Resistant Hypertension and Associated Comorbidities in a Veterans Affairs Population

Abstract

Resistant hypertension (RH) is understudied and its reported prevalence varies with study populations. The authors sought to determine its prevalence and association with certain comorbid conditions in a Veterans Affairs population. This cross‐sectional study utilized demographic and clinical data from 17,466 patients. Chi‐square or t test was used for comparing groups with and without RH. Multivariate logistic regression analysis was used to determine independent associations. Overall, the prevalence of RH was 9%, and 13% of all hypertensive patients met criteria for RH. After adjusting for confounding variables, RH was significantly associated with older age (odds ratio [OR], 1.007), higher body mass index (OR, 1.04), Framingham score (OR, 1.14), and coexisting coronary artery disease, cerebrovascular accident/transient ischemic attack, peripheral vascular disease, congestive heart failure, chronic kidney disease, diabetes mellitus, erectile dysfunction, and metabolic syndrome (OR, 1.3, 1.32, 1.29, 2.88, 2.13, 1.2, 1.12, and 1.2, respectively; all P<.05). Our results indicate a complex interplay of certain comorbid conditions among patients with RH and suggest the need for multifaceted interventions in this high‐risk population to prevent cardiovascular events.

Essential hypertension (HTN) is the most prevalent controllable disease in developed countries, affecting more than 25% of the adult population. Its global disease burden is immense, with 62% of strokes, 49% of heart disease, and 7.5 million deaths per year attributed to HTN.1, 2 National Health and Nutrition Examination Survey (NHANES) data show that HTN has become more prevalent in the past decade, with approximately 74.5 million of US adults affected. Even though HTN awareness and treatment are higher among patients older than 60 years, the proportion of patients with controlled blood pressure (BP) in this age group is lower when compared with the young.3 Multifactorial causes, including financial constraint, cognitive impairment, medication adherence, and polypharmacy, contribute to treatment resistance in the elderly.

Resistant HTN (RH) is a relatively common but significantly understudied clinical condition. In 2008, the American Heart Association defined RH as a BP above goal in spite of concurrent use of three antihypertensive agents of different classes ideally including a diuretic and all at optimal doses or BP controlled with four or more antihypertensive medications.4 Older age, obesity, higher baseline systolic BP, and left ventricular hypertrophy (LVH) have been found to be strong predictors of poor BP control in the Framingham cohort5 and the Antihypertensive and Lipid‐Lowering Treatment to Prevent Heart Attack Trial (ALLHAT).6 Target organ damage in the form of LVH and renal dysfunction as well as atherosclerotic disease, diabetes mellitus, and metabolic syndrome are frequently associated comorbid conditions.4, 7

The exact prevalence of RH is unknown,4 and the reported prevalence of RH varies with study populations. Veterans are at high risk for uncontrolled BP and its complications. We sought to determine the prevalence of RH and its association with other comorbid conditions in a Veterans Affairs (VA) population.

Methods

Patients

VA Northern California Healthcare System's institutional review board approved the study protocol. Electronic medical records (EMRs) were reviewed for 17,466 outpatients enrolled at our VA facility for subspecialty care as well as primary care. Demographic information and clinical data on disease diagnoses, laboratory markers, and medication prescription were collected from June 2009 through December 2010 for this cross‐sectional study.

HTN was defined by International Classification of Diseases, Ninth Revision (ICD‐9) code and antihypertensive medication prescription. RH was diagnosed for all hypertensive patients if BP was uncontrolled (>140/90 mm Hg) on three or more, or controlled on four or more agents, including a thiazide diuretic. Individualized data on medication adherence were not available. However, aggregated data on antihypertensive medication adherence as measured by medication possession ratio (MPR) in our VA facility showed an MPR >80% among 90% of the hypertensive patients. ICD‐9 codes were used for the diagnoses of coronary artery disease (CAD), myocardial infarction (MI), coronary artery bypass grafting (CABG), percutaneous coronary intervention (PCI), cerebrovascular accident (CVA)/transient ischemic attack (TIA), peripheral vascular disease (PVD), congestive heart failure (CHF), chronic kidney disease (CKD), obstructive sleep apnea (OSA), and erectile dysfunction (ED). Diabetes mellitus (DM) was defined by the ICD‐9 code; glycated hemoglobin >6.5%; insulin or oral hypoglycemic agent use; or random blood glucose >200 mg/dL on more than one occasion. Metabolic syndrome (MS) was defined by modified Third Report of the Adult Treatment Panel National Cholesterol Education Program (NCEP‐ATP III) criteria; BMI was used instead of waist circumference.

Statistical Analysis

Student t test or chi‐square test was used where appropriate for comparison between the groups with and without RH. A multivariate logistic regression model was used to control for confounders and to calculate the adjusted odds ratios (ORs) and 95% confidence intervals (CIs) to determine RH‐associated comorbid conditions. Statistical significance was defined as a two‐sided P value <.05. In multivariate logistic regression analysis, RH was used as the dependent variable and the independent variables included age; sex; BMI; Framingham score; current alcohol and tobacco use; diagnosis of DM, CAD, CVA/TIA, PVD, CHF, CKD, ED, OSA, depression, anxiety, and post‐traumatic stress disorder; and use of nonsteroidal anti‐inflammatory drugs (NSAIDs), tricyclic antidepressants, and selective serotonin reuptake inhibitors.

Results

Patient Characteristics and Prevalence of RH

The mean age of the study population was 67 years and the average BMI was 29.6. Ninety‐six percent of patients were men. The overall prevalence of HTN was 64% and RH was 9% among the study population. Thirteen percent of all hypertensive patients met criteria for RH.

Association Between RH and Certain Demographics and Comorbid Conditions

Chi‐square or t test was used for comparing groups with and without RH. Patients with RH were older, with a mean age of 72.9 years, when compared with the non‐RH population. They had significantly higher mean BMI values and higher Framingham scores. The prevalence of certain disease pathologies was higher in the RH group. More patients with RH had a history of MI, PCI, and CABG as well as overall prevalence of CAD. Atherosclerotic disease in other vascular beds, including CVA, TIA, and PVD, was also more prevalent in these patients. Significantly more patients with RH had MS, DM, CHF, CKD, ED, and OSA (Table 1).

Table 1.

Comparison of Characteristics of Patients With and Without Resistant Hypertension

	Resistant Hypertension (n=1576)	No Resistant Hypertension (n=15,890)	P Value
Age, y	72.9±11.0	66.3±14.1	<.001
BMI, kg/m2	31.1±5.8	29.4±5.9	<.001
Current smoker, %	300 (19)	3560 (22)	.225
SBP, mm Hg	151.2±11.5	126.7±15.5	<.001
DBP, mm Hg	74.8±12.1	70.4±10.9	<.001
HR, beats per min	68.7±13.0	72.8±13.1	<.001
Framingham score	21.7±3.3	17.9±5.4	<.001
MS	1194 (75)	8866 (55)	<.001
DM	777 (49)	4099 (25)	<.001
CAD	406 (25)	1922 (12)	<.001
CHF	318 (20)	715 (4.5)	<.001
CVA/TIA	266 (17)	1398 (8.8)	<.001
PVD	438 (27)	2097 (13)	<.001
CKD	321 (20)	937 (5.9)	<.001
ED	476 (30)	3845 (24)	<.001
OSA	43 (2.7)	190 (1.2)	<.001
Glucose, mg/dL	131.6±55.3	119.9±44.3	<.001
Glycated hemoglobin	6.4±1.37	6.1±1.27	<.001
Creatinine, mg/dL	1.47±0.94	1.17±0.52	<.001
LDL cholesterol, mg/dL	95.2±33.4	104.1±34.2	<.001
Statin	929 (59)	6356 (40)	<.001
HCTZ	1576 (100)	3178 (20)	<.001
ACE inhibitor	1134 (72)	4925 (31)	<.001
ARB	236 (15)	795 (5)	<.001
β‐Blocker	1056 (67)	3178 (20)	<.001
CCB	835 (53)	1906 (12)	<.001
Nitrate	94 (6)	317 (2)	<.001
Hydralazine	63 (4)	64 (0.4)	<.001
Spironolactone	79 (5)	159 (1)	<.001
Clonidine	63 (4)	127 (0.8)	<.001
NSAIDs	1071 (68)	10487 (66)	.39
TCA	58 (3.7)	604 (3.8)	.46
SSRI	236 (15)	2542 (16)	.40

Abbreviations: ACE, angiotensin‐converting enzyme; ARB, angiotensin receptor blocker; BMI, body mass index; CAD, coronary artery disease; CCB, calcium channel blocker; CHF, congestive heart failure; CKD, chronic kidney disease; CVA/TIA, cerebrovascular accident/transient ischemic attack; DBP, diastolic blood pressure; DM, diabetes mellitus; ED, erectile dysfunction; HCTZ, hydrochlorothiazide; HR, heart rate; LDL, low‐density lipoprotein cholesterol; MS, metabolic syndrome; NSAIDs, nonsteroidal anti‐inflammatory drugs; OSA, obstructive sleep apnea; PVD, peripheral vascular disease; statin, HMG‐CoA reductase inhibitor; SBP, systolic blood pressure; SSRI, selective serotonin reuptake inhibitors; TCA, tricyclic antidepressant. Categoric variables are expressed as number (percentage) and continuous variables are expressed as mean±standard deviation. P values are based on chi‐square test for categorical and Student t test for continuous variables.

Adjusting for confounding factors, including demographics, certain comorbid conditions and medications, multivariate logistic regression analysis did not change the significant association of RH with older age (OR, 1.007; 95% CI, 1.001–1.014; P=.033), higher BMI (OR, 1.042; 95% CI, 1.031–1.053; P<.001), and higher Framingham score (OR, 1.141; 95% CI, 1.119–1.164; P<.001). The multivariate logistic regression analysis also revealed that some of the comorbid disease processes remained significantly associated with RH. These were MS (OR, 1.204; 95% CI, 1.038–1.398; P=.014), DM (OR, 1.203; 95% CI, 1.056–1.370; P=.005), CAD (OR, 1.304; 95% CI, 1.134–1.5; P<.001), CHF (OR, 2.881; 95% CI, 2.443–3.397; P<.001), CVA/TIA (OR, 1.315; 95% CI, 1.124–1.538; P=.001), PVD (OR, 1.287; 95% CI, 1.124–1.475; P<.001), CKD (OR, 2.128; 95% CI, 1.824–2.483; P<.001), and ED (OR, 1.123; 95% CI, 1.082–1.382; P=.001) (Table 2).

Table 2.

Binary Multivariate Logistic Regression Analysis for Individual Associations of Resistant Hypertension

	Odds Ratio	95% Confidence Interval
Age	1.007	1.001–1.014
BMI	1.042	1.031–1.053
Framingham score	1.141	1.119–1.164
MS	1.204	1.038–1.398
DM	1.203	1.056–1.370
CAD	1.304	1.134–1.500
CHF	2.881	2.443–3.397
CVA/TIA	1.315	1.124–1.538
PVD	1.287	1.124–1.475
CKD	2.128	1.824–2.483
ED	1.123	1.082–1.382

Abbreviations: BMI, body mass index; CAD, coronary artery disease; CHF, congestive heart failure; CKD, chronic kidney disease; CVA/TIA, cerebrovascular accident/transient ischemic attack; DM, diabetes mellitus; ED, erectile dysfunction; MS, metabolic syndrome; PVD, peripheral vascular disease. Odds ratios represented in tabular format are derived from multivariate logistic regression analysis comparing different characteristics between patients with and without resistant hypertension and are not comparable between variables.

Discussion

Prevalence

In this study, we found the prevalence of RH to be 9%. Of all veterans seen at the primary care clinic, 64% had HTN. Among hypertensive patients, 13% qualified as having RH. Our findings fell within the general range of what has been reported in the literature. According to NHANES data, the prevalence of RH among US hypertensive population was estimated at 8.9% and among those being treated at 12.8%.8 Five percent of the patients seen in the primary care setting and up to 50% seen by nephrology specialists have been reported to have treatment resistance.9 Approximately 11% to 18% of patients seen in tertiary care clinics may have RH.10, 11 Clinical trials have reported a higher rate of resistance to antihypertensive therapy. In the large HTN intervention trial ALLHAT, at the completion of 5 years of follow‐up, 27% of patients were taking 3 or more antihypertensive medications.6 A higher occurrence of RH in treatment trials may be explained by the enrollment of older patients at higher cardiovascular risk.12

Age

Following the trend of HTN in general, RH is almost universally more prevalent in the elderly. With a mean age of 64 years,13 veterans are at high risk for uncontrolled BP and its complications. Not surprisingly, we found that patients with RH were significantly older, with a mean age of 72.9 years when compared with 66.3 years in the non‐RH group. This significant association of RH with age is probably a product of arterial stiffening, impaired baroreceptor function, endothelial dysfunction, and oxidative and inflammatory stress accumulated over time. As the population ages, treatment resistance is also expected to rise.

Obesity

Unlike age, controllable correlates of RH such as obesity are potential targets to help reduce eventual end‐organ damage. Obesity is on the rise at an alarming rate and is increasingly affecting the younger population. Continuation of this trend in the United States can be a major setback to efforts for HTN control. Obesity predisposes to treatment resistance14, 15 by activation of renin‐angiotensin‐aldosterone axis and sympathetic overstimulation.16 We found more obese patients in the RH group. This is consistent with results of previous studies including ALLHAT.

Framingham Risk Score

Framingham score takes age, sex, BP, cholesterol, and smoking history into account to provide a composite 10‐year coronary heart disease risk assessment.17 An analysis of NHANES data recently published showed a risk score of more than 20% to be independently associated with apparent treatment‐resistant HTN.18 We found a similar correlation between RH and Framingham score. Patients with RH had a mean risk score of 21.7%, whereas those without RH had a score of 19.7%. However, because of our large sample size, this statistically significant relative difference of 14% between the two groups may represent only a trend.

Diabetes Mellitus

DM and HTN frequently coexist. It has been reported that as many as three or four antihypertensive agents may be required to adequately control BP in patients with diabetes.19 Presence of DM predicted poor BP control in ALLHAT patients.6 Consistently, in our study, more patients in the RH group had comorbid DM. Insulin resistance may partially be responsible for this correlation.

Metabolic Syndrome

Obesity, insulin resistance, dyslipidemia, and HTN comprise MS, which is another predictor of cardiovascular mortality.20 Detrimental effects of increased aldosterone levels have been implicated in the etiology of MS and RH by impairing pancreatic beta cell function, reducing insulin sensitivity, and causing endothelial dysfunction.7

CAD, CHF, and CVA

HTN, as the foremost risk factor for CAD and CVA, is responsible for the majority of cardiovascular morbidity and mortality in the United States. It is also the leading cause of CHF, either directly causing hypertensive heart disease or indirectly contributing to ischemic cardiomyopathy. A large retrospective cohort study with a mean follow‐up of 3.8 years, found significantly higher combined outcomes of death, MI, CHF, CVA, and CKD in RH patients, with a hazard ratio of 1.47.21 RH patients in the Reduction of Atherothrombosis for Continued Health (REACH) registry had a higher composite outcome of cardiovascular death, MI, or CVA at 4 years, with a hazard ratio of 1.11. They also had higher risk of CVA and number of hospitalizations for CHF.22 Accounting for different study design, we found CAD, CHF, and CVA/TIA to be more prevalent in patients with RH when compared with those without RH, with ORs of 1.30, 2.88, and 1.32, respectively.

Chronic Kidney Disease

CKD is a common complication in patients with HTN and DM. Renal dysfunction causes increased sodium and water retention. These patients frequently have fluid overload, which, in turn, makes BP control difficult. Persistently elevated BP causes nephrosclerosis, leading to further kidney damage and perpetuating a vicious cycle. Prevalence of HTN varies inversely with glomerular filtration rate. Adequate BP control slows the progression of glomerular filtration rate decline in patients with proteinuria.23 However, achieving this target is a significant challenge. Only 27% of patients with CKD had BP below the therapeutic target of 140/90 mm Hg in the NHANES data subanalysis.24 Around 15% of nondiabetic patients with CKD had treatment resistance in a cross‐sectional study.25 We found CKD to be almost four times more common in RH patients (20.4% vs 5.9%), with an OR of 2.13. A strong association exists between the two conditions with complex reciprocal interaction.

Peripheral Vascular Disease

PVD results from atherosclerosis in the extremities. HTN is a known risk factor and has been associated with PVD in several large population‐based reports including the Framingham Offspring Study,26 the Atherosclerosis Risk in Communities (ARIC) study, and subanalysis of the NHANES data.27 We found a similar correlation.

Erectile Dysfunction

Endothelial dysfunction and atherosclerosis have also been cited as the underlying pathology for ED.28 In a large managed care claims database, more than 40% of patients with ED had a concomitant diagnosis of HTN,29 and another cross‐sectional study suggested that BP control was associated with a lower prevalence of ED. This association was independent of age and cardiovascular disease.30 Thus, it is not surprising that we found a statistically significant correlation between RH and ED. To our knowledge, this is the first report of such an association between ED and RH.

Obstructive Sleep Apnea

OSA is an important reversible risk factor for secondary HTN. Excessive sympathetic drive in these patients has been attributed as the cause.31 Moreover, OSA severity correlates with poor response to antihypertensive medications. In a study of 41 participants with RH undergoing sleep study, an 83% correlation was found between RH and OSA.32 In our study, 2.7% of the RH population had OSA in comparison to 1.2% of non‐RH patients, a significant difference by chi‐square test (Table 1). This association, however, was not statistically significant in the subsequent multivariate logistic regression analysis. This may represent underreporting of OSA in our EMR as we exclusively used ICD codes for OSA diagnosis. Nevertheless, higher prevalence of OSA in patients with RH deserves special diagnostic considerations and treatment strategies.

Limitations

There are several limitations to our study. First, this cross‐sectional study is designed to suggest association only and does not assess causality. Second, data on patient adherence to medications were not retrievable for this study with relatively large samples. Nonadherent patients frequently have elevated BP at primary care visits and often receive a prescription for additional antihypertensive agents. Third, elevated BP readings from a single clinic visit caused by inappropriate measurement techniques and white‐coat effect could contribute to inaccurate diagnosis. Fourth, some widely used over‐the‐counter drugs, especially NSAIDs and decongestants, can lead to elevated BP. Similarly, excessive consumption of caffeine and alcohol and use of illicit drugs can also lead to difficult‐to‐control HTN. Using available data, we made an effort to adjust for some of these confounding factors by multivariate logistic regression analysis, although a few other variables, such as use of over‐the‐counter NSAIDs and decongestants and illicit drugs, were either incomplete or unavailable in our EMR. Fifth, the retrospective nature of the study with use of ICD‐9 codes for defining disease status leads to underdiagnosis of certain diseases. Lastly, the patients in this study were predominantly men and the findings should thus be generalized with caution.

Conclusions

Overall prevalence of RH in this study fell in the range reported in the general population. We found certain cardiovascular and metabolic diseases and conditions with target organ damage to be significantly more prevalent in patients with RH.

Contributors

Dr Huang was the principal investigator of this study, supervised its conduct and data collection and analysis, and was primarily responsible for the writing of this paper. Dr Acharya was responsible for data verification and organization and the draft of the manuscript. Dr Tringali was responsible for verification of data analysis and manuscript revision. Dr Singh assisted in the draft of this manuscript.

Disclaimer

This material is the result of work supported with resources and the use of facilities at the VA Central California Health Care System. The views expressed herein are those of the authors and do not reflect the official policy or position of the Department of Veterans Affairs.

J Clin Hypertens. 2014;16:741–745. DOI: 10.1111/jch.12410. © 2014 Wiley Periodicals, Inc.