Abstract
There is no study to compare different class of antihypertensive drugs on new‐onset diabetes mellitus (NOD) in elderly. We aimed to investigate the risk of antihypertensive drugs on NOD in elderly patients. The databases were retrieved in an orderly manner from the dates of their establishment to October, 2018, including Medline, Embase, Clinical Trials, and the Cochrane Database, to collect randomized controlled trials (RCTs) of different antihypertensive drugs in elderly patients (age > 60 years). Then, a network meta‐analysis was conducted using R and Stata 12.0 softwares. A total of 14 RCTs involving 74 042 patients were included. The relative risk of NOD mellitus associated with six classes of antihypertensive drugs was analyzed, including placebo, angiotensin‐converting enzyme inhibitors (ACEIs), angiotensin II receptor blockers (ARBs), calcium channel blockers (CCBs), diuretics, and β blockers. Patients with ACEIs or ARBs appeared to have significantly reduced risk of NOD compare with placebo: ACEIs (OR = 0.49, 95% CrI 0.28‐0.85), ARBs (OR = 0.37, 95% CrI 0.26‐0.52), while CCBs, diuretics, and β blockers appeared to have not significantly reduced risk of NOD mellitus compare with placebo: CCBs (OR = 1.10, 95% CrI 0.85‐1.60), diuretics (OR = 1.40, 95% CrI 0.92‐2.50), β blockers (OR = 1.40, 95% CrI 0.93‐2.10). The SUCRA of placebo, ACEIs, ARBs, CCBs, diuretics, and β blockers was, respectively, 65.3%, 69.3%, 92.3%, 44.1%, 12.1%, and 16.5%. According to the evidence, ARBs have an advantage over the other treatments in reducing the risk of NOD in elderly patients.
Keywords: antihypertensive, diabetes, meta‐analysis, randomized control trial
1. INTRODUCTION
Diabetes mellitus (DM) has become a public health crisis in both developed and developing countries and is one of the main risk factors for the occurrence and development of cardiovascular disease.1 NOD refers to the phenomenon of diabetes occurring during treatment observation in patients who did not have diabetes, and accounts for the increasing proportion of the total of diabetes mellitus.2 Hypertension is a factor to induce or develop diabetes mellitus.3 High blood pressure increases the burden of renal function, and can lead to the destruction of renal cells by glucose infiltration, blood vessels, and tissues. Moreover, high blood pressure will affect the secretion of insulin and the health of various organs.4, 5
Antihypertensive drugs play a hypotensive effect mainly by affecting sympathetic nervous system, renin‐angiotensin‐aldosterone system and endothelin system, mainly including ACEIs, ARBs, CCBs, diuretics, and β blockers. Since 1958, people have known that some antihypertensive drugs have a tendency to lower glucose tolerance and diabetes.6, 7 In addition, two meta‐analyses compare different class of antihypertensive drugs on NOD and found that both ACEIs and ARBs could reduce the incidence of NOD8, 9; however, no study to compare different class of antihypertensive drugs on NOD in elderly.
The evidence on the relation between different class of antihypertensive drugs and NOD in elderly risk is still unknown. According to the evaluation of the Cochrane system, the purpose of this paper was to provide clinical decision makers with evidence‐based medical evidence of the impact of antihypertensive drugs on the risk of NOD in the elderly to guide clinical rational drug use.
2. METHODS
2.1. Search strategy
By using the combination of subject words and free words, the databases were retrieved in an orderly manner from the dates of their establishment to October 2018, including Medline, Embase, Cochrane Database, and Clinical Trials, with keywords including “Diabetes Mellitus” [MeSH] OR “NOD” [MeSH] OR “New‐Onset Diabetes Mellitus” [MeSH] OR “Type 2 Diabetes Mellitus” [MeSH] OR “Type 1 Diabetes Mellitus” [MeSH] AND “Antihypertensive Agents” [MeSH] OR “Anti Hypertensives” [MeSH] OR “Antihypertensive Drugs” [MeSH] AND “Randomized Controlled Trial” [MeSH].
2.2. Inclusion
The following selection criteria were applied: (a) publicly published RCT, comparable between groups; (b) patients were given antihypertensive drugs; (c) study was on elderly patients over 60 years; (d) Interventions: the control group was given an antihypertensive drugs or placebo, and the experimental group was given an antihypertensive drugs; (e) Contains the main outcome indicator is number of NOD.
2.3. Exclusion criteria
We exclude literature with obvious errors, defects, or unknown information provided by relevant queries in the trial design, and literature in which baseline data are not comparable without inter‐group equilibrium comparison. We also exclude review literature such as meta‐analysis, newsletters, research progress, and conference abstracts, as well as animal experiments.
2.4. Data extraction and study quality evaluation
According to the inclusion and exclusion criteria, the title and abstract of the literature were screened by two researchers independently of each other, and the unrelated literature was eliminated. Then, through reading the full text, exclude the literature that does not accord with this research scheme, and record the reasons and quantity of exclusion. Finally, the selected literature was cross‐checked by two researchers, and the disagreement was resolved through discussion or consultation with a third researcher. Using excel 2013 software design data extraction table to extract the key information in the literature. The quality of included literature was evaluated by Cochrane collaboration network evaluation risk tool. The quality of literature was evaluated according to random method, distribution concealment, blind method, incomplete outcome data, selective outcome report, and other biased sources.
2.5. Statistical analysis
Stata 12.0 software was used for statistical analysis. I 2 test was used to analyze the heterogeneity among the studies. If I 2 < 50%, it indicated that there was homogeneity among the studies, which could be directly combined and analyzed by fixed effect model. If I 2 ≥ 50%, the heterogeneity of each study is indicated, and the random effect model is used for statistical analysis. Bayesian network model based on Markov chain Monte Carlo operation is used for analyzing the therapeutic effects of drugs in two groups and multiple groups. All the included drugs were sorted using the surface under the cumulative ranking (SUCRA) to determine the pros and cons of the antihypertensive drugs on NOD in elderly patients.10 The larger the SUCRA, the better the effect. Bayesian network analysis using R software.
3. RESULTS
3.1. Literature search results
The retrieval process is shown in Figure 1. A total of 987 clinical research literatures were retrieved according to the corresponding retrieval method. The literatures were imported into Endnote X9 and removed, and 952 articles were obtained. By reading the summary of the title and the full text, according to the established the inclusion criteria, the exclusion criteria gradually screened the literature that met the criteria, and finally 14 articles were included11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24 (Table 1). Figure 2 showed the risk of bias of 14 studies included in this meta‐analysis. The reticular relationship between five antihypertensive drugs and placebo is shown in Figure 3. Each circle represents an intervention, and the larger the circle, the more sample size the intervention is accepted; the line between the circle and the circle represents a comparison of the two interventions, and the thicker the line, the more research literature is compared.
Figure 1.
Flow diagram of the study selection process
Table 1.
Characteristics of included studies
| Trials | Year | Duration (y) | Treatments | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Treatments 1 | Age (y) | New cases of diabetes/total | Treatments 2 | Age (y) | New cases of diabetes/total | Treatments 3 | Age (y) | New cases of diabetes/total | |||
| ALLHAT22 | 2002 | 4.0 | ACEIs | 67.0 | 119/4096 | CCBs | 67.0 | 154/3954 | Diuretics | 67.0 | 302/6766 |
| EWPHE24 | 1991 | 4.7 | Diuretics | >60 | 29/416 | Placebo | >60 | 20/424 | |||
| MRC‐E18 | 1992 | 5.8 | β blockers | 70.2 | 37/1102 | Diuretics | 70.2 | 43/1081 | Placebo | 70.2 | 34/2213 |
| SCOPE17 | 2003 | 3.7 | ARBs | 76.0 | 93/2167 | Placebo | 76.0 | 115/2175 | |||
| SHEP16 | 1998 | 3.0 | Diuretics | 76.0 | 140/1631 | Placebo | 76.0 | 118/1578 | |||
| STOP‐215 | 1999 | 4.0 | ACEIs | 70.0‐84.0 | 93/1970 | β blockers | 70.0‐84.0 | 97/1960 | CCBs | 70.0‐84.0 | 95/1965 |
| ADaPT13 | 2012 | 4.0 | ACEIs | 69.0 | 151/896 | Diuretics | 69.0 | 76/423 | |||
| EMPHASIS‐HF11 | 2012 | 1.8 | ARBs | 69.0 | 33/894 | Placebo | 69.0 | 36/952 | |||
| COPE12 | 2012 | 3.0 | ARBs | >60 | 7/498 | β blockers | >60 | 18/534 | Diuretics | >60 | 15/501 |
| VALUE14 | 2004 | 4.2 | ARBs | 67.0 | 690/5087 | CCBs | 67.0 | 840/5074 | |||
| ANBP‐223 | 2015 | 4.1 | ACEIs | 65.0‐84.0 | 138/2000 | Diuretics | 65.0‐84.0 | 200/2826 | |||
| INVEST19 | 2003 | 2.7 | CCBs | >60 | 665/8098 | Placebo | >60 | 569/8078 | |||
| HOPE21 | 2001 | 4.5 | ACEIs | >60 | 102/2837 | Placebo | >60 | 155/2883 | |||
| INSIGHT20 | 2000 | 3.0 | CCBs | 60.0‐70.0 | 96/2508 | Diuretics | 60.0‐70.0 | 137/2511 | |||
Abbreviations: ACEIs: angiotensin‐converting enzyme inhibitors; ADaPT: ACE inhibitor‐based vs diuretic‐based antihypertensive primary treatment in patients with pre‐diabetes; ALLHAT: The Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial; ANBP‐2: Second Australian National Blood Pressure trial; ARBs: angiotensin II receptor blockers; CCBs: calcium channel blockers; COPE: The Combination Therapy of Hypertension to Prevent Cardiovascular Events; EMPHASIS‐HF: The Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure; EWPHE: The European Working Party on High Blood Pressure in the Elderly; HOPE: Heart Outcomes Prevention Evaluation; INVEST: International Nifedipine GITS Study: Intervention as a Goal in Hypertension Treatment; MRC‐E: Medical Research Council in the Elderly; SCOPE: The Study on Cognition and Prognosis in the Elderly; STOP‐2: The Swedish Trial in Old Patients with Hypertension‐2 study; VALUE: The Valsartan Antihypertensive Long‐term Use Evaluation.
Figure 2.
Risk of bias of the included RCTs (review authors' judgments about each risk of bias item for each included study. +, low risk; −, high risk; ?, unclear risk)
Figure 3.
Network of randomized controlled trials comparing different antihypertensive drugs on risk of new‐onset diabetes in elderly. The thickness of the connecting lines represents the number of trials between each comparator, and the size of each node corresponds to the number of subjects who received the same pharmacological agent (sample size). (A: Placebo; B: ACEIs; C: CCBs; D: Diuretics; E: Beta‐blockers; F: ARBs)
3.2. Results of pairwise meta‐analysis
Table 2 displayed the results produced by pairwise meta‐analysis. Patients with ACEIs or ARBs appeared to have significantly reduced risk of NOD compare with placebo: ACEIs (OR = 0.72, 95% CrI 0.60‐0.87), ARBs (OR = 0.66, 95% CrI 0.51‐0.85), while CCBs, diuretics, and β blockers appeared to have not significantly reduced risk of NOD compare with placebo: CCBs (OR = 0.98, 95% CrI 0.90‐1.06), diuretics (OR = 1.18, 95% CrI 0.93‐1.48), β blockers (OR = 0.77, 95% CrI 0.38‐1.58).
Table 2.
Summary odds ratios of antihypertensive drugs and heterogeneity for each direct comparison
| Comparison | OR (95% CI) | P‐heterogeneity | I 2 | τ 2 |
|---|---|---|---|---|
| ACEIs vs Placebo | 0.72 (0.60, 0.87) | – | – | <0.001 |
| CCBs vs Placebo | 0.98 (0.90, 1.06) | – | – | 0.951 |
| Diuretics vs Placebo | 1.18 (0.93, 1.48) | 0.449 | 0.0% | 0.168 |
| Beta‐blockers vs Placebo | 0.77 (0.38, 1.58) | – | – | <0.001 |
| ARBs vs Placebo | 0.66 (0.51, 0.85) | 0.114 | 20.3% | <0.001 |
| CCBs vs ACEIs | 0.84 (0.65, 1.10) | 0.248 | 42.2% | 0.207 |
| Diuretics vs ACEIs | 0.84 (0.64, 1.09) | 0.315 | 36.4% | 0.190 |
| Beta‐blockers vs ACEIs | 0.99 (0.84, 1.16) | – | – | 0.890 |
| Diuretics vs CCBs | 0.60 (0.24, 1.49) | 0.179 | 44.74% | 0.644 |
| Beta‐blockers vs CCBs | 0.86 (0.67, 1.13) | – | – | 0.746 |
| ARBs vs CCBs | 1.04 (0.94, 1.15) | – | – | 0.490 |
| Beta‐blockers vs Diuretics | 1.09 (0.76, 1.56) | 0.481 | 0.0% | 0.644 |
| ARBs vs Diuretics | 1.07 (0.68, 1.12) | – | – | 0.562 |
| ARBs vs Beta‐blockers | 0.79 (0.52, 1.02) | – | – | 0.112 |
Abbreviations: ACEIs: angiotensin‐converting enzyme inhibitors; ARBs: angiotensin II receptor blockers; CCBs: calcium channel blockers.
Italic values indicate P < 0.05.
3.3. Network meta‐analysis
Table 3 displayed the results produced by network meta‐analysis. Patients with ACEIs or ARBs appeared to have significantly reduced risk of NOD compare with placebo: ACEIs (OR = 0.49, 95% CrI 0.28‐0.85), ARBs (OR = 0.37, 95% CrI 0.26‐0.52), while CCBs, diuretics and β blockers appeared to have not significantly reduced risk of NOD compare with placebo: CCBs (OR = 1.10, 95% CrI 0.85‐1.60), diuretics (OR = 1.40, 95% CrI 0.92‐2.50), β blockers (OR = 1.40, 95% CrI 0.93‐2.10).
Table 3.
Network meta‐analysis comparisons
| Placebo | ACEIs | CCBs | Diuretics | Beta‐blockers | ARBs | |
|---|---|---|---|---|---|---|
| Placebo | 1 | 2.04(1.18,3.57) | 0.88(0.63,1.20) | 0.73(0.40,1.09) | 0.73(0.48,1.10) | 2.70(1.92,3.84) |
| ACEIs | 0.49(0.28,0.85) | 1 | 0.90(0.66,1.20) | 0.74(0.56,0.98) | 0.75(0.50,1.10) | 1.20(0.81,1.90) |
| CCBs | 1.10(0.85,1.60) | 1.10(0.81,1.50) | 1 | 0.83(0.61,1.10) | 0.83(0.55,1.20) | 1.30(0.94,2.00) |
| Diuretics | 1.40(0.91,2.50) | 1.30(1.00,1.80) | 1.20(0.91,1.60) | 1 | 1.00(0.68,1.50) | 1.60(1.10,2.50) |
| Beta‐blockers | 1.40(0.93,2.10) | 1.30(0.90,2.00) | 1.20(0.81,1.80) | 0.99(0.68,1.50) | 1 | 1.60(1.10,2.70) |
| ARBs | 0.37(0.26,0.52) | 0.82(0.53,1.20) | 0.74(0.50,1.10) | 0.61(0.40,0.89) | 0.62(0.38,0.96) | 1 |
Abbreviations: ACEIs: angiotensin‐converting enzyme inhibitors; ARBs: angiotensin II receptor blockers; CCBs: calcium channel blockers.
The corresponding results of SUCRA values are presented in Figure 4. The SUCRA of placebo, ACEIs, ARBs, CCBs, diuretics, and β blockers was, respectively, 65.3%, 69.3%, 92.3%, 44.1%, 12.1%, and 16.5%. Angiotensin II receptor blockers have an advantage over the other treatments in reducing the risk of NOD in elderly patients.
Figure 4.
Surface under the cumulative ranking curve (SUCRA), expressed as percentages, ranking the therapeutic effects and safety of treatments for new‐onset diabetes in elderly. For efficacy and safety assessment, the pharmacological agent with the highest SUCRA value would be the most efficacious and safe treatment. (A: Placebo; B: ACEIs; C: CCBs; D: Diuretics; E: Beta‐blockers; F: ARBs)
3.4. Publication bias
All data points are evenly distributed on both sides of the inverted funnel plot, suggesting that there is less likelihood of publication bias (Figure 5).
Figure 5.
Comparison‐adjusted funnel plot for the network meta‐analysis. The red line suggests the null hypothesis that the study‐specific effect sizes do not differ from the respective comparison‐specific pooled effect estimates. Different colors represent different comparisons. (A: Placebo; B: ACEIs; C: CCBs; D: Diuretics; E: Beta‐blockers; F: ARBs)
4. DISCUSSION
High blood pressure, diabetes mellitus is a common clinical disease and frequent incidence, serious harm to public health. There is a very close relationship between hypertension and diabetes. 10%‐20% of hypertensive patients with diabetes. Diabetes patients with hypertension can reach 50%, those over 70 years old are up to 60%, and almost 100% of patients with diabetes and kidney damage have high blood pressure. Half of newly diagnosed diabetic patients have high blood pressure. It is currently believed that hypertension and diabetes have a common pathogenesis, leading to the clustering of two diseases.25, 26 Blood pressure is a risk factor for NOD in relatively healthy people. Study found that the NOD risk for the baseline blood pressure <120/75 mm Hg group was 0.66%, 1.0% for the 120‐129/75‐84 mm Hg group, and 1.42% for the 130‐139/85‐89 mm Hg group, while >140/90 mm Hg group was as high as 2.03%. At the same time, the risk of NOD increased during the observation period. According to the evidence, basal blood pressure levels and blood pressure progression status are strong and independent risk factors for NOD.27, 28 The five commonly used antihypertensive drugs can reduce cardiovascular deaths and events in patients with hypertension. However, the impact on NOD is not the case, and some drugs may increase the incidence of NOD. Two meta‐analyses compare different class of antihypertensive drugs on NOD and found that both ACEIs and ARBs could reduce the incidence of NOD; however, β‐blocker and CCB can significantly increase the risk of NOD.8, 9 There is no study to compare different class of antihypertensive drugs on NOD in elderly. This network meta‐analysis attempted to explain the effectiveness of different class of antihypertensive drugs on NOD in elderly. Our analysis suggests that ACEIs or ARBs can significantly reduced risk of NOD compare with placebo, ARBs have an advantage over the other treatments in reducing the risk of NOD in elderly patients.
β blockers, glucocorticoids, thiazide diuretics, niacin, and pentamidine can induce elevated blood sugar. Long‐term blood glucose elevation through inflammatory response, oxidative stress, deposition of glycosylation products, and other mechanisms can lead to complications such as autonomic nervous system, microvascular, and large and medium blood vessels, eventually leading to secondary cardiovascular and cerebrovascular diseases, fundus lesions, glomerular vascular injury, and peripheral circulatory disorders and other complications occur, severe cases can lead to amputation, blindness, hemiplegia, and other adverse events, bringing a heavy financial burden to individuals and families. Thiazide diuretics mainly reduce the body's potassium content, which in turn reduces insulin secretion and induces blood sugar elevation. This effect is dose‐dependent and can be eliminated by potassium supplementation or withdrawal. Low potassium may reduce ATP‐K+ channel function in islet cells and decrease insulin release. Low potassium inhibits the conversion of proinsulin to insulin. Since the biological activity of proinsulin is lower than that of insulin, a decrease in blood insulin level may result in an increase in blood glucose, an abnormal glucose tolerance or DM. A clinical study by Amery et al found that the incidence of fasting blood glucose increased significantly when blood potassium was <3.9 mmol/L.29 The SHEP study found that for every 0.5 mmol/L reduction in blood potassium, the risk of NOD increased by 45%. However, when the blood potassium decreased from 5.0 mmol/L to 4.5 mmol/L, the NOD was not increased significantly, but from 4.0 mmol/L to 3.5 mmol/L, the NOD increased significantly. It is suggested that the obvious reduction of blood potassium is more unfavorable. Early NOD caused by chlorthalidone treatment is associated with decreased blood potassium, and potassium supplementation may prevent NOD caused by chlorthalidone.16 The decrease of insulin sensitivity is closely related to the occurrence of diabetes.30 Studies show that the increase or decrease of insulin sensitivity is closely related to the effect of antihypertensive drugs on skeletal muscle blood flow.31 Diuretics and β blockers can reduce the blood flow of skeletal muscle tissue by reducing cardiac output and blood volume, decrease glucose and insulin entering skeletal muscle tissue, decrease glucose uptake and utilization, lead to increased blood sugar and forcing the release of more insulin, which causes insulin resistance and contributes to the development of diabetes. On the contrary, ACEIs, CCBs, and ARBs could induce vasodilation, increase skeletal muscle blood flow and improve insulin sensitivity.32 ACEI and ARB, as inhibitors of renin‐angiotensin system, play a fundamental role in the treatment of hypertension. Angiotensin‐converting enzyme inhibitor can reduce angiotensin production by inhibiting angiotensin‐converting enzyme activity in circulatory system and tissue. By selectively blocking angiotensin receptor I, ARB inhibits a series of physiological effects of Angiotensin II (Ang II) and produces pharmacological effects similar to those of ACEI. However, the patient's tolerance to ARB is better than that of ACEI, and the side effects such as irritating cough will not occur.33, 34
The incidence of NOD in hypertensive patients treated with ACEI and ARB is reduced, and its mechanism may be related to the interaction between RAS and insulin signaling pathways. Hyperglycemia and high insulin levels activate activation of RAS during insulin resistance. Fighting against over‐activated RAS systems helps to alleviate insulin resistance.35, 36 It was found that ARB also had the activation of peroxisome proliferators‐activated receptor‐γ (PPAR‐γ), especially irbesartan and telmisartan. The effect of ARB is similar to that of thiazolidinedione, which increases insulin‐mediated glucose uptake in peripheral tissues and protects islet B‐cell function by activating PPAR‐γ. In order to achieve the purpose of improving insulin resistance and effectively controlling blood glucose.37, 38
This meta‐analysis also has some limitations. First of all, different doses included in the literature and different administration schemes of the patients resulted in clinical heterogeneity. Second, we only evaluated the NOD in elderly patients, while the incidence of other diseases could not be analyzed. Finally, the small sample size of the interventions included in the study, and the possible shortage of statistical efficiency may be insufficient. Based on the shortcomings of the existing research, clinicians should consider the influence of the above factors and choose carefully when applying the conclusions of this study.
In summary, based on this study, the results of network meta‐analysis showed that ACEIs or ARBs can significantly reduced risk of NOD compare with placebo, ARBs have an advantage over the other treatments in reducing the risk of NOD in elderly patients. The samples included in this study are small, therefore, in the future, large, multicenter, high‐quality randomized controlled trials should be included, and long‐term follow‐up mechanisms should be established, as far as possible, in order to obtain high‐quality, more convincing clinical studies, to provide more evidence‐based medical evidence for scientific research and clinical practice.
CONFLICT OF INTEREST
The authors Jinhua Zhang, Aihua Tong, Yan Dai, Jie Niu, Fengquan Yu, and Fangjiang Xu have nothing to disclose.
AUTHORS CONTRIBUTION
Jinhua Zhang, Fengquan Yu, and Fangjiang Xuand Aihua Tong were responsible for the conception and design, acquisition of data, analysis and interpretation of data, drafting the initial manuscript, and revising it critically for important intellectual content. Yan Dai, Jie Niu, and Fangjiang Xu wrote the final draft of the manuscript. Jinhua Zhang, Aihua Tong, Yan Dai, Jie Niu, Fengquan Yu, and Fangjiang Xu approved the final manuscript as it is.
ETHICAL APPROVAL
This meta‐analysis is based on previously conducted studies and does not contain any studies with human participants or animals performed by any of the authors.
Zhang J, Tong A, Dai Y, Niu J, Yu F, Xu F. Comparative risk of new‐onset diabetes mellitus for antihypertensive drugs in elderly: A Bayesian network meta‐analysis. J Clin Hypertens. 2019;21:1082–1090. 10.1111/jch.13598
Data Availability Statement: All data generated or analyzed during this study are included in this published article.
DATA AVAILABILITY STATEMENT
All data generated or analyzed during this study are included in this published article.
REFERENCES
- 1. Kannel WB, McGee DL. Diabetes and glucose tolerance as risk factors for cardiovascular disease: the Framingham study. Diabetes Care. 1979;2(2):120‐126. [DOI] [PubMed] [Google Scholar]
- 2. Messerli FH, Grossman E, Leonetti G. Antihypertensive therapy and new onset diabetes. J Hypertens. 2004;22(10):1845‐1847. [DOI] [PubMed] [Google Scholar]
- 3. Gress TW, Nieto FJ, Shahar E, Wofford MR, Brancati FL. Hypertension and antihypertensive therapy as risk factors for type 2 diabetes mellitus. Atherosclerosis Risk in Communities Study. N Engl J Med. 2000;342(13):905‐912. [DOI] [PubMed] [Google Scholar]
- 4. Emdin CA, Anderson SG, Woodward M, Rahimi K. Usual blood pressure and risk of new‐onset diabetes: evidence from 4.1 million adults and a meta‐analysis of prospective studies. J Am College Cardiol. 2015;66(14):1552‐1562. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Bangalore S, Parkar S, Grossman E, Messerli FH. A meta‐analysis of 94,492 patients with hypertension treated with beta blockers to determine the risk of new‐onset diabetes mellitus. Am J Cardiol. 2007;100(8):1254‐1262. [DOI] [PubMed] [Google Scholar]
- 6. Luna B, Feinglos MN. Drug‐induced hyperglycemia. JAMA. 2001;286(16):1945‐1948. [DOI] [PubMed] [Google Scholar]
- 7. Wilkins RW. New drugs for the treatment of hypertension. Ann Intern Med. 1959;50(1):1‐10. [DOI] [PubMed] [Google Scholar]
- 8. Li Z, Li Y, Liu Y, Xu W, Wang Q. Comparative risk of new‐onset diabetes mellitus for antihypertensive drugs: a network meta‐analysis. J Clin Hypertension. 2017;19(12):1348‐1356. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Elliott WJ, Meyer PM. Incident diabetes in clinical trials of antihypertensive drugs: a network meta‐analysis. Lancet. 2007;369(9557):201‐207. [DOI] [PubMed] [Google Scholar]
- 10. Salanti G, Ades AE, Ioannidis JP. Graphical methods and numerical summaries for presenting results from multiple‐treatment meta‐analysis: an overview and tutorial. J Clin Epidemiol. 2011;64(2):163‐171. [DOI] [PubMed] [Google Scholar]
- 11. Preiss D, van Veldhuisen DJ, Sattar N, et al. Eplerenone and new‐onset diabetes in patients with mild heart failure: results from the Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure (EMPHASIS‐HF). Eur J Heart Fail. 2012;14(8):909‐915. [DOI] [PubMed] [Google Scholar]
- 12. Ogihara T, Matsuzaki M, Umemoto S, et al. Combination therapy for hypertension in the elderly: a sub‐analysis of the Combination Therapy of Hypertension to Prevent Cardiovascular Events (COPE) Trial. Hypertension Res. 2012;35(4):441‐448. [DOI] [PubMed] [Google Scholar]
- 13. Zidek W, Schrader J, Lüders S, et al. First‐line antihypertensive treatment in patients with pre‐diabetes: rationale, design and baseline results of the ADaPT investigation. Cardiovasc Diabetol. 2008;7:22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Julius S, Kjeldsen SE, Weber M, et al. Outcomes in hypertensive patients at high cardiovascular risk treated with regimens based on valsartan or amlodipine: the VALUE randomised trial. Lancet. 2004;363(9426):2022‐2031. [DOI] [PubMed] [Google Scholar]
- 15. Hansson L, Lindholm LH, Ekbom T, et al. Randomised trial of old and new antihypertensive drugs in elderly patients: cardiovascular mortality and morbidity the Swedish Trial in Old Patients with Hypertension‐2 study. Lancet. 1999;354(9192):1751‐1756. [DOI] [PubMed] [Google Scholar]
- 16. Savage PJ, Pressel SL, Curb JD, et al. Influence of long‐term, low‐dose, diuretic‐based, antihypertensive therapy on glucose, lipid, uric acid, and potassium levels in older men and women with isolated systolic hypertension: the Systolic Hypertension in the Elderly Program. SHEP Cooperative Research Group. Arch Intern Med. 1998;158(7):741‐751. [DOI] [PubMed] [Google Scholar]
- 17. Lithell H, Hansson L, Skoog I, et al. The Study on Cognition and Prognosis in the Elderly (SCOPE): principal results of a randomized double‐blind intervention trial. J Hypertens. 2003;21(5):875‐886. [DOI] [PubMed] [Google Scholar]
- 18. BMJ . Medical Research Council trial of treatment of hypertension in older adults: principal results. MRC Working Party. BMJ (Clinical research ed.). 1992;304(6824):405‐412. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Pepine CJ, Handberg EM, Cooper‐DeHoff RM, et al. A calcium antagonist vs a non‐calcium antagonist hypertension treatment strategy for patients with coronary artery disease. The International Verapamil‐Trandolapril Study (INVEST): a randomized controlled trial. JAMA. 2003;290(21):2805‐2816. [DOI] [PubMed] [Google Scholar]
- 20. Brown MJ, Palmer CR, Castaigne A, et al. Morbidity and mortality in patients randomised to double‐blind treatment with a long‐acting calcium‐channel blocker or diuretic in the International Nifedipine GITS study: Intervention as a Goal in Hypertension Treatment (INSIGHT). Lancet. 2000;356(9227):366‐372. [DOI] [PubMed] [Google Scholar]
- 21. Yusuf S, Gerstein H, Hoogwerf B, et al. Ramipril and the development of diabetes. JAMA. 2001;286(15):1882‐1885. [DOI] [PubMed] [Google Scholar]
- 22. The ALLHAT Officers and Coordinators for the ALLHAT Collaborative Research Group . Major outcomes in high‐risk hypertensive patients randomized to angiotensin‐converting enzyme inhibitor or calcium channel blocker vs diuretic: the Antihypertensive and Lipid‐Lowering Treatment to Prevent Heart Attack Trial (ALLHAT). JAMA. 2002;288(23):2981‐2997. [DOI] [PubMed] [Google Scholar]
- 23. Chowdhury EK, Ademi Z, Moss JR, Wing LM, Reid CM. Cost‐utility of angiotensin‐converting enzyme inhibitor‐based treatment compared with thiazide diuretic‐based treatment for hypertension in elderly Australians considering diabetes as comorbidity. Medicine. 2015;94(9):e590. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Fletcher A, Amery A, Birkenhager W, et al. Risks and benefits in the trial of the European working party on high blood pressure in the elderly. J Hypertens. 1991;9(3):225‐230. [DOI] [PubMed] [Google Scholar]
- 25. Abuissa H, Jones PG, Marso SP, O'Keefe JH Jr. Angiotensin‐converting enzyme inhibitors or angiotensin receptor blockers for prevention of type 2 diabetes: a meta‐analysis of randomized clinical trials. J Am Coll Cardiol. 2005;46(5):821‐826. [DOI] [PubMed] [Google Scholar]
- 26. Opie LH, Schall R. Old antihypertensives and new diabetes. J Hypertens. 2004;22(8):1453‐1458. [DOI] [PubMed] [Google Scholar]
- 27. Lloyd‐Jones DM, Evans JC, Levy D. Hypertension in adults across the age spectrum: current outcomes and control in the community. JAMA. 2005;294(4):466‐472. [DOI] [PubMed] [Google Scholar]
- 28. Kearney PM, Whelton M, Reynolds K, Muntner P, Whelton PK, He J. Global burden of hypertension: analysis of worldwide data. Lancet. 2005;365(9455):217‐223. [DOI] [PubMed] [Google Scholar]
- 29. Amery A, Bulpitt C, Schaepdryver A, et al. Glucose intolerance during diuretic therapy. Results of trial by the European Working Party on Hypertension in the Elderly. Lancet. 1978;1(8066):681‐683. [DOI] [PubMed] [Google Scholar]
- 30. Dronavalli S, Bakris GL. Mechanistic insights into diuretic‐induced insulin resistance. Hypertension. 2008;52(6):1009‐1011. [DOI] [PubMed] [Google Scholar]
- 31. Eriksson JW, Jansson PA, Carlberg B, et al. Hydrochlorothiazide, but not Candesartan, aggravates insulin resistance and causes visceral and hepatic fat accumulation: the mechanisms for the diabetes preventing effect of Candesartan (MEDICA) Study. Hypertension. 2008;52(6):1030‐1037. [DOI] [PubMed] [Google Scholar]
- 32. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444(7121):840‐846. [DOI] [PubMed] [Google Scholar]
- 33. Strauss MH, Hall AS. Angiotensin receptor blockers may increase risk of myocardial infarction: unraveling the ARB‐MI paradox. Circulation. 2006;114(8):838‐854. [DOI] [PubMed] [Google Scholar]
- 34. Verdecchia P, Angeli F, Repaci S, Mazzotta G, Gentile G, Reboldi G. Comparative assessment of angiotensin receptor blockers in different clinical settings. Vasc Health Risk Manag. 2009;5:939‐948. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Imazu M. Hypertension and insulin disorders. Curr Hypertens Rep. 2002;4(6):477‐482. [DOI] [PubMed] [Google Scholar]
- 36. Sowers JR, Epstein M, Diabetes F. Diabetes, hypertension, and cardiovascular disease: an update. Hypertension. 2001;37(4):1053‐1059. [DOI] [PubMed] [Google Scholar]
- 37. Ogihara T, Asano T, Ando K, et al. Angiotensin II‐induced insulin resistance is associated with enhanced insulin signaling. Hypertension. 2002;40(6):872‐879. [DOI] [PubMed] [Google Scholar]
- 38. Scheen AJ. Prevention of type 2 diabetes mellitus through inhibition of the Renin‐Angiotensin system. Drugs. 2004;64(22):2537‐2565. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
All data generated or analyzed during this study are included in this published article.