Blood Neutrophil to Lymphocyte Ratio as a Predictor of Hypertension

American Journal of Hypertension, Nov 2015

Hypertension is a significant global public health challenge. Low-grade inflammation is known to facilitate the development of essential hypertension and target-organ hypertensive damage. Neutrophil to lymphocyte ratio (NLR) is a simple and reliable indicator of inflammation that may also be useful in the prediction of hypertension.

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Blood Neutrophil to Lymphocyte Ratio as a Predictor of Hypertension

American Journal of Hypertension Blood Neutrophil to Lymphocyte Ratio as a Predictor of Hypertension Xing Liu 1 2 Qing Zhang 0 2 Hongmei Wu 1 2 Huanmin Du 1 2 Li Liu 0 2 Hongbin Shi 0 2 Chongjin Wang 0 2 Yang Xia 1 2 Xiaoyan Guo 1 2 Chunlei Li 1 2 Xue Bao 1 2 Qian Su 1 2 Shaomei Sun 0 2 Xing Wang 0 2 Ming Zhou 0 2 Qiyu Jia 0 2 Honglin Zhao 0 2 Kun Song 0 2 Kaijun Niu 0 1 2 0 Health Management Centre, Tianjin Medical University General Hospital , Tianjin , China 1 Nutritional Epidemiology Institute and School of Public Health, Tianjin Medical University , Tianjin , China 2 METHODS Participants were recruited from Tianjin Medical University's General Hospital-Health Management Centre. A total of 28,850 initially hypertension-free subjects were followed from 2007 to 2013. Adjusted Cox proportional hazards regression models were used to assess relationships between NLR categories and incidence of hypertension BACKGROUND Hypertension is a significant global public health challenge. Low-grade inflammation is known to facilitate the development of essential hypertension and target-organ hypertensive damage. Neutrophil to lymphocyte ratio (NLR) is a simple and reliable indicator of inflammation that may also be useful in the prediction of hypertension. blood pressure; hypertension; inflammatory markers; neutrophil to lymphocyte ratio - Hypertension is a global public health challenge and often leads to further complications and severe damage of target organs, such as the heart, kidney, and brain.1 Worldwide, hypertension is estimated to affect more than 1 in 3 adults aged 25 and over, or about 1 billion people.2 It was demonstrated that there were about 266 million hypertensive patients in China with more than 10 million patients increased annually.3 Despite extensive study, the precise etiology underlying most hypertension cases remains unknown; however, hypertension, like many other chronic diseases, is characterized by inflammation.4 Low-grade inflammation plays a crucial pathophysiological role in hypertension,5 as it facilitates the development of essential hypertension and target-organ damage.6 Inflammation participates in many processes that contribute to the development of elevated blood pressure (BP); for example, several studies have shown a positive association between hypertension and elevated white blood cell (WBC),7 C-reactive protein and interleukin-6 levels.8 The neutrophil to lymphocyte ratio (NLR) is commonly used as a reliable biomarker of systemic inflammatory status.9 Blood NLR is a simple marker for chronic low-grade inflammation that can be easily obtained from a differential WBC count.10 In addition, NLR is an emerging marker for both cardiac and noncardiac disorders, and recent studies have demonstrated the prognostic value of NLR in stable coronary artery disease,11 acute coronary syndromes,12 heart failure13 as well as patients undergoing percutaneous coronary interventions14 and coronary artery bypass grafting.15 Since hypertension can markedly increase the risk of these diseases, it has been hypothesized that NLR is a useful predictive factor for the incidence of hypertension; however, to date, only a few cross-sectional studies have suggested that NLR is positively related to hypertension.9,16 With this in mind, we designed a ~6-year follow-up cohort METHODS Participants study to investigate how NLR is related to the incidence of hypertension. This cohort study was conducted in Tianjin, is a city of approximately 10.43 million, located in the northeast of the North China Plain. The Tianjin Chronic Low-grade Systemic Inflammation and Health cohort study is a large prospective dynamic study focusing on the relationships between chronic low-grade systemic inflammation and the health status of an adult Tianjin population.17 Individuals who had a routine annual physical examination at the Tianjin Medical University General Hospital’s Health Management Centre (the largest and most comprehensive physical examination center in Tianjin) were recruited. NLR and other blood indicators, BP measurements and anthropometric parameters (height and body weight), provided in the annual health examinations once per year during follow up. All participants provided written informed consent. For this analysis, we chose individuals who participated in the Tianjin Chronic Low-grade Systemic Inflammation and Health cohort study from 2007 to 2013. During this period, there were 53,169 participants who received at least 1 health examination, agreed to participate, and provided informed consent for their data to be analyzed. For each participant, data of the first examination during follow-up was used as their baseline information. We excluded participants who did not undergo WBC counts (n  =  4,229) or who had (at baseline) or developed (during follow up) inflammatory diseases such as gastritis, chronic cholecystitis, nephritis, rhinitis, pharyngitis, bronchitis, myocarditis, rheumatoid arthritis, gout, immune system disorders and others (n  =  1,031), cardiovascular disease (CVD; n = 2,301) or cancer (n = 314), or if they had hypertension (n = 12,485) at baseline. A total of 8,189 participants who did not undergo health examinations during follow-up were also excluded. After these exclusions, the final cohort study population comprised 28,850 participants (Figure 1; follow-up rate: 77.9%; mean ± standard deviation age: 35.4 ± 11.1  years; male: 47.3%). We compared the baseline data from those 8,198 people to that from the whole 28,850 follow-up people. Compared with subjects who participated in this study, those subjects who dropped out had significantly higher age, body mass index (BMI), waist circumference, triglycerides and diastolic blood pressure, lower total cholesterol (TC), low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, and systolic blood pressure. Additionally, more subjects were male, or had hyperlipidemia or diabetes, smokers, drinkers or had a family history of CVD, hypertension, and diabetes. Otherwise, no significant difference was observed between groups. The protocol used for this study was approved by the institutional review board of the Tianjin Medical Participants who provided informed consent (n = 53,169) Follow-up participants (n = 37,039) Participants included in the final follow-up analysis (n = 28,850) Participants for whom leukocyte data were not available were excluded (n = 4,229) Participants with a history of inflammatory disease were excluded (n = 1,031) Participants with a history of cardiovascular disease were excluded (n = 2,301) Participants with a history of cancer were excluded (n = 314) Participants who had hypertension at baseline were excluded (n = 12,485) Participants who did not undergo health examinations during follow up were excluded (n = 8,189) University and conforms to STROBE guidelines for cohort studies. Assessment of NLR After a 12-h fasting period, blood samples were withdrawn from the cephalic vein using a traumatic venipuncture and immediately mixed with EDTA. Complete WBC counts, including neutrophil and lymphocyte counts, were measured using an automated hematology analyzer and expressed as ×1,000 cells/mm3, and NLR values were calculated. In order to investigate how baseline NLR level is related to incidence of hypertension, we divided participants into 5 categories (quintiles) according to NLR level as follows: Level 1 (0.24–1.19), Level 2 (1.19–1.45), Level 3 (1.45–1.72), Level 4 (1.72–2.12), and Level 5 (2.12–16.3). Correlations of baseline WBC with baseline neutrophils, lymphocytes, and the NRL were 0.90, 0.60, and 0.37, respectively (all P values < 0.0001). The correlation of NLR and neutrophils was extremely high (r  =  0.69, P value < 0.0001). Furthermore, 52% of participants had an increasing NLR value during follow-up. The proportion of participants with increasing NLR values across NLR quintiles were 74.1, 63.2, 52.5, 42.3, and 25.6, respectively. Assessment of hypertension BP was measured at least twice by an experienced physician using Andon KD-598 BP monitor and an appropriately sized cuff applied to the sitting subject’s left arm at heart level after 5 min of rest in a seated position. The mean of these 2 measurements was taken as the BP value. Hypertension was defined as average systolic blood pressure ≥ 140 mm Hg or average diastolic blood pressure ≥ 90 mm Hg or use of antihypertension medications. Incident cases of hypertension were defined when subjects were newly diagnosed during follow-up exams and a doctor confirmed the diagnosis. Subjects with secondary hypertension were excluded from incident cases. In most cases, new incidents of hypertension were diagnosed at least twice during different examination cycles; we assigned the date of onset of hypertension as the midpoint between the exam date when hypertension was first noted and the previous exam date. All participants were followed from the baseline examination to the date of incident hypertension or, for those with no hypertension, through the last examination date in 2013. Assessment of other variables Anthropometric parameters (height and body weight) were recorded using a standard protocol and were measured without shoes or outer clothing. BMI was calculated as body weight divided by the square of standing height (kg/m2). Socio-demographic variables, including gender and age, were also assessed. A detailed personal and family history of physical illness and current medications, as well as information on smoking and drinking status, was noted from “yes” or “no” responses to relevant questions from a questionnaire survey. Blood samples for the analysis of fasting blood sugar and lipids were collected in siliconized vacuum plastic tubes. Fasting blood sugar was measured by the glucose oxidase method, TC and triglycerides were measured by enzymatic methods, low-density lipoprotein cholesterol was measured by the polyvinyl sulfuric acid precipitation method, and high-density lipoprotein cholesterol was measured by the chemical precipitation method using appropriate kits on a Cobas 8000 analyzer (Roche, Mannheim, Germany). Statistical analysis Data were analyzed using the Statistical Analysis System version 9.3 for Windows (SAS Institute, Cary, NC). Descriptive data are presented as the mean (95% confidence interval, CI) for adjusted continuous variables and as percent ages for categorical variables. As for all of the continuous variables, as being non-normally distributed, they were logarithmically transformed to obtain substantially normal distributions before analysis and the geometric means (95% CI) were shown. For analysis, incidences of hypertension were used as dependent variables and we categorized baseline NLR into quintiles that were then used as independent variables. For baseline characteristics analysis, differences among NLR levels were examined using analysis of covariance for continuous variables, or multiple logistic regression analysis for proportional variables, after adjustment for age and sex. Bonferroni-corrected P-values were used for comparisons between NLR quintiles. Model fit of multiple logistic regression analysis was evaluated using the Hosmer–Lemeshow goodness-of-fit statistic. For all models, the test was not significant (P ≥ 0.25). The Cox proportional hazards model was used to evaluate the independent effect of NLR on risk of hypertension incidence. We used 4 models in our Cox analysis: a crude model, an age- and sex-adjusted model, an ageand sex- and BMI-adjusted model, and a multivariateadjusted model. The latter of these models adjusted for age at baseline, sex, BMI, baseline systolic blood pressure and diastolic blood pressure, smoking status, drinking status, diabetes (fasting blood glucose ≥ 7.0 mmol/L or history of diabetes), hyperlipidemia (TC ≥ 5.17 mmol/L or triglycerides ≥ 1.7  mmol/L or low-density lipoprotein cholesterol ≥ 3.37  mmol/L or history of hyperlipidemia) and as well as family history of CVD, hypertension, hyperlipidemia, and diabetes. The Cox proportional-hazard regression model with age as the timescale was used to examine the relationship between NLR categories and the incidence of hypertension. The assumption of proportional hazards was checked by examining the interaction term between the NLR categories and logarithm of the follow-up time. The result supported the proportional hazards assumption (P = 0.78). Interactions between the quintiles of NLR and potential confounders were tested by the addition of the cross product terms in the regression model. The tests for interactions between the quintiles of NLR and these potential confounders in the final models were not found to be significant (all P values for interaction > 0.12). Furthermore, as NLR and covariates such as BMI and TC level change over time, we also conducted a time-varying American Journal of Hypertension 28( 11 ) November 2015 1341 Cox regression model. In all models, age was the underlying timescale with entry time defined as the subject’s age in years at recruitment and exit time defined as the subject’s age in years at the diagnosis of hypertension or end of follow-up at 2013 or lost to follow-up. A  hazard ratio (HR) and 95% CI were calculated. The median value of each NLR quintile was used to calculate the P values for the linear trends. A  Pearson’s correlation coefficient (r) was calculated to evaluate the correlation of WBC with neutrophils, lymphocytes, and the NRL. All tests were 2-tailed and P < 0.05 was defined as statistically significant. RESULTS During the 6-year follow-up period between 2007 and 2013, 1,824 individuals developed hypertension. The median duration of follow-up (interquartile range) was 2.63 (2.58–2.68). Age- and sex-adjusted participant characteristics relative to NLR levels for follow-up analysis are presented in Table  1. Compared with participants in the lowest quintile, those in the top 4 NLR quintiles tended to be older and to have higher waist circumference, triglycerides, diastolic blood pressure, but lower TC and highdensity lipoprotein cholesterol. A  higher proportion of participants in the top 4 quintiles were female, overweight and obesity, were more likely to be current smokers and alcohol consumers, and a higher proportion had a family history of CVD, hypertension and diabetes (P for all trends ≤ 0.02). Other than these results, no significant differences were observed between participants among NLR quintiles. Incidence of hypertension was evaluated across the ~6-year follow-up period. During this period, a total of 1,824 participants received a new diagnosis of hypertension. The incidence of hypertension was 23 per 1,000 person-years. In the 5 NLR quintiles, the respective rates of hypertension were 19, 22, 22, 24, and 29 per 1,000 personyears. Table 2 shows the HRs of hypertension incidence by NLR quintiles. In the final multivariate model, adjusted HRs (95% CI) of hypertension were related to the gradual increase of NLR levels, compared with participants with the lowest NLR levels and were as follows: 1.08 (0.92, 1.26), 0.97 (0.83, 1.14), 1.10 (0.94, 1.28), 1.23 (1.06, 1.43), respectively (P for trend < 0.01). A sensitivity analysis was carried out in the participants (n  =  28,114) without type 2 diabetes (n = 736). After final multiple adjustments, the HRs (95% CI) of hypertension were 1.00 (reference), 1.07 (0.92, 1.26), 0.97 (0.83, 1.14), 1.07 (0.91, 1.25), and 1.23 (1.05, 1.43), respectively (P for trend < 0.01), for participants with NLR in the 1st, 2nd, 3rd, 4th, and 5th quintiles (P for trend < 0.01). Moreover, after adjustment for potential of confounders, the HRs (95% CI) of hypertension for increasing quintiles of WBC, neutrophil, and lymphocyte counts were 1.00, 1.00 (0.85, 1.18), 1.11 (0.94, 1.29), 1.17 (1.02, 1.36), and 1.23 (1.06, 1.43; P for trend < 0.01), and 1.00, 1.02 (0.87, 1.21), 1.15 (0.98, 1.35), 1.13 (0.97, 1.33), and 1.36 (1.17, 1.59; P for trend < 0.0001), and 1.00, 0.87 (0.75, 1.01), 0.87 (0.75, 1.01), 0.89 (0.76, 1.04), and 1.01 (0.87, 1.16; P for trend = 0.34), respectively (Figure 2). 1342 American Journal of Hypertension 28( 11 ) November 2015 DISCUSSION The dynamic cohort study examined the relationship between NLR quintiles and the incidence of hypertension in an adult population. To our knowledge, this is the first cohort study to demonstrate that elevated levels of NLR are significantly correlated with the incidence of hypertension. In 2008, Tatsukawa et al. have made a cohort study and demonstrated that elevated WBC count was significantly associated with an increased risk of developing hypertension among Japanese,18 but did not mention the relationship between NLR and hypertension. In Figure 2, we also show the relationship between the quintiles of WBC, neutrophil and lymphocyte counts, and hypertension, make our study more comprehensive. Oral antihypertensive drugs, lifestyle changes (such as exercise and dietary modifications), and traditional medicines (such as Chinese herbal medicines) are used for hypertension therapy, but none achieves complete reversal of symptoms.19 Novel therapeutics or interventions are needed for the prevention and treatment of hypertension. Since inflammation plays an important role in the pathogenesis of hypertension and elevated BP, therapeutic approaches aimed at low-grade inflammation could be effective at controlling hypertension and minimizing hypertensive damage.20 In the vasculature, inflammation can increase proliferation of smooth muscle cells and participates in vascular remodeling.5 In the kidney, inflammation is involved in many hypertensive models, such as salt-sensitive hypertension.21 Several inflammatory markers such as WBC,7,18 C-reactive protein, or interleukin-6 levels8 have been used to predict hypertension; however, most of these are time consuming and expensive.9 NLR has emerged as a straightforward and reliable indicator of the inflammatory status, and has been used to predict prognosis and survival in patients with cancers22 or coronary artery disease.23 Here, we show that the NLR is also an effective predictor of hypertension. Neutrophils secrete mediators that are responsible for the inflammatory response including elastase,24 myeloperoxidase,25 oxygen-free radicals,26 and various hydrolytic enzymes. Such mediators are associated with tissue damage and plaque disruption, and can lead to increased risk of hypertension.27 In addition, neutrophils can lead to the release of reactive oxygen species, which contribute to oxidative stress.28 Oxidative stress has been shown to be a factor in the pathogenesis of hypertension,29 in the vasculature, reactive oxygen species induce vasoconstriction and in the kidney, they cause sodium and water retention.30 In mice experimental models of hypertension, neutrophil counts rise prior to the development of hypertension.31 The immune system plays a fundamental roles in the development of hypertension and its complications.20 Several studies have shown that the adaptive immune response in particular contributes significantly to the pathophysiology of hypertension.30 Lymphocytes, particularly the CD4+ T cells, represent the regulatory arm of the immune system.32 Infusion of alloactivated T cells for treatment of cancer, increases BP in humans,33 preeclampsia (a life-threatening complication of pregnancy associated with high BP) involves activation of both NLRasaPredictorofHypertension D L l; .)36 ) ,ed) f,,,ged) d) ,f,,egd) f,,ed) .)94 ) ) trseo 1–2 )58 .85 6 .88 .27 .80 .18 .04 ,11 .92 .17 4 2 2 leoh .l(512ev   (75=n .,(5333 .437 .331 .96 .,(8377 .,(6844 .,(0511 .,(7622 .,(3711 .399 .(11436 .,(2577 .,(6744 .34 .213 .00 .278 .148 .234 .00 .111 itrceno eL .553 .687 .074 .701 .972 .831 .411 .727 .964 ilpop ) .)12 ) ,fe) d) d) d) d) .49 ) ) .,)0885 .l(7–2214eveL   )(7595=n ,...(348243543 .074 .733 .610 ,...(790687887 ,...(477374574 ,...(109601701 ,...(287282824 ,...(140831931 .504 .,.(3114116411 ,...(727327275 ,...(471864740 .732 .022 .000 .792 .841 .632 .00 .411 ;rsagudDH il.rcsyedeg 2 ) o ir   e lo t  = ng b , n( ra ( y it s n e d h g i h , 0 L lodo ;reT pea . 5 u re .0 jittrcssccebueaognd l..()e2ve119–154L   ,()5770=n ..,.()333303335 .473 .314 .945 d..,.()770877872 ..,.()479774482 d..,.()105041106 ..,.()288852290 d..,.()141401142 .394 ..,.()114411411174 ..,.()724227726 ..,.()460794472 .241 .200 .002 .279 .130 .224 .002 .102 iiil;,tsscseaedaboBPD lilt,rysscssoboodepP frsxageodeandhew l.)sveua P . :.)005< Piit  :rrrr)ccoenoon0< Pit:  ..)rrconeo050< Pi:t  ..)rrcone050< Pi:t  ..)rrcone050< o h d B t h n e c o o iilittftrrcsscsceaoeneha .l.)(11–29eve104L ,  )(6975=n b.,..)(243023232 .448 .428 .538 .,..)(777377577 .,..)(864248448 .,..)(031010210 .,..)(942291288 .,..)(461144143 .9380 .,.)(41146114311 .,..)(327271719 .,..)(724470469 .716 .184 .003 .262 .118 .213 .000 .097 il;,rrvcsxcodaauaeVCD ililt;t/trycyeohoaohpSm ljiirrysssssanaudageeon illlit;frvcscaenuandoene iittfrrrrr(ccnooeoehoneB iilfftt(sLonoequneBNR iiliftf(rronnoeneoLBRN iliftf(rrconnoeenoLBNR iiliftf(rrconnoeenoLBNR ab idn po itc c o ow uq iu u ) ) s u ig 5% cah lhe 2nd r3d t4h r q q s t s 8 a e o (9 e t 2 ) Abbreviations: BMI, body mass index; NLR, neutrophil/lymphocyte ratio. aAnalysis by Cox proportional hazards model. bAdjusted hazard ratios (95% confidence interval; all such values). cAdjusted for age, sex, BMI, baseline systolic blood pressure and diastolic blood pressure, smoking status, drinking status, diabetes (fasting blood glucose ≥7.0 mmol/L or history of diabetes), hyperlipidemia (total cholesterol ≥ 5.17 mmol/L or triglycerides ≥1.7 mmol/L or low-density lipoprotein cholesterol ≥ 3.37 mmol/L or history of hyperlipidemia), and family history of cardiovascular disease, hypertension, hyperlipidemia, and diabetes. humoral and cellular immunity.34 Conversely, suppression of the adaptive immune system can inhibit hypertension. During adaptive immunity, T cells play a crucial role in the BP elevation caused by angiotensin II (a hormone increases thirst, promotes salt retention by the kidney, causes vasoconstriction, and enhances catecholamine release35) response to sodium and volume challenges.36 In recent years, experimental evidence has strongly supported a previously undefined role of T cells in hypertension. For example, human T lymphocytes have been shown to be endowed with a functional active renin–angiotensin system,6 and, a famous experiment by Guzik et  al.37 showed 1344 that mice-lacking T cells (RAG-1/mice) have blunted hypertension and are protected from target-organ damage during angiotensin II infusion. NLR has been associated with worse outcomes in various diseases, including hypertension, as we demonstrate here. High levels of circulating von Willebrand factor and increased NLR might reflect vascular inflammation in hypertensive patients.38 Exercise and catecholamine release can cause increases in both the individual neutrophil and lymphocyte count,39 but will affect the NLR to a lesser extent; as NLR uses counts of both neutrophils and lymphocytes, the result will be more accurate. In addition, the short life of neutrophils (around 7 h) and their brief steady kinetic state might warrant repeated measurements and utilization of a mean NLR for better prognostication.40 As with any novel prognostic indicator, many unknowns remain. First, the normal reference range for NLR has not been systematically explored and established. The reference ranges for absolute neutrophil and lymphocyte counts are wide, making it difficult to establish a “normal” NLR range for our study population. Second, whether the NLR is merely a marker of poor prognosis or whether it plays a substantial part in the pathogenesis of the adverse outcomes remains to be seen. Finally, the 5th quintile had an enormous effect on hypertension; the significant P for trend across quintiles is fully driven by the 5th quintile in this study. Further studies are needed to explore whether there is a useful cutoff NLR value of NLR that might accurately predict the incidence of hypertension. One limitation of this study warrants noting, namely, it is observational in design and thus further intervention trials will be required in order to determine a causal relationship between NLR levels and hypertension. Although the followup rate is relatively high in this study (77.9%), as many participants are relatively healthy compared with subjects who drop out, these results might not accurately reflect the true physical examination status of the cohort. CONCLUSIONS In conclusion, this large-scale epidemiological study demonstrates that elevated NLR levels are significantly correlated with an increased risk of developing hypertension in an adult population. Our results indicate that inflammation may play an important role in the development of hypertension, and that neutrophils and lymphocytes may be involved. These findings may be useful for clarifying the mechanism underlying the pathogenesis of hypertension, and in the development of new therapeutic approaches aimed at lowgrade inflammation for the control of hypertension and hypertensive damage. FUNDING This work was supported by grants from the key technologies R&D program of Tianjin (key project: 11ZCGYSY05700, 12ZCZDSY20400, and 13ZCZDSY20200), the Technologies development program of Beichen District of Tianjin (bcws2013-21 and bc2014-05), the technologies project of Tianjin Binhai New Area (2013-02-04 and 2013-02-06), and the Science Foundation of Tianjin Medical University (2010KY28), China. ACKNOWLEDGMENTS We gratefully acknowledge all of the people who participated in the study and Tianjin Medical University General Hospital-Health Management Centre for creating the possibility to perform the study. DISCLOSURE REFERENCES The authors declared no conflict of interest. 1345 1. Sliwa K , Stewart S , Gersh BJ . Hypertension: a global perspective . Circulation 2011 ; 123 : 2892 - 2896 . 2. World Health Organization. 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Liu, Xing, Zhang, Qing, Wu, Hongmei, Du, Huanmin, Liu, Li, Shi, Hongbin, Wang, Chongjin, Xia, Yang, Guo, Xiaoyan, Li, Chunlei, Bao, Xue, Su, Qian, Sun, Shaomei, Wang, Xing, Zhou, Ming, Jia, Qiyu, Zhao, Honglin, Song, Kun, Niu, Kaijun. Blood Neutrophil to Lymphocyte Ratio as a Predictor of Hypertension, American Journal of Hypertension, 2015, 1339-1346, DOI: 10.1093/ajh/hpv034