovigilance in complying with the regulatory requirements of a licensed drug.
We searched Web of Science and ClinicalTrials. A manual search of references from articles that met eligibility criteria was performed in addition to a manual review of relevant review articles, systematic reviews, and meta-analyses. Study authors were not contacted to identify additional studies. For our literature search, study selection, data abstraction, calculation of summary measures, and synthesis of results, we used a standardized written protocol; whereas for reporting results, we used the preferred reporting items for systematic reviews and meta-analyses PRISMA statement checklist and flow diagram.
In addition to the aforementioned terms, synonyms and similar terms to the above were also added to the Embase search. More detailed information on our search strategy is outlined in Appendix A. All searches were filtered by RCTs and human subjects.
Two teams, each comprised of two investigators, independently reviewed articles generated by the literature search using the MeSH and keyword terms previously specified. Articles were evaluated using the inclusion criteria previously mentioned. The title and abstract of all identified articles were reviewed, and those articles deemed ineligible were excluded.
Articles that met these inclusion criteria based on the initial title and abstract review were retrieved and reviewed in depth to determine further eligibility by these independent teams.
For articles selected for review by both teams, the selection results were compared to ensure that all relevant articles were retrieved. A third investigator adjudicated any discrepancies between the two reviews. For the results of studies that were published more than once, only those with the most complete and up-to-date information were included in the analysis. All data were gathered using a standardized collection form. Initially, a pilot data extraction form was used; discrepancies in recorded data were discussed with all group members.
As there were five members in the initial group, two sub-groups were formed for data extraction. Data were independently extracted by two researchers from each sub-group. The results from the sub-group data collection were compared. Discrepancies in the results between the two members in each sub-group were discussed to reach consensus.
The characteristics of the trial and its participants were collected in the standardized data collection form. Items collected included: information for the cited trial e. The relationship between thiazide diuretics and serum lipid level was examined by calculating the net mean change in lipid profile parameters. For crossover trials, the net change in means was calculated by finding the mean difference in values between the end of the diuretic trial; T and non-diuretic control; C therapy periods: XT-XC.
When the average percentage of the change in lipid profile was reported by studies, the mean difference was calculated from the baseline lipid profile. The results of each trial were separately weighted by the inverse of the variance of change in each of lipid profile markers. If the variance for the net effect size was not reported, the variance was calculated from confidence intervals, P values, or test statistics. In parallel trials, when measures of variances were provided for control and comparison groups separately, they were pooled using the sample size within each group.
For crossover studies, the variance was imputed using the paired analysis equation, assuming a correlation coefficient of 0. The effect estimate was then pooled by using both fixed effects and the Dersimonian and Laird random-effects models. The heterogeneity of effect size across studies was assessed by Q statistic and I2 index. Heterogeneity was explored further with an influence analysis, a sensitivity analysis, and a subgroup analysis. A sensitivity analysis was performed to assess the robustness of our findings.
As part of the sensitivity analysis, we conducted a quality assessment of all studies included based on the Cochrane Handbook RevMan 5. Each trial was sequentially removed to determine the magnitude of its effect on the overall pooled estimate i. Each item was judged based on the review of the full text and was labeled as either low risk green circle , high risk red circle , or unclear risk yellow circle.
For example, studies that used a computer to generate random trial assignments or those studies that specifically mentioned using a collaboration center to uniformly randomize the patients were labeled as low risk for randomization of the study.
For blinding, if the study mentioned blinding as either double or triple blinding, we labeled this as low risk if there was no obvious loophole to circumvent the blinding in the methods or if the article did not report an error in the blinding.
For incomplete reports, we compared the patient number at baseline to that at the outcome to determine how many were lost to follow-up, drop-out, etc. Graphs were made to show the assessment of individual studies and the pooled quality assessment of our entire analysis, respectively. The potential for publication bias was examined by a visual inspection of a funnel plot in which standard errors were plotted against the effect size for each study.
The Egger regression asymmetry test was used to test the asymmetry of the funnel plot. In addition, the Begg rank correlation test was employed to examine the association between effect estimates and their variances. In the initial phase of the selection process, searches of Embase and PubMed were performed for relevant articles that fulfill our inclusion criteria by using the previously mentioned combination of different search and MeSH terms. A total of articles were selected for reviews from these databases.
Duplicates were identified by using the RefWorks manager; 72 articles were found. Articles were selected or excluded on the basis of predefined inclusion criteria. Any disparity between team members was discussed and a consensus was made before finalizing the articles selected. In total, articles were excluded by the two groups, and 70 articles were selected for a full-text review. Of the 70 articles, the full text was available for review for 26 while for 44 articles, the full text was not available for review.
After a review of the 26 available articles, 21 articles were excluded for various reasons: on the basis of outcome seven , non-randomized assignment three , differences between the comparison of the intervention and the control group was not solely the treatment 10 , and an additional article was found to be a duplicate one. We selected five blinded RCT studies that show the effect of diuretics on lipid profiles. Carlsen J et al. McVeigh G et al. Weidmann P et al. Peng J et al. A study by McLaughlin D et al.
There were 45 participants in McVeigh G et al. In the intervention group, the TC was 5. In the control group, the TC was 5. There were participants in Carlsen J et al. The mean age was 57 years in the intervention group, The mean age was 57 years in the control group, 23 There were participants in Weidmann P et al. There were 15 participants in the McLaughlin D et al. The mean age was 53 years with an SD of two. There were participants in Peng J et al.
The mean age was The mean age in the control group was
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