BMI) to be relevant to lifespan. These and similar parameters have been well‐characterized as risk factors in the relatively narrow context of cardiovascular disease and mortality in middle to old age. In contrast, we demonstrate here that such measures can be used to predict all‐cause mortality from mid‐adulthood onward. Further, we find that different clinical measurements are predictive of lifespan in different age regimes. Specifically, blood pressure and BMI are predictive of all‐cause mortality from ages 35 to 60, while blood glucose is predictive from ages 57 to 73. Moreover, we find that several of these parameters are best considered as measures of a rate of ‘damage accrual’, such that total historical exposure, rather than current measurement values, is the most relevant risk factor (as with pack‐years of cigarette smoking). In short, we show that simple physiological measurements have broader lifespan‐predictive value than indicated by previous work and that incorporating information from multiple time points can significantly increase that predictive capacity. In general, our results apply equally to both men and women, although some differences exist.Using longitudinal data from a cohort of 1349 participants in the Framingham Heart Study, we show that as early as 28–38 years of age, almost 10% of variation in future lifespan can be predicted from simple clinical parameters. Specifically, we found diastolic and systolic blood pressure, blood glucose, weight, and body mass index ( With its large cohort, consistent longitudinal measurements of basic physiology, and excellent level of follow‐up in terms of rate and length, the FHS offers a unique opportunity to investigate the contributions of biomarkers from very young ages, as well as the evolution of biomarker effectiveness throughout the aging process. The FHS population also allows us to focus on a single longitudinal cohort of individuals, avoiding the possible confounding effects of using additional cross‐sectional data. In this work, we use the Framingham data to understand the proportion of variation in all‐cause mortality that can be predicted from basic clinical measurements. We study these effects from early‐ to mid‐adulthood, and examine how they evolve as a result of the aging process Table .To understand the mortality‐predictive ability of various physiological biomarkers, we began by selecting a well‐defined and homogeneous cohort of individuals to analyze. In order to study the effect of biomarkers on mortality risk at a young age and the effects of incorporating past measurements into predictive models, we chose to focus on the youngest individuals in the original cohort of the Framingham Heart Study. The data from these individuals are both the most extensive and begin earliest in life. Moreover, this cohort, aged 28–38 years at the first Framingham exam, shares a birth decade, limiting the opportunity for confounding effects due to cultural and medical changes over time.Of the hundreds of measurements made by the Framingham investigators, we chose to focus on basic parameters that were not indicators for any specific pathology and which had a wide dynamic range of variation . After eliminating parameters that were not consistently measured across the first 28 clinical exams (over 50 years) of the study, we obtained a panel containing weight, height, systolic and diastolic blood pressure, BMI, and blood glucose.p = 8.52 × 10−32).In order to determine the fraction of variability in lifespan that can be predicted from the first exam, we employed multiple linear regression to assign weights to our six selected measurements. This allowed us to combine the six variables into a single composite ‘risk score’ and to assess its relationship with mortality . The relationship between predicted lifespan and results is shown in Fig. r2 of 0.085, suggesting that these results are indeed not overfit.In this type of analysis, weights for each measured parameter are chosen based on the known survival time of each individual. With sufficiently many parameters, models constructed in this fashion can become ‘overfit’ and not generalize well to future data. In this case, we have few parameter weights (seven: six measurements plus a constant offset) compared to the size of the data, and thus, the model is unlikely to be overfit. To demonstrate this directly, we estimated the ability of the model to generalize to future data using five‐fold cross‐validation, in which different subsets of the data were used to fit the weights vs. evaluate the goodness of that fit. This generated a Pearson Thus, even relatively early in adulthood, a modest but meaningful fraction of future lifespan is already predictable. Further, the lack of sharp demarcations on the scatterplot indicates that this correlation is not driven exclusively by individuals with overt pathologies. Rather, the effect is graded, and is spread over much of the dynamic range that exists for both the clinical measurements and the length of known survival.Next, we asked how the proportion of predictable mortality from single time points changes as the cohort ages. Figure First, we used the weights that were computed to be optimal for predicting lifespan at exam 1, when the mean age of the cohort was 34.5 years  and ‘cumulative’  versions of our variables and analyzed their correlations with mortality. We first attempted several formulations of ‘rates of change’: taking the difference between successive exams; reducing noise by finding the slope of a line fitted to three exam time points rather than two; and smoothing the data by averaging multiple adjacent exams before obtaining pointwise rates of change as above. We found that no ‘rate of change’ formulation was predictive of mortality (data not shown).We next focused on the accumulation hypothesis, in which integrating past values for a given measurement might yield improved predictive ability. To explore the idea of accumulated risk, we constructed variables analogous to pack‐years for smoking by simply summing past measurements, weighed to account for the uneven timing of the Framingham exams. If, as hypothesized, a particular variable represents a ‘rate of change’ of health, then its accumulated history will be more predictive of mortality than its current single time value. Continuing the example of smoking, an individual's accumulated pack‐years of smoking should have a stronger correlation with survival than their current smoking rate. Further, looking at intermediate amounts of history should yield intermediate levels of predictive capacity. For example, if we obtain individuals' smoking history for only the previous 5 years, that variable's correlation with mortality should be greater than the correlation from the single time measurement, but less than the correlation obtained for their full lifetime history of smoking. If, on the other hand, integrating the most recent 5 years or so of history improves predictive abilities but earlier historical data adds nothing, this may suggest that the ‘integrated recent history’ may simply be a de‐noised estimate of the current physiological state. While such denoising may be clinically useful, it is not good evidence that the risk factor truly is cumulative.et al., For this analysis, we begin with the single time correlation at a particular exam , then trace the mortality‐predictive abilities of individual clinical parameters as progressively more years of history are incorporated Fig. . In thisTo further examine these trends, we focused on diastolic blood pressure, BMI and blood glucose, which appear to be cumulative when considered from the perspective of exams 16 and 20. For each variable, Fig. We surveyed the amount of variation in all‐cause mortality that could be predicted from physiology at early‐ to mid‐adulthood, finding a modest but nontrivial effect: 9.7% of variation in mortality at ages 28–38 can be predicted using the common physiological measurements of height, weight, BMI, blood glucose level, and systolic and diastolic blood pressure. In addition, we have shown that our results are generally valid for both men and women. Although there are several quantitative differences in the magnitudes of effects and their precise timing, our overarching conclusions apply to both genders.Further, the amount of predictable mortality generally decreases as a cohort ages and the least healthy individuals die off. This result is consistent with survivorship bias: as the unhealthy individuals die off, the surviving cohort becomes more homogeneous. As a result, the surviving cohort will have less predictable variation in survival; that is, a greater proportion of the variation will be random and not predictable.Specifically, Fig. In parallel, Fig. The simplistic explanation for these observed ‘critical periods’ is that the changing predictive ability of blood glucose and other measurements is entirely due to the aging process: In general, perhaps blood pressure becomes a less important predictor with increasing age while the predictive value of blood glucose increases. This interpretation, however, is confounded by the changing life habits of the American population over recent history. Shifts in diet and lifestyle have steadily increased the contribution of diabetes mellitus to morbidity and mortality over the past half‐century, and advances in hypertension treatment have altered the physiological interpretation of blood pressure measurements. Disentangling these effects calls for additional analysis of both the Framingham data as well as other cohorts.In addition to surveying mortality predictivity in the single‐time‐point context, we investigated trends in variables over time. Rates of change for height, weight, BMI, blood glucose level, and systolic and diastolic blood pressure were utterly unpredictive of future mortality, despite several different approaches to estimating these rates of change. However, in many cases the measured variables' accumulated history yielded substantially higher correlations in comparison with the single‐time‐point context.Specifically, the ability of diastolic blood pressure and BMI to predict all‐cause mortality risk increases steadily and roughly linearly as more historical information is included for individuals below the age of 67. For blood glucose, this effect is observed most prominently from the age 58 onward. In conjunction with our result that indicates that blood glucose is mortality‐predictive at later ages than blood pressure and BMI, these ‘accumulating regimes’ indicate that these variables' effects on mortality are cumulative.et al., et al., This is consistent with the current understanding of the harms mediated by obesity, high blood glucose, and high blood pressure. While the precise mechanisms by which high blood pressure is pathological are still a subject of active research, the consensus so far is that the hemodynamic forces of hypertension initiate a signal which is transduced by endothelial cells, initiating various pathways involving ion channels, growth factors, extracellular matrix interactions, and various other molecular components  were computed using the Python programming language and associated packages.It should be noted that although we made every effort to reconstruct the Framingham and Pooled Cohort Equations risk scores as completely as possible, the smoking and high‐density lipoprotein cholesterol terms had to be excluded due to the lack of consistent longitudinal measurement in the Framingham Heart Study. For example, early blood cholesterol measurements did not distinguish between high‐, low‐, and very low‐density lipoproteins. The data from smoking questionnaires also varied among clinical exams, and were difficult to interpret consistently for all longitudinal time points.To minimize the confounding effects of blood pressure treatment in Figs Pulse pressure, a derived variable defined as the difference between an individual's systolic and diastolic blood pressures, was included as a seventh variable in our analysis from Fig. To adjust for unequal timing of clinical exams, we assumed that at any given point in time, each patient has the same measurement as the closest clinical exam. For example, if a patient has a measured systolic blood pressure (in mm Hg) of 120 in 1960, 130 in 1966, and 140 in 1976, our analysis would use this adjustment to assign blood pressures of 120 for 1960–1963, 130 for 1964–1971, and 140 for 1972–1976. Further, to avoid artificially diminishing the impact of the first and last available time points, we pad the first and last exams with half of the average interexam period. In the given example, we would actually assign blood pressures of 120 for 1956–1963, 130 for 1964–1971, and 140 for 1972–1980.ZP and WZ are supported by NIH grant R00 AG042487 and Longer Life Foundation grant 2015‐008. WZ is additionally supported by NIH grant 5T32 GM07200.None declared.WZ and ZP designed the experiments. WZ carried out the analysis, and WZ and ZP wrote the manuscript.Fig. S1. For men in early‐to‐mid adulthood (participants aged 28–38), 9.3% of variation in future lifespan can be predicted from a weighted combination of systolic and diastolic blood pressure, blood glucose, height, weight, and body mass index.Fig. S2. For women in early‐to‐mid adulthood (participants aged 28–38), 6.6% of variation in future lifespan can be predicted from a weighted combination of systolic and diastolic blood pressure, blood glucose, height, weight, and body mass index.Fig. S3. The individual variables' ability to predict survival in a single‐time point context, stratified by gender.Click here for additional data file.


Supplemental Digital Content is available in the text Glycated albumin (GA) exhibits atherogenic effects and increased serum GA levels are associated with the development of cardiovascular complications in diabetic patients. GA production also increases with aging, oxidative stress, and renal dysfunction. We performed this study to further ascertain the association between GA and arterial stiffness in nondiabetic chronic kidney disease (CKD) patients.We enrolled 129 nondiabetic CKD patients. Arterial stiffness was measured by brachial-ankle pulse wave velocity (baPWV) using a volume plethysmographic instrument along with simultaneous measurements of GA. Insulin resistance was determined with the homeostatic model assessment. The estimated glomerular filtration rate was calculated using serum creatinine and cystatin C according to the CKD-EPI Creatinine-Cystatin C equation adjusted for age, sex, and race (eGFRcr-cys).P = 0.004). In the subgroup analysis, the patients who had both a higher GA level and a lower eGFRcr-cys, showed the highest baPWV compared with patients with a higher GA or a lower GFR alone.Nondiabetic CKD patients with arterial stiffness (baPWV ≥1400 cm/s) showed higher GA levels than those without arterial stiffness  and fasting serum glucose level , whereas The homeostatic model assessment of insulin resistance did not show any significant correlation with baPWV. Systolic blood pressure (r = +0.401 P < 0.001), age , high-density lipoprotein (HDL)-cholesterol level , and eGFRcr-cys  had a significant correlation with baPWV. According to multivariable logistic regression analysis, higher GA and systolic blood pressure were the independent risk factors affecting arterial stiffness.By Spearman's correlation analysis, GA correlated significantly with baPWV (Our results suggest that serum GA is a potential risk factor of arterial stiffness in nondiabetic CKD patients. Inflammation, malnutrition, endothelial dysfunction, and albuminuria are frequently observed in CKD patients and they have been reported as nontraditional risk factors contributing to increased cardiovascular mortality rate.5Cardiovascular disease (CVD) is a major cause of death in chronic kidney disease (CKD) patients.8 Arterial stiffness in CKD patients is of multifactorial etiologies including old age, vascular calcification, hypertension, inflammation, uremic toxins, and the renin-angiotensin-aldosterone system.9 Recent studies have identified accumulation of advanced glycation end products (AGEs) as a novel contributor to arterial stiffening. AGE formation is markedly enhanced in diabetics because of sustained hyperglycemia. In uremia, however, the presence of carbonyl stress contributes to AGE modification of proteins, and plasma AGE levels rise dramatically, independent of hyperglycemia. Therefore, AGE concentrations in excess of normal aging or diabetes are frequently found in uremic plasma, irrespective of the presence of diabetes. The accumulation of AGEs or binding of AGEs to receptors in the vessel wall is associated with the cross-linking of collagen and induction of cell signaling, which result in oxidative stress, increased expression of cytokines and adhesion molecules, and activation of nuclear factor–kappa B (NF-kB). The augmentation of these events would result in the increased arterial stiffness observed in CKD patients.13Increased arterial stiffness plays an important role in the causation of CVD in CKD patients and is regarded as a nontraditional risk factor for CVD in CKD patients. Moreover, several studies have suggested that arterial stiffness itself may also contribute to the progression of CKD.1C) in hemodialysis patients with diabetes. In addition to its role as a sensitive marker of glycemic status, there is growing evidence that GA is associated with increased oxidative stress and endothelial injury resulting in diabetic vasculopathy.14 Increased GA concentrations are associated with accelerated atherosclerosis as well as presence and severity of coronary artery disease in type 2 diabetic patients.17 Furthermore, GA demonstrated significant positive correlation with arterial stiffness measured by brachial-ankle pulse wave velocity (baPWV) values in diabetic hemodialysis patients.18 These studies support the role of GA in predicting diabetic vascular complications.Glycated albumin (GA), a precursor for generation of AGEs, is the major form of circulating Amadori-type glycated proteins. It has been reported to be a better glycemic indicator than glycated hemoglobin , and the amount of proteinuria.19 Few clinical studies have examined the role of GA in predicting nondiabetic vascular complications. Therefore, we aimed to investigate whether elevated GA levels are associated with increased arterial stiffness in nondiabetic CKD patients.In nondiabetic participants with mild-to-advanced CKD, GA levels were shown to have a significant negative correlation with glomerular filtration rate (GFR) and were independent of HbA2 with or without the presence of kidney damage. Kidney damage for >3 months was defined as structural or functional abnormalities of the kidney with or without decreased GFR, manifested by either pathologic abnormalities or markers of kidney damage including abnormalities in the composition of the blood or urine or on imaging tests.20 The eGFR was calculated by serum creatinine and cystatin C using the CKD-EPI creatinine-cystatin C equation adjusted for age, sex, and race.21 A medical history and a physical examination were performed to gather additional information, including sex, underlying disease that may have caused CKD, comorbidity including cardiovascular disease and cerebrovascular disease, use of antihypertensive agents , statin use, blood pressure, and BMI (kg/m2). The laboratory findings measured on the day of baPWV assessment such as hemoglobin, fasting serum glucose, insulin, albumin, total cholesterol, triglycerides, high-density lipoprotein (HDL)-cholesterol, low-density lipoprotein (LDL)-cholesterol, serum creatinine, blood urea nitrogen, cystatin C, urine protein-creatinine ratio (UPCR), and GA were included in this study. Serum GA levels were determined using an enzymatic method . The coefficient of variation for GA was 2.49% at 0.6 g/dL and 1.81% at 1.5 g/dL. Insulin resistance was calculated by the homeostatic model assessment of insulin resistance (HOMA-IR) index (plasma glucose [mmol] × [plasma insulin level/22.5]).23One hundred twenty-nine nondiabetic CKD patients were enrolled during their routine clinical visits between March 2012 and October 2013. All patients were diagnosed with CKD according to the National Kidney Foundation K/DOQI Guidelines based on an estimated GFR (eGFR) of <60 mL/min/1.73 mThis study was approved by the Institutional Review Board (3–2014–0234) of Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea.24 Patients had abstained from caffeine and any other medications, including antihypertensive agents, for at least 12 hours before the baPWV assessment. The baPWV measurements were obtained at the bedside of each participant using a volume plethysmographic instrument . Assessments of both baPWV values were performed after at least 5 minutes of rest in the supine position in an air-conditioned room (24°C ∼26°C). For our analysis, the mean baPWV was used. The validity, reliability, and reproducibility of this instrument were assessed in a previous study.24 The participants with baPWV value of ≥1400 cm/s were defined as “Stiffness” group, whereas those with baPWV <1400 cm/s were grouped as “non-stiffness” group, as previously reported.25Arterial stiffness was assessed by baPWV, as previously reported.®) version 20.0 . All continuous variables are described as the median (interquartile range) based on results from Kolmogorov-Smirnov tests, which identified data that were not normally distributed. Categorical data are expressed as the number with percentages. Statistical comparisons between groups were performed using Mann-Whitney U tests or χ2 tests, both nonparametric statistical methods. Spearman correlation coefficient was used for comparisons between pairs of variables. The predictive values of HOMA-IR, fasting glucose, and GA for increased baPWV were calculated by constructing receiver-operating characteristic (ROC) curves, and comparison of the ROC curves was performed using the Delong method. The value of the cutoff point for GA for predicting arterial stiffness was calculated using the Youden method.26Statistical analyses were performed using the Statistical Package for the Social Sciences -Bonferroni correction for multiple testing.Multivariable logistic regression analyses were used to estimate multiple correlations between arterial stiffness and clinical and laboratory risk factors. A 2 and the median GA levels were 13.6%. The median baPWV was 1456.5 cm/s. Patient characteristics for males and females are included in sTable 1.The baseline characteristics of participants are shown in Table P = 0.004, Table Table We also constructed receiver-operating characteristics (ROC) curves to predict arterial stiffness based on GA levels or other glycemic indices. The area under the ROC curve (AUC) of GA levels for arterial stiffness was significantly larger than that of HOMA-IR or fasting glucose levels    Table .2), whereas 77 patients (59.7%) were classified in the “Higher GFR group” (eGFRcr-cys greater than 60 mL/min/1.73 m2). In the “Lower GFR” group, UPCR and GA levels were higher, and eGFRcr-cys values were lower than those in the “Higher GFR” group (Table P = 0.011)  were classified in the “Lower GFR group” . As a result, the patients who had higher GA levels with a lower eGFR (Group I) showed the highest baPWV among the 4 subgroups . However, no significant differences were found between the group with a lower GA and a higher GFR and the group with a higher GA alone or the group that only had lower eGFR (P = 0.838)  and fasting glucose level , whereas HOMA-IR did not show any significant correlation with baPWV  and age  were significantly associated with baPWV  and eGFRcr-cys  showed a significant negative correlation with baPWV  and systolic blood pressure  were significant independent factors affecting arterial stiffness , male sex, systolic blood pressure, and serum HDL-cholesterol, were entered as the independent variables affecting arterial stiffness. Higher GA  in patients with type 2 diabetes mellitus without any coronary heart disease and peripheral artery disease.32 Moreover, a retrospective longitudinal study has shown that the serum level of GA predicted progression of carotid IMT in patients with type 2 diabetes mellitus after adjustment of common atherogenic risk factors such as age, sex, and LDL-cholesterol.15 Taken together, GA could be considered to be an atherogenic protein in the development of diabetic atherosclerosis.32 Although there is no direct histologic evidence demonstrating GA involvement in arterial stiffness, the above findings suggest that increased GA causally contributes to diabetic vasculopathy. The present study identified a relationship between GA and PWV independent of fasting glucose and insulin resistance in non-diabetic CKD patients. These results suggest that GA could be a biomarker of arterial stiffness beyond glucose metabolism in nondiabetic CKD patients.The formation of AGEs is an important pathway in the development of arterial stiffness in diabetic patients. Recent experimental studies have proposed that GA may also play a role in the mechanism of increased arterial stiffness in diabetes. In vitro experiments have demonstrated that GA promotes inflammation via NF-kB activation in endothelial cells and stimulates vascular smooth muscle cell proliferation.1C, systolic blood pressure, BMI, and total cholesterol in multivariate analysis.20 Our results showed that participants with higher GA levels had significantly lower eGFRcr-cys and also demonstrated the significant negative association between eGFRcr-cys and GA levels in nondiabetic CKD patients (data not shown). However, we did not find any significant association between eGFRcr-cys and baPWV after adjusting GA levels, age, sex, and HDL-cholesterol levels. GA might be considered as a powerful risk factor affecting on arterial stiffness in non-diabetic CKD patients regardless of renal function in the present study.Ma et al implied that the impact of GA to eGFR could be masked because the glycemic status strongly affects the GA concentration in diabetic patients. They demonstrated that GA concentrations were significantly correlated with GFR only in nodiabetic CKD patients even after adjusting for proteinuria, hematocrit, HbA29 Therefore, the accumulation of GA as a result of impaired renal clearance was assumed to play an important role in the progression of vasculopathy in CKD patients via the promotion of oxidative stress, production of inflammatory cytokines, and endothelial damage.14GA was also reported to stimulate TGF-β and increase oxidative stress, which could induce vasculopathy in experimental models.37 In stage 3 CKD patients, eGFR was not an independent determinant, but traditional risk factors including age, mean arterial pressure, and diabetes were the strongest independent determinants of a higher PWV.33 Sengstock et al reported a significant relationship between GFR and PWV, but only 2% of the variation in PWV could be explained by GFR in multivariate analysis when conventional determinants of arterial stiffness, including age, systolic blood pressure, diabetes, and obesity, were analyzed as covariates.36 These results suggested that previous reports regarding the relationship of renal insufficiency and arterial stiffness might be attributable to common underlying CVD risk factors in CKD patients. The present study also demonstrated that GFR could not be an independent determinant of arterial stiffness in nondiabetic CKD patients in multivariable regression analysis.On the contrary, several recent studies have reported that the association of arterial stiffness with different stages of CKD or GFR was unsubstantiated. Although the univariate analysis showed a significant association of arterial stiffness and GFR, traditional risk factors for CVD might be more important determinants of arterial stiffness than GFR in multivariate analysis.2. Taken together, these findings suggested that nondiabetic CKD patients with increased GA and impaired renal function should be closely monitored for the development of arterial stiffness.To investigate which factors profoundly influence increased arterial stiffness in nondiabetic CKD patients, we performed a subgroup analysis of the PWV according to the GA levels and eGFR. The subgroup with both an increased GA and impaired renal function also had the highest PWV compared with the other subgroups. Interestingly, GA levels showed a significantly positive correlation only in CKD patients with impaired renal function compared with those in CKD patients with eGFRcr-cys ≥60 mL/min/1.73 m38 Recently, baPWV has been shown to represent both central and peripheral arterial stiffness and is regarded as a useful tool for evaluating the risk assessment of CVD towing to the ease of the measurement technique relative to that of cfPWV.38There are several limitations to this report. Our observations were cross-sectional in nature with a small sample size. Therefore, a lack of understanding regarding the exact relationship between GA and arterial stiffness still exists. Prospective studies should be performed to determine whether increased GA can predict the progression of arterial stiffness in CKD. Second, urinary glycosylated protein levels were not obtained; therefore, we could not determine whether increased GA levels were induced by impaired renal clearance or glycemic status. However, only nondiabetic CKD patients with lower mean GA levels than those reported for diabetic patients were enrolled in this study. Therefore, increased GA itself could be meaningful in the progression of vasculopathy as a risk for CVD in nondiabetic CKD patients, regardless of impaired renal clearance. Finally, baPWV was used as a measurement of arterial stiffness instead of carotid-femoral PWV (cfPWV).In conclusion, GA showed a significant correlation with baPWV and was the independent risk factor affecting baPWV in nondiabetic CKD patients. Additionally, patients who have higher GA levels together with lower eGFRcr-cys should be monitored for arterial stiffness carefully. The measurement of serum GA concentrations may be predictive of arterial stiffness in nondiabetic CKD patients.


To assess the intraocular pressure (IOP) and its association in children in a population living in an oasis in the Gobi Desert.The cross-sectional school-based study included all schools in the Ejina region. The children underwent an ophthalmic examination, non-contact tonometry and measurement of blood pressure and body height and weight.P<0.001; standardized coefficient beta: −0.13; regression coefficient B: −0.13; 95% Confidence interval (CI):−0.18, −0.07), higher diastolic blood pressure , higher corneal refractive power , more myopic refractive error , and Han Chinese ethnicity of the father . If age and diastolic blood pressure were dropped, higher IOP was associated with higher estimated cerebrospinal fluid pressure (CSFP)  after adjusting for higher corneal refractive power (P<0.001) and Han Chinese ethnicity of the father (P = 0.04). Correspondingly, higher IOP of the left eye was associated with younger age , female gender , higher corneal refractive power , more myopic refractive error , and higher estimated CSFP .Out of eligible 1911 children, 1565 (81.9%) children with a mean age of 11.9±3.5 years (range: 6–21 years) participated. Mean spherical refractive error was −1.58±2.00 diopters. In multivariate analysis, higher IOP (right eye) was associated with younger age (In school children, higher IOP was associated with steeper corneal curvature and with younger age and higher blood pressure, or alternatively, with higher estimated CSFP. Corneal curvature radius should be included in the correction of IOP measurements. The potential association between IOP and CSFP as also assumed in adults may warrant further research. Intraocular pressure (IOP) is one of an important variable for the physiology and pathophysiology of the eye. Its normal distribution and its associations with other ocular and systemic parameters have been examined in numerous preceding investigations 2 in the western part of the Chinese province of Inner Mongolia. The territory of the oasis stretches from 100.90° to 101.42° East longitude and from 41.85° to 42.50° North latitude. With extremely arid conditions, the study area belongs to the north temperature climate zone with a mean annual precipitation of approximately 40 mm and a mean pan evaporation of 3700 and 4000 mm. Average winter temperature minimums are close to −40°C, while summertime temperatures are warm to hot, with highs that range up to 50°C. The main vegetation are poplar trees. The study included all three schools in Ejinaqi which has a total population of 18,030 inhabitants . The next settlement is located in a distance of approximately 400 km. Ejinaqi can be reached by train  and by road.The Desert Gobi Children Eye Study was a cross-sectional, school-based study which was performed in city oasis of Ejinaqi, locating in the most western part of the Chinese province of Inner Mongolia. The Ethics Board of the Affiliated Hospital of Inner Mongolia Medical University Hohhot and the local Administration of the Education and School Board of Ejinaqi approved the study and informed written consent was obtained from the parents or guardians of all children. Ejinaqi oasis in the Gobi desert is located in the Ejinaqi region which covers an area of 114,000kmThe three schools in Ejinaqi (Ejinaqi primary school (911 students), Ejinaqi middle school (765 students), and Minority school (235 students)) included altogether 1911 children with all children from Ejinaqi attending one of the three schools. All children underwent an ophthalmological examination including measurement of presenting visual acuity and uncorrected visual acuity, a slit lamp-based examination of the anterior ocular segment, and tonometry. IOP was measured by a non-contact tonometer . Ocular motility, binocularity and presence of strabismus was examined. After instilling 1% cyclopentolate eye drops  at least three times, cycloplegia was achieved and auto-refractometry was performed . Each eye was measured at least 3 times. The spherical equivalent of the refractive error was defined as the spherical value of refractive error plus one half of the cylindrical value. After medical mydriasis, ophthalmoscopy was carried out for examination of the fundus.The non-ophthalmological examination included measurement of body height (using a stadiometer) and body weight, heart rate and blood pressure . The body mass index was calculated as the ratio of body weight (expressed in kg) divided by the square of body height (expressed in m).2] + 0.16 × Diastolic Blood Pressure [mmHg] – 0.18 × Age [Years] - 1.91 Using the measurements of diastolic blood pressure and body mass index, we estimated the cerebrospinal fluid pressure (CSFP) using the formula of CSFP [mmHg]  =  0.44 × Body Mass Index [kg/mP-value ≤0.10). All P-values were based on two-sided test and were considered statistically significant if less than 0.05.Statistical analysis was performed using a commercially available statistical software package . The normal distribution of data was tested using the Kolmogorov-Smirnov test. As a first step of the statistical analysis, we calculated the mean and standard deviations of the parameters. As a second step, we search for associations between IOP and other ocular and systemic parameters in a univariate analysis. As a first step, we performed a multivariate regression analysis, with IOP as the dependent variable and all those parameters as independent variables which were significantly associated with IOP in the univariate analysis  children (801 (51.2%) boys) with a mean age of 11.9±3.5 years  . Mean spP<0.001). Mean body mass index (BMI) was 19.1±4.0 kg/m2, with 6.2% of the children having a BMI higher than 25 and ≤30, and 1.5% of the children having a BMI higher than 30.Mean IOP was 17.1±3.6 mm Hg  in the right eye and 17.1±3.4 mm Hg  in the left eye. For both eyes, the distribution of IOP showed approximately a Gaussian distribution curve with a minor skew to the right . For botP<0.05).When divided into three age groups, mean systolic and diastolic blood pressure and mean body mass index increased with older age group while the mean IOP decreased . Within P<0.001; standardized coefficient beta: −0.07; regression coefficient B: −0.07; 95%CI: −0.11, −0.02) (P = 0.02), higher blood pressure (P<0.001), higher estimated CSFP (P<0.001) (P = 0.04), and higher keratometric readings (P<0.001)  . In univP<0.001) , Han ChiP<0.001) .P-value ≤0.10. In a first step, we dropped the parameters of mean blood pressure, systolic blood pressure and body weight from the list of independent variables due to the collinearity with diastolic blood pressure and with body mass index. We then dropped in a combination of stepwise, forward and backward regression analysis, all those parameters which were no longer significantly associated with IOP in the multivariate analysis. In the final model, higher IOP of the right eye was significantly associated with the non-ocular parameters of younger age (P<0.001), higher diastolic blood pressure (P<0.001), higher corneal refractive power (P<0.001), more myopic refractive error (P = 0.035), and Han Chinese ethnicity of the father (P = 0.03) , higher corneal refractive power , and Han Chinese ethnicity of the father .We then performed a multivariate linear regression analysis, which included intraocular pressure as the dependent variable and all those parameters as independent variables which were associated with intraocular pressure in the univariate analysis with a  = 0.03) . If age P<0.001), higher diastolic blood pressure (P<0.001), higher corneal refractive power (P<0.001), and additionally, with female gender (P<0.001) , female gender , higher corneal refractive power , and higher estimated CSFP .If the IOP of the left eye was taken as dependent variable in the multivariate analysis, similar results were obtained: higher IOP of the left eyes was associated with younger age (P<0.001) . If diasP<0.001) associated with higher estimated CSFP. In the multivariate model, IOP was not significantly associated with BMI.In our population-based study on school children in an oasis in the Gobi Desert, higher IOP was significantly associated with younger age, higher diastolic blood pressure, steeper cornea and more myopic refractive error. If diastolic blood pressure were dropped from the analysis in the otherwise unchanged statistical model, higher IOP was significantly  again agrees with preceding studies on adults in which similar correlation have been reported In contrast to previous studies on adults, IOP was not significantly associated with BMI in our study population IOP decreased with older age in our study population –4. TheseHigher IOP was associated with higher estimated CSFP in the multivariate analysis in our study, if diastolic blood pressure or additionally age . With all limitations of the formula to estimate the CSFP, the finding may point to an association between IOP and CSFP. A similar relationship has been measured in adults using lumbar pressure measurements of CSFP, and has also been postulated in other population-based studies of various ethnicities Potential limitations of our study should be mentioned. First, the oasis city of Ejinaqi in West China is not representative for whole China. For the vast Western region of China, however, our study was the first one to report on IOP in children. Second, as in any population-based study, the participation rate is of concern. In our study, the response rate of 81.9% of eligible children participating may be sufficient as basis for a population-based statistical analysis. Third, we did not measure central corneal thickness which without doubt influences the IOP measurements. Previous studies on adults showed however, that with or without inclusion of central corneal thickness into the multivariate model, higher IOP was associated with higher blood pressure and flatter cornea shape In conclusion, higher IOP in school children in West China was associated with steeper corneal curvature and with younger age and higher blood pressure, or alternatively, with higher estimated CSFP. Corneal curvature radius should be included for the correction of IOP measurements. The potential association between IOP and CSFP as also assumed in adults may warrant further research.


Hypertrophic cardiomyopathy (HCM) is the most common cause of sudden cardiac death (SCD) in young adults, mainly ascribed to ventricular tachycardia (VT). Assuming that VT is the major cause of (pre-) syncope in HCM patients, its occurrence is essential for SCD risk stratification and primarily preventive ICD-implantation. However, evidence of VT during syncope is often missing. As the differentiation of potential lethal causes for syncope such as VT from more harmless reasons is crucial, HCM patients were screened for orthostatic dysregulation by using a simple orthostatic blood pressure test.Over 15 months  100 HCM patients  were evaluated for (pre-)syncope and VT  within the last five years. Eighty patients underwent an orthostatic blood pressure test. Logistic regression models were used for statistical analysis.In older patients (>40 yrs) a positive orthostatic test result increased the chance of (pre-) syncope by a factor of 63 . No correlation with VT was shown. A prolonged QTc interval also increased the chance of (pre-) syncope by a factor of 6.6 .The orthostatic blood pressure test is highly valuable for evaluation of syncope and presyncope especially in older HCM patients, suggesting that orthostatic syncope might be more relevant than previously assumed. Considering the high complication rates due to ICD therapies, this test may provide useful information for the evaluation of syncope in individual risk stratification and may help to prevent unnecessary device implantations, especially in older HCM patients. Hypertrophic cardiomyopathy (HCM) is the most common monogenic inherited cardiovascular disease and the most frequent cause of sudden cardiac death (SCD) in young athletes, while being a less common cause in the elderly . As syncThe orthostatic blood pressure test is part of cardiologic routine in evaluating otherwise unexplained vertigo and syncope in non-HCM patients and is proven to be useful for the diagnosis of orthostatic dysregulation . HoweverIn this regard, a single centre observational study was performed to analyse the relationship between orthostatic dysregulation and the occurrence of cardiac adverse events, such as syncope, presyncope and VT in HCM patients. In addition, QTc prolongation as an independent risk factor for VT was also assessed.One hundred HCM patients ≥ 18 yrs) were recruited between January 2011 and June 2013 and observed for a median duration of 15 months  in our outpatient clinic. Diagnosis of HCM was based on two-dimensional echocardiographic evidence of a hypertrophied, non-dilated left ventricle with maximum wall thickness of ≥ 15 mm, in the absence of abnormal loading conditions or another cardiac or systemic disease that could produce the magnitude of hypertrophy evident , dynamic yrs were; 20) in The study protocol was in line with the principles outlined in the Declaration of Helsinki. The research protocol was approved by the local ethics committee of the “Ärztekammer Hamburg”, Germany, and all subjects gave written informed consent to participate in the study.Adverse events were defined as the occurrence of not otherwise explained syncope and presyncope, or documented VT. Twice a year each patient was interviewed for syncope and presyncope during their routine visits. In 35 patients with implanted devices, the device’s memory was read out to detect VT. In patients without a device, an ambulatory 24h-ECG was performed at least once a year. A non-sustained VT was defined as a ventricular run of more than three action potentials [A 12-lead electrocardiogram (ECG) was routinely performed at each visit. The QTc interval represents the duration of cardiac depolarisation and subsequent repolarisation adjusted to heart frequency . AutomatTwo-dimensional transthoracic echocardiography was performed using an E133 Philips ultrasound system, assessing LV ejection fraction and maximum end-diastolic wall thickness. LVOT obstruction was identified by a peak instantaneous outflow gradient ≥30 mmHg at rest or ≥50 mmHg under valsalva maneuver or symptom limited exercise.NT-proBNP values and routine laboratory tests were taken, comprising blood count, creatinin, transaminases, C-reactive protein (CRP) and thyroid-stimulating hormone (TSH) to rule out other important causes for orthostatic hypotension, like renal impairment, anemia, infections or hypothyroidism.Eighty patients were investigated using the orthostatic blood pressure test. Heart rate and blood pressure were measured every minute using a DINAMAP device by applying oscillometry, stepwise deflation and a two-tube inflate/monitor system to gain the best possible accuracy in blood pressure measurements. Values were initially obtained with the patient lying horizontally for five minutes and subsequently in upright position for further ten minutes. Orthostatic hypotension was defined as a decrease of at least 20 mmHg in systolic- and/or 10 mmHg in diastolic blood pressure within the first three minutes after changing from supine to upright position. All values were obtained during daily routine in our outpatient clinic and the respective nurse was blinded to the underlying disease of the patient.Continuous variables are reported as mean ± standard deviation (SD) or interquartile ranges (IQR) and categorical variables are presented as frequencies and percentages. Logistic regressions were used to evaluate possible influence of medication, NT-proBNP value, septum wall thickness and the LVOT gradient on the orthostatic test and a prolonged QTc interval. To determine the performance of the orthostatic test and a prolonged QTc interval as a predictor for adverse events, we calculated sensitivity, specificity, positive predictive values (PPV) and negative predictive values (NPV) with 95% confidence intervals (CI) and logistic regressions. All models were adjusted for age and sex. Odds ratios (OR) with 95%-CI are presented, as well as adjusted prevalence where appropriate. A two-tailed p-value <0.05 was considered statistically significant. All analyses were carried out using STATA 13 (StataCorp. 2013).Baseline characteristics are listed in The effect of medication, NT-proBNP value, septum-thickness and the LVOT gradient adjusted for the patient’s age and sex were investigated as predictors for the orthostatic test result and QTc interval. As shown in Tables The orthostatic test was positive in 37 (46%) of all patients tested for orthostatic hypotension  and in 3Logistic regressions revealed the respective test results to be a significant predictor for the occurrence of adverse events in both groups. Comprising all ages , the tesIn 26 out of 100 patients (26%) and in 22 (28%) of the patients investigated for orthostatic hypotension (n = 80) the QTc interval was prolonged. While 22 of 26 patients (85%) with QTc prolongation had an adverse event, this was seen in only 32 of 74 patients (43%) with a normal QTc interval . Thus thOrthostatic test result and QTc interval as joint predictors for adverse events Of all patients with QTc prolongation, 77% (n = 17) also showed a positive orthostatic test result, whereas 35% (n = 20) of the patients with a normal QTc had a physiological orthostatic reaction. A total of 25 patients (53%) had either a positive orthostatic test or a prolonged QTc  and documented VT in the device memory, so that some VT might have been missed.Due to a short observation period and an overall low rate of SCD in this cohort, the prognostic value of the orthostatic test and QTc prolongation on SCD was not investigated. Hence, we can only deduce a very high or low risk for syncope but cannot conclude that this would ultimately lead to a fatal event.


Objective. To determine the effect of hemodialysis (HD) on choroidal thickness (CT). Methods. The right eyes of 41 patients with end-stage renal disease (ESRD) undergoing HD were included. All patients underwent an ophthalmic examination, including CT measurement via optical coherence tomography, intraocular pressure (IOP), blood pressure, and body weight measurement immediately before and after a HD session. Results. Mean subfoveal choroidal thickness (SFCT) after HD decreased significantly from 254.59 ± 84.66 µm to 229.34 ± 77.79 µm (p < 0.001). CT at the temporal and nasal regions also decreased significantly after HD (both p < 0.001). IOP changes after HD were insignificant (p = 0.958). CT difference was insignificant in patients with diabetes mellitus (DM) and without DM before and after HD, respectively (p = 0.285 and p = 0.707). Stepwise multivariate linear regression analysis showed that diastolic blood pressure was the best fitted factor to explain the changes in CT (r = 0.327 and p = 0.040).  Conclusion. CT was decreased in the patients with ESRD following a HD session. This study suggested that the changes in CT may be related to the changes in systemic blood pressure. Hemodialysis (HD) sustains life for more than 1 million patients with end-stage renal disease (ESRD) worldwide and has been doing so since 1980 . Dry weiIt has been reported that the patients undergoing HD showed choroidal perfusion defect on fundus angiography (FFA) and indocyanine green angiography (ICGA) –6. TradiThis prospective, cross-sectional study included 41 patients with stage 5 ESRD who were undergoing HD. Because of the high correlation between all parameters in the right and left eyes, only the patients' right eyes were analyzed. Pathologic conditions that could alter choroidal structure and CT, such as macular degeneration, smoking, ocular trauma, ocular surgery, ocular inflammation, and refractive errors outside −5 to +3 D, were excluded.−1 and blood flow rate of 250–300 mL min−1. Predialytic and postdialytic body weight were measured in each patient. Systolic and diastolic blood pressure  were measured every hour during HD. Ultrafiltration volume was noted following HD. To avoid HD induced hypoglycemia, all patients received 200 cc of 5% dextrose solution at the end of HD.All patients were undergoing three 4-hour HD sessions each week. The bicarbonate used was diazole with a dialysate flow rate of 500 mL min−1. Tissue depth resolution was 5.0 μm with transverse resolution of 15 microns. The device had a 40° Widefield Enface OCT reference scan.All patients underwent detailed ophthalmologic examination, including best-corrected visual acuity, intraocular pressure (IOP) before and after HD , and lens status. CT scanning was performed using RTVue SD-OCT system . The repeated OCT measurements were obtained by an operator (AÜ) at approximately 0700 and 1100, respectively, to avoid diurnal variations. The system utilized a wavelength of 840 ± 10 nm and was capable of 26,000 A-scans sPatients were seated at the front of the device to obtain reasonable choroidal images. The patients were informed to fixate the internal fixation light of the RTVue SD-OCT during image acquisitions. After the patients' heads were correctly positioned, a fovea-centered, 6 mm, horizontal high definition line scan (4096 A-scan/frame line) was obtained with the chorioretinal line mode. Postdialytic scans were obtained using the follow-up mode to obtain the images from the previous location. All images underwent manual segmentation by two researchers  who were blinded to the patients. RTVue manual measurement tools included calipers for delineating the boundaries of the choroid.CT was measured perpendicularly from the outer edge of the retina pigment epithelium to the inner sclera, as previously reported . CT was t-test and Pearson's coefficient test were utilized to compare pre-HD and post-HD data. The level of statistical significance was set at p < 0.05.Data were analyzed using SPSS v.17.0 for Windows . The normality of the distribution of data was determined using the Kolmogorov-Smirnov test. All continuous data were normally distributed. There was a high correlation between the patients' right and left eyes; therefore, only right-eye data were used for further analysis. Descriptive statistics are presented as mean ± SD. For continuous data, Student's paired The right eyes of 41 patients  with ESRD were included. Mean age of the patients was 53.2 ± 14.6 years and mean duration of HD treatment was 42.81 ± 30.38 months. Eight of the 41 patients had diabetes mellitus (DM) .p = 0.958). Mean body weight decreased significantly from 65.77 ± 10.50 kg to 63.65 ± 10.41 kg after HD (p < 0.001). SBP and DBP decreased significantly following HD; the differences were 21.63 ± 23.06 mmHg and 14.00 ± 21.87 mmHg, respectively. IOP and systemic findings are shown in IOP changes after HD were insignificant (μm to 229.34 ± 77.79 μm (p < 0.001) after HD. There was also a significant decrease in all measurement points from the fovea  decreased significantly from 254.59 ± 84.66 he fovea .μm and 257.67 ± 82.09 μm, respectively, in the patients with DM and those without DM (p = 0.285). After HD, the mean SFCT was 203.0 ± 84.96 μm and 235.73 ± 75.96 μm, respectively, in patients with DM and those without DM (p = 0.707).There was no difference in CT between the patients with and without DM before and after HD. The mean SFCT was 241.88 ± 99.57 r = 0.311, R2 = 0.097, and p = 0.047). Stepwise multivariate linear regression analysis showed that only change in DBP could explain 14% of the changes in SFCT .Associations between the difference in SFCT and the other parameters, including age, gender, DM, duration of HD, dry body weight, serum osmolarity, plasma osmotic colloid pressure, ultrafiltration volume, and the percentage of the change in IOP, SBP, DBP, and body weight, were evaluated . There wThe primary goal of HD is to maintain the kidneys' excretory functions in ESRD patients. During a HD session, ultrafiltration removes excess fluid from plasma, which leads to blood volume depletion, an increase in the plasma protein concentration (increase in plasma colloid osmotic pressure), and a decrease in serum osmolarity. Blood volume depletion is equilibrated by vascular refilling from the interstitial and intracellular space , 12. TheJung et al.  studied On the other hand, Yang et al.  observedBased on the association between the changes in CT and DBP, we hypothesized that the CT thinning may be a result of the increase in choroidal vascular and nonvascular smooth muscle contraction due to activation of the sympathetic autonomic nervous system. It is well known that retinal vascular circulation is autoregulatory and that choroidal circulation is controlled primarily by the extrinsic autonomic system . The parIn the present study, the changes observed in SFCT were positively correlated with changes in DBP. It is known that blood volume depletion causes diastolic dysfunction, whereas contractility dysfunction of the heart leads to systolic dysfunction. Barth et al.  reportedEarlier findings on CT in DM patients have been inconsistent –21. ReceThe present study has several limitations. Only predialysis serum osmolarity and plasma colloid serum osmotic pressure were measured, which limited our ability to analyze the correlation between changes in those parameters and SFCT. In a previous study, CT was shown to have a negative correlation with axial length . In addiIn conclusion, CT decreased after HD in patients with ESRD. We suggest that sympathetic activation triggered by blood volume depletion to prevent hypotension might cause choroidal vascular and nonvascular smooth muscle constriction, which leads to a decrease in CT. The decrease in DBP and SFCT following HD may be a consequence of systemic compensatory mechanisms. Additional large-scale randomized studies are needed to more fully determine the effect of HD on CT and the relationship between CT and changes in systemic parameters.


Hallux valgus and claw toe remains the most common and disabling pathologies of the foot. The goal was to assess the difference between the patients suffered hallux valgus combine with claw toe and the patients without any complications.7 severe HV patients  and 7 patients suffered HV combine with claw toe (HVC)  were recruited in this study. The F-Scan in-shoe system  were used to record the data of plantar pressure at a sampling frequency of 50 Hz. Subjects were instructed to wear the custom shoes with F-Scan sensor pad and perform a 5 meter walking task on their self speed. For plantar pressure assessment, each footprint is divided into 12 regions  to enable analysis of the instant of peak pressure (kg/cm2) and maximum force that were normalized with body weight (MxF(%BW)). The independent t test was used to determine the differences of foot regions for two groups. Results were considered statistically significant when the p<0.05.The result of anthropometric feature of the individuals recruited for the study was showed in Table In past study, Plank found a medial shift in peak pressure in most of the hallux valgus group, with a significant decrease in pressure beneath the fourth and fifth metatarsal heads and this finding was also be found from HV and HVC group. In the present study, when patients suffered HV combined with claw toe represented high peak pressure and MxF at the M2and M3 regions. It would result in the metatarsal heads bear more weight and become painful during walking.


In addition, statistically significant higher systolic (p < 0.05) and diastolic blood pressure (p < 0.01) was observed in the second quartiles compared to the first quartiles. Because a strong association was also detected between the sodium to potassium ratio and blood pressure even at a low level of sodium to potassium ratio, a lower sodium to potassium ratio diet than a usual diet is recommended to control high blood pressure in Korea.This study investigated the effect of the sodium to potassium ratio on hypertension prevalence and blood pressure. The study population was constructed by pooling the Korean National Health and Nutrition Examination Surveys between 2010 and 2014. The study population was divided into quartiles based on the sodium to potassium ratio, and the effect was inferred by the difference in hypertension prevalence across quartiles by six pairwise comparisons using a propensity score matching technique. The quartiles with the higher sodium to potassium ratio had higher hypertension prevalence rates based on the following pairwise comparisons: the first vs. third quartile, the first vs. fourth quartile, the second vs. third quartile, and the second vs. fourth quartile. The prevalence differences were 2.74% point ( The hypertension prevalence rates of Korean male and female adults aged 30 years or above are 32.4% and 22.2% in Korea , respectThe 2013 Institute of Medicine (IOM) report acknowledged the overall association between sodium intake and blood pressure based on previous studies. However, individual studies do not show a consistent relationship between sodium intake and blood pressure ,5. In reHe, Li, and MacGregor  concludeObservational studies carried out in various countries also show very inconsistent results. For instance, Du et al.  found stThe inconsistencies in the results of observational studies reflect the necessity for further evidence regarding the association between Na:K ratio and blood pressure, because widely varying results of observational studies regarding the association between sodium intake and blood pressure or hypertension status could be due to the incorrect measurement of sodium intake and the improper statistical analyses . AdditioThe objective of this study is to examine the effect of the Na:K ratio on hypertension prevalence. The effect of the Na:K ratio was examined because previous studies found that the joint effect of low sodium and high potassium intake on blood pressure may be larger than the effects of either sodium or potassium alone ,17,18, aIn pursuing the objective, the authors resolve the statistical issues raised by the American Heart Association Science Advisory including reverse causality, residual confounding due to incorrect adjustments, and covariate balances across different Na:K ratio groups . To mitiThis study used five years of data from the Korea National Health and Nutrition Examination Survey (KNHANES) collected by the Korea Center for Disease Control and Prevention. The study population consists of 30,206 subjects aged between 20 and 79 years from KNHANES data pooled form 2010 to 2014. Subjects with chronic diseases, such as chronic renal failure, diabetes, cardiovascular diseases, stroke, and dyslipidemia were excluded from the study population to mitigate the reverse causality problem, because strict diets were recommended by physicians to patients with the above chronic diseases. The concern over reverse causality due to hypertension can be eased because the prevalence rates of the lower Na:K ratio groups (Q1 and Q2) were actually lower than the study population average and those of the higher ratio groups, as shown in Since the sodium and potassium intake data are calculated from the 24 h recall food intake survey, too little or too much calorie intake could signal an incorrect food intake survey. Therefore, it is necessary to remove the observations with extreme calorie intake values to control the outliers. Following Kwock and Park , intakesThis study used the propensity score matching technique to estimate the approximate effects of the Na:K ratio on hypertension prevalence. The matching technique was employed because it could resolve the issue of selection bias caused by the determination of membership between the control and treatment groups in observational studies . SelectiIn addition to hypertension risk factors, various socio-demographic variables, such as age, education, income, etc. were included in the hypertension models. Some of these socio-demographic variables affect other covariates as well as the dependent variable. For example, an age variable, which is a significant risk factor of hypertension, is a confounding variable since it can also influence the treatments and the Na:K ratios through the insensitivity of salty taste from aging. Because these confounding variables can influence the direction of the association between the Na:K ratio and hypertension prevalence, they need to be adjusted properly . The proThe basic idea behind propensity score matching is to find a group of untreated subjects similar to the treated subjects in terms of the subject characteristics. However, since finding a subject with similar characteristics increases in difficulty as the number of subject characteristics increases, Rosenbaum and Rubin  suggesteThe propensity score is usually estimated with a conventional probit or logistic function. The dependent variable has a value of “1” if a subject belongs to the treatment group; otherwise, the value is “0”. The variables that influence the outcome and treatment variables are used as the covariates. Once the propensity score is estimated, the subject who has the closest propensity score in the control group is matched with a subject in the treatment group using matching algorithms. Balance is achieved between the control and treatment groups during this matching process. Because the distributions of covariates that characterize the subjects in the control and treatment groups are more similar after matching than the random sample, a correct treatment effect can be obtained . The mos2 values should be compared to assess the overall balance of the covariates. Then, the pseudo-R2 should be very low since the covariates are similar in both control and treatment groups.The matching quality is checked after matching by testing the balances of the covariates in the control and treatment groups. Then, a t-test is used to test the equality of the covariate means across the control and treatment groups. If the matching was executed properly, the null hypothesis of equal means should not be rejected. The percent standardized bias should also be checked for each covariate, and 5% should be sufficient ,36. SianIn random clinical trials, the outcome difference between the control and treatment groups is the treatment effect because the subjects are randomized. Although cross-sectional studies cannot determine rigorous causal effect, the propensity score matching technique can provide an approximation of the treatment effect . BecauseThe specific objective of this study was to test the significance of differences in hypertension prevalence across different Na:K ratio levels. For this objective, the subjects were divided into quartiles based on their Na:K ratio levels, and then the means of the hypertension prevalence of the quartiles were compared. Instead of comparing four (N) treatments with different Na:K ratios at the same time, six (N × (N − 1)/2) different pairwise comparisons were performed because they were practical alternatives . For the2), marital status, monthly household income, education in years, walking hours per day, smoking status, drinking status, stress level, use of nutritional labels, family history of hypertension, etc. The definitions of the variables used to estimate the propensity score are shown in The probability function used to estimate the conditional probability of being a member of a treatment group is a logistic function: its dependent variable has a value of “1” if the subject is the member of treatment group and “0” otherwise. Covariates used in the logistic function were age, sex, body mass index . The common support restriction was used, and the observations in the range between the minimum and maximum propensity scored of treatment group were used. The observations outside of this range were excluded.After matching, the balance was confirmed by a two-sided t-test to determine the equality of the sample means of the control and treatment groups for each covariate. The percent biases were also evaluated for every covariate to determine whether they were within the 5% limit. Finally, pseudo-R2 values for all pairwise comparisons were assessed to determine whether the overall balance of the covariates was satisfied.t-test was used to test the significance of the effect. A one-sided t-test was conducted for each pairwise comparison to test the null hypothesis; the groups with the higher Na:K ratios had the higher hypertension prevalence.Once balance was achieved between the control and treatment groups, the difference in the hypertension prevalence rates in the two groups was the approximation of the treatment effect, and a All statistical analyses  were performed with STATA Release 12 .Overall, the average hypertension prevalence was 19.56%, which was relatively low. The low prevalence was found because subjects with hypertension as a comorbidity of other chronic diseases were excluded. The average BMI was 22.87 ± 0.03; this was also affected by the exclusion of obese subjects with chronic diseases. The average age was approximately 46 years, and the proportion of females was 68.19%. The proportions of smokers and drinkers were lower due to the high female to male ratio.Q1 shows a low intake of calories and fat and a high intake of fiber, potatoes, and fruits which are major the sources of potassium, as shown at the bottom of p < 0.05) based on the one-sided t-test. This result favors the hypothesis that the group with the higher Na:K ratio has higher hypertension prevalence. In the pairwise comparison between Q1 and Q4, Q4 had a higher hypertension prevalence by 3.44% point (p < 0.01). In the pairwise comparisons between Q2 and Q3 and between Q2 and Q4, the groups with higher Na:K ratios had a higher hypertension prevalence by 2.47% point (p < 0.05) and 2.95% point (p < 0.01), respectively.Four pairwise comparisons, Q1 vs. Q3, Q1 vs. Q4, Q2 vs. Q3, and Q2 vs. Q4, showed higher hypertension prevalence in the higher Na:K ratio groups. The pairwise comparisons Q1 vs. Q2 and Q3 vs. Q4 did not show any differences in hypertension prevalence.The first significant difference in hypertension prevalence was from the comparison of Q1 and Q3. The subjects in Q1 had an average intake of 2610.23 mg/day of sodium and 3641.29 mg/day of potassium, whereas the subjects in Q3 had an average intake of 4628.49 mg/day of sodium and 2833.01 mg/day of potassium. The hypertension prevalence rates were 17.13% and 19.87% for Q1 and Q3, respectively. In this pairwise comparison, the effect of one unit change in Na:K ratio on the hypertension ratio is 3.08% point.2 show that there were no significant differences in matched samples. The pseudo-R2 values obtained from the re-estimation of the propensity score with only matched data were all very low, and some were close to 0.01, as shown at the bottom of To examine the effect of the Na:K ratio on systolic (SBP) and diastolic blood pressure (DBP), further propensity score matching analyses were performed. For this purpose, all subjects who were previously diagnosed and currently taking hypertension medications were excluded from the dataset used in the above pairwise comparisons. This exclusion removed any remaining possibility of reverse causality after the exclusion of chronic patients. The propensity scores were estimated and matched again after the exclusion, and the differences in mean SBP and DBP were estimated for all six pairwise comparisons. p < 0.05), 0.88 (p < 0.05), 1.41mmHg (p < 0.01) compared to Q1, respectively. In comparisons of DBP, two pairwise comparisons, Q1 vs. Q2 and Q1 vs. Q4, showed higher DBP in the higher Na:K ratio groups by 0.83 (p < 0.01) and 0.92 (p < 0.01), respectively. From the significant differences in SBP and DBP between Q1 and Q2, we could infer 2.37 and 1.80 mmHg increases in SBP and DBP, respectively, in response to one unit of change in the Na:K ratio. Therefore, the results showed that the Na:K ratio also had a significant effect on the blood pressure, and especially, Q1 had significantly lower blood pressure compared to the other quartiles.Three pairwise comparisons, Q1 vs. Q2, Q1 vs. Q3, and Q1 vs. Q4, showed higher SBP in the higher Na:K ratio groups while the remaining pairwise comparisons showed no significance in the SBP differences. Q2, Q3, and Q4 had higher SBP by 1.09  had the lowest risk in blood pressure, and the blood pressure results showed almost a linear dose-response relationship between the Na:K ratio and SBP. These results deny the possibility of an existence of a U-shaped relationship between the Na:K ratio and hypertension and between the Na:K ratio and blood pressure.The mechanisms by which sodium and potassium affect blood pressure are multiple. In salt-sensitive individuals, salt ingestion causes sodium and water retention and extracellular volume expansion, which results in the release of substances increasing heart and blood vessel contraction and affecting renin-angiotensin-aldosterone system ,43. PotaOur result is consistent with the results of some observational studies in various countries that Na:K ratio has a significant effect on hypertension prevalence and/or blood pressure ,11,12,51The results of our study were obtained using the sound statistical approaches recommended by the American Heart Association Science Advisory. Especially, the effect of the Na:K ratio on blood pressure was obtained after removing almost all of the salt sensitive subjects by excluding the subjects taking hypertension medications. Even though the actual blood pressure difference in SBP and DBP from the pairwise comparisons was not huge, the small shift of whole blood pressure distribution could have a significant effect on the burden of hypertension .However, our study has a few potential limitations. One limitation of our study is the use of cross-sectional data; assessments of nutrients intake and blood pressure were made at the same time. Therefore, our study cannot determine whether the nutrient intake preceded the blood pressure change and, hence, whether the nutrient intake caused the blood pressure change. However, the propensity score matching can provide a useful approximation of random trial and an approximate effect of the Na:K ratio on health outcomes .The second potential limitation is that our study used the Na:K ratio based on the food intake survey, because the incorrect measure of sodium and potassium intake could bias the results. Our result regarding blood pressure favors lower Na:K ratio, and Na:K ratio is positively associated with blood pressure increases even if the quantity of blood pressure increase is small. Thus, the direction of association seems reasonable, but the small quantity of blood pressure increase could be a limitation. Since errors in sodium intake measurement could attenuate the association between sodium intake and health risk , larger Our study contributes to the literature by providing evidence of an association between the Na:K ratio and the hypertension prevalence and blood pressure based on the sound statistical method. The relationship between sodium intake and cardiovascular diseases and/or stroke has become more plausible than ever with this evidence since hypertension is a direct risk factor of those diseases. Moreover this study provides a quantitative effect of the Na:K ratio on the hypertension prevalence and blood pressure from a large pool of subjects. However, there exists large difference in sodium sensitivity among different ethnic groups as suggested by Franco and Oparil , therefoFurther research is needed to determine whether the results will hold up after controlling for genetic factors since more results are being reported that assess the effect of not only sodium intake but genetic variations on the blood pressure ,55. A si


The Angiotensin-Converting Enzyme-2 (ACE2) gene, located on chromosome X, is believed to be implicated in blood pressure regulation. However the few studies that have examined this association have yielded mixed results. The objective of this study was to assess the association between tag single nucleotide polymorphisms (SNPs) in the angiotensin-converting enzyme-2 gene with blood pressure and blood pressure change in adolescents.Participants in the Nicotine Dependence in Teens (NDIT) cohort study with blood or saliva samples and at least 3 blood pressure measurements over 5 years were included in the analytic sample (n = 555). Linear growth curve models stratified on sex and ethnicity were used to assess the association between four tag SNPs in the ACE2 gene and systolic (SBP) and diastolic blood pressure (DBP), and blood pressure change.In males of European descent, rs2074192 and rs233575 were significantly associated with SBP and DBP, and rs2158083 was associated with SBP. In French Canadian males, rs233575 and rs2158083 were significantly associated with DBP. Among females of European descent, rs2074192, rs233575, and rs2158083 were significantly associated with change in SBP over 5 years.This is the first study to assess the association between the ACE2 gene with blood pressure and blood pressure change in a cohort of adolescents. Results indicate that several ACE2 gene SNPs are associated with blood pressure or blood pressure change in persons of European descent. However the therapeutic potential of these SNPs should be explored. Hypertension (HTN) is a major risk factor for cardiovascular disease. Half of all strokes and ischemic heart disease, and 25% of other cardiovascular diseases are due to elevated blood pressure . In 2000The Angiotensin-Converting Enzyme-2 (ACE2) is a negative regulator of the renin-angiotensin aldosterone system -9 and plPast studies on ACE2 SNPs were conducted in adults and were primarily case–control or cross-sectional. The results are subject to confounding by preexisting chronic diseases or treatments for high blood pressure. Because young people generally do not have chronic disease or take blood pressure medications, assessing the association between blood pressure and ACE2 using data from adolescents may improve our understanding of the implication of this gene in blood pressure regulation. Thus, the aim of this study was to assess the association between blood pressure and ACE2 gene SNPs in an ongoing cohort study of healthy adolescents.The Nicotine Dependence in Teens (NDIT) Study is an ongoing prospective cohort investigation designed to assess the development of nicotine dependence symptoms after cigarette smoking onset in adolescents . ParticiParticipants completed 45-minute self-reported questionnaires every 3–4 months during the 10-month school year, for a total of 20 waves of data collection during high school. Data from the baseline and the first five years of follow-up were used in this study. Blood pressure and anthropometric measures were obtained in survey cycle 1, 12 and 19 during secondary school . The blood or saliva samples for DNA extraction were provided by 852 of the 1293 participants (65.9%) in 2002 and 2007. All participants and a parent or guardian provided written informed consent at baseline; a separate consent was provided by parents for the blood draw in grade 9 (when participants were 14–15 years of age), and informed consent was obtained from participants  for saliva samples in 2007. The study was approved by Institutional Review Boards at the CRCHUM, the Direction de santé publique de Montreal and McGill University.After voiding and a 5-minute rest, blood pressure was measured on the right arm of seated subjects according to a standardized protocol by a trained and certified technician. Measurements were made with an automated oscillometric device  calibrated against a mercury sphygmomanometer before each data collection period. SBP and DBP were measured 3 times at 1-minute intervals. If the SBP and DBP measurements differed by more than 10 and 5 mmHg respectively, fourth and fifth measurements were obtained. The mean of the two closest measurements (after exclusion of the first measurement) was used for analysis.Duplicate measurements of height and weight were obtained with participants wearing light clothing without shoes, using a stadiometer  for height and a scale  for weight. A third measurement was obtained if the difference between the two measurements was greater than 0.5 cm for height and 0.2 kg for weight. The average of the two closest measurements was used in the analysis. To assess inter-rater reliability of height and weight, measures of every 1 in 10 participants were repeated. Inter-rater reliabilities were 0.99 for height and weight ,19. Sex-We used the greedy pairwise tagging approach  as imple2 tests.Participants with only one or two blood pressure measurements during the five years of high school were excluded from analyses because of the potential for over fitting. Because females begin puberty before males, and the evolution of blood pressure differs between males and females in adolescence ,24, the change of SBP or DBP with the four ACE2 SNPs. SBP and DBP were modeled as continuous variables in separate models; time was represented by age centered at 12 years, ethnicity was defined as French Canadian, European descent, or Other , and the major allele genotypes served as the reference category . All models adjusted for height and whether or not the participant was overweight or obese. Statistical analyses were carried out using SAS 9.2 software .Due to evidence of heterogeneity between ethnicities, analyses were also stratified by ethnicity . Analyses assessing the association between baseline blood pressure and the major and minor SNP genotypes were conducted with linear regression analyses. Major and minor SNP genotypes were identified in accordance with the dbSNP database . A lineap < 0.05) but did not differ in sex, ethnicity, whether or not they were overweight or obese, SBP or DBP .Participants with fewer than three blood pressure measurements (n = 570), or those who did not provide a blood or saliva sample (n = 168) were excluded. Therefore a total of 555 participants of the original 1,293 were retained for analyses. At baseline, adolescents who were excluded were significantly younger than those retained in analyses , but DBP was not statistically significantly different (p > 0.05 in wave 12 and wave 19). SBP increased 10.1 mmHg on average over the 5-year follow-up (p < 0.0001) in males, and increased 2.0 mmHg on average in females (p = 0.0003), a statistically significant difference (p < 0.0001). DBP increased 3.4 mmHg on average over the 5-year follow-up in males (p < 0.0001), and 2.2 mmHg on average in females (p < 0.0001), but the difference was not statistically significant by sex (p > 0.05). These results were unchanged after excluding heterozygote females (data not shown).Over half (52%) of the participants in the complete sample (n = 555) were male Table . Femalesp = 0.01), and an A allele frequency of 27% in males of other ethnicity compared to 41% in females of other ethnicity (p = 0.01). SNPs rs233575, rs2158083, and rs1978124 were in Hardy-Weinberg Equilibrium . All SNPs were in linkage disequilibrium with each other , and the T allele of SNP rs233575 was associated with lower SBP  and DBP . French Canadian females carrying the T allele for rs233575 or rs2158083 had baseline DBP that was 4 mmHg higher (59 mmHg vs 55 mmHg) than French Canadian females carrying the C allele (p < 0.05).In multivariable linear regression analyses, SNP rs1978124 was not associated with SBP or DBP at baseline in either males or females (p = 0.02) and 2.3 mmHg lower (p = 0.003), respectively than in males of European descent carrying the G allele (Table p = 0.01) and 2.4 mmHg higher (p = 0.003), respectively, than in males of European descent carrying the T allele. In addition, males carrying the C allele of rs2158083 had SBP that was 3.4 mmHg higher (p = 0.02) than males carrying the T allele. French-Canadian males with the C allele of rs233575 and rs2158083 had 2.9 mmHg (p = 0.001) and 2.7 mmHg (p = 0.01) lower DBP than males with the T allele of these respective SNPs. There were no statistically significant associations between any of the four SNPs and change in SBP or DBP during follow-up among boys (data not shown).Sex- and ethnicity-stratified analyses suggested that after adjusting for height and weight status, SBP and DBP in males of European descent carrying the A allele of rs2074192 were 3.3 mmHg lower . Females of European descent carrying the C allele of rs233575 and rs2158083 had a change in their SBP that was 1.9 mmHg (p = 0.002) and 1.20 mmHg (p = 0.04) higher, respectively, compared to females of European descent carrying the T allele.In general none of the SNPs were associated with either SBP or DBP in females after adjustment for covariates (data not shown). However, there were statistically significant associations between several SNPs and es Table . FemalesAs a part of the renin-angiotensin aldosterone system, an important regulator of blood pressure homeostasis, ACE2 is believed to have a role in blood pressure regulation . Indeed,To the best of our knowledge, our study is the first to investigate the association between tag SNPs in the ACE2 gene with blood pressure and blood pressure change in adolescents using multiple measures of blood pressure over five years of follow-up. Interestingly, we observed two associations (rs2074192 and rs233575) in males and females that were entirely driven by participants of European ancestry. Our results indicate that the ACE2 gene and more specifically, the major allele of rs2074192 and the minor allele of rs233575 significantly increase SBP and DBP among males of European ancestry, and significantly increase SBP change among females of European ancestry.All previous studies on the ACE2 gene were carried out in adults using cross-sectional or case–control designs with single-point estimates, or follow-up time less than a month. In contrast, our study utilized nearly five years of follow-up among adolescents. The use of multiple blood pressure measurements in longitudinal data are less affected by random sources of variation than measurements taken at one time  and thusOur study is not without limitations. Candidate gene studies and Genome Wide Association Studies have both been criticized for their low replication of results, and candidate gene studies are additionally criticized for the subjectivity of their gene selection . HoweverWe acknowledge that restricting the analysis to homozygous females discards some information and can lead to a loss of power. Clayton 2008, 2009) has suggested tests of associations for SNPs located on the X chromosome that take into account X inactivation by giving a weight of ½ to the heterozygous genotype in females, essentially using an additive coding for the genotype  ,32. We a, 2009 haWhile 92% of our participants were Canadian-born, 28% of their mothers and 37% of their fathers were foreign-born, and ethnicity has been shown to modify the association between SNPs and blood pressure . Our tagDespite these limitations, our results suggest that several ACE2 gene SNPs are associated with either blood pressure levels or blood pressure change among males and females of European ancestry. Whether these SNPs could be new therapeutic targets, or potential primordial targets in persons of European descent should be further explored.ACE2: Angiotensin-converting enzyme-2; BMI: Body mass index; DBP: Diastolic blood pressure; HTN: Hypertension; NDIT: Nicotine dependence in teens study; SBP: Systolic blood pressure; SNPs: Single nucleotide polymorphisms.The authors have no competing interests to declare.LM performed the statistical analysis, interpreted the data, and drafted the manuscript. LK contributed to the interpretation of the data and participated in the drafting of the manuscript. JOL conceived of and designed the study, obtained the funding, participated in its coordination, contributed to the interpretation of the data, and participated in the drafting of the manuscript. LP, PH, JT, conceived of and designed the study, obtained the funding, contributed to the interpretation of the data, and participated in the drafting of the manuscript. GP participated in the conception of and design of the study, contributed to the interpretation of the data, and participated in the drafting of the manuscript. M-H R-G and AL contributed to the statistical analysis, interpretation of the data and participated in the drafting of the manuscript. All authors read and approved the final manuscript.The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2350/14/117/prepubLinkage disequilibrium between SNPs in homozygous females .Click here for fileMean blood pressure (mmHg) at baseline according to genotype among homozygous participants .Click here for fileAssociation between minor ACE2 alleles and blood pressure differences among females  using the additive model.Click here for fileAssociation between minor ACE2 alleles and blood pressure change among females  using the additive model.Click here for fileAssociation between minor ACE2 alleles and blood pressure differences among females  using the dominant model.Click here for fileAssociation between minor ACE2 alleles and blood pressure change among females  using the dominant model.Click here for fileAssociation between minor ACE2 alleles and blood pressure differences among females  using the recessive model.Click here for fileAssociation between minor ACE2 alleles and blood pressure change among females  using the recessive model.Click here for file


There is evidence that myocardial ischemia in patients with diabetes mellitus is often present without the exhibition of symptoms. Moreover, recent data suggests that silent ischemia is associated with occurrence of cardiac events and poor outcome. Aim of our study was to determine the prognostic value of a reversible perfusion deficit assessed by adenosine perfusion cardiac magnetic resonance imaging (CMR) in a consecutive cohort of diabetes mellitus patients independent of the exhibition of clinical symptoms.Consecutive patients with diabetes mellitus type 2 of any duration that were referred for adenosine perfusion CMR were screened for enrollment. It was irrelevant whether the patients exhibited symptoms that were likely to be of ischemic origin or not. A reversible perfusion deficit was assessed by adenosine-perfusion imaging and late gadolinium enhancement on a 1.5 T whole-body CMR-scanner and was defined as hypoperfusion during adenosine infusion without corresponding late gadolinium enhancement. The primary endpoint was defined as cardiac death, non-fatal myocardial infarction or stroke.The study population consisted of 239 consecutive patients with prior diagnosed diabetes mellitus. During the follow-up period of 5.0 ± 2.1 years 33 primary endpoints occurred. Patients with an event were significantly older , had lower left ventricular ejection fractions  and more often a reversible perfusion deficit (21 (63.6%) vs. 57 (27.7%), p < 0.0001) than patients without. In a multivariate analysis, a reversible perfusion deficit was the strongest predictor for an event with a 3.76-fold increased risk (p = 0.0003). Whether the patients presented symptomatically at enrollment had no influence on their particular risk and event-free survival.Adenosine perfusion CMR allows excellent risk stratification in patients with diabetes mellitus, independent of other risk factors or the presence of ischemic symptoms.None.