Abstract
To determine the prevalence of multidrug antihypertensive therapy (MDAT), records were evaluated for patients with both type 2 diabetes and hypertension during a 5‐year period at Joslin Diabetes Center. Hypertension control was defined as requiring multiple drugs if three or more antihypertensive drugs were used, one of which must be a diuretic (unless patient is receiving dialysis), or use of four or more antihypertensive drugs, one of which a diuretic (unless patient is receiving dialysis) was established. The objective was to determine the prevalence of multidrug requirement for hypertensive therapy in relationship to four levels of renal function estimated by the Modification of Diet in Renal Disease formula for glomerular filtration rate (GFR). Among 10,151 patients, mean estimated GFR was 80 mL/min. Using standard (ASN) classification for renal function, we noted the following breakdown of MDAT use:
| Estimated GFR | Drugs, Mean No. | ≥3 Drugs, No. (%) | ≥4 Drugs, No. (%) |
|---|---|---|---|
| <30 | 3.1 | 379 (67) | 214 (38) |
| 30–60 | 2.7 | 1233 (55) | 538 (24) |
| 60–90 | 2.0 | 1279 (33) | 458 (12) |
| >90 | 1.5 | 600 (17) | 185 (5) |
Prevalence of multidrug antihypertensive therapy is markedly increased in the presence of reduced renal function.
In spite of continuing efforts to control high blood pressure (BP) and an ever‐expanding arsenal of new drugs and procedures, we fall short of adequate control in the majority of patients with decreased renal function. Although it is unclear how much the role of noncompliance plays in the adequacy of BP control, patients who require additional medication because of diabetes are more likely to noncomply (simply on the basis of number of drugs and cost). Yet, no population experiences more adverse microvascular and macrovascular events than the cohort with associated type 2 diabetes.
Depending on the definition used, the prevalence of resistant hypertension in the overall population has been estimated to be 9%.1 A significant increase in the prevalence of treatment‐resistant hypertension has been reported in a review of 10,700 patients in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study with advancing chronic kidney disease (CKD) and increasing urine albumin to creatinine ratios. We sought to determine the prevalence of therapy resistance as defined by the number of classes of medication required to treat diagnosed hypertension in a community‐dwelling population treated at a tertiary care center devoted to the treatment of diabetes.
Methods
To determine the prevalence of treatment‐resistant hypertension in type 2 diabetes we evaluated medication records for patients who had been seen at least twice during a sample 5‐year period at Joslin Diabetes Center diagnosed with both type 2 diabetes mellitus and hypertension. This study was approved by the human studies institutional review board of the Joslin Diabetes Center as an exploration of ranges of medications required to meet institutional guidelines in BP control (<140/90 mm Hg). All patient records/information were anonymized and de‐identified prior to analysis. A total of 10,148 patients were identified as meeting criteria of at least two visits between January 2006 and December 2011 with complete demographic information regarding height, weight, body mass index (BMI), estimated glomerular filtration rate (eGFR), and medication prescription records available. Data on patient demographics, BP medications, BMI, and eGFR were as of the date of initial visit within the prespecified time frame.
Multidrug antihypertensive therapy (MDAT) was defined by either the use of at least three antihypertensive drug classes, with one of which being a diuretic (unless the patient was receiving dialysis), or use of at least four antihypertensive drug classes, with one of which being a diuretic (unless the patient was receiving dialysis). We stratified BMI and sex by four levels of eGFR (by the Modification of Diet in Renal Disease formula). Antihypertensive drug classes included the following: diuretics, angiotensin receptor blockers, angiotensin‐converting enzyme inhibitors, direct renin inhibitors, calcium channel blockers, α‐adrenergic blockers, β‐blockers, vasodilators, nitrates, and direct central nervous system active agents. We anticipated that the extent to which aspirin and lipid‐lowering medications were prescribed in this population at high risk for major adverse cardiovascular events might be related to the prevalence of MDAT.
Statistical Analysis
All baseline information is presented as means and standard deviations or, for skewed variables, medians and interquartile ranges for continuous variables, and counts and percentages for dichotomous variables. Analysis for trend across eGFR categories was conducted using linear regression, Cuzick nonparametric trend test, and Cochran‐Armitage test for trend, respectively. Global tests for quality were tested using analysis of variance, Kruskal‐Wallis test, and Pearson chi‐square test, respectively. P values less than .05 were considered to be significant. All analyses were conducted using STATA 13 (StataCorp, College Station, TX, USA).
Results
There were 5623 men/4528 women, with a mean BMI of 31 (30/32), height of 67 inches (69/63), and weight of 198 pounds (212/182). The systolic BP range was 75 mm Hg to 233 mm Hg (53% at 120 mm Hg to 140 mm Hg, 23% >140 mm Hg, and 24% <120 mm Hg). Mean eGFR was 78 mL/min (78/78 mL/min), and 90% of patients received lipid‐lowering medications (statins 78%/73%) and 60% (63%/60%) also received aspirin. Table 1 describes the demographics of groups divided by baseline level of renal function. It also lists the number of antihypertensive drug classes per patient. Despite the requirement for a diagnosis of hypertension, 33% of our patients were not prescribed antihypertensive medications at baseline, 29% were prescribed a single agent, 23% were prescribed two antihypertensive agents, and 15% were taking at least three agents for this diagnosis. It is notable that there was a strong relationship between the number of drugs prescribed for control of high BP and the level of renal function at baseline. Prevalence of MDAT as defined by antihypertensive medication use in a database of patients across all levels of renal function increased in groups with diminished renal function.
Table 1.
Demographic and Medication Data in Patients Identified as Having Hypertension and Type 2 Diabetes by GFR Categories
| eGFR <30 (n=565) | eGFR 30–60 (n=2230) | eGFR 60–90 (n=3924) | eGFR >90 (n=3432) | P for Trend | |
|---|---|---|---|---|---|
| Age, y | 71.0 (60.0–79.0) | 73.0 (66.0–81.0) | 67.0 (59.0–74.0) | 57.0 (49.0–64.0) | <.001 |
| Male sex, No. (%) | 293 (51.9) | 1116 (50.0) | 2090 (53.3) | 2124 (61.9) | <.001 |
| Height, in | 66.0 (63.0–69.0) | 66.0 (63.0–69.0) | 67.0 (63.8–70.0) | 68.0 (65.0–70.5) | <.001 |
| Weight, lb | 186.0 (154.8–220.6) | 190.0 (162.0–224.0) | 192.0 (163.6–224.0) | 198.0 (170.0–231.0) | <.001 |
| BMI | 29.9 (25.3–35.0) | 30.4 (26.6–35.3) | 30.1 (26.3–34.5) | 30.2 (26.6–34.9) | .52 |
| eGFR | 21.4 (13.9–25.7) | 48.1 (41.2–54.6) | 76.3 (68.6–81.9) | 105.6 (96.7–120.0) | <.001 |
| A1c | 7.3 (6.6–8.2) | 7.5 (6.7–8.4) | 7.4 (6.7–8.3) | 7.6 (6.8–8.6) | <.001 |
| Antihypertensive medication, No. | 2.0 (2.0–3.0) | 2.0 (1.0–3.0) | 1.0 (0.0–2.0) | 0.0 (0.0–1.0) | <.001 |
| Medications, No. (%) | |||||
| None | 36 (6.4) | 264 (11.8) | 1242 (31.7) | 1792 (52.2) | <.001 |
| One | 85 (15.0) | 575 (25.8) | 1287 (32.8) | 986 (28.7) | |
| Two | 168 (29.7) | 781 (35.0) | 914 (23.3) | 467 (13.6) | |
| Three or more | 276 (48.8) | 610 (27.4) | 481 (12.3) | 187 (5.4) | |
| MDAT | 250 (44.2) | 564 (25.3) | 446 (11.4) | 178 (5.2) | <.001 |
| Statin | 421 (74.5) | 1810 (81.2) | 3029 (77.2) | 2446 (71.3) | <.001 |
| Nonstatin | 68 (12.0) | 279 (12.5) | 365 (9.3) | 256 (7.5) | <.001 |
| Aspirin | 358 (63.4) | 1524 (68.3) | 2462 (62.7) | 1741 (50.7) | <.001 |
| Insulin | 462 (81.8) | 1563 (70.1) | 2469 (62.9) | 2297 (66.9) | <.001 |
| Insulin only | 396 (70.1) | 955 (42.8) | 1267 (32.3) | 1218 (35.5) | <.001 |
| Other than insulin | 65 (11.5) | 547 (24.5) | 1283 (32.7) | 1015 (29.6) | <.001 |
| Insulin and other | 66 (11.7) | 608 (27.3) | 1202 (30.6) | 1079 (31.4) | <.001 |
| Metformin | 8 (1.4) | 642 (28.8) | 2128 (54.2) | 1891 (55.1) | <.001 |
| Sulfonamide | 98 (17.3) | 625 (28.0) | 1033 (26.3) | 820 (23.9) | .62 |
| Thiazolidinedione | 11 (1.9) | 83 (3.7) | 101 (2.6) | 73 (2.1) | .018 |
| DPP‐4 | 38 (6.7) | 257 (11.5) | 382 (9.7) | 235 (6.8) | <.001 |
| Acarbose | 2 (0.4) | 11 (0.5) | 16 (0.4) | 27 (0.8) | .08 |
| Nateglinide | 1 (0.2) | 3 (0.1) | 7 (0.2) | 3 (0.1) | .53 |
| Repaglinide | 9 (1.6) | 34 (1.5) | 59 (1.5) | 31 (0.9) | .03 |
| Pramlintide | 3 (0.5) | 15 (0.7) | 36 (0.9) | 54 (1.6) | .004 |
| GLP‐1 | 2 (0.4) | 54 (2.4) | 169 (4.3) | 170 (5.0) | <.001 |
Abbreviations: A1c, glycated hemoglobin (n=8798); CNS, central nervous system active; DPP‐4, dipeptidyl peptidase 4; GLP‐1, glucagon‐like peptide‐1; MDAT, multidrug antihypertensive therapy (defined as taking at least three antihypertensive drug classes with one of them a diuretic). Antihypertensive medications included diuretics, calcium channel blockers, α‐ and β‐blockers, CNS, direct renin inhibitors, nitrates, and vasodilators.
Discussion
In this cross‐sectional cohort of patients diagnosed with type 2 diabetes mellitus as well as hypertension, the prevalence of MDAT (classification by number of medication classes required to treat hypertension) was unrelated to BMI. However, a strong relationship was demonstrable between prevalence of number of medication classes required to treat hypertension and eGFR. Indeed, the hypertensive diabetic population with diminished renal function demonstrated an incrementally increased use of antihypertensive drug classes and markedly increased prevalence of MDAT as defined.
Although the populations studied were not totally comparable, our results confirm and extend those of Tanner and colleagues2 in a large predominantly African American population, 50% of whom had diabetes. In that study, hypertensive patients taking no medications or not yet controlled by one or two antihypertensive medication classes were excluded. Thus, the prevalence estimate of resistant hypertension is not strictly comparable to the present report. Despite the differences in the populations and definitions, there are similarities in observations. The Tanner study estimated an increasing prevalence of resistant hypertension with diminished renal function (increasing from 15.8% with eGFR >60 mL/min to 33.4% with eGFR <45 mL/min) but did not address the question of the percentage of type 2 diabetic patients who had resistant hypertension according to the distribution of eGFR. The reports by Calhoun and colleagues3 and Chobanian and colleagues4 noting that target BP for the definition of controlled vs uncontrolled BP vary according to presence or absence of CKD (<130/80 mm Hg) or diabetes (<130/80 mm Hg), review primary data from other studies (the Framingham Heart Study, the Antihypertensive and Lipid Lowering Treatment to Prevent Heart Attack Trial, and the National Health and Nutrition Examination Survey) and support the hypothesis that both the presence of diabetes and renal dysfunction are important in the genesis of therapy resistance. Each of these studies represent >10,000 diabetic individuals. This is the only presentation of data that focuses on distribution of eGFR and resistant hypertension specific to the diabetic cohort.
Multiple prior investigators and guideline committees have analyzed prevalence of resistant hypertension using several definitions, with or without outcome data.3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 The highest‐risk population for cardiovascular endpoints is the hypertensive diabetic group with renal insufficiency. A recent international study focused on this population. The Trial to Reduce Cardiovascular Endpoints With Aranesp Therapy (TREAT) enrolled 4038 patients during the years 2005 to 2009 (a similar time frame to our database) in order to determine whether programmed use of darbepoetin improved healthcare outcomes among patients with type 2 diabetes and moderately severe renal insufficiency.20 22 Although the TREAT trial was not designed to evaluate prevalence of resistant hypertension or results of antihypertensive therapy, it would appear that use of multiple antihypertensive agents at baseline was also greater in lower tiers of renal function and that antidiabetes medications varied according to baseline eGFR as well.21 The current evaluation extends this observation to a cohort of hypertensive type 2 diabetic patients with wider ranges of renal function.
Our database indicates a four‐ to five‐fold increased prevalence of difficult to control hypertension as renal function diminishes below an eGFR of 60 mL/min (Table 2). The number of drugs required to treat hypertension appears to double from eGFR >90 mL/min to <30 mL/min. One third of our population had an eGFR >90 mL/min, which is in the normal range. Approximately one third had an eGFR of 60 mL/min to 90 mL/min. The bottom third had an eGFR <60 mL/min (stage 3 and 4 chronic renal insufficiency).
Table 2.
Demographic and Medication Data in Patients Identified as Having Hypertension and Type 2 Diabetes by Sex Categories
| Male (n=5623) | Female (n=4528) | P for Difference | |
|---|---|---|---|
| Age, y | 64.0 (55.0–73.0) | 66.0 (57.0–75.0) | <.001 |
| Height, in | 69.8 (67.5–71.3) | 63.5 (62.0–65.5) | <.001 |
| Weight, lb | 205.8 (180.0–237.0) | 174.0 (149.8–209.0) | <.001 |
| BMI | 30.0 (26.6–34.1) | 30.6 (26.1–36.0) | .003 |
| eGFR | 80.0 (59.6–100.8) | 75.8 (55.2–93.8) | <.001 |
| A1c | 7.5 (6.7–8.4) | 7.5 (6.7–8.5) | .41 |
| Medications, No. (%) | <.001 | ||
| None | 1888 (33.6) | 1446 (31.9) | |
| One | 1561 (27.8) | 1372 (30.3) | |
| Two | 1243 (22.1) | 1087 (24.0) | |
| Three or more | 931 (16.6) | 623 (13.8) | |
| MDAT | 842 (15.0) | 596 (13.2) | .009 |
| Statin | 4386 (78.0) | 3320 (73.3) | <.001 |
| Nonstatin | 604 (10.7) | 364 (8.0) | <.001 |
| Aspirin | 3539 (62.9) | 2546 (56.2) | <.001 |
| Insulin | 3776 (67.2) | 3015 (66.6) | .55 |
| Insulin only | 2096 (37.3) | 1740 (38.4) | .23 |
| Other than insulin | 1632 (29.0) | 1278 (28.2) | .38 |
| Insulin and other | 1680 (29.9) | 1275 (28.2) | .058 |
| Metformin | 2635 (46.9) | 2034 (44.9) | .052 |
| Sulfonamide | 1529 (27.2) | 1047 (23.1) | <.001 |
| Thiazolidinedione | 193 (3.4) | 75 (1.7) | <.001 |
| DPP‐4 | 501 (8.9) | 411 (9.1) | .77 |
| Acarbose | 25 (0.4) | 31 (0.7) | .10 |
| Nateglinide | 8 (0.1) | 6 (0.1) | .90 |
| Repaglinide | 70 (1.2) | 63 (1.4) | .52 |
| Pramlintide | 58 (1.0) | 50 (1.1) | .72 |
| GLP‐1 | 214 (3.8) | 181 (4.0) | .62 |
Abbreviations: A1c, glycated hemoglobin; BMI, body mass index; DPP‐4, dipeptidyl peptidase 4; eGFR, estimated glomerular filtration rate; GLP‐1, glucagon‐like peptide‐1; MDAT, multidrug antihypertensive therapy (defined as taking at least three antihypertensive drug classes with one being a diuretic).
Unlike the situation with multiple antihypertensive agent use varying incrementally according to glomerular filtration rate, there appears to be no such gradation in use of aspirin or statins, although there was a trend for eGFR values >30 mL/min. We found that 78% of our diabetic population required medication to control hyperglycemia, 75% required statins to control hyperlipidemia, and 60% required aspirin to control platelet hyperactivity. Thus, although guidelines for treatment of hyperglycemia, hyperlipidemia, and hypertension exist, they are applied differently in populations with diminished kidney function. Guidelines are generally developed in groups with normal renal function and may not reflect best care when renal function is impaired.
Table 3.
Demographic and Medication Data Based on Control of Diabetes at Baseline (A1c >7)
| A1c ≤7 (n=3151) | A1c >7 (n=5647) | P for Difference | |
|---|---|---|---|
| Age, y | 68.0 (59.0–76.0) | 63.0 (54.0–73.0) | <.001 |
| Male sex, No. (%) | 1749 (55.5) | 3131 (55.4) | .96 |
| Height, in | 67.0 (63.8–70.0) | 67.0 (64.0–70.0) | .42 |
| Weight, lb | 190.0 (162.4–221.6) | 195.4 (166.6–229.0) | <.001 |
| Heart rate, beats per min | 73.0 (64.0–82.0) | 76.0 (66.0–86.0) | <.001 |
| A1c | 6.5 (6.2–6.8) | 8.1 (7.5–9.0) | <.001 |
| BMI | 29.6 (26.0–34.3) | 30.4 (26.7–35.2) | <.001 |
| eGFR | 78.1 (58.0–94.6) | 80.0 (60.7–100.8) | <.001 |
| Medications, No. (%) | <.001 | ||
| None | 996 (31.6) | 2010 (35.6) | |
| One | 914 (29.0) | 1645 (29.1) | |
| Two | 745 (23.6) | 1226 (21.7) | |
| Three or more | 496 (15.7) | 766 (13.6) | |
| Statins | 2374 (75.3) | 4309 (76.3) | .31 |
| Nonstatin | 293 (9.3) | 526 (9.3) | .98 |
| Aspirin | 1920 (60.9) | 3351 (59.3) | .14 |
| Insulin | 1412 (44.8) | 4437 (78.6) | <.001 |
| Insulin only | 823 (26.1) | 2431 (43.0) | <.001 |
| Other than insulin | 1426 (45.3) | 1151 (20.4) | <.001 |
| Insulin and other | 589 (18.7) | 2006 (35.5) | <.001 |
| Metformin | 1595 (50.6) | 2576 (45.6) | <.001 |
| Sulfonamide | 743 (23.6) | 1536 (27.2) | <.001 |
| Thiazolidinedione | 99 (3.1) | 138 (2.4) | .05 |
| DPP‐4 | 313 (9.9) | 487 (8.6) | .04 |
| Acarbose | 24 (0.8) | 31 (0.5) | .22 |
| Nateglinide | 4 (0.1) | 8 (0.1) | .86 |
| Repaglinide | 47 (1.5) | 59 (1.0) | .07 |
| Pramlintide | 23 (0.7) | 71 (1.3) | .02 |
| GLP‐1 | 114 (3.6) | 240 (4.3) | .15 |
Abbreviations: A1c, glycated hemoglobin; BMI, body mass index; DPP‐4, dipeptidyl peptidase 4; eGFR, estimated glomerular filtration rate; GLP‐1, glucagon‐like peptide‐1.
One possible explanation for increased medication use as renal function diminishes is the increase in patient noncompliance attributable to cost, side effects, gastroparesis, and uremic gastritis. Our study, however, was not designed to assess either patient or physician compliance with various guidelines for BP control. Nor was the study designed to ferret out whether multidrug therapy was being prescribed at lower levels in order to avoid potential therapeutic side effects. It is also possible that differences in antidiabetic polypharmaceutical approaches might result in substantially different antihypertensive therapeutic responses. Other possible explanations relate to pharmacologic stimulation of erythropoiesis as renal function deteriorates or factors coincident with insulin resistance and diabetes control (Table III).
Several interacting mechanisms have been described to explain antihypertensive therapy resistance in type 2 diabetes with obesity and insulin resistance. These include:
A central nervous system reflex in which neighboring centers are inhibited (leptin receptor) or activated (sympathetic receptor).22
An interaction between the renin‐angiotensin‐aldosterone system found in excess adipose tissue and the high BP of obesity.23 Adipose has also been found to secrete a cytokine, which behaves like aldosterone.24
The combination of a vasoconstrictor (angiotensin II) and the absence of a vasodilator (nitric oxide) operating at the level of the vascular endothelium.25
An inhibition of insulin signaling both by angiotensin II excess26 and nitric oxide deficiency.27
In this population of diabetic patients with known hypertension, we determined that prevalence of those classified as having resistant hypertension on the basis of prescribed drug use was markedly higher than that reported in predominantly nondiabetic populations. In our single center, the prevalence of diabetic patients classified as having MDAT and the number of drugs used to control BP are incrementally higher in the presence of reduced kidney function. We note a nearly 10‐fold difference in prevalence of therapy resistance when a population with eGFR of <30 mL/min is compared with one with an eGFR of >90 mL/min. The alarming requirement for three to five classes of drugs to control BP in addition to a diuretic in more than one third of patients deserves further evaluation. For the moment, it is unclear whether the use of multiple agents to control BP in this population adds benefit or produces excess risk.
The cost and burden of multiple therapies directed at hypertension cannot be overestimated and their quantitation has not been adequately evaluated. Although such therapies may be renoprotective in certain populations, and reduce cardiovascular events in populations undergoing renal replacement therapy, the difficulties encountered in populations with stage 4 and 5 CKD as well as diabetes related to BP control, cost, and side effects have not been adequately explored. The multiple current guidelines favoring therapies aimed at biomarker targets (BP, glycated hemoglobin, low‐density lipoprotein) may not reflect the best quality of life result. Perhaps in studying the reasons for apparent resistance of BP control associated with diminished eGFR, we can physiologically target the problem and relieve some of the burden on patients who require huge numbers of pills (and injections) per day.
Study Limitations and Strengths
This is an observational, cross‐sectional study from a single center dedicated to the treatment of diabetes. As such it may not reflect the care given by centers with a broader focus. No attempt was made to influence treatment. The study was undertaken as part of a quality‐of‐care analysis to determine whether a computer data set could adequately demonstrate the extent to which current evidence‐based guidelines were being implemented during a fixed time period. The study was not designed to assess the pathogenesis of hypertension, adequacy of clinical or BP control, diabetes, lipid or renal management, or medication compliance. The study design does not permit assessment of effectiveness of therapy or healthcare outcomes associated with individual or combination medication regimens. In addition, newer antidiabetic agents (liraglutide) that enhance renal sodium excretion were not in widespread use during the time of our review (<7% of patients), an issue also noted in other major studies.28, 29 Recent suggestion that dipeptidyl peptidase 4 inhibitors (sitigliptan) may cause excess incident heart failure cannot be analyzed using the current database.30, 31, 32 The greatest strength (and limitation) of this study derives from its use of a cohort not limited by exclusionary criteria that would be necessary in a formal research study. This snapshot “at the bedside” should be used to better inform future research on the use of multiple drug therapy in the diabetic hypertensive population already burdened by the requirement for multiple drugs to achieve better outcomes. Whatever the cause for MDAT, we suggest that future scientific therapeutic investigations (pharmaceutical and device) among type 2 diabetic patients with “resistant hypertension” or MDAT need to factor eGFR into their estimations of required study size.
Conclusions
When dealing with difficult to control hypertension, if one bases the diagnosis of resistance on the number of drug classes required for control, the prevalence of this diagnosis is higher in type 2 diabetic populations than in reports from mostly nondiabetic cohorts. Our study confirms a strong relationship between multidrug antihypertensive use and lower levels of renal function. Because diabetic patients with renal insufficiency have the greatest expected morbidity and mortality, efforts are warranted to explore appropriate guidelines for hypertension therapy resistance in this population.
J Clin Hypertens (Greenwich). 2016;18:878–883. DOI: 10.1111/jch.12776. © 2016 Wiley Periodicals, Inc.
References
- 1. Persell SD. Prevalence of resistant hypertension in the United States, 2003–2008. Hypertension. 2011;57:1076–1080. [DOI] [PubMed] [Google Scholar]
- 2. Tanner RM, Calhoun DA, Bell EK, et al. Prevalence of apparent treatment‐resistant hypertension among individuals with CKD. Clin J Am Soc Nephrol. 2013;8:1583–90. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Calhoun DA, Jones D, Textor S, et al. Resistant hypertension, diagnosis, evaluation and treatment: a scientific statement of the American Heart Association Professional Education Committee of the Council for High Blood Pressure Research. Hypertension. 2008;51:1403–1419. [DOI] [PubMed] [Google Scholar]
- 4. Chobanian AV, Bakris GL, Black HR, et al. The Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment: the JNC7 report. JAMA. 2003;289:2560–72. [DOI] [PubMed] [Google Scholar]
- 5. Hajjar I, Kotchen TA. Trends in prevalence, awareness, treatment, and control of hypertension in the United States, 1988‐2000. JAMA. 2003;290:199–206. [DOI] [PubMed] [Google Scholar]
- 6. Egan BE, Zhao Y, Axon RN, et al. Uncontrolled and apparent treatment resistant hypertension in the United States, 1988 to 2008. Circulation. 2011;124:1046–58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. 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. JAMA. 2002;288:2981–97. [DOI] [PubMed] [Google Scholar]
- 8. Tsioufis C, Kasiokogias A, Kordalis A, et al. Dynamic resistant hypertension patterns as predictors of cardiovascular morbidity: a 4‐year prospective study. J Hypertens. 2014;32:415–22. [DOI] [PubMed] [Google Scholar]
- 9. Lithovius R, Harjutsalo V, Forsblum C, et al. Antihypertensive treatment and resistant hypertension in patients with type 1 diabetes by stages of diabetic nephropathy. Diabetes Care. 2014;37:709–17. [DOI] [PubMed] [Google Scholar]
- 10. De Nicola L, Gabbai FB, Agarwal R, et al. Prevalence and prognostic roles of resistant hypertension in chronic kidney disease patients. J Am Coll Cardiol. 2013;61:2461–7. [DOI] [PubMed] [Google Scholar]
- 11. Sim JJ, Bhandari SK, Shi J, et al. Characteristics of resistant hypertension in a large ethnically diverse population of an integrated health system. Mayo Clin Proc. 2013;88:1099–107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Daugherty SL, Powers JD, Magid DJ, et al. Incidence and prognosis of resistant hypertension in hypertensive patients. Circulation. 2012;125:1635–1642. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Weitzman D, Chodick G, Shalev V, et al. Prevalence and factors associated with resistant hypertension in a large health maintenance organization in Israel. Hypertension. 2014;64:501–507. [DOI] [PubMed] [Google Scholar]
- 14. Carey RM. Resistant hypertension. Hypertension. 2013;61:746–750. [DOI] [PubMed] [Google Scholar]
- 15. Solini A, Zoppini G, Orsi E, et al, for the Renal Insufficiency and Cardiovascular Events (RIACE) Study Group . Resistant hypertension in patients with type 2 diabetes mellitus: clinical correlates and association with complications. J Hypertens. 2014;32:2401–10. [DOI] [PubMed] [Google Scholar]
- 16. Muntner P, Davis BR, Cushman WC, et al. Treatment‐resistant hypertension and the incidence of cardiovascular disease and end stage renal disease: results from the Antihypertensive and Lipid‐lowering Treatment to prevent Heart Attack Trial (ALLHAT). Hypertension. 2014;64:1012–21. [DOI] [PubMed] [Google Scholar]
- 17. Achelrod D, Wenzel U, Frey S. Systematic review and meta‐analysis of the prevalence of resistant hypertension in treated hypertensive populations. Am J Hypertens 2014;28:355–361. [DOI] [PubMed] [Google Scholar]
- 18. Esler M. Sympathetic nervous system moves toward center stage in cardiovascular medicine: from Thomas Willis to resistant hypertension. Hypertension. 2014;63:e25–e32. [DOI] [PubMed] [Google Scholar]
- 19. Shimbo D, Levitan EB, Booth JB, et al. The contributions of unhealthy lifestyle factors to apparent resistant hypertension: findings from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. J Hypertens. 2013;31:370–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Pfeffer MA, Burdmann EA, Chen CY, et al, for the TREAT Investigators . A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. N Engl J Med 2009;361:2019–32. [DOI] [PubMed] [Google Scholar]
- 21. Weinrauch LA, D'Elia JA, Finn P, et al. Strategies for glucose control in a study population with diabetes, renal disease and anemia (TREAT study). Diabetes Res Clin Pract 2016;113:143–151. [DOI] [PubMed] [Google Scholar]
- 22. Greenfield JR, Miller JW, Keogh JM, et al. Modulation of blood pressure by central melanocortinergic pathways. N Engl J Med. 2009;360:44–52. [DOI] [PubMed] [Google Scholar]
- 23. Schling P, Mallow H, Trindl A, Löffler G. Evidence for a local renin angiotensin system in primary cultured human adipocytes. J Obes Relat Metab Disord. 1999;23:336–411. [DOI] [PubMed] [Google Scholar]
- 24. Goodfriend TL, Ball DL, Egan BM, et al. Epoxy‐keto derivative of linoleic acid stimulates aldosterone secretion. Hypertension 2004;43:358–363. [DOI] [PubMed] [Google Scholar]
- 25. Giani JF, Janjulia T, Kamat N, et al. Renal angiotensin‐converting enzyme is essential for the hypertension induced by nitric oxide synthesis inhibition. J Am Soc Nephrol. 2014;25:2752–2763. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Folli F, Kahn CR, Hansen H, et al. Angiotensin 2 inhibits insulin signaling in aortic smooth muscle cells at multiple levels. J Clin Invest. 1997;100:2158–2169. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Sydow K, Mondon CE, Cooke JP. Insulin resistance: potential role of the endogenous nitric oxide synthase inhibitor ADMA. Vasc Med. 2005;10:S35–43. [DOI] [PubMed] [Google Scholar]
- 28. Lovshin JA, Barnie A, DeAlmeido A, et al. Liraglutide promotes natriuresis but does not increase circulating levels of atrial natriuretic peptide in hypertensive subjects with type 2 diabetes. Diabetes Care. 2015;38:132–139. [DOI] [PubMed] [Google Scholar]
- 29. Zoungas S, Chalmers J, Neal B, et al. Woodward M for the ADVANCE‐ON collaborative group. N Engl J Med. 2014;371:1392–1406.25234206 [Google Scholar]
- 30. Lipska KJ, Ross JS, Miao Y, et al. Less is more: potential overtreatment of diabetes mellitus in older adults with tight glycemic control. JAMA Intern Med 2015;175:356–362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Weir DL, McAllister FA, Senthilselvan A, et al. Sitagliptan use in patients with diabetes and heart failure. J Am Coll Cardiol: Heart Failure. 2014;2:573–585. [DOI] [PubMed] [Google Scholar]
- 32. Bhatt DL, Cavender MA. Do dipeptidyl peptidase‐4 inhibitors increase the risk of heart failure? J Am Coll Cardiol: Heart Failure. 2015;2:583–585. [DOI] [PubMed] [Google Scholar]