Pulse pressure variation (PPV) has been shown to predict fluid responsiveness in ventilated intensive care unit (ICU) patients. The present study was aimed at assessing the diagnostic accuracy of PPV for prediction of fluid responsiveness by using the grey zone approach in a large population.The study pooled data of 556 patients from nine French ICUs. Hemodynamic  and cardiac output) and ventilator variables were recorded. Responders were defined as patients increasing their stroke volume more than or equal to 15% after fluid challenge. The receiver operating characteristic (ROC) curve and grey zone were defined for PPV. The grey zone was evaluated according to the risk of fluid infusion in hypoxemic patients.P <0.001). A grey zone of 4 to 17% (62% of patients) was found for PPV. A tidal volume more than or equal to 8 ml.kg−1 and a driving pressure (plateau pressure - PEEP) more than 20 cmH2O significantly improved the area under the ROC curve for PPV. When taking into account the risk of fluid infusion, the grey zone for PPV was 2 to 13%.Fluid challenge led to increased stroke volume more than or equal to 15% in 267 patients (48%). The areas under the ROC curve of PPV and CVP were 0.73 : 0.68 to 0.77) and 0.64 (95% CI 0.59 to 0.70), respectively (In ventilated ICU patients, PPV values between 4 and 17%, encountered in 62% patients exhibiting validity prerequisites, did not predict fluid responsiveness. T <8 ml/kg−1), low plateau pressure, low pulmonary compliance and low heart rate to respiratory rate (HR/RR) ratio reduce the accuracy of PPV in predicting fluid responsiveness [et al. [et al. [T was 7.9 ± 1.3 ml/kg body weight, with 51% of patients being ventilated with VT ≥8 ml/kg−1. We recently reported that during anaesthesia, patients were mechanically ventilated with a mean VT =8.8 ± 1.4 ml/kg−1 ideal body weight (IBW) and 18% patients were ventilated with a VT >10 ml/kg−1 IBW [T (<8 ml/kg−1) has been shown to improve patient outcome in acute respiratory distress syndrome (ARDS) patients and to prevent the occurrence of acute lung injury in mechanically ventilated patients [T associated with positive expiratory pressure and recruitment manoeuvres decreases postoperative complication rate and length of stay in ICU [T.In intensive care units (ICUs), a fluid challenge based on clinical criteria leads to a significant increase in cardiac output (CO) in approximately 50% of patients . Improvisiveness -15. Thessiveness . The ovesiveness ,11,15 cosiveness -19. The siveness -19. In csiveness . Between [et al.  demonstr [et al. , the VT kg−1 IBW . In ICU patients -25. Morey in ICU . TherefoT, respiratory driving pressure, respiratory system compliance and HR/RR). We also defined a model for benefit-risk assessment of fluid administration to further evaluate the predictive value of PPV in patients according to their partial arterial oxygen pressure (PaO2) to inspiratory oxygen fraction (FiO2) ratio.The present study was aimed at assessing the diagnostic accuracy of PPV for prediction of fluid responsiveness by using the grey zone approach in a large ICU population. As a secondary endpoint, we studied respiratory variables that could affect the accuracy of PPV to predict fluid responsiveness (that is VThe present study pooled data obtained from eight published studies (460 patients) in nine French hospitals  ,27-32. T−1/h−1, arterial lactate >2.5 mMol/L−1, presence of skin mottling, unsuccessful attempt to decrease vasopressor infusion rate). Patients with spontaneous breathing, cardiac arrhythmias, unsatisfactory cardiac echogenicity (in patients in whom CO was assessed by echography), increase in intra-abdominal pressure suspected by clinical context and examination, known tricuspid insufficiency, or cardiogenic pulmonary oedema were excluded. Moribund, parturient patients and those younger than 18 years were not included.Mechanically ventilated and sedated patients with acute circulatory failure in whom a fluid challenge was indicated participated in the study. Acute circulatory failure was defined as systolic arterial blood pressure <90 mmHg or mean arterial pressure <65 mmHg with signs of hypoperfusion (oliguria less than 0.5 ml.kgT (ml/kg−1 of IBW), RR (cycles/min−1), the level of positive end-expiratory pressure  and plateau pressure (cmH2O), FiO2, and PaO2 (mmHg) were recorded when available. The following haemodynamic variables were recorded: HR (beats.min−1/bpm) and mean arterial blood pressure . MAP and CVP (when available) were measured invasively with a zero referenced to the middle axillary line. PPV was calculated as follows [For each patient, age, sex, weight, height, body mass index (BMI), and Acute Physiology and Chronic Health Evaluation (APACHE) II score  or the S follows :\documen(PP: pulsed pressure)In each measurement and after verifying the absence of cardiac arrhythmia and spontaneous breathing, CO was measured either by thermodilution technique  or pulmonary artery catheter ), echocardiography  or oesophageal Doppler .−1 in 29 patients, as performed by Reuter et al. [When indicated, a fluid challenge using either colloid or isotonic crystalloid solutions was performed over 15 to 30 minutes. The infused volume was most often 500 ml . Fluid et al. [We expected to include a large sample of patients with at least 100 events (responders) to allow an accurate determination of the ROC curves and cut-off values. Assuming a proportion of responders close to 50%, about 200 patients would be necessary. However, because we intended to perform bootstrap analysis and subgroup analyses, we decided to include at least 500 patients, a number close to that previously used by Cannesson et al. .t tests, Mann-Whitney tests, chi-square test, and the Fisher exact method when appropriate. Receiver operating characteristic (ROC) curves were created to assess the discriminative power of PPV and CVP to predict the effect of fluid challenge. The ROC curves were also created by using a bootstrap methodology, which creates multiple samples  by randomly drawing instances, with replacement, from the original study population [et al. [Results are expressed according to variable distributions (mean ± standard deviation (SD) or median ) for quantitative variables and frequencies with percentages for qualitative variables. Patients were divided into responders and non-responders according to response to fluid challenge. Comparisons were performed using unpaired Student pulation . Bootstrpulation ,36. This [et al. .The grey zone approach determines a range of values for which no conclusion may be drawn concerning potential fluid responsiveness -19,38. TMoreover, grey zones were determined according to potential factors that could impact on the ability of PPV to predict fluid responsiveness.28 (ARDS network) and a lower mortality rate [aO2/FiO2 ratio could influence the clinician’s decision as to perform a fluid challenge or not. For example, a PaO2/FiO2 < 100 with impaired left ventricular function could influence the clinician towards avoiding unnecessary volume loading. In contrast, a patient with a PaO2/FiO2 ratio ≥200 and a preserved/normal left ventricular function is a patient in whom fluid loading may be beneficial and the risk of fluid overload may be low. Therefore, a cost ratio /cost ) was defined according to the recent international definition of ARDS [aO2/FiO2 ratio was <100 (severe ARDS group), R was arbitrarily defined as 2 . When the PaO2/FiO2 ratio was <200 (moderate ARDS group), R was defined as 1 and when the PaO2/FiO2 ratio was ≥200 (mild ARDS group), R was defined as 0.5 . All P values were two-sided, and a P value <0.05 was considered significant. Statistical analyses were performed with R 2.15.1 .In patients with ARDS, restrictive fluid management has been shown to be associated with a higher number of ventilator-free days at Dayity rate -41. In p of ARDS . When thT >8 ml/kg−1. The correlation between baseline PPV values and the increase in CO induced by the fluid challenge was 0.23 (P <0.001)  defined as responders. The comparisons between responders and non-responders are shown in Table P <0.001)  and 0.64 (95% CI = 0.59 to 0.70), respectively (P <0.01).Using the alternative grey zone approach, inconclusive values spreading from 4 to 17% and from 6 to 15 mmHg were found for PPV and CVP, respectively , respiratory compliance (VT/(plateau pressure - PEEP), HR/RR ratio, use of vasopressors. Only a VT ≥8 ml/kg−1 (P <0.001) and a driving pressure >20 cmH2O (P <0.001) were associated with a significantly greater area under the ROC curve for PPV. Figure Table aO2/FiO2 ratio was available for 250 patients. For the severe group (n = 57), the best threshold value for PPV was 7%, AUC = 0.67 (95% CI = 0.54 to 0.80), grey zone = 1% to 12%; for the moderate group (n = 111), the best threshold value for PPV was 5%, AUC = 0.73 (95% CI = 0.60 to 0.80), grey zone = 2 to 14%; for the mild group (n = 82) the best PPV threshold value was 12%, AUC = 0.67 (95% CI = 0.57 to 0.74), grey zone = 2 to 14%. For the whole population, when the clinical risk of fluid infusion during ARDS was taken into account by the ratio of costs for severe and mild groups, the best threshold values for PPV and CVP were 14% and 2 mmHg, respectively. When taking into account the risk of fluid infusion in the whole population, the grey zone for PPV was 2% to 13%.A PT ≥8 ml/kg−1 and/or driving pressure >20 cmH2O significantly improve the ability of PPV to predict fluid responsiveness; and (4) even when taking into account the risk of fluid loading in ARDS patients, the grey zone remains too large (2 to 13%) to be informative.The present study demonstrated that, when using a grey zone approach in a large population of mixed ICU patients: (1) PPV cannot reliably predict fluid responsiveness when its value is between 4% to 17%; (2) 62% of patients  had PPV values within this grey zone; (3) a VT in patients with ARDS to prevent baro- or volo-trauma. In the early 2000s, dynamic variables were validated in critically ill patients ventilated with high VT (>8 mL/kg−1 of IBW) [T, low driving pressure or low pulmonary compliance significantly impairs the ability of dynamic variables to predict fluid responsiveness [T (<8 ml/kg−1 of IBW), our hypothesis is that low VT is the main explanation for the poor predictive performance of PPV. This hypothesis is supported by the fact that PPV accuracy is improved in patients with driving pressure >20 cmH2O and VT >8 mL/kg−1. The PPV is due to the transmission of pulmonary pressure to the intra-thoracic circulatory compartment and thus, VT and driving pressure directly participate in the pressure transmitted to intra-thoracic components. Surprisingly, in the present report, the compliance of the respiratory system did not modify the ability of PPV to predict fluid responsiveness. In a recent study, Monnet et al. [T. To elucidate such conflicting results, a study using oesophageal pressure  could be useful to precise the effect of pulmonary pressure on PPV [et al. [T =6 mL/kg−1). However, in this study, a relatively high PEEP level (>10 cmH2O) was applied in contrast with the present report and with Monnet’s [2O). Indeed, a high level of PEEP could facilitate the transmission of pulmonary pressure to the intra-thoracic circulatory compartment and explain these apparent conflicting results. Specific studies are needed to elucidate this point especially with recording of pleural pressure.Our results are in accordance with previous large reports that emphasized the superiority of dynamic over static variables, but contrast with the very high predictive value of PPV previously reported ,43. This>8 mL/kg− of IBW [ of IBW) ,43,44. Ssiveness ,15,45,46e on PPV . Finally [et al.  recentlyT >7 to 8 ml/kg was an inclusion criterion, with positive results  and cut-off values around 12% [T ≥8 ml/kg−1 and/or a driving pressure >20 cmH2O significantly improve the ability of PPV to predict fluid responsiveness.In the present study, pooled data were obtained from studies where Vound 12% ,28,32 wiound 12% ,32. Thisound 12% . The preaO2/FiO2 ratio <100), we considered that the risk of excessive fluid infusion was twice as high when compared with less severe patients. For the severe ARDS group, our results show that when applying a cost ratio of 2 (two-fold increased risk in case of fluid infusion) the best cut-off value for PPV moved from 7 to 14%. This suggests that the more severe the ARDS, the higher the cut-off, in order to limit the risk of unnecessary fluid loading. Nevertheless, because the grey zones were 1 to 12% for the moderate ARDS group, 1 to 14% for the mild ARDS group and 2 to 14% for the severe ARDS group, we failed to show any relevant difference in the grey zone regardless of severity.The potential deleterious consequences of unwarranted fluid infusion are crucial during ARDS since a restrictive strategy has been shown to reduce mechanical ventilation duration in these patients ,40,41. TT <8 mL.kg−1 even if these indices have yet to be assessed with a grey zone approach [Clinical implications: when a given value of PPV is in the grey zone, physicians cannot use this index to proceed with or to exclude the need for fluid therapy in the ICU. In such a case, a passive leg-raising test, an end-expiratory occlusion test or ‘minifluid’ challenge could be valuable alternatives in ventilated patients with low Vapproach ,46. Convapproach ,18,19. IThe present study shows a grey zone of 4 to 17%, meaning that PPV cannot reliably guide fluid loading in 62% of studied population. Only rarely (17% of the study population), when under the threshold of 4%, does PPV rule out any use of fluid loading, which could then be avoided. In contrast, a PPV value above 17% can be considered as a useful tool to indicate fluid infusion. Nevertheless, an isolated value of PPV (even above 17%) cannot be considered as the sole argument to decide fluid therapy. The latter should be only considered when signs of a clinical hypoperfusion are associated with PPV value above 17%. In other words, PPV should be considered as a tool, not as a target. Moreover, the great variability according to the centres suggests that the patient case mix and different management protocols could influence the reliability of PPV to predict fluid responsiveness.It could be hypothesized that the important variation of grey zone value among centres probably reflects the fact that PPV was measured by different techniques. In particular, PPV was manually or automatically measured according to each study centre’s procedures. This heterogeneity reflects the real daily practice of PPV. There may be differences between absolute PPV values obtained from automated or manual calculation. There may also be differences between different automatic devices. Finally, it is also possible that actual criteria for accurate PPV measurement were not uniform among centres at the time of study, especially for right ventricle failure detection . This hiT. All these limitations are emphasized by the limited number of patients in whom PPV can be measured. Indeed, recommendations in sedation and in mechanically ventilation tend to favour spontaneously breathing modes in order to decrease the duration of mechanical ventilation [Our study presents several limitations that should be considered when assessing the clinical relevance of our results. First, this study is not prospective, which limits the power of the conclusions. Second, the methods of PPV and CO measurements were not uniform and this may have extended the PPV grey zone. However, thermodilution and echocardiography have both been validated and this methodological issue was considered as acceptable in a previous report . Furthertilation ,54. Thestilation . In addiIn ventilated ICU patients, the grey zone approach identifies a wide range of PPV values, between 4 and 17%, for which fluid responsiveness cannot be accurately predicted, corresponding to 62% of patients in whom criteria for measuring PPV are valid. The heterogeneity in measurement method and in tidal volume value can contribute to the present findings.In 564 ICU mechanically ventilated patients, a grey zone approach showed that pulsed pressure variations (PPV) cannot reliably predict fluid responsiveness when its value is between 4% and 17%In this population, 62% of patients  had PPV values within this grey zoneT ≥8 ml/kg−1 and/or driving pressure >20 cmH2O significantly improve the ability of PPV to predict fluid responsivenessA VEven when taking into account the risk of fluid loading in ARDS patients, the grey zone remains too large (2 to 13%) to be informative.


To assess whether patients’ willingness to add a blood pressure-lowering drug and the importance they attach to specific treatment characteristics differ among age groups in patients with type 2 diabetes.2-tests. Multinomial logit models were used to assess and compare the importance attached to the characteristics.Patients being prescribed at least an oral glucose-lowering and a blood pressure-lowering drug completed a questionnaire including a discrete choice experiment. This experiment contained choice sets with hypothetical blood pressure-lowering drugs and a no additional drug alternative, which differed in their characteristics (i.e. effects and intake moments). Differences in willingness to add a drug were compared between patients <75 years (non-aged) and ≥75 years (aged) using Pearson χOf the 161 patients who completed the questionnaire, 151 (72%) could be included in the analyses . Aged patients were less willing to add a drug than non-aged patients . In both age groups, the effect on blood pressure was most important for choosing a drug, followed by the risk of adverse drug events and the risk of death. The effect on limitations due to stroke was only significant in the non-aged group. The effect on blood pressure was slightly more important in the non-aged than the aged group (P = 0.043).Aged patients appear less willing to add a preventive drug than non-aged patients. The importance attached to various treatment characteristics does not seem to differ much among age groups. There is growing interest to tailor drug treatment to the individual patient's clinical and personal needs. In general, the incorporation of patient preferences in treatment decisions is high on the agenda in our society. Particularly in drug treatment it is important to take patient preferences into account since such preferences are related to a patient’s willingness to take a drug. The willingness to take a drug improves adherence and leads to a more effective treatment –3.A patient’s willingness to take a drug is influenced by factors related to the drug, the physician, the disease, and patient’s own characteristics –7. Drug-The role of patient’s age on drug choices may be particularly important for preventive treatment, such as the use of blood pressure-lowering drugs in patients with type 2 diabetes to reduce their risk for cardiovascular morbidity and mortality . With reA useful and commonly used method to assess patient preferences for treatment is the discrete choice experiment ,24. In sThe aim of this study is to assess whether patients’ willingness to add a blood pressure-lowering drug and the importance they attach to specific treatment characteristics differ among age groups in patients with type 2 diabetes.This study was conducted in 2014 and has a cross-sectional design in which we compared patients <75 years with ≥75 years of age. Patients were eligible to participate when they were aged ≥18 years and had been prescribed at least an oral glucose-lowering and a blood pressure-lowering drug in the past 6 months. We aimed to include 150 patients in our study, since it has been shown that the precision of discrete choice experiments rapidly decreases at sample sizes less than 150 . PharmacThe outcome variable in this study was the choice patients made in a hypothetical situation with respect to adding a blood pressure-lowering drug.Attributes in the discrete choice experiment were based on a two-step literature review. In the first step, the literature was assessed for factors which may influence a patient’s willingness to take blood pressure-lowering drugs or drugs for primary cardiovascular disease prevention in general. This review revealed that lowering the blood pressure, achieving risk reduction of complications , reducing ADEs and improving quality of life were relevant factors –7. DurinLevels of efficacy were established using clinical trial data of blood pressure-lowering treatment effects and cardiovascular risk reduction between tight and less tight blood pressure control, and using the UKPDS risk engine for assessing differences among different ages . We estiA d-efficient design  of 30 chA pilot study was conducted in which ten patients with type 2 diabetes completed the full questionnaire. Based on this pilot study, minor changes in wordings were made and a separate instruction form for the choice sets was included. An example of a final choice set is presented in In the questionnaire, patients were asked their age. We used a cut-off level of ≥75 years to define aged patients. This cut-off level has been used in guidelines  and obsePharmacists provided the age and gender for all eligible patients, as well as overviews of prescribed drugs in the last six months for those patients who gave written informed consent. The Anatomical Therapeutic Chemical (ATC) classification system of the World Health Organization was used to classify the prescribed drugs.2-test respectively. Differences in characteristics between non-aged and aged patients were tested using Pearson χ2-tests for categorical variables and Mann-Whitney U tests for non-normally distributed, continuous variables. The Fisher freeman-halton test was used for categorical variables in which one or more cells contained less than five patients.Descriptive statistics are presented for patient characteristics. Differences in age and gender between patients who completed the study and those who did not participate or complete the study were assessed using the T-test and Pearson χ2-test. The choices were further analysed using multinomial logit models (asclogit function in Stata) to assess 1) the willingness to add a blood pressure-lowering drug when controlling for all attributes, and 2) the relative importance of the attributes. Four models were assessed, that is, one including all patients, one including non-aged patients, one including aged patients, and one with all patients in which the interaction terms between these two age groups and the attributes were included.Differences in the number of patients who chose at least once an additional drug on the choice sets (willing to add) versus never (unwilling to add) were compared between the age groups using the Pearson χU indicating the utility that a patient assigns to a treatment which is the sum of a systematic, explainable component V and a random, unexplainable component ε. The explainable component is a function of the attributes of the alternatives. The constant β0 indicates the relative weight patients place on choosing an additional blood pressure-lowering drug versus no additional blood pressure-lowering drug when controlling for the attributes. The β1 to β7 coefficients indicate the relative importance of each of the attributes. Coefficients reflect continuous variables of the attributes, except β6 and β7 which reflect the dummy-coding of respectively the level one drug in the morning and one in the evening (coded as 1) versus two drugs in the morning (coded as 0), and the level combination tablet (coded as 1) versus two drugs in the morning (coded as 0). The sign of the beta-coefficients indicates whether the effect on the utility is positive or negative. Attributes with beta-coefficients with a two-sided P-value <0.05 were considered as being important for the treatment choice. Important attributes were ranked according to their relative importance. This was determined by calculating the difference between the smallest part worth utility and the largest part-worth utility of the levels of an attribute, and dividing this difference by the sum of the difference scores for all attributes [We followed the random utility model by assuming that patients choose the alternative in each choice set which maximizes their utility. The estimated model was the following:tributes .Patients who chose the non-preferable drug in the dominant choice set were excluded from the analyses. Sensitivity analyses were conducted in which these patients were not excluded. Additional sensitivity analyses were conducted to assess the multinomial logit model for patients <65 years and patients aged ≥80 years. The analyses were conducted using Stata version 13 .β-blockers were the most commonly prescribed class in aged patients. Most of the patients reported that their blood pressure was <160 mmHg, that they used one or two drugs to lower their blood pressure, and that they preferred to leave decisions about their drugs to the general practitioner . The same is reflected in the drug choice model where the constant is more negative in the aged than in the non-aged .Drug attributes that significantly influenced the choices for an additional blood pressure-lowering drug in the total group were the effect on the blood pressure, the risk of experiencing ADEs, the risk of death within the next 5 years, and the risk on limitations due to stroke within the next 5 years . These rA sensitivity analysis in which the patients who failed the dominant choice set were included, revealed similar results . In addiOnly the impact of the blood pressure-lowering effect turned out to be significantly different among the age groups . In this study, age seemed to be a reasonable proxy for life-expectancy. There are also some strengths and limitations to a discrete choice experiment. A major strength is that it comes close to the trade-offs and choices that have to be made in real life, and can thus provide better estimates of the relative importance of different treatment characteristics than when asking patients to rate the importance of each characteristic separately. The evaluation of several treatment alternatives and attributes at one time reveals a rich source of data [This study was conducted in the north of the Netherlands, which includes a mostly caucasian population. Selection bias may have occurred since only 17% of the contacted patients completed the questionnaire and less females completed the study. Regarding age there were no differences between those who completed the study and those who did not. Although we reached a sample size of 150 patients, it should be noted that the included number of patients per age group was lower which may have reduced the efficiency of the models for the separate groups. This limitation may especially apply to the aged group (≥75 years) since only 45 patients were included. In the aged group, more blood pressure-lowering drugs and especially  of data ,51. More of data . Aged pa of data . Further of data ,55. Some of data , but theIn conclusion, it is important to acknowledge that aged patients may be less willing to add a blood pressure-lowering drug than non-aged patients. This finding underlines the importance of discussing patients' preferences even when they prefer to leave the final treatment decision to their general practitioner. When choosing a drug, aged patients attach as much importance to reduce their risk of death within the next 5 years and of experiencing ADEs as non-aged patients. Therefore, treatment decisions in clinical practice should focus on quality of life as well as life extension in both age groups in which the individual patient’s preferences and willingness to add a drug should be taken into account.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S1 Minimal Anonymized Dataset(DTA)Click here for additional data file.


Development of simple instruments for the determination of the level of adherence in patients with high blood pressure is the subject of ongoing research. One such instrument, gaining growing popularity worldwide, is the Hill-Bone Compliance to High Blood Pressure Therapy.The aim of this study was to adapt and to test the reliability of the Polish version of Hill-Bone Compliance to High Blood Pressure Therapy Scale.A standard guideline was used for the translation and cultural adaptation of the English version of the Hill-Bone Compliance to High Blood Pressure Therapy Scale into Polish. The study included 117 Polish patients with hypertension aged between 27 and 90 years, among them 53 men and 64 women. Cronbach’s alpha was used for analysing the internal consistency of the scale.2 = 248.87; p < 0.001. The Cronbach’s alpha score for the entire questionnaire was 0.851.The mean score in the reduced sodium intake subscale was M = 5.7 points (standard deviation SD = 1.6 points). The mean score in the appointment-keeping subscale was M = 3.4 points (standard deviation SD = 1.4 points). The mean score in the medication-taking subscale was M = 11.6 points (standard deviation SD = 3.3 points). In the principal component analysis, the three-factor system  accounted for 53 % of total variance. All questions had factor loadings > 0.4. The medication-taking subscale: most questions (6 out of 9) had the highest loadings with Factor 1. The appointment-keeping subscale: all questions (2 out of 2) had the highest loadings with Factor 2. The reduced sodium intake subscale: most questions (2 out of 3) had the highest loadings with Factor 3. Goodness of fit was tested at chiThe Hill-Bone Compliance to High Blood Pressure Therapy Scale proved to be suitable for use in the Polish population. Use of this screening tool for the assessment of adherence to BP treatment is recommended. Hypertension, or high blood pressure (HBP), is considered the most common disorder in the general population. The World Health Organization (WHO) Report for 2008 states that 40 % of the world’s population over the age of 25 have high blood pressure . WorldwiThe adaptation was performed using the standard methodology . The PolThe study was carried out at a private medical center in Wrocław, between March and September, 2015, and included 117 sequential patients diagnosed with HBP in accordance with the ESC criteria. The patients filled in the questionnaire during a regular follow-up visit. The refusal rate was 0 %, and the acceptance rate was 100 %. The only exclusion criterion was cognitive impairment and/or communication barriers interfering with questionnaire completion. The sample size was based on literature data, indicating that the minimum number of participants in a validation study should be five times the number of variables analyzed . TherefoThe results obtained were analyzed using Statistica 10 software . The normality of variable distribution was verified using the Kolmogorov–Smirnov test, and the statistical characteristics of variables were presented using arithmetical means ± standard deviations (SD), median values and interquartile ranges (IQR). The statistical characteristics of discrete and qualitative variables were presented using number distributions (n). The internal consistency and the intraclass correlation coefficients of the Polish adaptation were assessed based on Cronbach’s alpha.The socio-demographic and clinical characteristics of the 117 patients studied are summarized in Table The mean sodium intake score among the patients studied was M = 5.7 points (standard deviation SD = 1.6 points). The mean appointment-keeping score in the group was M = 3.4 points (standard deviation SD = 1.4 points). The mean medicine-taking score was M = 11.6 points (standard deviation SD = 3.3 points).2 = 248.87; p < 0.001  accounts for 53 % of total variance. All questions have factor loadings >0.4. The medication-taking subscale: most questions (6 out of 9) have the highest loadings with Factor 1. The appointment-keeping subscale: all questions (2 out of 2) have the highest loadings with Factor 2. The reduced sodium intake subscale: most questions (2 out of 3) have the highest loadings with Factor 3. Goodness of fit was tested at chiAnalysis of correlation with external criteria (systolic and diastolic blood pressure) – Spearman’s rank correlation coefficients Table . The insInternal consistency was tested using Cronbach’s alpha, and the intraclass correlation coefficient was determined. The Cronbach’s alpha score for the whole questionnaire was 0.80, and for the medicine-taking subscale it was 0.78. Cronbach’s alpha was not calculated for the remaining subscales due to the insufficient number of questions. Coefficients of correlation with the total score ranged from 0.14 (question 3) to 0.653 (question 10). The intraclass correlation coefficient for the whole questionnaire was 0.851  , 16, SouThe Hill-Bone Compliance to High Blood Pressure Therapy Scale proved to be suitable for use in the Polish population. The use of this screening tool for the assessment of adherence to BP treatment is recommended.The study protocol was approved by the Independent Bioethics Committee of the Wroclaw Medical University (decision no. KB 136/2015). All participants gave written informed consent after thorough explanation of the procedures involved.Not applicableThe datasets supporting the conclusions of this article are included within the article.


Data is suggesting that non-balanced conventional crystalloids  are not only associated with the occurrence of hyperchloremic, metabolic acidosis but increased incidence of acute kidney injury and even morbidity and mortality. Experimental data suggested infusion of hyperchloremic crystalloids to be associated with hypotension in experimental sepsis. We aimed to investigate whether use of modern balanced crystalloids lead to better hemodynamic stability compared to 0.9% saline in the perioperative period.We performed a subanalysis of a prospective, randomized, controlled trial comparing effects of 0.9% saline or an acetate-buffered, balanced crystalloid during the perioperative period in patients with end-stage renal disease undergoing cadaveric renal transplantation. Blood pressure and need for catecholamine therapy were the primary measures.A total of 150 patients were included in the study. 76 were randomized to 0.9% saline while 74 received an acetate-buffered balanced crystalloid. There was no difference in the volume of fluid administered . Chloride was significantly higher in the saline group (109 [107-111] versus 107 mmol/L [105-109]). Mean blood pressure was significantly higher in the balanced group. Mean minimum blood pressure was significantly lower in the saline group . More patients received noradrenaline in the group receiving 0.9% saline .Our data suggest that use of 0.9% saline results in hyperchloremic metabolic acidosis and is associated with a higher incidence of hypotension and vasopressor use in the perioperative period.


Complementary and alternative medicine (CAM) has often been regarded as a practical, holistic, and personalized medical approach. However, the CAM research community in the past two decades has witnessed a huge disconnection between clinical studies and preclinical studies including authentication, quality control, pharmacology, and toxicology of CAM agents. Meanwhile, novel translational research approaches, including cutting-edge-omics technologies, new bioinformatics tools, novel imaging modalities, well-designed clinical trial metrics, protocols, and outcome measures, are still lacking in the CAM research. In this special issue, we aim to promote research that can translate from bench to bedside in CAM diagnosis and treatments.n = 63) who were classified into two TCM syndromes, “Liver-Kidney Yin Deficiency” or “Dampness-Heat Internal Smoldering,” and healthy subjects (n = 31) were recruited, and a combined gas chromatography, as well as liquid chromatography mass spectrometry, was used to profile the urine samples of the study participants. The results underscored several key urinary metabolite markers, including glycoursodeoxycholate, cortolone-3-glucuronide, and L-aspartyl-4-phosphate, that can readily differentiate between the two TCM syndromes. T. Wu et al. applied a mass spectrometry-based metabolomics approach to characterize the distinct alterations of serum metabolites among diabetes patients who can be classified into “excess” and “deficiency” TCM syndromes. The results suggest that patients with the excess syndrome have more oxidative stress than the deficiency syndrome, highlighting a novel diabetic patient subtyping method using a metabolomics approach.This issue contains seven papers, where two papers reported novel approaches to human metabolic disease diagnosis using metabolomics technology. X. Wang et al. reported a novel syndrome differentiation strategy investigated in a clinical study. A group of liver cirrhosis patients ( Citrus aurantium L. var. amara (neroli oil) on menopausal symptoms, stress, and estrogen in postmenopausal women. Sixty-three healthy postmenopausal women were randomized to inhale 0.1% or 0.5% neroli oil  or almond oil (control) for 5 minutes twice daily for 5 days. They report that systolic blood pressure and diastolic blood pressure were significantly lower among participants inhaling neroli oil than the control group, suggesting that neroli oil may have potential as an effective intervention to reduce stress and improve the endocrine system.Dr. G. H. Seol's group reported an interesting clinical trial to investigate the effects of inhalation of the essential oil of Apocynum, Chrysanthemum, and Fangchi and widely used in China to treat patients with hypertension. Their experimental data provided evidence that AT inhibits cardiac hypertrophy from pressure overload and thus explained a possible mechanism of the effective AT treatment in patients with cardiac hypertrophy. The authors also suggested that selective ERK1/2 and AKT modulation for cardioprotection as possible therapeutic targeting may be feasible.J. Qi et al. evaluated the therapeutic effect and mechanisms of a traditional Chinese medicine, Apocynum Tablet (AT), on cardiac hypertrophy in a mouse model of cardiac hypertrophy. AT is formulated mainly withThe traditional kampo medicine tokishakuyakusan increases ocular blood flow in healthy subjects,” S. Takayama et al. reported a clinical study with healthy volunteers to examine the effects of oral administration of kampo medical formulas on ocular blood flow. A crossover protocol was used to randomly administer 5 grams of one of the 4 kampo medical formulas to 13 healthy subjects (mean age: 37.3 ± 12.3 years). Laser speckle flowgraphy was used and blood pressure and intraocular pressure were also recorded in the study. The authors concluded that one of the kampo formulas, tokishakuyakusan, can significantly increase ocular blood flow, at 30 to 60 minutes after administration, without affecting blood pressure or intraocular pressure in healthy subjects.In the paper entitled “ Alpinia officinarum. The authors comprehensively identified the polysome-associated mRNAs in a human B lymphoblastoid cell line and examined changes to the mRNA profile caused by each of three A. officinarum diarylheptanoids. The microarray-based translatome analysis was able to reveal the inhibitory effects on proinflammatory mediators and cytotoxic and antiviral activity of plant bioactives, highlighting the application of omics technologies in advancing our understanding of molecular effects of CAM agents.T. Kakegawa et al. conducted a translatome analysis to investigate the mechanisms and modes of action of three diarylheptanoids isolated from a medicinal plant,A review of botanical characteristics, traditional usage, chemical components, pharmacological activities, and safety of Pereskia bleo (kunth) DC” S. Zareisedehizadeh et al. provided an up-to-date and comprehensive review of the botanical characteristics, traditional usage, phytochemistry, pharmacological activities, and safety of P. bleo. The review highlighted the association between the traditional usage of the plant and the anticancer, antibacterial, and antinociceptive effects reported in different studies.In the paper entitled “In summary, these 7 papers represent exciting CAM research activities with translational strategies embedded in design and context. The articles will help readers to follow translational research in CAM with a wide range of topics, from clinical trials to omics technologies and bioinformatics that will collectively contribute to an improved understanding of mechanisms and pharmacology of the CAM treatments.


To investigate potential associations between resting heart rate, blood pressure and the product of both, and the brachial-ankle pulse wave velocity (baPWV) as a maker of arterial stiffness.The community-based “Asymptomatic Polyvascular Abnormalities in Community (APAC) Study” examined asymptomatic polyvascular abnormalities in a general Chinese population and included participants with an age of 40+ years without history of stroke and coronary heart disease. Arterial stiffness was defined as baPWV≥1400 cm/s. We measured and calculated the product of resting heart rate and systolic blood pressure (RHR-SBP) and the product of resting heart rate and mean arterial pressure (RHR-MAP).P<0.0001) linear relationships were found between higher baPWV and higher resting heart rate or higher arterial blood pressure, with the highest baPWV observed in individuals from the highest quartiles of resting heart rate and blood pressure. After adjusting for confounding parameters such as age, sex, educational level, body mass index, fasting blood concentrations of glucose, blood lipids and high-sensitive C-reactive protein, smoking status and alcohol consumption, prevalence of arterial stiffness increased significantly (P<0.0001) with increasing RHR-SBP quartile (Odds Ratio (OR): 2.72;95%Confidence interval (CI):1.46,5.08) and increasing RHR-MAP . Similar results were obtained in multivariate linear regression analyses with baPWV as continuous variable.The study included 5153 participants with a mean age of 55.1±11.8 years. Mean baPWV was 1586±400 cm/s. Significant (Higher baPWV as a marker of arterial stiffness was associated with a higher product of RHR-SBP and RHR-MAP in multivariate analysis. In addition to other vascular risk factors, higher resting heart rate in combination with higher blood pressure are risk factors for arterial stiffness. Brachial-ankle pulse wave velocity (baPWV) is an index of arterial stiffness and a marker of atherosclerosis that can be measured noninvasively P = 0.83) and gender (P = 0.79). A total of 5,440 participants were eventually eligible and participated in the APAC study.APAC is a community-based, observational, prospective, long-term follow-up study to investigate the epidemiology of asymptomatic polyvascular abnormalities in Chinese adults BaPWV, blood pressure and RHR were assessed with the person sitting for at least five minutes in a controlled environment at a room temperature of 22°C to 25°C. The study participants had refrained from smoking and drinking of coffee, tea or alcohol for at least three hours nor had any exercise been performed for the last 30 minutes prior to the measurement of baPWV, blood pressure and RHR. All examinations were carried out by specially trained physicians and nurses. All subjects were in a supine position in light clothing without pillow and were asked to stop moving and talking at the time of the examination. Electrodes of the electrocardiogram were placed on both wrists, a microphone for detecting heart sounds was placed on the left edge of the sternum, and cuffs were wrapped on both arms and ankles. The lower edge of the arm cuff was placed 2–3 cm above the transverse striation of cubital fossa, while the lower edge of the ankle was placed 1–2 cm above the superior aspect of the medial malleolus. Two readings of baPWV were taken from each body side, and the second reading was used. Then, the higher value of the left side and right side was used for the data analyses. The rationale for this procedure was that the higher value represented the more severe arterial stenosis of the whole body. In addition, we also used the lower value of the left side and right side in the sensitivity analysis, and the results were similar.Blood pressure was measured on the left arm to the nearest 2 mmHg using a mercury sphygmomanometer and standard procedures. Three readings of the systolic and diastolic blood pressure were recorded, taken at 5-minute intervals. The average of three readings was used for the statistical analysis. If two of the three measurements differed by more than 5 mmHg, an additional reading was taken. Mean arterial pressure (MAP) was calculated as diastolic blood pressure plus one third of the difference of systolic blood pressure minus diastolic blood pressure. A 10-second 12-lead electrocardiography was carried out to measure the RHR after the individual had rested in the supine position for 5 minutes. The number of R-R intervals (number of QRS complexes - 1) was divided by the time difference between the first and last heartbeat, and the results were converted to beats per minute (bpm).All participants underwent a clinical examination and a standardized interview including questions on smoking and alcohol consumption, socioeconomic parameters, diet, lifestyle, family medical history, physical activity, and sleeping time and quality, known diagnosis of arterial hypertension, coronary heart disease, diabetes mellitus, hyperlipidemia, and stroke, and about the current treatment of these diseases. Anthropomorphic parameters such as body height and weight and waist und hip circumference were measured. The body mass index was calculated as the ratio of body weight (measured in kg) divided by the square of body height (measured in meter). Fasting blood samples were biochemically examined for the concentration of glucose, high-density lipoproteins (HDL), low-density lipoproteins (LDL), triglycerides, total cholesterol and high-sensitive C-reactive protein (CRP) The statistical analysis was performed using a commercially available software program .P = 0.05 in two-tailed tests.Arterial stiffness was defined as baPWV≥1400 cm/s, since a baPWV≥1400 cm/sec has been described as an independent risk factor in the Framingham score and for the discrimination of patients with atherosclerotic cardiovascular disease Out of the 5,440 subjects who were originally included into the APAC study, we excluded 218 participants without measurements of baPWV and 69 individuals without RHR or blood pressure data. Eventually, 5153 (94.7%) subjects (3110 men) were eligible for inclusion in this study. Mean age was 55.1±11.8 years (range: 40–94 years).P<0.0001) linear relationships between the quartiles of all three variables, i.e., resting heart rate, mean arterial blood pressure or systolic blood pressure, and baPWV were found  older, had a higher proportion of men, higher body mass index, lower prevalence of married status and high-school graduation, higher reported income, higher prevalence of current smoking and alcohol consumption, higher systolic and diastolic blood pressure, higher blood concentration of glucose, low-density lipoprotein cholesterol, triglycerides, total cholesterol, and high-sensitive C-reactive protein, and lower concentrations of high-density lipoprotein cholesterol  individuals had a baPWV of ≥1400 cm/s. This subgroup with arterial stiffness compared to the subgroup with a baPWV of <1400 cm/s was significantly  with increasing RHR-SBP quartile and higher RHR-MAP quartile. After adjusting for all independent variables assessed in the study and comparing the highest quartiles with the lowest quartiles of RHR-SBP or RHR-MAP revealed an OR of 2.72 (95%CI: 1.46–5.08) for RHR-SBP and an OR of 2.10 (95%CI: 1.18–3.72) for RHR-MAP  increased significantly  and a high product of resting heart rate multiplied with the mean arterial blood pressure (RHR-MAP) were significantly associated with a higher prevalence of arterial stiffness. These associations were maintained after adjusting for systemic parameters in multivariate analysis. Fitting with the hypothesis, the findings suggest that RHR-SBP and RHR-MAP were independently of other systemic vascular risk factors associated with arterial stiffness.The results of our study agree with the findings of previous investigations in that the baPWV was associated with factors such as older age, hypercholesterolemia, diabetes mellitus, cigarette smoking, higher blood concentration of C-reactive protein, and presence of a metabolic syndrome The results of our study may have importance clinically and in the discussion of the pathogenesis of arterial stiffening. Clinically, one may consider the product of heart rate and blood pressure as an additional marker in the assessment of the general vascular risk spectrum of patients. Pathogenetically, one has previously postulated that the age-related increase in pulse wave velocity is caused by a fatigue fracture of elastic elements in the arterial vessel wall Potential limitations of our study should be mentioned. First, a cross-sectional study as ours cannot prove a causal relationship which usually has to be shown in a longitudinal investigation. The results of our study only allow concluding on an association between RHR-SBP or RHR-MAP and arterial stiffness, while the role of RHR-SBP or RHR-MAP as a risk factor for arterial stiffness may be shown in follow-up investigations. The lack of analysis on causality may be of particular importance for our study, since it is unclear whether the observed association between baPWV and resting heart rate, blood pressure or the product of both was truly attributable to mechanical reasons, or only because they share some common risk factors, such as an increased sympathetic tone. Second, baPWV has limitations as a biomarker of arterial stiffness, since here is no real artery passing through the brachial point and ankle point. An alternative to the baPWVC would have been the carotid-femoral pulse wave velocity which may be addressed in future investigations. Third, the RHR was calculated from one electrocardiography recording. The RHR however depends on the daytime, so that the assessment of the mean RHR might have been more precise if performed in several measurements during a 24 hours profile.In conclusion, a higher baPWV as a marker of arterial stiffness was associated with a higher product of RHR and blood pressure in multivariate analysis. In addition to other vascular risk factors, higher RHR in combination with higher blood pressure are risk factors for arterial stiffness. Using the product of RHR and blood pressure may be useful in the clinical assessment of the vascular risk spectrum of patients.


The study sought to compare the relative discrimination of various cardiopulmonary exercise testing (CPX) variables between cardiac and respiratory disease.2/WR slope) have been proposed as diagnostic of cardiac dysfunction, but multiple variables have not been compared.CPX testing is used in many cardiorespiratory diseases. However, discrimination of cardiac and respiratory dysfunction can be problematic. Anaerobic threshold (AT) and oxygen-uptake to work-rate relationship  (n = 25), heart failure with reduced ejection fraction (HFrEF) (n = 40), or combined COPD and HFrEF (n = 8) were recruited and underwent CPX testing on a bicycle ergometer. Following a familiarization test, each patient underwent a personalized second test aiming for maximal exercise after ∼10 min. Measurements from this test were used to calculate area under the receiver-operator characteristic curve (AUC).2 was similar between the 2 principal groups . Breathing reserve (AUC: 0.91) and percent predicted oxygen uptake efficiency slope (OUES) (AUC: 0.87) had the greatest ability to discriminate between COPD and HFrEF. VO2/WR slope performed significantly worse (AUC: 0.68). VO2 at the AT did not discriminate (AUC for AT as percent predicted peak VO2: 0.56). OUES and breathing reserve remained strong discriminators when compared with an external cohort of healthy matched controls, and were comparable to B-type natriuretic peptide.Peak VO2/WR slope showed poor to moderate discriminant ability. Breathing reserve and OUES discriminate heart failure from COPD. Despite it being considered an important determinant of cardiac dysfunction, the AT could not discriminate these typical clinical populations while the VO A BR cutoff of 30% and an AT cutoff of 40% of predicted peak VO2 have typically been used to discriminate between respiratory and cardiac limitation respectively. However, it may be difficult to establish etiology if abnormalities in cardiac and respiratory function coexist Cardiopulmonary exercise testing (CPX) is recommended for the identification of the key-limiting organ in a patient presenting with exercise intolerance or dyspnea It is also unclear how best to assess change in status using serial measurements of a single patient when pulmonary and cardiac pathologies coexist, which is not uncommon. In 1 study of chronic heart failure (CHF) patients 40% had spirometry suggestive of chronic obstructive pulmonary disease (COPD) This study aimed to establish which CPX variables showed the best ability to discriminate between respiratory and cardiac limitation in a prospective cohort of patients with COPD, heart failure with reduced ejection fraction (HFrEF), and coexisting COPD and HFrEF.Patients with a diagnosis of HFrEF or COPD were eligible for the study. HFrEF patients were prospectively recruited from a heart failure clinic. They must have been symptomatic at some point in the past. Sequential symptomatic COPD patients were recruited from an outpatient clinic. Four patients with COPD found to have ventricular dysfunction, and 4 patients with HFrEF with obstructive spirometry and COPD features  were subsequently reclassified into a mixed group.2), angina, recent cardiorespiratory decompensation, anemia, morbid obesity, and standard contraindications to exercise testing. All patients’ care was managed by Imperial College Healthcare NHS Trust, or Royal Brompton and Harefield Hospital NHS Trust . The study conformed to the principles of the Declaration of Helsinki and was approved by the Imperial College Healthcare NHS Trust Research Ethics Committee. Participants provided written informed consent.Exclusion criteria included: inability to perform an exercise test, significant renal impairment  study, from which normal equations have been derived for a number of CPX variables. Study methodology has been described elsewhere All HFrEF and COPD participants underwent full lung function testing using a Spiro Air , and exercise testing on an ergoselect 100 ergometer  in an air-conditioned room. Twelve-hour abstention from caffeinated products was encouraged. CPX was performed using COSMED Quark CPX System , calibrated before each test. Three minutes of unloaded cycling preceded a 10 W/min ramp protocol exercising to exhaustion, with breath-by-breath gas exchange data. Blood pressure was recorded every 3 min using a manual sphygmomanometer. Patients underwent a second CPX at least 2 h after this familiarization test. This was similar to the first test, with 3 min unloaded, then incremental exercise but with a ramp protocol of 6, 8, 10, 12, 15, or 20 W/min depending on the results of the initial test, to elicit exhaustion between 8 and 10 min of incremental exercise. If 6 incremental minutes were achieved on the familiarization test a 6 W second test protocol was deemed suitable; 20 min on the familiarization test led to a 20 W protocol, and so forth.2 at AT, minute ventilation:carbon dioxide (VE/VCO2) ratio at AT, and end-tidal CO2 (PETCO2) (mm Hg) were taken at this time point. The oxygen uptake efficiency slope (OUES) was calculated as the slope of the regression line between log10 minute ventilation (x-axis) and VO2 (y-axis). The VE/VCO2 slope was calculated using data until the ventilatory compensation point − slope 1, and using all exercise data, including exercise after ventilatory compensation point − slope 2. Maximal voluntary ventilation (MVV) was calculated as: 40 · forced expiratory volume in 1 s (FEV1). Predicted values for peak VO2 and OUES were generated from the SHIP study 2.Full details of calculations and abbreviations are provided in the A number of CPX variables were never calculated in the SHIP cohort, and so these variables were only analyzed for the 2 disease groups.Echocardiography was performed using an IE33 ultrasound system  and B-type natriuretic peptide (BNP) was measured.1, percent predicted FEV1, and the transfer coefficient corrected for Hb (KCO(Hb)) and CPX variables were assessed using a multivariate model including age, gender, and weight as pre-specified covariates.Statistical analysis was performed using Stata version 11.1 for Windows . Normality of continuous variables was assessed using the Shapiro-Wilk test. Skewed variables were log transformed or nonparametric analyses used. A one-way analysis of variance was used to compare differences; for non-normally distributed variables a Kruskal-Wallis test was used. Categorical variables were compared with a chi-square test. Associations between FEV2 substituting for VO2 at AT in those not achieving AT. For net reclassification improvement and integrated discrimination improvement we compared accepted cutoffs (AT <40% predicted peak VO2) to identify HFrEF with the optimal variable identified from ROC curve analysis. Patients were scored +1 (patient correctly reclassified to HFrEF), zero (did not change groups), or –1 (patient incorrectly reclassified as not having HFrEF).The ability of each variable to discriminate between the 3 groups was assessed using the area under the receiver-operator characteristic (ROC) curve (AUC) with their 95% confidence interval. AUC ≥0.8, 0.7 to 0.8, and <0.7 were considered good, moderate, and poor respectively. Variables with good AUC were compared using the Stata roccomp command while all values were compared using the rocgold command with a Bonferroni correction. The primary analysis was a comparison of AUC in HFrEF against COPD patients (excluding mixed disease). Secondary analyses were both groups against the healthy matched controls, and the 2 disease groups including the mixed disease patients by original diagnosis. The ROC was arranged to give values ≥0.50. Variables requiring the AT to be achieved were initially only assessed in the patients who achieved the AT. To correct for the reduced number of patients achieving AT further analysis was done with peak VOA p value of <0.05 was considered significant throughout.A total of 73 patients  were recruited; 44 had HFrEF, 15 were awaiting CRT, 16 had previously undergone CRT, and 29 had COPD. Patient characteristics of the groups are shown in Within the COPD category, 2 patients were categorized as mild, 12 were moderate, 10 were severe, and 3 were very severe.The SHIP cohort matched 134 healthy controls.2 was similar between the 2 principal groups . Unadjusted peak VO2 correlated with estimated glomerular filtration rate  and Log10BNP  but not with hemoglobin or sodium. Fourteen individuals had atrial fibrillation or flutter but there was no significant difference in peak VO2 compared to sinus rhythm (p = 0.24).Among the patients, peak VO2 did not relate to FEV1 in patients with HFrEF (p = 0.20). Only breathing reserve at AT (p = 0.03) and peak (p = 0.01), and peak minute ventilation (p = 0.04) related to FEV1, while only O2-pulse related to KCO(Hb) with borderline significance (p = 0.047).On multivariate regression analysis peak VO2, the AT, the VE/VCO2-slope and ratio at AT, end-tidal CO2, and circulatory power all showed significant differences between healthy controls and each disease group, but not between the disease groups. OUES, OUES/kg, and percent predicted OUES differed significantly between COPD and HFrEF, and between HFrEF and healthy controls. OUES also differed between COPD and healthy controls but not when corrected for weight or percent predicted. The unadjusted O2-pulse differed between all groups, and was significantly higher in the HFrEF than the COPD group but the 2 disease states did not differ as percent predicted. Double product differed between all groups, with lowest values in the HFrEF group, and highest in healthy controls. Breathing reserve at the AT was significantly lower in the COPD compared to the HFrEF group and at peak was significantly lower in the COPD compared with both other groups. VO2 to work-rate relationship was significantly lower in patients with HFrEF compared to the other groups. OUEP was significantly lower in the COPD compared to the HFrEF group.A comparison of results across groups is shown in 2 pulse were moderate discriminators but not significantly different from breathing reserve (the discriminator with the greatest AUC) after a Bonferroni correction. Other variables were either significantly worse discriminators or did not discriminate at all.2, VE/VCO2 at AT, O2-pulse, and circulatory power.Variables with good discrimination between COPD and healthy controls were breathing reserve, peak VO2, circulatory power, VE/VCO2 slope, and VO2 at AT.Variables with good discrimination between HFrEF and healthy controls were OUES, double product, peak VOIncluding patients with mixed disease under their primary diagnosis worsened discrimination marginally .2 was substituted for the AT in these patients. The AUC for the VO2 at AT in ml/min was 0.60 and 0.57 as percent predicted peak VO2, both similar to the values seen when those not achieving the AT were excluded.To ensure that patients not achieving AT were not influencing its power to detect a difference in groups, peak VOBNP measurements were obtained in 55 of 65 patients and showed an AUC of 0.91, which was not significantly different from BR or percent predicted OUES . The addOptimal cutoffs were identified for percent predicted OUES and BR. A threshold of 89.2% predicted OUES showed sensitivity of 80% and specificity of 85% to predict HFrEF, correctly classifying 54 of 65 patients without mixed disease. A threshold of 33.6% for BR showed sensitivity of 80% and specificity of 100% to predict respiratory disease, correctly classifying 56 of 65 patients without mixed disease.2, and BR of 30%, 26 of 65 patients were correctly classified. Net reclassification improvement for percent predicted OUES over AT showed an improvement of 74.0% (p < 0.001), with an integrated discrimination improvement of 29.6% (p < 0.001).Using a previously determined algorithm Among CPX variables OUES and breathing reserve displayed the greatest ability to discriminate between HFrEF and COPD, and were the only CPX discriminators with AUC >0.8. This discriminant ability was similar to that seen with BNP. OUES also strongly discriminated HFrEF from healthy adults, while BR discriminated COPD from healthy adults.A potential algorithm to help distinguish patients based on these variables is shown in 2, the most widely known CPX variable, had no capacity to discriminate between cardiac and pulmonary causes of exercise limitation (AUC: ∼0.50); both diseases depressed peak VO2. Importantly this similarity of peak VO2 between our 2 principal groups allowed us to compare the ability of other measures to discriminate between cardiac and lung disease without concerns that observed differences merely related to differences in peak VO2.Peak VO2 at AT are described individually in detail subsequently. Select other variables are described now briefly.OUES, BR, and VO2/WR slope had significantly lower values in patients with HFrEF but was only moderately discriminant, while in COPD it behaved similarly to healthy adults. A previous study showing lower slopes in cardiovascular disease compared with healthy controls VO2-pulse, a surrogate for stroke volume, was unexpectedly higher in HFrEF, compared to COPD, although this difference was not seen when corrected using predictive equations. We believe that high beta-blockade use within the HFrEF group led to lower heart rates, greater filling times, and therefore higher stroke volumes. Second, the O2-pulse is dependent on arteriovenous oxygen content difference, often reduced in COPD patients with lower arterial saturations and higher peak venous saturations. The predicted O2-pulse was unsurprisingly significantly higher in healthy controls compared to both disease groups.The O2 relationship failed to discriminate the disease groups, but were significantly higher than healthy controls. In patients with HFrEF they are abnormal due to hyperventilation and perfusion to ventilation mismatching 2 relationship including mismatching of ventilation to perfusion.All measurements of the VE/VCO2 and minute ventilation 1 have lower peak VO2 but not OUES 1 or KCO(Hb).The OUES, largely effort independent, is calculated as the slope of the semilog relationship between OOUES was significantly lower in HFrEF than COPD, despite similar exercise capacities, and healthy controls, and on ROC curve analysis OUES, when weight adjusted or as a percent predicted, was a good diagnostic indicator of HFrEF with similar power to discriminate these 2 common causes of breathlessness as BNP. Importantly, OUES, when corrected, appears unaffected by COPD. Given the small numbers of patients within the mixed group further evaluation of the role of the OUES in patients with mixed disease would be beneficial.2 but may still ventilate to high levels. A considerable portion of exercise occurs where the VE and VO2 relationships are decoupled because of anaerobic metabolism and hyperventilation. This results in increasing levels of alveolar pO2, worse ventilatory efficiency towards peak exercise, and a “flattened” relationship Why did OUES differ? Patients with heart failure typically have an abnormal peak VO2 as a result of anaerobic metabolism is less pronounced, and alveolar pO2 may actually fall toward peak, thereby rendering ventilation more efficient 2/log10VE curve may be “shifted” rightward (higher log10VE for any given VO2) but the curve’s gradient itself is unchanged. This hypothesis may also explain why our mixed cohort had OUES values close to predicted.In contrast COPD patients behave similar to healthy adults failing to progress to maximal exercise, and are less anerobic at peak exercise. Furthermore, due to the increasing ventilatory constraint during exercise the increase in alveolar pOBreathing reserve has long been suggested as a discriminator of respiratory limitation The BR at peak is useful in identifying the principal physiology limiting exercise. However, unlike OUES, the magnitude is unlikely to be useful when measuring disease severity, so its role in serial studies in 1 patient may be limited.1) is typically much lower, leading to a smaller gap between peak minute ventilation and MVV; the BR. Patients with mixed disease had low BR values suggesting this variable may not be able to distinguish between those with COPD alone or those with mixed disease.BR is low in COPD because although in both HFrEF and COPD peak minute ventilation is reduced, in COPD patients the maximum voluntary ventilation  has poor discriminant ability between the disease groups, and only showed moderate discrimination between healthy adults and the 2 groups. We suggest that this variable is critically determined by muscle function and any chronic process that impairs muscular function will reduce the AT.In previous CPX algorithms a reduced AT would identify heart failure 2 for the VO2 at AT in patients failing to achieve AT allowed for all patients to be involved in the analysis of the AT variables but did not significantly change the ROC results.There may be a concern that the number of patients without a measured AT influenced our results. Our results are similar to other studies in terms of numbers of COPD patients failing to achieve AT 2. We hope to inspire future studies addressing more severely affected patients, for example those awaiting heart or lung transplant. We also made an assumption that principal pathophysiology was limiting exercise capacity. It is possible that patients were limited by musculoskeletal problems or adiposity. However, this should attenuate between-group differences.Some of the patients within the study population were not as symptomatic as expected, with 16% achieving 85% predicted peak VOPrevalence of mixed disease was lower than anticipated—only 9% of HFrEF and 14% of COPD patients. Consequently it was not feasible to analyze mixed disease as a separate group. We performed sensitivity analyses by comparing inclusion with exclusion of these individuals and found it had minimal effects on estimates of discrimination. However, future studies including patients with confirmed coexistent COPD and HFrEF would be valuable.When comparing the mean values for CPX variables between the groups, corrections were not made for multiple comparisons, and so with large numbers of statistical comparisons it is possible that some of the significant differences are due to chance. Whilst comparing AUC values for the primary analysis on ROC curve analysis Bonferroni corrections were used.Identification of the AT can be challenging; it is arguable that misidentification might have led to its results. Our protocol was designed for optimal exercise duration, with frequent, small workload increases (2 to 5 W increments every 12 to 20 s), which should aid identification. If despite this, misidentification still occurred it is arguably an inherent weakness of the AT, and does not negate our findings.2-pulse and OUES accounted for beta-blocker use, to minimize between-group differences.Medication use differed between groups, most importantly beta-blockade. Predictive equations for OCOPD was chosen as the archetypal respiratory, and HFrEF as the archetypal cardiac diseases. However the physiological abnormalities differ significantly from other respiratory diseases such as parenchymal lung disease, and other cardiac disease states such as heart failure with preserved ejection fraction or valvular disease. Therefore our results only apply to COPD and HFrEF. Further work would be needed to show that OUES and BR discriminate a fuller spectrum of cardiorespiratory disorders.2 at AT did not discriminate HFrEF patients from COPD. In a patient with exercise limitation, BR, and OUES could be used to identify the principal pathophysiology.PerspectivesCOMPETENCY IN MEDICAL KNOWLEDGE: The identification of markers of heart failure severity help health care professionals to target appropriate individuals for optimal disease management including advanced heart failure therapies such as transplantation and mechanical circulatory support. CPX testing already has a central role; here we show which measured variables are most, and least, affected by heart failure, and another common condition COPD, to give physicians greater understanding of the severity of their patients’ conditions.TRANSLATIONAL OUTLOOK: Heart failure and COPD commonly coexist, yet little research has been done into the exercise physiology of patients with both conditions. We show how 2 variables, OUES and BR, are good discriminators of these 2 conditions, and hope to inspire future researchers to further explore exercise pathophysiology in patients with coexistent cardiac and respiratory conditions. We also hope to promote further research into a potential role for the OUES in patient selection for advanced heart failure therapies.OUES and breathing reserve were the best CPX variables at discriminating HFrEF from COPD, and similar to BNP. VO


The goal was to develop familiar blood pressure (BP) charts representing BP percentile curves similar to CDC growth charts to improve screening of both high and low BP in children.Fourth Report data source and equations to calculate the BP threshold value for each gender and 5 cm height group. By slightly underestimating a child’s BP percentile for high BP and slightly overestimating a child’s BP percentile for low BP, these charts guarantee 100 % sensitivity in detecting abnormal BP. Sensitivity and specificity of the chart cut-offs were confirmed in a sample of 1254 healthy children from a school-based blood pressure screening program.Since height accounts for substantially more BP variability than age and is a more direct measure of body size and maturation in children, height-specific BP percentile curves were drawn separately for males and females. We used the 2004 The 1st, 5th, 25th, 50th, 75th, 90th, 95th, and 99th BP percentile curves are depicted in the chart for each corresponding gender and height from 85 to 190 cm, mimicking the ubiquitous CDC “growth charts”. Shaded areas of the chart differentiate abnormal BP status categories: hypotension, normal BP, prehypertension, Stage 1 hypertension, and Stage 2 hypertension. Sensitivity was confirmed to be 100 % with specificity above 94 %.These simplified BP charts improve upon currently available BP screening reference with the following features: (a) tracking BP longitudinally in an individual child, (b) full physiological range of BP percentiles represented in percentile curve format for rapid identification both high and low BP, (c) easy to use with absolute height alone avoiding the additional step of determining height percentile, (d) incorporation of adult threshold for pre-hypertension to assist in accurate transition from adolescence into adulthood, (e) high sensitivity and specificity to ensure all children at risk are identified with very few false positives. Recognizing blood pressure (BP) abnormalities in children is more cumbersome than in adults and contributes to underdiagnoses in pediatrics –5. WhileThe American Academy of Pediatrics has endorsed NHLBI guidelines that recommend all children over 3 years of age have BP measured at least annually for early recognition of BP abnormalities such as hypertension or syncope , althougFourth Report which can be used to identify any BP percentile, including abnormally high or low pressures [The purpose of this paper is to create a simple and practical BP screening tool to use alongside existing growth charts by the Center Of Disease Control (CDC) and World Health Organization (WHO) . We crearessures . Becauseressures –18, we wFourth Report as the source for all threshold values in our simplified charts. Current Fourth Report tables contain 476 blood pressure threshold values for each gender, age, and height percentile generated from regression model equations provided in the appendix of the Fourth Report [Fourth Report. For low blood pressure percentiles  the highest blood pressure threshold value for each gender and 5-cm height group was used. Median threshold value was used for the 50th blood pressure percentile. The range of age and height used in the equations were taken directly from the 2000 CDC stature-for-age tables for age in half-years and height percentiles 3rd, 5th, 10th, 25th, 50th, 75th, 90th, 95th, and 97th (www.cdc.gov/growthcharts). Only ages over 3 years were included as recommended by the Fourth Report and charts were created separately for boys and girls.Although the study was approved by the local IRB (HSC-MS-12-0432), no subjects were required for the analysis so no informed consent was necessary. We used the 2004 h Report . To creaFourth Report [Our BP threshold values are direct summary measures of the thresholds calculated in the h Report  such thah Report , 20. Accn = 4), had missing BMI measurements (n = 6), or had missing age (n = 2). The 2nd, 3rd, and 4th average of blood pressures at the initial screen are used for classification by our simplified chart and compared to the gold standard Fourth Report thresholds: 95th percentile for hypertension and 90th percentile (or 120/80) for prehypertension. We did not estimate sensitivity or specificity estimates for hypotension since there is no gold standard for this diagnosis. Demographics were reported in mean (min- max), and count (%).We determined exact sensitivity and specificity estimates from a sample of 1254 healthy children whose blood pressure was measured as part of the University of Texas Houston Pediatric and Adolescent Hypertension Program (HPAHP) school-based blood pressure screenings. All children with blood pressure measured 4 times on 3 separate occasions with a Spacelabs 90217 oscillometric device at cross-sectional blood pressure screenings in 2011 and 2012 were included. We excluded children who reported use of hypertensive medication  years, BMI percentile 63.6 (0–100), height 158.0 (65.5–188.5) cm, 56.0 (21.5–143.2) kg, and 403 (32.1 %) females. The overall prevalence of hypertension was 103 (8.2 %) and prehypertension 143 (11.4 %) at the initial screening. The simplified BP charts identified 100 % of systolic and diastolic hypertension and prehypertension cases, as designed to maintain 100 % sensitivity  [Fourth Report thresholds [Fourth Report guidelines [While the threshold values in the BP charts come directly from t tables , the mosFourth Report thresholds and none include both upper and lower BP limits. Currently in pediatrics, definitive values for the diagnosis of systolic or diastolic hypotension are lacking. Most of the current guidelines used by the Pediatric Advanced Life Support (PALS) course [Fourth Report data [Currently no BP charts exist for use in children that are based on current ) course , Brain T) course , and Int) course  define hort data . The incort data , these tIn summary, we provide simple BP charts for children representing percentile curves similar to CDC growth charts for rapid detection of both high and low BP. These BP charts parallel standard growth charts and improve upon current BP threshold resources with the following features: (a) tracking BP at various ages in the same child, (b) full physiological range of BP percentiles represented in curve format for rapid identification both high and low BP, (c) easy to use with absolute height alone avoiding the additional step of determining height percentile, (d) incorporation of adult threshold for pre-hypertension to assist in accurate transition from adolescence into adulthood, and (e) high sensitivity and specificity to ensure all children at risk are identified with very few false positives.BP, blood pressure; HTN, hypertension


A 53-year-old male was referred to our Department for refractory primary hypertension. Despite high doses of 6 anti-hypertensive drugs, ambulatory monitoring of blood pressure (BP) revealed a mean BP of 160/90 mmHg. Under local anaesthesia, renal denervation with radiofrequency was performed supported by high-resolution 3D angiography, which helped confirm the position of the applications in a spiroid fashion. High blood pressure is an independent cardiovascular risk factor with high prevalence . PreciseA 53-year-old Caucasian male was referred to our Department for refractory primary hypertension. Despite high doses of six anti-hypertensive drugs , ambulatory monitoring of blood pressure (BP) revealed a mean BP of 160/90 mmHg. Exhaustive blood tests, CT scan and renal arteries ultrasound suggested primary hypertension as the most probable diagnosis . CoronarRenal denervation has been proposed as an effective treatment for refractory primary hypertension for patients with inadequate blood control despite high doses of numerous drugs . Simplic


Background. This study is provided to increase the efficiency of the treatment of kidney transplant recipients by predicting the development of the late allotransplant dysfunction. Methods. 330 patients who have lived for more than one year with functioning kidney allograft were evaluated. To predict the subsequent duration of the well-functioning of allotransplant the prognostic significance of 15 baseline clinical and sociodemographic characteristics on the results of the survey one year after transplantation was investigated. The result was considered to be positive in constructing the regression prognostication model if recipient lived more than 3 years from the time of transplantation. Results. It was established that more late start of renal allograft dysfunction after transplantation correlates with the more time it takes till complete loss of allograft function. Creatinine and hemoglobin blood concentration and the level of proteinuria one year after transplantation within created mathematical model allow predicting the loss of kidney transplant function three years after the transplantation. Patients with kidney transplant dysfunction are advised to renew the program hemodialysis upon reaching plasma creatinine concentration 0.5–0.7 mmol/L. Conclusion. Values of creatinine, hemoglobin, and proteinuria one year after transplantation can be used for subsequent prognostication of kidney transplant function. Significant improvement of kidney transplantation results in the early postoperative period during recent decades is accompanied by the expansion of the pool of patients with long periods of observation. The most difficult problem of the late postoperative period is chronic nephropathy of the transplant –6. Late The objective of this study is to increase the efficiency of the treatment of recipients in the late period after kidney transplantation by estimating the probability of loss of function of kidney transplant in the long-term period after transplantation.330 patients who had been receiving renal replacement therapy since 1987 till 2012 and living longer than one year with a functioning kidney transplant were selected in the study group. There were 61.2% males and 38.8% females. Age was ranging from 6 to 71 years. The median recipient age was 42.6 years. The main disease was glomerulonephritis (78.2%). Polycystic disease, diabetes, or other causes were more seldom. Most of them were on hemodialysis (96%); 13 patients received preemptive transplant. 56% of transplants were performed from deceased donors and 44% from the living donors. The “Custodiol HTK Solution” was used for cold storage of kidney transplants. The cold ischemia time was no more than 24 hours. Immunosuppression  consisted of cyclosporine, azathioprine, and steroids. Later (since the year 2000) in all cases of induction anti-CD-25 monoclonal or other depleting antibodies were used. Immunosuppression maintenance spectrum was added by tacrolimus, prolonged-release tacrolimus, mycophenolate mofetil, mycophenolate sodium, or everolimus.The duration of observation after transplantation averaged 6.5 ± 1.4 years. Clinical and laboratory monitoring of the patient and kidney transplant were usually carried out on outpatient basis. Surveys were carried out depending on the period after kidney transplantation with a frequency of once a month up to 2–4 times per year. Particular attention was paid to the level of blood pressure, hemoglobin in the full blood count, creatinine concentration in blood plasma, and daily protein excretion. If necessary, sonography of transplant was performed.We considered as appropriate the immunosuppression in which concentration of immunosuppressants in the blood was within the “therapeutic range” and the number of leukocytes in full blood analysis corresponded to normal.The diagnosis of anemia was made at hemoglobin concentration of less than 130 g/L for men and less than 120 g/L for women. The blood pressure less than 140/90 mm Hg was considered as normal, blood pressure more than 140–159/90–99 mm Hg was considered as moderately elevated, and the blood pressure more than 160/100 mm Hg was considered as high. The degree of proteinuria was assessed by daily urinary protein excretion: minimum: loss of protein <0.5 g/day, moderate: 0.5–1 g/day, and severe: more than 1.0 g/day. In order to standardize the results, as a starting point of late dysfunction we conventionally adopted the increase of creatinine level to 0.3 mmol/L in plasma for the first time detected after kidney transplantation. We used SF-36 scale to assess patients' quality of life.In order to identify the features that can be used to assess the degree of risk of death with a functioning transplant or return to the program hemodialysis the method of constructing of mathematical predicting models has been used.To predict the subsequent duration of the well-functioning of allotransplant the prognostic significance of 15 baseline clinical and sociodemographic characteristics on the results of the survey one year after transplantation was investigated.We studied age of the recipient at the time of renal transplantation, primary diagnosis, which led to the development of end-stage renal failure, type of donation (cadaveric or living), duration of hemodialysis treatment before kidney transplantation (in years), the presence of an induction immunosuppressive therapy with antibodies, the presence of hepatitis B or C infection at time of transplantation, education , type of residence , number of previous transplantations , the concentration of creatinine in the blood one year after transplantation (mmol/L), blood pressure one year after transplantation (mm Hg), the concentration of hemoglobin in the blood one year after transplantation (g/L), proteinuria one year after transplantation , and the duration of satisfactory function of renal transplant (in years) to death with a functioning graft or to return to the program hemodialysis.The choice of factors taken as a basis was determined, first of all, by their accessibility to the wide range of physicians having the recipients in the late postoperative period under supervision. That is why we studied the possibility to use the most informative ones to predict the loss of kidney transplant function.To assess the data obtained we used methods of parametric statistics including definition of their accuracy according to Student's criterion.To reveal the most informative signs at assessing the degree of death risk with the functioning transplant or returning to programmed hemodialysis, for the purpose of possible correction of emergent threat, Cox multiple-factor regression model with the calculation of correlation coefficients was used. In this model the influence of each factor under study is characterized by an assessed coefficient which reflects the specific weight of the factor itself in the complex of assumed influence. The connection between studied separate risk factors of kidney transplant function loss was analyzed with the use of conjugation tables and by means of calculating the correlation coefficients.In constructing of regression model of prognostication the result was considered positive if the recipient lived for more than 3 years from the time of transplantation.β-coefficients of the generalized regression model for the forecast was performed. On a dedicated set of features predictive model was created and optimized after model's decision-rejection threshold training.Analysis of Statistical packet SPSS was used for data processing.Standardization of all stages of pre-, intra-, and postoperative period facilitated an increase in one-year survival rate of kidney transplants especially in separate years of the last decade till 100%. In the late period in a year or later after the kidney transplant recipient's quality of life was close to the quality of life of healthy people and is significantly higher than the patients who continued dialysis .So the quality of life after transplantation was largely determined by the presence or absence of renal transplant dysfunction which dominated in the structure of adverse outcomes in transplant transplantations in late postoperative period. This is the reason why all the necessary measures should be carried out including prognostication and influence upon the modifying factors to ensure the stable kidney transplant function. Development of renal allograft dysfunction usually associated with anemia, hypertension, proteinuria, infections, and other adverse events.In the analysis of the anemia prevalence in the late period after kidney transplantation and its correlation with survival of patients and transplants it is revealed that before kidney transplantation 98.7% of patients had signs of anemia. One year after kidney transplantation 20% of patients had anemia signs, three years after 28%, in 5 years 37%, in 10 years 45%, and in 15 years 46%. Functional survival of patient's transplants with normal levels of hemoglobin in the blood after 15 years of the operation was three times higher than that in the group of patients with anemia .Before kidney transplantation 1.8% of patients had normal blood pressure (BP), one year after kidney transplantation normal blood pressure occurred in 27% of patients, after 3 years, in 31% of patients, after 5 years, in 37% of patients, after 10 years, in 45% of patients, and after 15 years, in 54% of patients. Functional survival in patient's transplants with normal blood pressure after 15 years was 2.8 times higher than that in the group of patients with hypertension, and patients survival rate was almost 5 times higher . Our datThe average duration of transplant functioning from the moment of the detection of minimal proteinuria was 4.3 ± 2.5 years, with moderate proteinuria it was 2.7 ± 2.2 years, and in severe proteinuria it was 0.8 ± 0.3 years.We found out that the rate of chronic nephropathy development in renal transplant depended on the duration of satisfactory function of renal transplant.Patients who had signs of late dysfunction one year after transplantation returned to hemodialysis in 19.4 ± 2.6 months after the first recorded increase of the plasma creatinine up to 0.3 mmol/L.Patients who had symptoms of late dysfunction 2-3 years after transplantation returned to hemodialysis in 40.0 ± 0.6 months after the first recorded increase of the plasma creatinine up to 0.3 mmol/L.Patients who had symptoms of late dysfunction 5 years after transplantation returned to hemodialysis in 44.5 ± 0.9 months after the first recorded increase of the plasma creatinine up to 0.3 mmol/L.In order to predict the duration of satisfactory function of the transplanted kidney we investigated the predictive value of 15 basic clinical laboratory and sociodemographic variables of the survey one year after transplantation .β-coefficients of the generalized regression model showed that three characteristics can be deemed the most significant (P < 0.001) for the forecast: blood creatinine and hemoglobin level and degree of proteinuria.233 (70.6%) kidney transplant patients with functioning graft have been living over three years. Analysis of P < 0.001): creatinine concentration in the blood (X1), hemoglobin concentration in the blood (X2), and severity of proteinuria (X3).It was found that three signs can be the most significant , X2 is hemoglobin (g/L), and X3 is proteinuria in a year after transplantation (g/L). Y is a prognostic criterion. The value Ycrit = 0.435 is obtained. If as a result of calculation within the created model Y value is less than Ycrit, a negative result is predicted (a loss of transplant function in three years from the time of transplantation) and otherwise a positive (favorable) result is predicted.The resulting predictive model using these factors was described by the equation: Determination of creatinine and hemoglobin level in the blood as well as the concentration of protein in the urine in one year after kidney transplantation with the calculation of prognostic criterion predicts the loss of renal allotransplant function in 3 years after surgery. The advantages of the method are the possibility of quantitative forecasting of renal allotransplant losses which is based not only on its excretory function assessment, but also on an assessment of other characteristics that may have important prognostic value and does not always directly correlate with changes in its excretory function. In order to assess the risk of death with a transplant functioning or return to the program hemodialysis the predictive model was implemented in tabular processor Excel. For the use of the model it is quite enough to input the value of the given indices. Calculation and prognosis will be automatically done in the electronic table .http://uapatents.com/4-68339-sposib-prognozuvannya-vtrati-funkci-nirkovogo-transplantata.html) and is available on the Internet (https://yadi.sk/i/w9DaT4YrsFRnZ). The accuracy of prediction of renal transplant function loss three years after transplantation was 92%.The calculator designed by us has been patented  short courses of low doses of steroids administered orally or intravenously can be effective.Progression of chronic renal dysfunction of the transplant is accompanied by the simultaneous loss of the benefits of a successful transplantation and the growth of problems due to immunosuppression. Based on a retrospective analysis of results of treatment of kidney transplant of the recipients with blood creatinine higher than 0.3 mmol/L, we adhere to the following principles in the correction of immunosuppression which allow decreasing the rate of chronic dysfunction of the transplant development or decreasing the risk of complications in case of loss of its function.According to plasma concentration of creatinine at the return to hemodialysis the patients were divided into 3 groups. In the first group the creatinine concentration in blood plasma was 0.5–0.69 mmol/L, in the 2nd group concentration in blood plasma was 0.7–1.0 mmol/L, and in the third group concentration in blood plasma was more than 1.0 mmol/L.Dates of the return of transplant recipients with delayed renal transplant dysfunction are largely dependent on the psychological state of the patient, severity of depression, the desire to ensure the irreversibility of the transplanted kidney dysfunction, and fear that the dialysis will contribute to the deterioration of renal transplant function.The survival rate of patients of the first group after return to hemodialysis was 7.4 + 2.8 years, and in the second and third groups it was, respectively, 5.3 ± 3.2 and 2.8 + 2.6 years.In general, the noninvasive prediction of loss of renal transplant function based on quantitative criteria which diversely characterized the state of renal transplant enabled timely influence on modifiable risk factors for dysfunction of the transplanted kidney, correct immunosuppression, or return kidney transplant recipients to dialysis treatment.Our experience of renal transplantation confirms the principle possibility to achieve a guaranteed high level of patient's rehabilitation. The quality of medical and social rehabilitation after kidney transplantation is comparable with healthy individuals and is much better than the patients being treated with hemodialysis.The results of kidney transplantation are largely determined by the presence of renal allotransplant dysfunction which dominated in the structure of the causes of an unfavorable outcome of kidney transplantation in the late postoperative period. More later development of the kidney transplant dysfunction correlated with the greater duration of the period prior to the loss of its function.The absence of anemia and proteinuria after kidney transplantation allows counting on a significant improvement in survival of renal allotransplant and a recipient. Correction of blood pressure also allows counting on a significant improvement in the results of renal transplantation in the late postoperative period.Determination of creatinine and the hemoglobin concentration in blood and the protein concentration in urine one year after transplantation with the calculation of prognostic index allows predicting the loss of renal allotransplant function in 3 years after transplantation with accuracy up to 92%. The constructed mathematical model for predicting the loss of renal allotransplant function can be realized in the tabular processor Excel and thus be used in medical practice.For patients with delayed renal allotransplant dysfunction it is reasonable to restart the hemodialysis program at achieving plasma concentrations of creatinine of 0.5–0.7 mmol/L. At the same time hemodialysis immunosuppressive therapy must be canceled.