We prospectively enrolled 27 hypovolemic ARDS patients ventilated with low VT 6 ml/kg and three levels of PEEP  randomly. Each stage lasted for at least 5 min to allow for equilibration of hemodynamics and pulmonary mechanics. Then, fluid expansion was given with 500 ml hydroxyethyl starch (Voluven 130/70). The hemodynamics and PPV were automatically measured with a PiCCO2 monitor. The PPV values were significantly higher during PEEP15 than those during PEEP5 and PEEP10. PPV during PEEP15 precisely predicts fluid responsiveness with a cutoff value 8.8% and AUC (area under the ROC curve) of ROC (receiver operating characteristic curve) 0.847, higher than the AUC during PEEP5 (0.81) and PEEP10 (0.668). Normalizing PPV with driving pressure (PPV/Driving-P) increased the AUC of PPV to 0.875 during PEEP15. In conclusions, high PEEP 15 cmH2O can counteract the drawback of low VT and preserve the predicting accuracy of PPV in ARDS patients.The prediction accuracy of pulse pressure variation (PPV) for fluid responsiveness was suggested to be unreliable in low tidal volume (VT) ventilation. However, high PEEP can cause ARDS patients relatively hypovolemic and more fluid responsive. We hypothesized that high PEEP 15 cmH Michard F1 proposed that for hypovolemic patients on mechanical ventilation, respiratory variations in the pulse pressure and LV stroke volume are magnified because (1) the inspiratory transmission of pleural pressure into the right atrium (RA) increases when the RA is underfilled and compliant in terms of pressure and the venous system is collapsible by pleural pressure and (2) the inspiratory effect on the RV afterload is exaggerated, and both RV and LV are sensitive to preload change when they operate on the steeper portion of the Frank–Starling curve.During inspiration with the support of mechanical ventilation, increased pleural and transpulmonary pressure reduces the right ventricular (RV) preload and increase the RV afterload, thus decreasing RV ejection. Because of the increase in the blood pulmonary transit duration, the inspiratory RV stroke volume decreases, which leads to a reduction in the expiratory left ventricular (LV) preload volume after a phase lag of two to three heart beats. Consequently, positive-pressure ventilation induces a cyclic inspiratory increase and an expiratory decrease in the LV stroke volume3 have concluded that mechanical ventilation–induced dynamic preload indicators predict fluid responsiveness accurately in critically ill patients. Nearly all studies demonstrating high predictive accuracy of pulse pressure variation (PPV) have set the tidal volume (VT) to > 8–10 mL/kg.Recent systematic reviews4, acute respiratory distress syndrome (ARDS) is the most likely outcome of the deleterious effects of fluid overloading. Precisely predicting fluid responsiveness is crucial for avoiding hypovolemia-induced arterial hypotension and low cardiac output (CO) and for minimizing the risk of fluid overload–induced pulmonary edema exacerbation. To avoid volutrauma, the VT must be decreased to 6 mL/kg5, which is lower than the minimum requirement of 8 mL/kg proposed by De Backer6. With low VT ventilation, cyclic changes in pleural and intrathoracic pressure may not be sufficient to induce considerable cyclic variations in LV filling, which are required for identifying fluid responsiveness7. Therefore, the predictability of PPV for fluid responsiveness in ARDS patients has been demonstrated to be unreliable in studies applying a low VT11.Because of the markedly increased permeability of lungs after acute lung injury (ALI)13. Recently, a meta-analysis14 of three multicenter controlled trials  concluded that higher levels of PEEP (15.3 versus 9.0 cmH2O) are associated with improved survival among ARDS patients.In addition to the low VT, adequate positive end-expiratory pressure (PEEP) for the reduction of ventilator-induced lung injury (VILI) from repetitive opening and closing of unstable lung units is another indispensable key requirement of the protective ventilatory strategy18. Through the augmentation of both pleural and transpulmonary pressure, PEEP decreases venous return and increases the RV afterload, exacerbating preexisting hypovolemia. Therefore, high PEEP results in a leftward shift on the Frank–Starling curve to the steeper portion, making ARDS patients more hypovolemic and more fluid responsive19. High PEEPs have been demonstrated to increase PPV in ALI humans19 and increase RV and LV stroke volume variation (SVV) in animals20. Regarding the accurate prediction of fluid responsiveness, contrary to the findings of the aforementioned studies where all patients were ventilated with low PEEP, increased PEEP was used in ALI pig and septic ALI patients by da Silva Ramos et al.21 and Freitas et al.22, respectively, which revealed that PPV is a favorable predictor of hypovolemia. However, the effects of various PEEP levels on the predictive accuracy of fluid responsiveness of ARDS patients have seldom been reported. Therefore, this study investigated whether high PEEP can counteract the drawback of low VT (6 mL/kg) and whether PPV predicts fluid responsiveness more effectively when ventilated with high PEEP (15 cmH2O) or low PEEP (5 and 10 cmH2O) in the same ARDS patient.PEEP affects the predictive performance of dynamic preload indicators through not only preload change but also complex heart–lung interactions23 and were administered fluid resuscitation were enrolled. Their enrollment was based on the presence of at least one clinical sign of inadequate tissue perfusion, which included the following: (1) systolic blood pressure (BP) < 90 mm Hg or the need for vasopressors with norepinephrine; (2) urine output < 0.5 mL/kg/h for at least 2 h; (3) tachycardia (heart rate [HR] > 100/min); and (4) presence of skin mottling. Patients were excluded if they had cardiac arrhythmia or hemodynamic instability, defined as a variation in HR or BP by > 10% over a 15-min period, before the start of the procedure. Furthermore, patients with renal failure requiring renal replacement therapy were excluded.The Institutional Review Board (IRB) for Human Studies of Chang Gung Memorial Hospital approved the study protocols . Informed written consent was obtained from the patients’ nearest relatives. This study was performed in accordance with the Declaration of Helsinki and was registered in Clinical Trials.gov with the identifier NCT01716962. Patients who conformed to the Berlin definition of ARDSHemodynamic data, including HR, BP, cardiac index (CI), stroke volume index (SVI), PPV, and SVV, were downloaded directly and continuously at a frequency of once every 12 s from a bedside PiCCO2 hemodynamic monitoring system  in a spreadsheet format for subsequent calculations. The data of the last 2 min (11 sets of data) of each time interval were averaged to represent the hemodynamic data of that time interval. The PiCCO2 algorithm searches for the maximum and minimum pulse pressure in a 7.5-s window within the floating 30 s. PPV was calculated using the following equation: PPV = (PPmax − PPmin)/PPmean.Respiratory mechanics, including the respiratory rate (RR), VT, plateau and mean airway pressure, PEEP and auto-PEEP levels, and respiratory system compliance (Crs), were derived beat-by-beat from the GALILEO GOLD ventilator . The average of five successive data at the end of each time interval was used to represent the pulmonary mechanics of that setting interval. The GALILEO ventilator automatically measures Crs breath-by-breath by using a statistical technique called the least-squares fit method. This method is applied on a breath-by-breath basis, without the need for special inspiratory flow patterns and occlusion maneuvers, provided that the patient is relaxed.2 at > 90%. After the stabilization of hemodynamics at baseline, transpulmonary thermodilution cardiac output (CO) measurement was performed for calibrating pulse contour continuous CO. Following the calibration, patients received all the three levels of PEEP  in a random order. Each PEEP level was maintained for at least 5 min to allow for the stabilization of hemodynamics, respiratory system mechanics, and arterial oxygenation. Arterial blood gas was drawn at the end of each PEEP setting. After all the three PEEP levels, the ventilator was returned to its prestudy settings. Then, volume expansions (VEs) were performed with the infusion of 500 mL hydroxyethyl starch (Voluven 130/0.4) at a rate of 10 mL/kg/h. Another transpulmonary thermodilution CO was then performed for calibration at the end of VEs.All patients were sedated with a continuous infusion of midazolam  and paralyzed with cisatracurium  to abolish spontaneous triggering of mechanical ventilation. Patients were ventilated with the pressure-control mode; driving pressure was set to derive the VT to be approximately 6 mL/kg of the predicted body weight, and RR was set at 25 breaths/min. The mean PEEP level set before entry into the study was 14.3 (1.5) cmH2O. FiO2 was titrated to maintain SaO22, patients were classified as VE responders or nonresponders depending on whether the VE-induced CI increase at the end of VE was ≥ 15% or < 15%. The rates of intravenous fluid and vasopressor infusion and the settings of mechanical ventilation were kept constant throughout the study period.According to the criteria used in previous studiest test or Mann–Whitney U test. Spearman’s rank correlation was used to analyze the relationships of static lung compliance with PPV of the three PEEP levels before the fluid challenge. The prediction ability of the studied variables for positive fluid responsiveness after VE was tested using the receiver operating characteristic (ROC) curve. The cutoff value of the data is the maximum Youden’s index (J = sensitivity + specificity − 1). Sensitivity, specificity, and positive and negative predictive values are expressed as mean and 95% confidence intervals. All statistical analyses were conducted using SPSS for Windows , and a p value of < 0.05 was considered statistically significant.All variables were indexed to the body surface area and are expressed as mean ± standard deviation (SD). The Kolmogorov–Smirnov test was used to verify the normality of the distribution of continuous variables. Significance differences of variables among the three PEEP levels were analyzed using the repeated measures analysis of variance  or Friedman test followed by the Wilcoxon Signed Ranks test for nonparametric analysis. The differences in the various pre-VE values of responders and nonresponders were evaluated using the independent In total, 30 patients with early ARDS fulfilling the inclusion criteria were enrolled. The duration from ARDS diagnosis to the study procedures were within 2 days for all patients. Two patients were excluded because arrhythmia occurred during the study, and one patient was excluded because the VT was set too low (< 5 mL/kg). The main characteristics of the remaining 27 patients are summarized in Table The hemodynamics, pulmonary mechanics, blood gas data, and dynamic preload indicators of each time interval are listed in Table For predictive performance, PPV during PEEP15 had the highest area under the curve (AUC) of the ROC curve (0.85) than those during PEEP5 (0.81) and PEEP10 (0.67). The cutoff value of PPV during PEEP15 was 8.8%. However, the cutoff value of PPV during PEEP5 (3.2%) was too low to be clinically significant. Indexing PPV with Crs did not significantly increase the AUC of all the three PEEP levels Table . The ROCNormalizing PPV based on Driving-P further increased the AUC from 0.85 for PPV to 0.88 for PPV/Driving-P during PEEP15. However, the prediction performance remained poor for PEEP10 (AUC 0.67 versus 0.72) and was even poorer for PEEP5 (AUC 0.81versus 0.75) Table .p value for PEEP5: 0.77; PEEP10: 0.99; and PEEP15: 0.32) or fluid responders . The AUCs of PPV of Crs ≤ 30 versus Crs > 30 for PEEP5, PEEP10, and PEEP15 were 0.49 versus 0.55, 0.56 versus 0.70, and 0.49 versus 0.54, respectively.No significant correlation was observed between PPV and Crs for all the three PEEP levels irrespective of the total cases (The main findings of our study are as follows: (1) high PEEP of 15 cmH2O considerably decreased hemodynamics but increased the dynamic preload indicators of PPV, SVV, and PPV/Driving-P compared with those of PEEP5 and PEEP10; (2) Despite low VT, automatically measured PPV during PEEP15 had high predictive accuracy for fluid responsiveness, with the cutoff value of 8.8% and AUC of 0.85, which are higher than the AUC of PPV during PEEP5 (0.81) and PEEP10 (0.67); (3) correcting PPV with driving pressure further improved the prediction performance of PPV of PEEP15. Our study entirely focused on ARDS patients and investigated the effects of various PEEP levels on PPV predictability for fluid responsiveness. Furthermore, three PEEP levels were maintained in the same ARDS patients rather than analyzing various PEEPs in different patient groups who were already ventilated.9 and human studies have demonstrated that PPV is a poor indicator of fluid responsiveness. In the ARDS subgroup in De Backer’s study with a VT of < 8 mL/kg and PEEP of 11 cmH2O, the reported AUC of ROC curve was 0.716. Similarly, low AUC (0.64) was also found in the low VT group (6.6 mL/kg) (20/42 patients had ARDS) of Vallee’s study with PEEP set only at 6 (4–8) cmH2O [8]. Moreover, Lakhal et al.10 indicated that the performance of PPV was poor (AUC 0.75) in 65 people with ARDS ventilated with low VT [6.5 (1.4) mL/kg] and low PEEP [8.5 (3.2) cmH2O]. Recently, Monnet et al. reported a low AUC of 0.69 in a low-compliance ARDS group11, with PEEP and VT set at 7 cmH2O and 7.1 mL/kg, respectively. Contrary to the aforementioned studies involving low PEEP, Michard et al.19 demonstrated that PPV increased from 9% ± 7% to 16% ± 13% in ALI patients ventilated with VTs of 8–12 mL/kg when the PEEP increased from 0 to 10 cmH2O. Furthermore, both Kubitz et al.20 and Renner et al.25 showed increased PPV values with high PEEPs in anesthetized pigs. The excellent predictive performance of PPV in patients ventilated with high PEEP were demonstrated in septic ALI patients by Freitas et al. 22 and in ALI pigs by da Silva Ramos et al. 21. Our data support the aforementioned inferences and show that PPV during PEEP15 had higher AUC (0.85) than that during PEEP10 (0.67) and PEEP5 (0.81)  in Vallee’s study8. Furthermore, Lakhal et al. reported that in ARDS patients with low VT (6.5 mL/kg) and low PEEP (8.5 cmH2O) and PPV/Driving-P (AUC 0.72) did not improve the AUC of PPV (0.75)10. This negative performance is because pressure transmission from airway to pleura cannot be reliably estimated from the difference between plateau and PEEP28. In our data, the PPV/Driving-P during PEEP15 was significantly higher than during PEEP10 and PEEP5  and PEEP10 (AUC 0.67 versus 0.72) in the current study. However, the predictive performance of PPV/Driving-P improved compared with PPV during PEEP15 (AUC 0.88 versus 0.85)  Table .29. Teboul et al.30 proposed that low VT and low lung compliance account for the poor ability of PPV for predicting fluid responsiveness in ARDS. Recently, Monnet et al.12 demonstrated that the prediction ability of PPV is inversely related to Crs. If Crs was < 30 mL/cmH2O, then the PPV became less accurate for predicting fluid responsiveness. On the contrary, Venus et al.31 demonstrated that airway pressure transmission to pleural space reduced in ALI. However, with a constant VT, pleural pressure changes remained unaltered by changes in lung compliance. Scharf and Ingram32 and Romand et al.29 have proposed that the primary determinant of changes in pleural or intrathoracic pressure is the amount of lung inflation and not a specific change in compliance. Lakhal et al.10 demonstrated that PPV performance in patients with Crs less and more than its median value is similar, suggesting that this respiratory parameter fails to identify patients with higher PPV performance. Moreover, we did not find a considerable correlation between PPV and Crs in the total number of cases or in fluid responders for all three PEEP levels. The predictive accuracy of subgroups with Crs > 30 mL/H2O was not higher than that of subgroups with Crs < 30 mL/H2O. Furthermore, unlike PPV/Driving-P, adjusting PPV based on Crs even worsened the predictive performance of PPV in all three PEEP levels  to 25% under protective ventilation (6–9 mL/kg). Nearly all of our ARDS patients were enrolled within 2 days of ARDS diagnosis and were ventilated with low VT (6 mL/kg). Therefore, the influence of acute cor pulmonale on the predictive accuracy of PPV may not be as serious in our study. Table However, our study did have the limitation that the PA pressure was not obtained from the PiCCO2 monitor, and no echocardiography was performed to determine whether false-positive results were caused by acute cor pulmonale resulting from RV dysfunction. However, Vieillard-Baron et al.In conclusion, a high PEEP of 15 cmH2O considerably decreases the hemodynamics and increases the PPV. Ventilation with a high PEEP of 15 cmH2O can offset the disadvantage of low VT and preserve the high predictability of automatically calculated PPV for fluid responsiveness of ARDS patients. Normalizing PPV with driving pressure can further improve PPV predictability during a PEEP of 15 cmH2O.


The cerebrovascular resistance (CVR) shows that the CVR of hypertensive patients is higher than that of healthy people and stroke patients (p < 0.1), indicating that the cerebral vascular resistance of hypertensive patients is slightly higher. From the patient’s blood flow and vascular characteristics, it can be observed that the cardiovascular system is different from those in healthy people. Baroreflex sensitivity (BRS) decreased in stroke patients (p < 0.05). Chaotic analysis revealed that the blood pressure disturbance in hypertensive patients has a higher chaotic behavior change and the difference in initial state sensitivity. Cross-correlation (CCF) analysis shows that as the course of healthy→hypertension→stroke progresses, the maximum CCF value decreases significantly (p < 0.05). That means that blood pressure and cerebral blood flow are gradually not well controlled by the self-regulation mechanism. In conclusion, cardiovascular control performance in hypertensive and stroke patients displays greater variation. This can be observed by the bio-signal analysis. This analysis could identify a measure for detecting and preventing the risk for hypertension and stroke in clinical practice. This is a pilot study to analyze cardiovascular control variation in healthy, hypertensive and stroke groups.Cardiovascular diseases have been the leading causes of mortality in Taiwan and the world at large for decades. The composition of cardiovascular and cerebrovascular systems is quite complicated. Therefore, it is difficult to detect or trace the related signs of cardiovascular and cerebrovascular diseases. The characteristics and changes in cardiopulmonary system disease can be used to track cardiovascular and cerebrovascular disease prevention and diagnosis. This can effectively reduce the occurrence of cardiovascular and cerebrovascular diseases. This study analyzes the variability in blood pressure, cerebral blood flow velocity and the interaction characteristics using linear and nonlinear approaches in stroke, hypertension and healthy groups to identify the differences in cardiovascular control in these groups. The results showed that the blood pressure and cerebral blood flow of stroke patients and hypertensive patients were significantly higher than those of healthy people (statistical differences ( Cardiovascular diseases (CVD) have become a leading health care burden in many areas of the world. It was reported that high blood pressure is the main risk factor to induce CVD. Most deaths are caused by ischemic heart disease and ischemic stroke . TherefoIn this study, 3 groups were enrolled: 1) 11 healthy subjects (57.4 ± 8.4 years) that have no history of related cardiovascular diseases. 2) 11 hypertensive patients (50.8 ± 10.3 years) from the Neurology Section of Cheng-Ching General Hospital, Taiwan. Hypertension was according to BP(‧)in Pi is the wave-through time index in the ith BP pulse beat. Therefore, MABPi is the mean BP value calculated by the ith pulse beat. Representation of the BP signal is shown as CBFV(‧) is the CBFV pulse signal continuously acquired by the TCD. Vi is the time index of the wave-through in the CBFV signal corresponding to the ith pulse beat. MCBFVi is the mean CBFV value for the ith pulse beat. The CBFV signal representation is shown as Mean value estimation is based on every waveform peak and valley location. The mean arterial blood pressure (MABP) value was calculated using each pulse as follows:Resistance index is a measure of peripheral blood flow resistance. Low vascular resistance has a higher diastolic blood flow velocity characteristic, and will have a lower RI. A high vascular resistance has a lower diastolic blood flow velocity characteristic, and will produce a higher RI. RI can be calculated using the following formula, SCBFV is the systolic blood flow velocity, and DCBFV is the diastolic blood flow velocity. RI can be obtained by PI can be obtained by The pulsation index is a measurement that describes the type of signal waveform. Low intracranial vascular resistance will reduce PI, and rising intracranial pulsations have been found to be related to rising intracranial pressure. The normal PI range is between 0.5 and 1.4, less than 0.5 may be an ischemic flow pattern under vascular dilation, and greater than 1.5 may be a decrease in vascular compliance or an increase in intracranial pressure. PI can be calculated using the following formula, SCBFV is the systolic blood flow velocity, DCBFV is the diastolic blood flow velocity, and MCBFV is the average blood flow velocity. CVR can be obtained using The cerebrovascular resistance can be expressed as the ratio of the average pressure to the average cerebral blood flow rate. The unit is mmHg/(cm/s). CVR can be calculated using the following formula, where MABP is the average blood pressure and MCBFV is the average cerebral blood flow. Cross-correlation analysis mainly observes the correlation between the two signals in the time domain. Taking the average cerebral blood flow signal and the average blood pressure signal as an example, the correlation and phase relationship between the average cerebral blood flow signal and the average blood pressure signal can be determined by the brain. The phase relationship between blood flow and blood pressure is used to explore the blood flow regulation mechanism using the cardiovascular system. Let the cross-correlation function be expressed as CCF(k), W is the length of the window, k is the number of peak-to-peak displacement points, N is the total length of the signal, and the MABP time series normalized with the average value is expressed as x(n), MCBFV time series is expressed as y(n), the time series of x(n) after band-pass filtering is expressed as, and the time series of y(n) after band-pass filtering is expressed as, then cross-correlation The analyzed formula is as follows :CCFi(k)The index is used to evaluate the pressure-sensitive reflex. In order to observe the changes in heart rate and blood pressure at the same time, the baroreflex sensitivity index observes the relationship between the heart rate signal and the blood pressure signal. Assuming that the systolic blood pressure sequence SBP is S(n), and the heartbeat interval RR interval is R(n), the baroreflex sensitivity (BRS) T(n) can be expressed as: :T(n)=∑kN:number of pointsHE:Heaviside step functionHE = 1, if R-| Xi- Xj | ≧ 0HE = 0, otherwiseXi, Xj)The Euclidean distance of an attractor in 1 dm dimension is:(The correlation dimension (CD) can quantify the properties of the attractors from the time series and determine the singularity of the attractors, which is estimated by the correlation function by calculating the pairs of points where the attractors fall on the radius of the “sphere”. The correlation function Cd(R) is defined as :Cd(R)=ldc, the logarithm of both sides can be obtained:The relationship between the correlation integral and R is: Cd(R)∼RdL (0), and then the distance becomes dL(t) due to the trajectory divergence at time t, soλ1) in the time series. This method calculates the divergence rate of the reference trajectory and adjacent trajectories in the attractor. The maximum positive LE of the time series can be expressed as  is used to quantitatively analyze the chaotic behavior by measuring the sensitivity of the attractor initial state. Its physical meaning is the exponential rate of the divergence of adjacent trajectories in the attractor. It is used to measure the degree of attraction or separation between two adjacent trajectories in phase space. For example: the initial distance between two points of adjacent trajectories is essed as :λ1=limNKolmogorov entropy is a quantitative method for measuring the degree of chaotic behavior. It can also be used to distinguish the characteristics of dynamic systems: chaotic or non-chaotic. “Entropy” is adopted from the concept of thermodynamics as a method for expressing information characteristics, that is, the prediction of an uncertain system. The Kolmogorov entropy concept can be expressed as:K stands for Kolmogorov entropy. The unit is bit/s. S is the amount of change in the time development information predicted by the initial information S(t1) after one (t2—t1) time. Assume that the initial entropy information is S(t1), after a time interval t2—t1, the information change to become S(t2). The change difference information is K(t2—t1). Thus, it can be derived: S(t2) = S(t1) + K(t2—t1). When S(t1) > S(t2), so K(t2—t1) = S(t1)—S(t2). Assume S(t1) = lnCd(R), S(t2) = lnCd+1(R). Cd(R) is the signal correlation function. The equation for K2 is derived as below .as below :K2=lnCdp < 0.05). Diastolic arterial blood pressure (DABP) is statistically different in stroke patients (DABP: 101.69 ± 18.02 mmHg) as opposed to hypertensive patients (DABP: 87.01 ± 18.16 mmHg) (p < 0.05). It can be seen that cardiovascular diseases  do have obvious changing factors and trends to increase blood pressure. The systolic cerebral blood flow velocity (SCBFV) and mean cerebral blood flow velocity (MCBFV) showed that the value of stroke patients  was significantly higher than that of hypertension patients  and healthy people , and there was a statistical difference (p < 0.05). Diastolic cerebral blood flow velocity (DCBFV) is statistically different between stroke patients (DCBFV: 45.12 ± 24.78 cm/s) and healthy people (DCBFV: 23.69 ± 6.90 cm/s) (p < 0.05), and there is no significant difference in diastolic cerebral blood flow between hypertensive patients and stroke patients. p < 0.05) higher than those in healthy people . On the other hand, the BP values of hypertensive patients between healthy and stroke patients were without significant difference and this might indicate an increasing BP trend toward abnormal. The cerebral blood flow velocity of stroke patients is higher than that of healthy people. The systolic cerebral blood flow velocity values revealed a significant statistical difference .healthy: 2.32 ± 0.32; CVRhypertension: 3.9 ± 2.78), hypertensive patients vs. stroke patients  while in supine position (p < 0.1). There was no significant difference in PI in the subjects tested this time. Only the PI values of hypertensive patients and stroke patients tended to be slightly higher than normal. The cerebrovascular resistance index CVR shows that the CVR of hypertensive patients is higher than that of normal people and stroke patients (p < 0.1), which shows that the cerebral vascular resistance of hypertensive patients is higher, but it is speculated that once a stroke develops, the cerebral vascular lesions Instead, it reduces the vascular resistance in the brain.healthy > BRShypertension > BRSstroke, and BRS decreases accordingly. Healthy people vs. hypertension , healthy people vs. stroke , there are significant differences in both supine and tilting positions (p < 0.05).The pressure-sensitive reflex degree—baroreflex sensitivity (BRS)  is used as a measure of the autonomous control of the cardiovascular system. Usually BRS is a measure of the response of autonomic effectors to a given change in arterial pressure. When the position of a person changes from supine to a head-up position, blood pressure drops. This decreasing blood pressure can be compensated by the baroreflex through the conduction of the vagus nerve reflex. The sensory signal caused by the pressure receptor can inhibit the activity of the parasympathetic nerve and promote the activity of the sympathetic nerve, which increases the heart rate and vasoconstriction, helping to maintain proper blood pressure when standing. stroke:3.04 ± 0.28, K2hypertension:2.58 ± 0.39, K2healthy:2.59 ± 1.11), and there are statistical differences (p < 0.05) as shown in hypertension:1.28 ± 0.67,Tilt-LEhypertension:0.69 ± 0.43p < 0.05), such as shown in There are three main parameters in chaotic analysis: 1. Correlation dimension (CD) represents the complexity of a system, and the higher the CD value, the higher the system complexity. 2. Lyapunov exponent (LE) represents the sensitivity of the initial system state. A positive LE value indicates that the system dynamic behavior is chaotic, and a negative value or zero indicates regular behavior. 3. Kolmogorov entropy (K2) is a quantitative method for the degree of chaotic behavior. It is used to predict the information loss rate of future behavior, that is, the degree of unpredictability. For a regular system, K2 is zero. For a completely random system, the K2 value is infinite. For a chaotic system, the K2 value is finite and positive. p < 0.05) in the K2 index between supine and tilting positions. While in supine position, the K2 value of stroke was higher than that of healthy people, with a statistical difference . After head-up tilting, the K2 values of stroke patients were higher than those in hypertension patients and healthy people, and there was a statistical difference  as shown in hypertension:1.11 ± 0.43; tilting LEhypertension:0.64 ± 0.25, p < 0.05).p < 0.05). That means the relationship between blood pressure and cerebral blood flow decreased, reaching a statistical difference (p < 0.05). The time domain analysis results indicate that high blood pressure is one of the most important factors influencing the stroke process. Higher blood pressure and blood flow increase the risk for stroke . AlthougChaotic analysis can extract hidden behavior in a system. The K2 value is finite and positive for a chaotic system. Using the BP K2 results in chaotic analysis, it can be speculated that the changes in blood pressure in stroke patients are more unpredictable than in healthy people and hypertensive patients . AccordiThis study demonstrated the results from assessing the link change in linear and nonlinear analysis in healthy, hypertensive and stroke groups. The significant differences might indicate high blood pressure would be a critical factor that affects cardiovascular control with regulation function and blood vessel properties in hypertension and stroke subjects. The results from this study revealed the time domain analysis included BP and BFV levels, BRS, CVR and CCF. The nonlinear measures included LE, and K2, which are suitable parameters to explore the hidden components of circulation characteristics and performance in hypertensive and stroke patients. We speculate that an irregular cardiovascular system would tend toward dysfunction in various sub-systems and less predictable behavior. This could be as a measure for detecting and preventing the risk for hypertension and stroke in clinical practice .


Differential pressure valves are a popular treatment modality, with evidence suggesting that incorporation of gravitational units helps minimise over-drainage. This study seeks to describe the utility of the proGAV®2.0 valves and Miethke fixed-pressure valves between 2014 and 2019 at our tertiary centre were analysed. Patient demographics, indication for shunt and valve insertion/revision and time to shunt/valve revision were collected. Ventricular linear metrics  and fronto-occipital horn width ratio (FOHWR)) were collected pre- and post-valve insertion. Microsoft Excel and SPSS v24 were used for data collection and statistical analysis.Clinical records and imaging of all patients fitted with proGAV®2.0 valves were inserted in a population of 77 patients , mean age 5.1 years (IQR: 0.4–11.0 years)). A total of 102 Miethke fixed-pressure valves were inserted over the same time period. Median follow-up was 17.5 months (1.0–47.3). One (1.1%) proGAV®2.0 was revised due to over-drainage, compared to 2 (1.9%) fixed-pressure valves (p > 0.05). ProGAV®2.0 insertion resulted in a significant decrease in the mean number of revisions per patient per year . Overall shunt system survival with the proGAV®2.0 was 80.4% at 12 months, and mean time to revision was 37.1 months, compared to 31.0 months (95%CI: 25.7–36.3) and 58.3% in fixed-pressure valves (p < 0.01). Significant decreases were seen following proGAV®2.0 insertion in both FOHR and FOHWR, by 0.014  and 0.037  respectively.Eighty-eight proGAV®2.0 provides effective decompression of hydrocephalic patients, significantly reduces the number of valve revisions per patient and had a significantly greater mean time to revision than fixed-pressure valves.The  Ventricular shunts have long formed the mainstay of hydrocephalus treatment with ventriculo-peritoneal shunts (VPS) proving the most popular, utilised in an estimated 3500 procedures annually in the UK . VentricproGAV®2.0 comprises an adjustable differential pressure unit (DPU) composed of a solid titanium body with a ball-in-cone valve. A pre-tensioned bow spring, externally adjustable via magnets, defines the opening pressure of the DPU. The pre-tensioning of the spring and thus the opening pressure can be adjusted by turning a rotor, with the valve implanted under the patient’s skin. Distal to the DPU lies a gravitational unit of fixed resistance, governed by the weight of a tantalum ball. When the patient is lying down, the gravitational unit remains open, and therefore CSF outflow from the skull meets little resistance. Hence, the opening pressure of the proGAV®2.0 is defined by the setting of the adjustable DPU. When the patient moves into an upright position, the gravitational unit closes. In addition to the opening pressure of the adjustable DPU, the weight of the tantalum ball has to be exceeded; thus, the opening pressure becomes the sum of both DPU and gravitational unit. Only when the sum of the intraventricular pressure and the hydrostatic pressure exceeds the opening pressure of the combined components is drainage permitted [The Miethke ermitted .Typically, failure of a fixed-pressure valve system requires valve replacement which is accompanied by the risk of complication. Limiting the need for repeat surgical intervention is a crucial advantage to programmable valves; however, they are accompanied by their own complications , 10, 11,proGAV®2.0 programmable valve.In complex patients for whom multiple valve revisions are required, the need to minimise the number of operations is crucial, and recent data from our centre has demonstrated the positive impact of using fixed-pressure valves in treating hydrocephalus . This stproGAV®2.0 valves at either initial insertion or revision of shunts at Alder Hey Children’s Hospital NHS Foundation Trust between January 2014 and September 2018 were collected. Data was collected according to the following headings: (i) patient demographics, (ii) symptomatology (pre and postoperatively), (iii) indication for shunt/valve insertion, (iv) frequency of surgical intervention, (v) frequency of valve setting alteration and (vi) ventricular linear metrics.Clinical notes of all patients receiving For comparison, Miethke fixed differential pressure valve survival data for those inserted between January 2014 and September 2018 was extracted from our centre’s database . MiethkeShunt failure was defined as a surgical intervention wherein a valve or entire shunt system was replaced. Systems in situ for <1 month were excluded from survival analysis to account for immediate postoperative or inpatient-related complications. Kaplan-Meier curves were produced for (i) overall shunt system survival, (ii) shunt system survival , (iii) de novo vs replacement valve survival and (iv) ≤12 months vs >12 months on valve insertion.Over-drainage was defined according to a combination of ventricular morphology, symptomatic presentation of the patient and, if performed, ICP monitor values. The rationale for selecting appropriate replacement valves in the cases where revision was necessary was decided on a case-by-case basis. Gravitational unit choice was made according to Miethke guidance: 20cmH2O for those under 5 years of age and 25cmH2O for over 5 years. DPU pressure setting on insertion was decided on a case-by-case basis, guided by Miethke manufacturer recommendations ranging from 5cmH2O to 10cmH2O and above in those with particularly wide ventricles. Adjustments to the DPU pressure setting were made according to either inadequate response in ventricular metrics, the patient remaining symptomatic or ICP monitor values.For all patients, preoperative and postoperative imaging was assessed to determine changes in ventricular linear metrics. T2-weighted MRI scans were used to measure frontal and occipital horn ratio (FOHR) and frontal and occipital horn width ratio (FOHWR). In the absence of T2-weighted MRI, CT scans were used. All measurements were taken at the level of the intraventricular foramen of Monro, as identified on axial images. The FOHR was defined as the mean value of the frontal and occipital horn width divided by twice the widest biparietal diameter (BPD) , 17. FOHp = 0.05 was used to determine significance.The latest versions of Microsoft Excel and SPSS statistical software were used for data collection and statistical analysis respectively. Kaplan-Meier curves and log-rank tests were used to assess survival outcomes. Chi-squared test was used to compare categorical variables. A threshold of proGAV®2.0 valve, of which n = 45 (58%) were male. The overall mean age of the cohort was 5.1 years (IQR: 0.4–11.0 years). Median age for de novo proGAV®2.0 insertion was 11 months and for revision was 60 months. The valve population was dichotomised into groups ≤12 months of age  and >12 months of age .Seventy-seven patients were identified as having received a proGAV®2.0 valves were inserted over the time period analysed; therefore, n = 88 cases were available for assessment. Of these, n = 42 (48%) were as part of de novo shunt insertions and the remainder as revisions . Sixty-six (86%) patients received n = 1 proGAV® 2.0, and 11 (14%) patients received n = 2. Causes of hydrocephalus that indicated initial shunt insertion included intraventricular haemorrhage , spina bifida , tumours  and aqueductal stenosis  (Table Median follow-up was 17.5 months (1.0–47.3 months). Eighty-eight proGAV®2.0s included valve obstruction , infection  and over-drainage   proGAV®2.0 valves required revision. Obstruction was the leading indication for proGAV®2.0 revision , followed by valve mechanism failure  and catheter failure  (Table ProGAV®2.0s were exchanged ‘like for like’ in n = 9 (20%) cases. Of these, indications for revision were valve blockage , catheter/distal tubing problem  and infection . N = 5 (56%) of proGAV®2.0 ‘like for like’ revisions remained in situ at the latest data collection.n = 14, 13.7%), 9/24 , 9/29 , 10/40  and DualSwitch . Over-drainage led to revision in n = 2 (1.9%) fixed-pressure valves. N = 42 required revision, due to valve obstruction , infection  and over-drainage   than in either proGAV®2.0  or Miethke fixed-pressure valves  (p < 0.01).The only significant difference in aetiology of failure between valve types was over-drainage, occurring significantly more often in the series of valves replaced by a proGAV®2.0 inserted (n = 88) was treated as an individual case when analysing symptomatology before and after valve insertion, of which n = 78 (89%) had available data . In those ≤12 months, increasing head circumference, vomiting, lethargy, behavioural changes and sunsetting occurred most frequently. In those >12 months of age, headache, vomiting, nausea, lethargy and behavioural changes were most common. All patients found to be over-draining presented with low-pressure headaches (Table Each N = 11 of 88 (12.5%) had available ICP monitoring data pre-insertion of proGAV®2.0, and n = 5 (5.7%) had available post-insertion data. Pre-insertion, n = 6 (54.5%) had raised ICP, and n = 5 (45.5%) had low ICP. Post-insertion, n = 1 (20%) was normal, n = 1 (20%) had high pressure and n = 3 (60%) low pressure .N = 44 (57.1%) patients were under 5 years and therefore received 20cmH20 gravitational units and n = 33 (42.9%) over 5 years and therefore received 25cmH20 gravitational units. Initial pressure setting data for the DPU of newly inserted proGAV®2.0s was available for n = 69 valves, of which the median was 10cmH2O (range: 5–14). Over the time period analysed, ‘pressure alteration’ data was available for n = 71 valves; n = 41 (57.7%) of which required no alteration. Of the 30 valves (42.3%) requiring adjustment, n = 16 (22.5%) required 1 adjustment, n = 8 (11.2%) required 2 adjustments and n = 6 patients (8.5%) required ≥3 adjustments.N = 3 (3.4%) proGAV®2.0 and n = 13 (12.7%) fixed-pressure valves were replaced within 1 month of insertion and so were excluded from further analysis. Overall mean time to valve revision in the proGAV®2.0 group was 37.1 months (95%CI: 32.8–41.3), and overall survival (OS) was 80.4% at 12 months compared to 31.0 months (95%CI: 25.7–36.3) and 58.3% at 12 months in the fixed valve group . After excluding infection and distal failure as cause of failure, mean time to revision rose to 38.0 months (95%CI: 33.8–42.2) and cumulative survival to 82.7% with a proGAV®2.0, compared to 35.1 months (95%CI: 29.6–40.6) and 66.6% at 12 months with fixed-pressure valves (p = 0.02)  , though not significantly so (p > 0.1). ProGAV®2.0s in patients ≤12 months had a mean OS of 35.3 months and cumulative survival at 12 months of 71.2%, compared to a mean OS of 37.3 months and 86.3% 12-month cumulative survival in those >12 months (p = 0.25) , whilst the mean decrease in FOHWR was 0.037  (Table Across the entire cohort of n = 5 (6.5%) had slit ventricles before and after treatment . N = 4 of these of these had measurable ventricular metrics, of which none changed significantly following insertion; however, all of these patients had improvement in their symptoms.Across the cohort, proGAV®2.0 programmable valve.This study aims to describe a tertiary paediatric neurosurgical centre’s experience with the proGAV®2.0 cohort, a marked improvement in symptoms was observed after valve insertion, accompanied by a significant decrease in ventricular metrics . In patients with slit ventricles and symptoms of over-drainage, despite clinically improving, little real change was seen in their ventricular metrics. Slit-ventricle syndrome is relatively poorly understood, and the persistence of slit ventricles despite intervention and clinical improvement may speak to the nature of ventricular compliance in the syndrome itself or perhaps suggest that FOHR and FOHWR are not useful metrics in this scenario. Regardless, further investigation is needed into slit-ventricle syndrome both independently and in relation to different valve/shunt systems.Across the proGAV®2.0 valve resulted in a decrease in mean revision rate from 1.77 to 0.25 per patient per year, demonstrating a significant reduction in the number of revisions per patient (p < 0.01). In the future, comparing this impact on the revision rate with that of fixed-pressure valves is crucial and may better inform valve selection for patients [Valve revision forms a significant part of the paediatric neurosurgical workload, and numerous sources have reviewed the risks associated with it –22. Theopatients .proGAV®2.0 was extensively investigated, with overall survival rates of 81–88.7% [proGAV®2.0 cohort  [proGAV®2.0 group, patients ≤12 months of age at insertion did have shorter mean valve survival times and cumulative survival at 12 months compared to those >12 months of age (35.3 months and 71.2% vs 37.3 months and 86.3% respectively), though this discrepancy was not significant (p = 0.25).In the  = 0.10) , 22. The = 0.10) . In the proGAV®2.0s was significantly greater than either proGAV®2.0 or Miethke fixed-pressure valves (p < 0.01)  in this study, though these were relatively small cohorts and further follow-up is required. In those that had a proGAV®2.0 inserted for over-drainage, no cases recurred following insertion, demonstrating the valve’s efficacy in tackling the condition. Infection as a cause of shunt revision constituted 10% of proGAV®2.0 revisions but occurred in only 2.2% of all proGAV®2.0 valves inserted. This is markedly lower than infection rates identified in the literature for other valves [Over-drainage was the indication for revision in 11% of all valve types requiring revision Table . The over valves , 11, 24,proGAV®2.0 provide an opportunity to delay the need for surgery, with minimal effort and risk. Anecdotally, practitioners at the centre found the means by which to adjust the proGAV®2.0, simple to understand and straightforward to perform.Whilst ICP monitoring may be utilised to determine whether valve revision is necessary prior to surgery, it played a relatively small role in our centre, with only 12.5% having ICP monitoring. Often if clinical suspicion of over-drainage persists despite unremarkable ICP values, surgery may be opted for regardless. As is evidenced by the frequent adjustments made to the valves in this cohort, programmable valves such as the Limitations to our study include the retrospective nature of the data and the fact that accurately determining aetiology of shunt failure is subject to observer bias. Our study also does not assess the impact of fixed-pressure valves on ventricular metrics or revision rate before and after insertion. This was not examined in the original study either ; therefoproGAV®2.0 programmable valve reduced the need for valve revision in patients with ventricular over-drainage, such that no cases re-occurred during the follow-up period. Both 12-month survival and mean time to revision were significantly greater in proGAV®2.0 programmable valves compared to Miethke fixed-pressure valves. This study provides evidence to support the wider use of programmable valves, but the impact of cost was not assessed, and further investigation is therefore required.The


Chronic kidney Failure (CKD), particularly End-Stage Renal Disease (ESRD), may be serious ill-health related to a high death rate. Uremic syndrome leads to increased oxidative stress, inflammation, and dyslipidemia. Our study aimed at identifying the association of NOS3 (rs 2070744) and SOD2 Val16Ala (rs4880) gene polymorphisms within ESRD Egyptian patients.This work was conducted on 100 ESRD and 16 CKD Egyptian patients who were compared to 100 healthy controls. DNA was genotyped for these variants using the (T-ARMS-PCR) technique.P = 0.032). In the contrast, the present study revealed that no statistically significant differences were found among the CKD, ESRD, and control groups as regards the SOD2 genotypes (P = 0.064).ESRD patients showed a significant association of the genotype of NOS3 gene polymorphism compared with healthy controls (Our findings indicated a significant association between NOS3 (rs 2070744) gene polymorphism and increased risk of ESRD and CKD among Egyptian patients. This pathology has a complicated interrelationship with other diseases. Diabetes (DM) and hypertension (HT) are the main risk factors for CKD, and CKD is also associated with cardiovascular morbidity and mortality, even in early stages and in young patients [Chronic kidney disease (CKD) is becoming a major public health problem worldwide. CKD is defined as a progressive loss of renal function, measured by a decline in glomerular filtration rate  .Chronic kidney disease is a complex heterogeneous disease, with contributions from both genomic and environmental factors. CKD heritability has been estimated to be high (30–75%) .CKD patients have many affected physiological pathways. Variations in the genes regulating these pathways might affect the incidence and predisposition to this disease .Several hundred genes are currently known to contain mutations that can cause single-gene disorders with a kidney phenotype, as well as dozens of genetic loci in which common genetic variants are associated with kidney function in the normal range and with complex kidney diseases .Most cases of CKD are caused by chronic-degenerative diseases and endothelial dysfunction is one of the reasons that contribute to its pathophysiology. One of the most imperative mechanisms for the suitable functioning of the endothelium is the regulation of the synthesis of nitric oxide .l-arginine through the action of the membrane-associated epithelium organic isoform of NO synthase (ecNOS). A reduced expression of eNOS might contribute to the epithelium pathology in nephritis [Nitric oxide (NO), the most dilator discharged by the epithelial tissue, is synthesized by the chemical reaction of ephritis .NOS3 (eNOS) gene has 23.605 bases and is located at 7q36.1. It has twenty-six exons and codes for NOS3, an enzyme composed of 1203 amino acids with an Mwt. of 133.289 Da [The eNOS factor has 2 common alleles comprise of 4 repeats (a) and 5 repeats (b) that manufacture 2 homozygous (aa and bb) and 1 heterozygous (ab) genotypes .The NOS3 gene polymorphisms 894G>T or Glu298Asp (rs1799983), 27-bp repeat in intron 4 (VNTR) 4b/a variations, and − 786 T>C have all been explored in numerous disorders linked to diabetic nephropathy in diverse publications .The functional effect of these variants is to reduce the expression of mRNA or change the function of eNOS, resulting in a reduction in NO production. Genetic variations in the eNOS gene have an essential role in the development of renal disease .Two alleles have been found in the 27 bp VNTR of intron 4, the larger of which has five tandem 27 bp repeats and the smaller of which has four 27 bp repeats. They dubbed these two alleles the “4b” and “4a” alleles, respectively, to describe the wild-type and mutant alleles. The impact of this polymorphism on eNOS expression and activity is poorly defined .Oxidative stress is linked to inflammation, cardiovascular disease, epithelium pathology, and CKD progression .Redox state in mitochondria is regulated by not only Mn-SOD but also other antioxidative enzymes, including Cu/Zn-SOD, GPx, and the PRx/TRx system. However, as Mn-SOD catalyzes the first step in ROS scavenging in mitochondria, treatments targeted at supporting Mn-SOD integrity and function may lead to effective treatments to prevent the onset and progression of kidney disease .Metal SOD (MnSOD) is one of the crucial enzymes that defend against ROS within the mitochondria. The SOD2 gene is set on the body at 6q25.3. Currently, many single-nucleotide polymorphisms (SNPs) within the MnSOD cistron are rumored, of that the foremost extensively studied one is Val16Ala .SOD2 (MnSOD) is a single-copy gene having five exons and four introns separated by normal splice junctions. The start site is used to illustrate the position and size of each exon in terms of DNA base pairs, as shown in Fig. The genetic variations that encode antioxidant enzymes were associated with creatinine levels, glomerular filtration rate (GFR), albumin and phosphorus levels, erythropoietin resistance index, C-reactive protein, and ferritin levels which play a serious role in CKD progression .Therefore, the purpose of this research is to see how NOS3 (rs 2070744) and SOD2 Val16Ala (rs4880) gene polymorphisms affect CKD progression in Egyptians.Before being included in the study, all individuals gave written informed consent, and blood samples were taken according to protocols approved by the hospital’s Outpatient Clinic’s Ethics Committee.ESRD group: this group included 100 females and males ESRD patients whose ages ranged from 18 to 82 years old (mean age = 47 years and SD = 16.1).CKD group: this group included 16 females and males CKD patients whose ages ranged from 15 to 58 years old (mean age =40 years and SD = 11.09). The clinical data of all patients were obtained from medical records. Patient's data included age, sex, and laboratory investigation such as Hb conc., creat conc., bilirubin, albumin, SGPT, SGOT, FBS, HBS Ag, and HCV.Control group: this group included 100 healthy samples  for comparison; their age and sex were matched with the chronic kidney disease patients, and their families did not have any record of chronic kidney disease history .Patients with CKD were screened and diagnosed between September 2018 and March 2019 from the Outpatient Clinic of the hospital. The study involved a total of 216 Egyptian adults, including 116 patients suffering kidney pathologies at different stages, and 100 controls. The participants were divided as follow:Three milliliters of peripheral blood was collected from all subjects using vacationers and transferred to test tubes containing EDTA solution as an anticoagulant to obtain whole blood, for extraction and purification of DNA. Peripheral blood samples are also utilized to investigate biochemical markers related to CKD.The handling and extraction of genomic DNA for all participants enrolled in this work was accomplished by using the generation DNA purification capture column kit . The extraction procedures were carried out based on the prescripts provided by the producer for the peripheral blood samples.DNA in the sample was released using proteinase K (PK) solution and lysis B buffer. The released DNA was bound exclusively and specifically to the biospin membrane in the presence of lysis B buffer and ethanol under the appropriate salt iron and pH conditions. Denatured protein and other contaminants were removed with twice washing procedures. With the elution buffer, the DNA was then eluted from the membrane .The amplification and genotyping of eNOS (rs 2070744) and MnSOD Val16Ala (rs4880) Gene variants were described using the tetra-primer amplification refractory mutation system polymerase chain reaction (T-ARMS-PCR) .T-ARMS-PCR was performed by using the tetra primer  and the amplicons purification using QIAquick PCR purification kit (Qiagen) .The DNA was amplified using specific oligonucleotide primers based on the published sequence . Two primer pairs were used to accentuate and designate the genotype of a deoxyribonucleic acid fragment, as well as the Ala16Val SNP within the human MnSOD sequence. The 3′-end of the allele-specific primers were underlinedF1 (forward) 5′-CACCAGCACTAGCAGCATGT-3′;F2 (forward)5′GCAGGCAGCTGGCTaCGGT-3′;R1 (reverse) 5′-ACGCCTCCTGGTACTTCTCC-3′and R2 (reverse)5′-CCTGGAGCCCAGATACCCtAAAG-3.PCR was conducted in an exceedingly total volume of 25 μL containing 4 μL of genomic DNA because the templet, 4 μL of every primer, 13 μL Master Mix (2×). PCR amplification was conducted with primary denaturation at 95 °C for 2 min, followed by 35 cycles of 1 min of denaturation at 94 °C, 1 min of hardening at 60 °C, 1 min of extension at 72 °C, and a further a pair of min extension at 72 °C at the tip of the ultimate cycle. Next, The PCR products were electrophoresed on 2% agarose gel and visualized using ethidium bromide under ultraviolet illumination below ultraviolet radiation.The PCR product for MnSOD cistron was detected at 189 bp for wild-type , and 366 bp for mutant type (Ala/Ala) then photographed by the photographic camera. Once the sample had a pair of bands at 189 bp in the wild tube and 366 bp within the mutant tube, it meant it had Val/Ala heterozygote genotyping. On the opposite hand, once the sample had a band that appeared at 189 bp in the wild-type tube and no band within the mutant factor, this meant it had Val/Val homozygote genotyping. Once the sample had a band at 366 bp within the mutant factor and no band in the wild-type factor, this meant it had Ala/Ala homozygote genotyping as shown in Fig. PCR was performed by using only one pair of primers, 2 oligonucleotide primers that flank the region of the 27-bp repeat sequence in intron 4 of the eNOS gene were used for polymerase chain reaction (PCR) amplification. The eNOS primers were synthesized by Integrated DNA Technologies, Inc. . The forward primer was 5′-AGGCCCTATGGTAGTGCCTTT-3′ and the reverse primer was 5′-TCTCTTAGTGCTGTGGTCAC-3′ .PCR was conducted in an exceedingly total volume of 25 μL in only one tube containing 4 μL of genomic DNA, 4 μL of every primer, 13 μL Master Mix (2×). The reaction mixture was heated to 95°C for 6 min for denaturation and then subjected to 35 cycles at 95 °C for 1 min, annealing at 58 °C for 1 min and extension at 72 °C for 2 min, followed by a final extension step at 72 °C for 7 min.The PCR products were electrophoresed on 2% agarose gel and visualized using ethidium bromide under ultraviolet illumination. The PCR product for the eNOS gene (intron 4a/4b) was detected at 420 bp for wild-type (4b) and 393 bp for mutant-type (4a) then photographed by the digital camera.When the sample had 2 bands at 420 bp wild-type 4b allele and 393 bp for mutant-type it meant it had 4ab heterozygote genotyping. On the other hand, when the sample had a band at 393 bp for mutant-type and no band at 420 bp for wild-type, this meant it had 4aa homozygote genotyping. When the sample had a band at 420 bp for wild-type and no band for mutant-type, this meant it had 4bb homozygote genotyping as shown in Fig. Data were collected, coded, revised, and entered into the Statistical Package for science (IBM SPSS) version 20. For qualitative data, mean, standard deviations, and ranges were used; for quantitative data with a parametric distribution, median with interquartile range (IQR) was used; and for quantitative data with a non-parametric distribution, median with interquartile range (IQR) was used.t test was used to compare two groups with quantitative data and a parametric distribution, while the Mann-Whitney test was used to compare 2 groups with qualitative data and a non-parametric distribution.When comparing two groups with qualitative data, the chi-square test was utilized, and the Fisher exact test was used instead of the chi-square test when the expected count in any cell was less than 5. The independent The one way analysis of variance (ANOVA) test was used to compare more than two groups with quantitative data and parametric distribution, and the Kruskal-Wallis test was used to compare more than 2 groups with quantitative data and non-parametric distribution.P value was deemed significant: P > 0.05: non-significant (NS), P < 0.05: significant (S), P < 0.01: highly significant (HS). Figure The margin of error acceptable was set to five because the confidence interval was set at 95%. Because of the following, the The genotypes of 216 individuals  and the essential clinical and demographic characteristics of CKD patients and unrelated healthy controls are described in Table P < 0.001. Also, there was a highly significant increase in Hb, creatinine, bilirubin, and SGPT in the CKD and ESRD groups in comparison to the control group. Moreover, ESRD patients had  a highly significant increase in Ca, Phosphate, and PTH in comparison to the control group . The genotypes of the groups were determined by PCR. Fragments containing 366 bp (Ala) and 189 bp . The genotype distribution in patients and controls is shown in Table The Val16Ala polymorphism in MnSOD was found to be in Hardy–Weinberg equilibrium. The Ala allele was found 18% in control patients, 31.2% in CKD cases, and 26% in ESRD cases  and 393 bp . The genotype distribution in patients and controls is shown in Fig. P = 0.032. This study shows that the a allele has a higher statistically significant difference between CKD, ESRD, and control group among eNOS Genotyping than b allele as shown in Table We found that there was a statistically significant difference between CKD, ESRD, and control group among eNOS genotyping where In our study, we found that there was a statistically significant increase in 4aa in comparison to 4ab and 4bb with phosphate and bilirubin in ESRD by comparison between eNOS genotype in ESRD among clinical data as shown in Table The chronic renal disorder could be a variety of renal disorders during which there's gradual loss of excretory organ performance over several months to years. Initially, there are generally no symptoms; later, symptoms could embody leg swelling, feeling tired, vomiting, loss of craving, and confusion .P = 0.004) among the study groups as regards gender as females represented 50%, 31%, 54% of the CKD, ESRD, and control groups respectively whereas males represented 50%, 69%, 46% of the CKD, ESRD and control groups respectively. Furthermore, a very highly statistically significant difference (P < 0.001) was found among the study groups as regards age which was mainly between the ESRD group, the gender distribution revealed in the current study comes in line with what was published by Goldberg and Krause in 2016 as they noted that while the prevalence of CKD tends to be higher in women, the disease is more severe in men, who also have a higher prevalence of ESRD. As regards the mean age of patients revealed in this study, it agrees with what was published by the Centers for Disease Control and prevention in 2020 as they mentioned that after the age of 40, kidney filtration begins to decline at a rate of about 1% per year. They went on to say that, in addition to natural renal aging, several illnesses that harm the kidneys, such as diabetes, high blood pressure, and heart disease, are more common in older persons.To our knowledge, this is the first study to interpret the association of the MnSOD Val16Ala and NOS3(rs 2070744) gene polymorphisms as a risk factor in Egyptian patients who had chronic kidney disease. The present study revealed a highly statistically significant difference  SOD2 gene polymorphism is the greatest investigated for disorders associated with CKD and its renal consequences. The SOD2 Val16Ala variations impair the antioxidant enzyme's processing efficiency by producing conformational changes that result in decreasing the efficiency of mitochondrial transit of the Val form, which can diminish MnSOD activity and level in the mitochondria and contribute to redox reactions .In terms of SOD genotypes, no statistically significant differences were detected between the CKD, ESRD, and control groups in this investigation. Furthermore, the current investigation discovered no statistically significant differences between the different SOD genotypes in the CKD group as regards the mean levels of creatinine, bilirubin, albumin, SGPT, SGOT, and FBS. Meanwhile, numerous studies have shown significant associations between the SOD2 gene Val16Ala polymorphism and albuminuria as in the studies published by Yang et al. ; Liu et Moreover, our study also revealed that no statistically significant differences were found between the different SOD genotypes as regards the prevalence of hypertension or diabetes. On the contrary, Val/Val genotype was found to be more common in both type 1 and type 2 diabetes patients by Flekac et al. , which wGenetic polymorphisms in the eNOS gene are shown to affect their activity and may also promote CKD progression in diabetic and hypertension patients .P = 0.032) between the patient and control groups as regards eNOS genotype with a higher percentage of those having 4aa and 4ab genotypes being in the patient’s group and a higher percentage of those having 4bb genotype being in the control group. eNOS gene is known as a candidate gene in cardiovascular and renal diseases [The current study revealed a highly statistically difference  and 104 healthy subjects .This is the first study that explores a significant association with NOS3 (rs 2070744) gene polymorphism within the increased risk of ESRD and CKD among Egyptian patients. However, some research did not detect a link; therefore, the findings are debatable. More research in different populations is needed to find potential genetic risk factors for CKD.


Although this situation is slowly changing, in everyday practice we continue to struggle with problems that are not clearly addressed in the guidelines. This literature review was conducted by an interdisciplinary group, which comprised a nephrologist, internal medicine specialists, and cardiologist. In this review, we discuss the difficulties in ruling out HF for patients with advanced CKD and issues regarding the cardiotoxicity of dialysis fistulas and the occurrence of pulmonary hypertension in patients with CKD. Due to the recent publication of the new HF guidelines by the European Society of Cardiology, this is a good time to address these difficult issues. Contrary to appearances, these are not niche issues, but problems that affect many patients.Is advanced chronic kidney disease (CKD) a cardiac “no man’s land”? Chronic heart failure (HF) is widely believed to be one of the most serious medical challenges of the 21st century. Moreover, the number of patients with CKD is increasing. To date, patients with estimated glomerular filtration rates <30 mL/min/1.73 m It is estimated that HF currently affects 1–2% of the adult population in developed countries . Chronic/1.73 m2 . With thWe searched PubMed for articles with the key words “heart failure”, “chronic kidney disease”, “pulmonary hypertension”, “arteriovenous fistula”, “natriuretic peptides”, “fluid overload”, “end stage renal disease”, and “hemodialysis”. In particular, we used the following search terms and logic: “chronic kidney disease AND heart failure” OR pulmonary hypertension AND “chronic kidney disease OR heart failure” or “chronic kidney disease AND arteriovenous fistula AND cardiotoxicity”. Additional studies were identified by examining the references of some articles. Articles were selected according to their title and abstract, based on eligibility criteria. We included English articles, adult populations, and all types of study, including narrative and systematic reviews, clinical studies, case reports, and expert opinions. Manuscripts published in a language other than English were excluded. In general, we excluded studies published earlier than in 2010, but we made single exceptions to this rule. The final analysis included 61 articles, which we selected, based on originality and relevance to the broader scope of our review. In the discussion of the basic issues concerning the pharmacotherapy of HF in the coexistence of advanced CKD, an additional 11 articles were cited, according to the subjective assessment of the authors of the review.According to the current diagnostic algorithm, we suspect HF on the basis of typical symptoms and signs in a patient with HF risk factors and an incorrect ECG . A conce2A reduction in the eGFR to < 60 mL/min/1.73 mKidney damage in imaging, histopathology, or laboratory tests.Nosologically, neither HF nor CKD are disease entities; instead, they are clinical syndromes. HF is currently defined as a “clinical syndrome consisting of cardinal symptoms  that may be accompanied by signs . HF is due to a structural and/or functional abnormality of the heart that results in elevated intracardiac pressures and/or inadequate cardiac output (CO) at rest and/or during exercise.” . The defTherefore, the diagnosis of CKD is determined by specific tests, not by clinical symptoms. According to the Kidney Disease: Improving Global Outcomes guidelines of 2012, there are five stages of CKD. A correct classification of the CKD stage requires assessments of GFR and albuminuria, and to determine the combination of causes; thus, the classification includes the GFR category (G1–G5), and albuminuria category (A1–A3), as proposed in the guidelines . Hence, The circulatory system consists of four main compartments—venous, arterial, pulmonary, and systemic. The distribution of fluid volumes within these compartments is asymmetric. The arterial system comprises 20–30% and the venous system comprises 70–80% of the fluid volume. The structure and function of the heart contribute to the maintenance of this physiological asymmetry. When disorders in the heart’s pumping function outweigh disorders of the return function, the cardiac muscle cannot generate an adequate CO, due to low stroke volume. The result is called forward failure. Conversely, when the return dysfunction is predominant, the result is called backward failure, and the predominant venous outflow results in organ congestion. Therefore, the consequence of HF is a redistribution of the intravascular volume, which leads to a permanent underfilling of the arterial compartment (10–15%) and displacement of the "extra" volume into the venous compartment (85–95%). Thus, ultimately, in HF, fluid overload is most often associated with hypovolemia. However, it should be emphasized that, in patients with CKD, fluid overload is associated with hypervolemia. As shown in A physical examination generally assesses the patient’s signs and symptoms, and severity is graded with the New York Heart Association (NYHA) classification. The examination typically includes a blood pressure measurement and assessments of the presence and severity of peripheral edema and the detection of crackles over the pulmonary fields. However, these assessments are not sufficient to make a reliable assessment of the degree of fluid overload ,20,21. MThe use of additional assessment methods is time-consuming. Therefore, research is ongoing on the development of simplified diagnostic schemes. Among the biochemical markers for assessing hydration status, natriuretic peptide concentrations are often measured. Both brain natriuretic peptide (BNP) and the inactive N-terminal prohormone-BNP (NT-proBNP) are produced at high levels in HF. However, the results should be interpreted carefully.Normally when HF is suspected, BNP/NT-proBNP concentration is of key importance in the diagnostic algorithm . They arFor patients with stage 3–5 CKD, the BNP threshold for diagnosing HF should be 200 pg/mL ,24,25,262; however, that finding was based on the adoption of cut-off thresholds that were double the typical NT-proBNP thresholds used for diagnosing HF in different age groups [2, and 259.7 pg/mL for patients with eGFRs > 30 mL/min/1.73 m2 [2, and 251 pg/mL for predicting cardiovascular death in patients with eGFRs < 60 mL/min/1.73 m2 [Deteriorating renal function affects the NT-proBNP concentration to a greater extent than the BNP concentration. In patients without CKD, these markers are equally important for the diagnosis of HF; however, in the context of a prognosis assessment, NT-proBNP has shown better value than BNP ,13,26. Ie groups . Many st/1.73 m2 . Şimşek NT-proBNP is also an important prognostic factor in patients on dialysis . Tsai etThe implantation of a venous catheter during hemodialysis is associated with an increased rate of infection and early mortality. Hence, the principle of “fistula first” has been widely promoted. However, although AVFs are associated with better clinical outcomes compared to other forms of vascular access, they are not without potential complications ,36. The When an AVF is generated, it causes an immediate decrease in systemic peripheral resistance and blood leaks through the low-resistance artificial arteriovenous junction. A decrease in systemic resistance increases sympathetic activity, which increases the CO to maintain blood pressure. Therefore, the first adaptive mechanism is the occurrence of hyperkinetic circulation ,38, whicp = 0.004), for RVLS, and 0.81 , for TRJV > 2.61 m/s [The therapeutic management of HF with a high CO is difficult. Standard pharmacological treatment does not seem to be particularly effective. In recent years, several case reports showed that a surgical fistula closure was associated with improved performance in HF ,44,45. H2.61 m/s . Additionally, it is worth noting that, in the Gumus and Saricaoglu study, the definition of RV HF included the natriuretic peptide concentrations and a number of echocardiographic parameters ; the presence of significant peripheral edema, ascites, or hepatomegaly; and laboratory markers of deteriorating liver or kidney function, compared to the state before the fistula creation . The litCurrently, we know little about how to apply the existing knowledge about the cardiotoxic potential of AVF in practice ,49. Amonoverhydrationpulmonary congestion, resulting from reduced LV compliance, and LV diastolic dysfunction (a consequence of arteriosclerosis and chronic hypertension)pulmonary vessel remodeling, caused by an increase in vasoactive factors inflammationcoexisting lung disease increased CO in the course of anemia, due to the presence of an AVF ,50Pulmonary hypertension is defined as a mean pulmonary artery pressure ≥25 mmHg at rest, based on a direct hemodynamic measurement. Pulmonary hypertension can occur secondary to many diseases of the heart, lungs, and pulmonary vessels. Classically, there are five groups of pulmonary hypertension. The fifth group includes: hematologic disorders, systemic diseases, metabolic disorders, chronic renal failure, and disorders leading to pulmonary vascular occlusion or compression. However, for patients with advanced renal failure, including those on dialysis, the pathophysiology of pulmonary hypertension is multifactorial. The pathophysiological mechanisms include:Ultimately, pulmonary hypertension affects 21–41% of patients with chronic kidney disease and up to 60% of patients treated with hemodialysis ,54,55,56Depending on the probability of pulmonary hypertension, assessed by echocardiography and the clinical picture, indications for cardiac catheterization are determined. Cardiac catheterization is the only examination that determines the diagnosis of pulmonary hypertension. During right heart catheterization the pulmonary capillary wedge pressure, pulmonary arterial pressure, and pulmonary vascular resistance are determined. Based on these results, three pulmonary hypertension subtypes are distinguished: (1) pre-capillary, (2) post-capillary, and (3) combined pre- and post-capillary .Concurrent CKD strongly influences both the pulmonary hypertension subtype and the associated mortality. Edmonston et al. showed that, among patients without CKD, the pre-capillary subtype was dominant, and was associated with the highest risk of death. In contrast, among patients with CKD, the combined pre- and post-capillary and isolated extra-capillary subtypes dominated . The mulThe main topic of our review is the issue of diagnostic difficulties, but it is impossible not to refer to the issue of pharmacotherapy. Medications that can improve prognosis in HF with reduced LVEF are angiotensin-converting enzyme inhibitors (ACE), angiotensin II receptor blockers (ARB), angiotensin receptor neprilysin inhibitors (ARNI), b-blockers, and mineralocorticoid receptor antagonists (MRA). Recently sodium-glucose cotransporter 2 inhibitors (SGLT-2) have joined this group, and according to current ESC guidelines blockade of the renin-angiotensin-aldosterone system with ACE, ARNI or ARB, beta-blocker, SGLT-2 inhibitor and MRA should be started as soon as possible after the diagnosis of HF with reduced LVEF . Until rAmong patients that first develop chronic progressive renal failure, it may be difficult to confirm concurrent HF. The clinical symptoms of HF and advanced CKD may be confusingly similar, particularly in patients on dialysis. The eGFR has a significant impact on natriuretic peptide concentrations—indeed, increases in these peptides result from both damage to the heart and their impaired elimination in the kidneys. Definitive cut-off points for BNP and/or NT-proBNP concentrations have not been established for diagnosing HF in patients with CKD. However, elevated levels of these peptides have been shown to have negative prognostic significance. Therefore, for patients with intermediate or preserved LVEF and CKD, there remains a need for new diagnostic criteria that can confirm or exclude HF as the primary cause of fluid overload. Moreover, the correct diagnosis of HF in patients classified as pre-dialysis may be a key issue in selecting the optimal vascular access. Despite the convincing pathophysiological basis, little evidence is available to support the potential cardiotoxicity of fistulas. However, new research has indicated that it may be possible to use an echocardiographic assessment of RV strain.


Many African countries including Nigeria are said to be at various stages of an epidemiological transition from communicable to non-communicable diseases (NCD).This study determined the current pattern and correlates of hypertension among adults in some rural communities in South West Nigeria.It was a descriptive cross-sectional study of 1012 individuals across 16 rural communities. The respondents' blood pressure, weight, height and waist circumference were measured. Bivariate and multivariate analyses were done.Among the participants, 461 (45.6%) had hypertension out of whom 217 (47.1%) and 244 (52.9%) had stage 1 and stage 2 hypertension respectively. The systolic, diastolic and mean arterial blood pressures increased with age. The significant predictors of hypertension were; increasing age (p<0.001), higher waist circumference (p = 0.01) and overweight / obesity (p = 0.03). While systolic blood pressure (SBP) had the strongest correlation with age, waist circumference (WC) was the strongest correlate of diastolic blood pressure (DBP).Despite being a rural population, there was a high prevalence of hypertension in the study area. Hypertension is the world's leading risk factor for global disease burden and it is projected to affect approximately 1.6 billion adults worldwide by 2025Most sub-Sahara African countries including Nigeria are said to be at various stages of an epidemiological transition from communicable to non-communicable diseases (NCD)Hypertension does not usually present with specific symptoms until complications begin to set in, hence its identification is usually through screeningThis study thus determined the pattern and correlates of high blood pressure among adults living in the rural communities of a local government area in Osun State, South West Nigeria. This will hopefully provide additional useful information to policy makers and relevant stakeholders. It will also contribute to the continuously updated database about the disease nationally and globally.This descriptive cross-sectional study was carried out in Ife East local government area (LGA) of Osun state, South-Western Nigeria. Ife East was purposively selected out of the 30 LGAs in the state. The 2016 estimated population based on the 2006 census and a national annual population growth rate of 2.5% is 259,700The LGA is divided into 10 administrative wards, out of which three wards were randomly selected for the study. Participants were recruited from all the major rural communities in the selected wards totaling 16 communities. Compared to general population, the population of the rural communities were tilted towards a predominance of the middle aged and elderly due to rural-urban migration by many of the younger ones.Each of the communities were estimated to have about 100 adults aged 20 years and above. It was a consecutive house to house survey. All eligible and consenting adults in every household were recruited until an average of 60 respondents were enrolled in each community. Pregnant women were excluded.The calculated minimum sample size, at 95% confidence level and 5% margin of error, was 378 using a previous prevalence of 46.4% from a similar studyData collection was done in line with the World health Organization's STEP-wise approachEach respondent's blood pressure was measured with Accosson® Mercury sphygmomanometer within the same time frame each day. The blood pressure reading was taken in sitting position after the respondent has rested for about ten minutes. The participants were informed, and it was ascertained that coffee, alcohol or cigarette was not used, nor was any physical exercise done least 30 minutes before the measurement. An appropriate sized cuff was used and the bell of the stethoscope was placed about 2cm above the antecubital fossa. The cuff was inflated to 20mmHG above the palpated systolic blood pressure and thereafter deflated gradually. The first sound (Korotkoff phase 1) and the disappearance of the sound (phase 5) were taken as the systolic blood pressure (SBP) and diastolic blood pressure (DBP) respectively. Two readings were taken at an interval of about five minutes and the average was recorded. The supervisor oversaw the measurements.A respondent was defined as having hypertension if he/she had a systolic blood pressure of ≥ 140mmHg and/or diastolic blood pressure reading of ≥ 90mmHg or was on pharmacological treatment for hypertension within the preceding two weeks2), overweight (BMI 25 -29.9 kg/m2) or not (BMI <25kg/m2). The waist circumference (WC) was measured at the midpoint between the sub-costal margin and the iliac crest. Abdominal obesity was defined as waist circumference of ≥ 102 cm for men and ≥ 88cm in womenThe weight, height and waist circumference were also measured. The weight was measured in light clothing to the nearest 0.1 kilograms without any accessories such as shoes, purses, cell phones, etc. The weighing scale was regularly adjusted to reset it to zero. The height was measured without foot-wears to the nearest 0.5 centimeter using a ruler attached to the wall. The body mass index (BMI) – defined as the weight in kilogram divided by the square of the height in meters – was calculated. Based on the BMI, the respondents were classified as either obese . Descriptive statistics was used to summarize the data. At the bivariate level, the Pearson chi-square test was used to determine the significance of association between hypertension and some categorical variables. The differences in some continuous variables based on gender were assessed by Students' t-test while Pearson's correlation was done to determine the degree of relationship between quantitative variables. The factors that were significant at the bivariate level were included in a multivariate binary logistic regression model to determine those which independently predicted the presence of hypertension. Collinearity diagnostic tests were done and there was no multicollinearity among the variables that were included in the model. The results were expressed as odds ratio (OR). The level of significance for all the statistical analyses was set at p < 0.05.All the eligible individuals who were approached for the study gave their consent to participate, yielding a 100% response rate. A total of 1012 individuals made up of 428 (42.3%) males and 584 (57.7%) females participated in the study. Their ages ranged from 20 to 103 years with a mean of 47.7 ± 16.7 years.Among the participants, a total of 461 (45.6%) were defined as having hypertension by blood pressure measurement. Thirty four respondents (3.4%) reported the use of anti-hypertensive drugs while 427 (42.2%) were newly diagnosed or not on medication. However, all those who were on medication also had a SBP ≥ 140mmHg and/or DBP ≥ 90 mmHg, hence were part of the total of 461 (45.6%). Blood pressure was optimal in 183 (18.2%) respondents while pre-hypertension stage was seen in 367 (38.3%). The pattern of blood pressure across the different age groups is shown in Analysis of the pattern of elevated blood pressure among the hypertensive subjects showed that 59.7% (275) of them had Systolic-Diastolic Hypertension (SDH) i.e. elevation of both the SBP and DBP, while 115 (24.9%) had isolated systolic hypertension (ISH), the remaining 15.2% had isolated diastolic hypertension (IDH). Furthermore, respondents who were 60 years and above had the highest (49.6%) prevalence of ISH. A comparison of gender distribution of some clinical parameters among the hypertensive respondents is shown on Among the respondents, hypertension was significantly associated with age (p<0.001), marital status (p<0.001), waist circumference (p<0.001) and BMI (p<0.001). . The preAs shown in 2 had higher odds of having hypertension.The significant factors from the bivariate analyses were entered into a multivariate binary logistic regression model with hypertension status as dependent variable . There wThe overall prevalence of hypertension in our study was 45.6% which is quite high but closely agrees with reports of 47.2%In a systematic review of the prevalence of hypertension in Nigeria, Akinlua et al.At the bivariate level of analysis, this study found that, in addition to age, the presence of hypertension was significantly associated with marital status, high BMI and central obesity. Other studies have reported similar findingsFurthermore, age was found to be the strongest correlate of SBP in this study. With increasing age, there is a decline in arterial compliance with resultant increase in peripheral resistance. This tends to affect the SBP more substantiallyThe multivariate binary logistic regression analysis revealed, in line with some earlier reportsIt must however be noted that the cross-sectional nature of this study limits the establishment of causal relationship between the hypertension and the identified factors. Furthermore, some other potentially confounding variables such as socio-economic status, lifestyle factors, presence of comorbidities e.g. diabetes, were not included in the model. Another limitation is the fact that hypertension was defined on the basis of measurement of blood pressure at a single contact which may affect the prevalenceThere was a high prevalence of hypertension in the study population and the predictive factors were age, BMI and waist circumference. There is the need for concerted efforts by health policy makers and all stakeholders towards putting in place effective primary and secondary preventive strategies. Modifiable risk factors such as obesity need to be reduced through appropriate public health promotion measures. The rural areas require an increased share of such attention than they currently receive.