Pre-transplant prognostic scores help to optimize donor/recipient allocation and to minimize organ discard rates. Since most of these scores come from the US, direct application in non-US populations is not advisable. The Survival Benefit Estimator (SBE), built upon the Estimated Post-Transplant Survival (EPTS) and the Kidney Donor Profile Index (KDPI), has not been externally validated. We aimed to examine SBE in a cohort of Spanish kidney transplant recipients. We designed a retrospective cohort-based study of deceased-donor kidney transplants carried out in two different Spanish hospitals. Unadjusted and adjusted Cox models were applied for patient survival. Predictive models were compared using Harrell’s C statistics. SBE, EPTS and KDPI were independently associated with patient survival . Model discrimination measured with Harrell’s C statistics ranged from 0.57 (KDPI) to 0.69 (SBE) and 0.71 (EPTS). After adjustment, SBE presented similar calibration and discrimination power to that of EPTS. SBE tended to underestimate actual survival, mainly among high EPTS recipients/high KDPI donors. SBE performed acceptably well at discriminating post-transplant survival in a cohort of Spanish deceased-donor kidney transplant recipients, although its use as the main allocation guide, especially for high KDPI donors or high EPTS recipients requires further testing. The survival benefit of kidney transplantation (KT) compared with remaining on dialysis and the rising prevalence of chronic kidney disease result in a continuous increase in the allograft demand/supply ratio.5. However, the improvement in survival associated with transplantation in old recipients (≥ 65 years) who receive marginal kidneys remains unclear7.As a consequence of this, changes in the acceptance criteria of donors into transplant programs have been implemented in order to increase the donor pool8. KDPI is a percentile measure calculated with ten donor variables which is currently applied in all deceased US donors to estimate the risk of post-transplant graft failure10. EPTS is also a percentile measure that includes four recipient variables and provides information about potential recipient survival after receiving a KT. Briefly, higher EPTS or KDPI scores indicate lower quality organs and worse expected survival of recipients. The OPTN KAS allocates kidneys with lower KDPI scores to candidates with lower EPTS scores to obtain the highest benefit11. Recently, a new scoring tool  has been developed to estimate post-transplant survival benefit based on KDPI and EPTS. SBE calculates the probability of 5-year post-transplant survival after receiving a kidney allograft from a specific donor. Results suggest that receiving a KT may be associated with lower mortality risk when compared to remaining on the waitlist across any possible KDPI and EPTS combination12.In 2014, the US Organ Procurement and Transplantation Network (OPTN) started a new kidney allocation system (KAS) based in donor (Kidney Donor Profile Index—KDPI) and recipient  scores. Their aims were to improve donor/recipient matching and to decrease organ discard rates14. In 2017, 45.7% of Spanish donors were ≥ 60 years, while only 4.9% of US donors were 65 years or older15. There were also significant differences regarding donor cause of death, diabetes or hypertension prevalence16. However, recent studies have shown the potential benefit that the application of these scores might have in non-US populations. KDPI has shown to improve the expanded criteria donor classification in order to provide an estimation of graft survival in a cohort of Spanish KT recipients17 while the introduction of the Kidney Donor Risk Index in the decision-making process to accept or decline deceased donor kidneys in a Eurotransplant center helped to increase its transplantation rate by 26%20.Nevertheless, application of these scores in non-US patients might not be advisable due to the intrinsic differences existing between transplant programs in the US and other countries such as SpainThe main objective of this study was to assess the prognostic performance of SBE in a two-center Spanish kidney transplant cohort. Secondary objectives of the study were (1) to evaluate the effectiveness of EPTS and KDPI when predicting post-transplant survival, (2) to describe the distribution of donors and recipients in our sample according to KDPI and EPTS scores and (3) to compare the characteristics of the study subjects with the US dataset.We designed a retrospective cohort study with adult (age ≥ 18 years) deceased-donor KT recipients performed from January 2000 to July 2015 in two different hospitals in Spain. KT from donors younger than 18 years old, living donors, multiple-organ transplants and recipients who were lost to follow-up during the first 5 years after transplantation were excluded from the analysis. Anthropometric, clinical, and analytical variables were collected from each site’s local transplant database. Time on dialysis was calculated considering all dialysis periods for patients that received more than one graft.21.This project was conducted in accordance with the ethical standards of the 2000 Declaration of Helsinki as well as the 2008 Declaration of Istambul. No organs were procured from prisoners. The Institutional Review Boards and Ethics committees of both centers approved the study . Informed consent was waived by the same authority that approved the study  due to the observational and retrospective nature of the study. The study is reported in accordance with guidelines set forth in the 2007 STROBE statement12, available at https://www.transplantmodels.com/kdpi-epts/. Briefly, SBE estimates the survival benefit  for a distinct recipient of receiving a kidney from a specific donor using a combination of EPTS and KDPI scores.Predicted 5-year patient survival was calculated using the prognostic score developed by Bae et al.Actual post-transplant patient survival was defined as the time from KT to death, censoring by the end of the study. All patients were followed-up long enough to establish 60-month survival, regardless the allograft status (functioning or not).9. EPTS was calculated using recipient variables including age, diabetes, time on dialysis and previous solid organ transplant, following the methods described in the OPTN site. EPTS scores vary from 0 to 100%. Patients with lower EPTS scores should experience more years of graft function from high-longevity kidneys compared to subjects with higher EPTS scores11.The following donor variables were used to calculate KDPI: Age, race, height, weight, hypertension, diabetes, serum creatinine, hepatitis C seropositivity and cause of death, using the methods depicted in the OPTN site. KDPI scores range from 0 to 100% and indicate the potential longevity and quality of a kidney graft compared to a reference populationTo examine the association of SBE score with patient survival, we stratified our sample by SBE quintiles. Adjusted models were built using SBE, EPTS or KDPI and other recipient variables of clinical relevance . Those variables already considered in the calculation of KDPI or EPTS scores were not included in this last analysis.Data are expressed as mean and standard deviation (SD) or median and range for non-normal distributions. Qualitative variables are described as frequencies and percentages. T tests and analyses of variance were used to assess continuous variables. Chi-square test was used to compare categorical data between groups.22, which was non-significant (P > 0.05). Multiple imputation by fully conditional specification was applied to the dataset. A total run length of 1000 iterations was used, creating 10 imputed data sets to take into account uncertainty associated with missing data. All variables needed to calculate EPTS and KDPI score were included in the procedure . Final results were averaged across the created sets.To address missing values, we first applied Little’s missing completely at random test to assess the assumption of missing completely at random for multivariate quantitative data23. Quintile distribution according to SBE score  was used to obtain groups of comparable size. Overall survival probabilities for each group were estimated using the Kaplan–Meier method and compared by the log-rank test. Hazard ratios (HRs) with 95% confidence interval (CI) were calculated using unadjusted and adjusted Cox proportional hazards regression modelling. To ensure confidence interval coverage and type I error rate as defined by Vitinghoff et al.24 the study sample included at least ten events per predictor variable. Model discrimination was estimated using Harrell’s C statistic25. Harrell’s C estimates the proportion of correct predictions, serving as a concordance index. The results of Harrell’s C index varied from 0.5 (no discrimination) to 1 (perfect discrimination). The Benjamini–Hochberg procedure was used to control for the false discovery rate26. We examined the Akaike information criterion (AIC), a technique based on in-sample fit to estimate the likelihood of a model to predict future values. The statistical significance level was set at p < 0.05. Statistical analysis was performed using IBM SPSS v.22 , GraphPad Prism v.7  and Microsoft Excel .To compare the original SBE cohort with our study cohort, mean and standard deviation were estimated on the basis of the reported median and range according to the method developed by Hozo SP et al.A total of 1200 KT were performed in two Spanish hospitals between January 2000 and July 2015. The final analysis included 935 KT patients. Flow-chart of patients is represented in Fig. Regarding baseline characteristics, a comparative between Bae´s cohort and our study cohort is summarized in Table Spanish recipients and donors were older and predominantly Caucasians (92.2%). Spanish recipients showed lower prevalence of diabetes, less time on dialysis before KT and lower rates of re-transplantation. The proportion of pre-sensitized patients was higher in Bae´s cohort, while KDPI scores were higher and EPTS scores were lower in the Spanish cohort.The study sample was divided into five groups according to SBE value distribution. Table Patients with worse estimated post-transplant survival were older, had longer dialysis vintage and suffered more frequently from diabetes or cardiovascular disease. These patients received kidneys from older donors with a higher prevalence of hypertension and diabetes. There was a higher percentage of KT from cardiac-death donors among recipients with better estimated post-transplant survival.In the Spanish cohort 36.6% of donors presented with KDPI > 80%, while a low number of recipients (10.3%) had high EPTS scores (EPTS > 80). The majority of recipients with EPTS > 85 62.9%) received a kidney from a KDPI > 85 donor. The distribution of KDPI and EPTS scores in our cohort is shown in Fig. .9% receiSBE was used to estimate 5-year patient survival at the time of transplantation. The study sample was divided into quintiles using the results of the SBE score. Figure Actual survival rates in our cohort were higher than predicted ones in the first and second highest and lowest SBE quintiles.In unadjusted analysis, higher SBE score was a significant protective factor for recipient death [HR: 0.95 0.93–0.96)], while higher KDPI and EPTS scores were significant risk factors for recipient death . All three scores were independently associated with post-transplant survival after adjustment  had a 23 median percentage point higher EPTS score and a 14 median percentage point higher KDPI score compared to the 2nd quintile group, actual survival between these two groups did not differ significantly . This difference was not significant after adjustment for multiplicity.Discrimination and calibration of SBE, EPTS and KDPI models are summarized in Table Clinical tools aimed to optimize selection of donor-recipient pairs and estimate the potential survival benefit that a specific organ could involve for a specific recipient have been recently developed.The present study evaluated the predictive performance of SBE in terms of 5-year patient survival after kidney transplant, even if the patient lost the graft during that time. In our sample, SBE, EPTS and KDPI score are associated with 5-year patient survival and they remained significant even after multi-adjusted survival analysis by recipient comorbidities Table .12. However, in this European population SBE tended to underestimate actual survival mainly in the subsets of patients with either highest or lowest SBE scores, therefore reflecting limited utility of this tool in these specific populations. Subjects within the worst and second-worst quintiles according to SBE estimated 5-year survival did not demonstrate significant differences in actual survival  in the second-worst quintile compared with the worst  and higher than that of KDPI (0.57). Surprisingly, the calculated C-statistic for the SBE score in our sample was higher than that obtained in its development sample (0.69 vs 0.64)val Fig. . This is28. Clayton et al. evaluated this score in 4983 kidney transplant recipients from the Australia and New Zealand Dialysis and Transplant (ANZDATA) Registry. The authors analyzed three different Cox models  and reported a Harrell’s C-statistic of 0.67, 0.68 and 0.69 for each model respectively18. We found similar discrimination power with a C-statistic of 0.71 in unadjusted analysis that improved to 0.74 when relevant clinical recipient variables were added to the model. EPTS was also tested as a prognostic tool after deceased-donor KT in Mexican patients, with an area under the receiver operating characteristic curve of 0.6429.EPTS score showed moderate discrimination in the original US data, with a C-statistic of 0.6930. Calvillo-Arbizu et al. also suggested that KDPI could constitute a potential indicator of patient survival, especially for recipients older than 60 years31. However, in another study with Spanish transplant patients no relationship was found between KDPI score and recipient death17.KDPI showed the lowest survival predictive power among the tools. This was an expected finding, as KDPI and Kidney Donor Risk Index were essentially designed as tools to estimate graft durability, but their potential application as predictors of post-transplant patient survival has been tested before. We found a 1.1% higher risk of mortality per percentage point of KDPI increase, and poor 5-year patient survival prediction capacity with a C-statistic of 0.57 in unadjusted analysis that improved to 0.65 when additional recipient variables were added to the analysis. Similar results were obtained by Peters-Sengers et al., reporting 5-year mortality C-statistic for Kidney Donor Risk Index (including deaths after graft loss) of 0.6812. In addition, Spanish recipients were older but with less prevalence of diabetes, shorter dialysis vintage and lower sensitization degree. Cold ischemia time was also shorter in our sample. These differences were translated into a lower EPTS score compared to that of Bae’s study. On the other hand, our donors were older and more frequently diabetics and with hypertension, which translated in a higher KDPI compared to that registered in SBE development sample12.The observed disparities between our results and American studies could be explained by several relevant demographic differences between the US and Spain. For instance, more than 90% of our donor and recipient sample was constituted by Caucasians whereas the cohort used in the development of SBE was much more ethnically diverse32. The Cox proportional hazards regression model used to develop Kidney Donor Risk Index was obtained from a sample of US kidney recipients from 1995–2005. Donor and recipient characteristics have changed significantly over the last 20 years, both in the US and in Europe34, as well as other factors such as dialysis-associated mortality or waitlist removal35. In addition, the increasing prevalence of chronic kidney disease, the growing demand for organ donations and the incorporation of expanded criteria donors as a viable organ source have modified even further the current transplant landscape in the last decades.Divergences in transplant era can also be a possible explanation of score performance discrepancies, as pointed by Rose et al.37. Although in Spain there are no official data regarding KDPI-associated discard rates as the use of KDPI is not routinely extended, Arias-Cabrales et al. reported that 35.5% of patients in their study received a kidney from a KDPI > 85 donor17, a percentage which was slightly lower (30.6%) in our current sample.Differences also affect transplant policies and organ allocation. Between 2004 and 2015 more than 50% of the retrieved kidneys with KDPI > 85% were discarded in the US, even after the initiation of the KDPI era38, with Medicare coverage for those drugs being lost after the first three years after transplantation39. In comparison, the transplant procedure, follow-up monitoring and all associated medication is completely covered in Spain and other European countries40, regardless of transplant duration.Results may also depend on other donor, recipient and procedure characteristics not accounted for during calculation of SBE, KDPI or EPTS scores, such as graft damage or abnormalities, excessive first warm ischemia time, additional recipient comorbidities or likelihood of transmission of diseases during transplantation. Additionally, divergences in health care systems between the US and Spain could explain some of the observed discrepancies. More than 70% of US kidney transplant patients report economic problems to access immunosuppressive medicationThe present analysis has some limitations. Extensive efforts were undertaken to adjust for potential confounding, but residual confounding due to unmeasured variables is still possible. Moreover, most of our sample consisted of Caucasians. Therefore, our results cannot be extrapolated to subjects of other ethnic groups. Likewise, most of the donors in this study were brain-dead so the studied scores may perform differently in other settings such as donation after cardiac death. Additionally, we only tested the predictive capabilities of the SBE score at the 5-year time point. As a consequence, our results should not be extrapolated to other time points. Finally, organ allocation strategies and policies may diverge considerably between countries and, to a lesser extent, between transplant centers, which may affect the predictive potential of scores such as SBE.But the present study has several strengths too. To our knowledge, this is the first study that offers an external validation analysis of the SBE score in European population. SBE scoring considers both donor and recipient characteristics to build a post-transplant survival estimation. Although the discrimination power was similar to that of EPTS in our sample, due to recipient traits being the most relevant to determine recipient survival, the inclusion of donor associated variables provides a small but important improvement to survival prediction, thanks to their significant effect on future graft function. Our sample was built using data from two different transplant centers and included survival information regardless of actual graft function.In sum, this is one of the first studies to provide external validation of the use of the SBE score as a standalone score in a non-US sample of kidney transplant recipients. Further analysis should be performed to adequately characterize its potential to produce accurate and individualized post-transplant survival predictions.


For a deeper understanding we conducted two surrogate analyses by substituting the systolic blood pressure by its reversed time series. These showed that the xBRS method was not able to quantify causal relationships between the two signals. It was not possible to distinguish between random and baroreflex controlled sequences. It appears xBRS rather determines the HRV/BPV quotient. We conclude that the xBRS method has a potentially large bias in characterizing the capacity of the arterial baroreflex under resting conditions. During slow breathing, estimates for xBRS are significantly increased, which clearly shows that measurements at rest only involve limited baroreflex activity, but does neither challenge, nor show the full range of the arterial baroreflex regulatory capacity. We show that xBRS is exclusively dominated by the heart rate to systolic blood pressure ratio . Further investigations should focus on additional autonomous testing procedures such as slow breathing or orthostatic testing to provide a basis for a non-invasive evaluation of baroreflex sensitivity.Spontaneous baroreflex sensitivity (BRS) is a widely used tool for the quantification of the cardiovascular regulation. Numerous groups use the xBRS method, which calculates the cross-correlation between the systolic beat-to-beat blood pressure and the R-R interval (resampled at 1 Hz) in a 10 s sliding window, with 0–5 s delays for the interval. The delay with the highest correlation is selected and, if significant, the quotient of the standard deviations of the R-R intervals and the systolic blood pressures is recorded as the corresponding xBRS value. In this paper we test the hypothesis that the xBRS method quantifies the causal interactions of spontaneous BRS from non-invasive measurements at rest. We use the term spontaneous BRS in the sense of the sensitivity curve is calculated from non-interventional, i.e., spontaneous, baroreceptor activity. This study includes retrospective analysis of 1828 measurements containing ECG as well as continues blood pressure under resting conditions. Our results show a high correlation between the heart rate – systolic blood pressure variability (HRV/BPV) quotient and the xBRS ( The baroreflex is an important component of cardiovascular regulation to maintain homeostasis. The idea of spontaneous baroreflex sensitivity is to estimate the concomitant effect of respiration on heart period and blood pressure based on non-invasive and non-pharmacological driven measurements. Originally, BRS has been assessed by the Oxford method, based on analysis of heart rate response to drug-induced blood pressure variations . This meFluctuations in blood pressure and heart period can be of clinical importance as risk markers for cardiovascular morbidity and mortality . HoweverTo allow comparison to the results in All measurements of the considered studies were performed under supine resting position for 30 min using the Task Force Monitor  or the PortaPres device . In total we gathered 1,828 time series containing the beat-to-beat values of heart rate (HR) as well as systolic blood pressure (SBP). Exclusion criteria were atrial fibrillation, pacemaker activity, technical artifacts, as well as ectopy time greater than 10%, reducing the number of time series to 1,576 – careful visual inspection for further technical and physiological artifacts reduced the subjects for reanalysis to 1,439.In addition to this comprehensive data set of rest measurements, recordings with certain autonomous testing procedures were analyzed in this paper. We used 245 measurements of 44 healthy pregnant women, mean age 30 ± 5.4 years, from the Fetal Autonomic Cardiovascular rEgulation (FACE) study which is currently in progress at the University of Leipzig Medical Center in cooperation with the TU Dresden and the Humboldt-Universität zu Berlin. The study was approved by the committee of ethics of the University of Leipzig Medical Center (357/17-ek). One aim of this study was to characterize the reaction of fetal autonomic regulation to maternal paced breathing based on a context dependent biosignal analysis. The measurements were performed under supine resting position using the PortaPres device , the fetal ECG signal was recorded from the abdomen of the pregnant woman. Our measurement protocol included 10 min of measurement at rest in supine position, 5 min of paced slow respiration (period 7.5 s – 8 respiration cycles per min), and 5 min of fast respiration (period 3 s – 20 cycles per min). Between both paced respiration conditions was one break of 5 min at rest. Exclusion criteria were rhythm disturbances (many of ventricular or supraventricular ectopic beats), technical artifacts, and incomplete study protocols. The data underwent a careful visual inspection for further artifacts by experts which reduced the analyzed data set to 184 records.Originally, BRS was measured by injecting vasoconstrictive agents to raise blood pressure, i.e., quantifying the reflex-like increased beat-to-beat intervals in the electrocardiogram (ECG). Later, attempts have been made to determine baroreflex sensitivity non-invasively, most often using spontaneous heart rate variability (HRV) and blood pressure variability (BPV) obtained from continuous finger pressure measurement . The undp < 0.05, two sided test for zero correlation). The BBI window with highest cross correlation is then selected. xBRS has two advantages: (a) it gives more valid “sequences” for the same time series compared to SME and (b) it allows to observe slow regulation circuits that are presumably arising from sympathetic control. Usually, the resulting number of valid “sequences” in the time series is large enough to enable the calculation of an “instant” measure for xBRS. The xBRS method was developed by p < 0.01). In the last revision  data. The original time series is resampled to obtain evenly sampled data at 1 Hz. Instead of sequences, xBRS uses sliding windows with a fixed length of 10 seconds. For every SBP window, there should exist at least one corresponding BBI window (in a lag range of 0–5) with positive and significant cross correlation Systolic blood pressure time-series were analyzed in reversed order, i.e., the first blood pressure value is now the last, the second now the second last etc. This results in surrogate data with the same distribution as the original data since the values of each point are the same, just in a different time position. However, any causal relationship between heart rate and blood pressure has been removed by this procedure cf. .FIGURE (b)S2).Beat-to-beat-intervals were shuffled using the IAFFT approach . By applBoth surrogate tests are used to test the following hypothesis: “xBRS does quantify causal relationships between heart rate and blood pressure.”Statistical analysis was performed using IBM SPSS Statistics version 24. To quantify significant relations between the parameters used in this study we applied Pearson’s correlation as a measure of the linear relationship between two continuous random variables. This measure does not assume normality, but assumes finite variance as well as covariance - properties which were assumed for our data sets.n = 1,439). The highest correlation coefficient r was found between xBRS and short-term variability parameters RMSSD . A more precise estimate yields the highest correlation coefficient for RMSSDRATIO , i.e., reversing one time series does not affect the results of xBRS. Moreover, the correlation coefficient between xBRSS1 and RMSSDRATIO was equally high with r = 0.94, p < 0.001. Finally, the correlation coefficient between original xBRS and surrogate xBRSS1 was extremely high with r = 0.99, p < 0.001  between xBRS.001 cf. .S2 and RMSSDHRV was r = 0.84, p < 0.001. Moreover, the correlation coefficient between xBRSS2 and RMSSDRATIO was equally high with r = 0.93, p < 0.001. Finally, the correlation coefficient between the original xBRS and surrogate xBRSS2 again was extremely high with r = 0.97, p < 0.001  the correlation coefficient between xBRS.001 cf. .n = 733) and got similar correlations . We conclude that the comparison of time series with different time bases has no influence on the results of xBRS. xBRS as an estimate for the spontaneous BRS shows a potentially large methodological bias. This contradicts the hypothesis that xBRS at rest quantifies causal relationships between heart rate and blood pressure.To overcome concerns for bias due to the presence of multiple measurements per subjects, we repeated our procedures on a reduced data set with only the first measurement per subject (p < 0.001), showing that measurements at rest only involves certain range baroreflex activation, but not the full capacity of the arterial baroreflex. However, these estimates are, again, exclusively dominated by the heart rate - systolic blood pressure ratio . Moreover, after performing the surrogate analyzes described above, the xBRS estimates do not change between original and surrogate data: The correlation coefficient at rest: xBRS to xBRSS1r = 0.98, to xBRSS2r = 0.96; 3 s (fast) breathing: xBRS to xBRSS1r = 0.98, to xBRSS2r = 0.94; slow respiration: xBRS to xBRSS1r = 0.99, to xBRSS2r = 0.97.In order to investigate whether any causal relationship could be quantified by xBRS under slow breathing conditions, we analyzed the data from the FACE study. In summary, we found that, even under controlled breathing conditions, no causal relationship between beat-to-beat intervals and the systolic blood pressures could be quantified by xBRS.Nevertheless, RATIO which is also based on non-causal interactions.In this paper we test the hypothesis that the xBRS method quantifies the causal interactions of spontaneous BRS from non-invasive, non-interventional measurements at rest. For the surrogate analysis we substituted the systolic blood pressure by its reversed time series and thusly removed their causal relationship. Our analysis showed that xBRS remains unchanged. Therefore, we conclude that xBRS is not able to estimate causal relationship between heart rate and systolic blood pressure. Our results of the surrogate analysis show, that xBRS can be mostly explained by the short-term HRV, quantified by the RMSSD. Minor deviations of this univariate model are adequately explained by the simple bivariate model RMSSDIn contrast, To investigate whether a causal relationship between heart rate and blood pressure exist under controlled breathing conditions, we analyzed the data from the FACE study. We found a clearly significant increase in xBRS and SME under slow breathing conditions compared to rest or fast breathing, showing that the latter ones involve only limited baroreflex activity. However, for all conditions these estimates are exclusively dominated by the heart rate – systolic blood pressure ratio. Moreover, after performing the surrogate analyzes, the xBRS does not vary between original and surrogate data. Thus, even under controlled breathing conditions, no causal relationship between beat-to-beat intervals and the systolic blood pressures could be found.RATIO carries similar vagally mediated information as xBRS. However, we found, under controlled breathing, a potentially large methodological bias in xBRS and SME as estimates for the baroreflex sensitivity. During slow breathing estimates for SME and xBRS are significantly increasing, which clearly shows that measurements at rest are only accompanied by limited baroreflex activity, but not to the full capacity of the arterial baroreflex. Further investigations should focus on additional autonomic testing procedures  to provide a better empirical foundation of non-invasive assessment of the baroreflex sensitivity.In conclusion, we demonstrated for all short measurements, under resting conditions and controlled breathing, that RMSSDThe data that support the finding of this study are fully available to the authors but cannot be shared publicly due to risk of violating privacy. Requests to access results datasets should be directed to NW.The studies involving human participants were reviewed and approved by the University of Leipzig Medical Center (357/17-ek). The patients/participants provided their written informed consent to participate in this study.NW, AG, KB, JKr, and JKu contributed conception and design of the study. NW, HM, and HS organized the database. AG performed the statistical analysis. NW wrote the first draft of the manuscript. All authors contributed to manuscript revision, read and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


High blood pressure (BP) is a key modifiable determinant of cardiovascular disease and a likely determinant of other adverse health outcomes. While socioeconomic inequalities in BP are well documented, it remains unclear (1) how these inequalities have changed across time, given improvements over time in the detection and treatment of high BP (hypertension); (2) whether BP inequalities are present below and above hypertension treatment thresholds; and (3) whether socioeconomic position (SEP) across life has cumulative effects on BP. We sought to address these gaps using evidence from two complementary sources: birth cohort and repeated cross-sectional datasets.We used three British birth cohort studies—born in 1946, 1958, and 1970—with BP measured at 43–46 years , and 21 repeated cross-sectional datasets—the Health Survey for England (HSE), with BP measured among adults aged ≥ 25 years (1994–2016). Adult education attainment was used as an indicator of SEP in both datasets; childhood father’s social class was used as an alternative indicator of (early life) SEP in cohorts. Adjusting for the expected average effects of antihypertensive medication use, we used linear regression to quantify SEP differences in mean systolic BP (SBP), and quantile regression to investigate whether inequalities differed across SBP distributions—below and above hypertension treatment thresholds.In both datasets, lower educational attainment was associated with higher SBP, with similar absolute magnitudes of inequality across the studied period. Differences in SBP by education  based on HSE data were 3.0 mmHg  in 1994 and 4.3 mmHg  in 2016. Findings were similar for diastolic BP (DBP) and survey-defined hypertension. Inequalities were found across the SBP distribution in both datasets—below and above the hypertension threshold—yet were larger at the upper tail; in HSE, median SBP differences were 2.8 mmHg  yet 5.6 mmHg  at the 90th quantile. Adjustment for antihypertensive medication use had little impact on the magnitude of inequalities; in contrast, associations were largely attenuated after adjustment for body mass index. Finally, cohort data suggested that disadvantage in early and adult life had cumulative independent associations with BP: cohort-pooled differences in SBP were 5.0 mmHg  in a score combining early life social class and own education, yet were 3.4 mmHg  for education alone.Socioeconomic inequalities in BP have persisted from 1989 to 2016 in Britain/England, despite improved detection and treatment of high BP. To achieve future reductions in BP inequalities, policies addressing the wider structural determinants of high BP levels are likely required, particularly those curtailing the obesogenic environment—targeting detection and treatment alone is unlikely to be sufficient. High blood pressure (BP) is a key modifiable determinant of cardiovascular disease, with higher risk continuing across its distribution beyond hypertension treatment thresholds . CardiovFirst, it is unclear how associations between SEP and BP have changed across time—and as such whether previous policies have effectively reduced such inequalities. In the UK and other high-income countries, average BP levels have declined from the 1970s onwards —a changeSecond, there are uncertainties regarding the life course nature of inequalities in BP—that is, when in life exposure to disadvantaged SEP impacts on adult BP outcomes. Existing studies have suggested that there are cumulative effects of disadvantaged SEP across life on higher BP (i.e. that there are independent effects of exposure to disadvantage in both child and adult life) , while oFinally, most existing studies have documented SEP differences in average levels of BP (via linear regression) or differences in the binary outcome of hypertension (via logistic regression) , with noStudies of BP inequalities have used different data sources separately—such as repeated cross-sectional  or singlConsistent with a fundamental cause model of health inequality , we hypoWe used two data sources: (1) three birth cohort studies and (2) 21 repeated cross-sectional studies. For each, participants gave verbal and/or written consent to be interviewed, to be visited by a nurse, and to have BP measurements taken during a home visit. Research ethics approval was obtained from relevant committees.N = 18,657: 1946c = 3186, 1958c = 8610, and 1970c = 6861. A flowchart summarising derivation of the analytical sample sizes is shown in Additional file n = 10 datasets; analyses using imputed data are presented) [Each cohort was designed to be nationally representative when initiated in 1946  .Trained nurses measured resting BP using standardised protocols via sphygmomanometers, following a rest time of 5 min. Specifically, in 1946c, BP was measured twice using the Hawksley random zero sphygmomanometer in the right arm; in 1958c, three times using an Omron 705CP BP monitor in the left arm; and in 1970c, three times using an Omron HEM 907 BP monitor in the right arm. To account for differences in device, as Omron devices provide higher estimates than sphygmomanometers, the 1946c readings were converted to automated Omron readings via a previously derived formulae . Pregnann = 129,118 non-pregnant adults aged 25 years and over with valid BP, medication, and education data; 25 was chosen as the lower age limit to avoid bias in the classification of highest educational attainment (see below). This represented 65% of all adult participants. Starting from 2003, weights have been created to minimise bias from non-response; the relevant weights for analysing BP data were therefore used from 2003 onwards.The Health Survey for England (HSE) is a cross-sectional, general population survey of individuals living in private households, with a new sample each year randomly selected by address . Data coBP was measured using standardised protocols with the use of Dinamap 8100 monitors before 2003, and Omron HEM 907 from 2003 onwards [Given evidence in a recent meta-analysis for the particular relevance of education for social gradients in BP , and eviIn addition to education, a comparable indicator of early life (childhood) SEP was used in analyses of birth cohort data. This was measured by father’s social class at age 4 in 1946c (occupation at birth was not used to avoid WWII-related misclassification), and at birth in 1958c and 1970c. Data at 10/11 years was used if missing at the earlier age. The Registrar General’s Social Class Scale was used with categories as follows—I , II , IIIN , IIIM , IV (partly skilled), and V (unskilled) occupations. To examine cumulative associations (see below), the ridit scores for social class at childhood and own education were combined into a single score and re-scaled.The analytical sample size was 147,775—those with BP outcomes at age 43–46 years (cohorts) or 25 years and over (HSE). The primary outcome for our study chosen a priori was the continuous level of systolic BP (SBP). In addition, analyses were repeated for two secondary outcomes: diastolic BP (DBP) and the binary outcome of survey-defined hypertension  and 5 mmHg (DBP) to the observed BP values among those on treatment to approximate “underlying” BP  ; this  as well as separately by birth cohort/survey year. To provide single quantifications of inequalities in a metric recommended for use in national health inequality statistics , the SEPNo adjustment was made in the birth cohort datasets as the age differences were small and were co-linear with birth year. Our regression models were also gender-adjusted, since gender differences in SEP and BP associations were not anticipated a priori. In the birth cohorts, childhood father’s social class was used as an additional indicator of SEP, and additional adjustment for other SEP indicators was made to examine the life course nature of inequalities in BP (see below). Investigation of change across time in the SEP and BP associations was performed by comparing the magnitude  of the birth cohort and survey-year specific estimates.To examine whether SEP across life had cumulative associations with outcomes, analyses in birth cohorts were conducted before and after mutual adjustment for childhood SEP , own education, and own social class at 43/46 years; mutual independence of association after adjustment provides evidence for a cumulative association. In further analyses, we used the combined score for father’s social class and own education in the regression models: a larger effect size for the combined score versus either in isolation also suggests a cumulative association.To examine if the magnitude of inequalities differed across the BP distributions, conditional quantile regression was used . QuantilTo examine how the adjustment for use of antihypertensive medication affected the direction and/or magnitude of inequalities in BP, associations between education and BP-lowering medication use were analysed using linear probability models, before and after adjustment for SBP (to indicate treatment need). Main analyses were repeated without adjustment for use of BP-lowering medication in order to estimate inequalities in observed rather than “underlying” BP.To examine the extent to which BMI contributes to BP inequalities (e.g. by attenuating the SEP-BP associations through likely mediation), associations between SEP and SBP outcomes were estimated before and after adjustment for BMI. BMI (weight in kilogrammes divided by height in metres squared) was ascertained at the same age as BP measures—it was calculated using height and weight measures obtained by trained interviewers using standardised protocols, as described elsewhere , 17.To examine the robustness of associations of early life SEP with BP—to a different parental respondent and different dimension of disadvantage—maternal educational status was used instead of father’s social class. This was measured via a binary indicator of whether the participant's mother had left formal education at the mandatory leaving age . To examine whether differences in missing outcome data may have biased cross birth-cohort study estimates, analyses were repeated using multiple imputation to additionally impute BP outcomes in the eligible target population . Gender-specific analyses were conducted to examine if any change over time in BP inequalities differed by gender. Likewise, age-specific analyses  using the HSE datasets were conducted to examine if age modified the magnitude of inequalities.Comparing 2016 with previous years, both cohort and HSE datasets indicated increased higher educational attainment, more prevalent use of BP-lowering medication, and lower mean SBP and DBP —the education-related (SII) difference in antihypertensive medication use after adjustment for SBP was 3.8  percentage points in a cohort-pooled model and 4.6  in HSE  differences in SBP were 3.4 mmHg  before and 1.8 mmHg  after adjustment for BMI—an attenuation in the SII estimate of almost 50% , and 5.6 mmHg  in a score combining maternal and own education. Findings were also similar when imputing cohort SBP data (data available upon request), and when conducted separately in men and women . In contrast, associations were markedly attenuated (~ 50%) upon adjustment for BMI. Finally, our analysis of birth cohort data suggests evidence for persisting cumulative associations of more disadvantaged SEP across life on these outcomes.Our findings of persistent inequalities in BP extend prior analyses of area-based SEP differences in high BP using HSE data (1994–2008) , and stuOur findings also add to evidence from other countries—many of which, as in the UK, have also experienced declining average BP levels and increases in higher education attainment. Such evidence is typically derived from repeated cross-sectional studies investigating inequalities in the binary outcome of hypertension  , as wellWhile there is evidence (from multiple study designs) that the links between lower SEP and higher BP are causal in nature , bivariaWe found that absolute inequalities in SBP were largely attenuated after adjustment for BMI in our models. However, as BP and BMI were measured contemporaneously, our findings do not provide strong evidence for the temporal direction of such mediation. While similar findings have been found in longitudinal analyses which adjust for BMI , formal Strengths of this study include the use of multiple comparable nationally representative datasets with complementary advantages. Our co-ordinated analyses of these enabled the investigation of long-run trends in SEP inequalities in BP, the incorporation of data on BP-lowering medication, and the use of multiple indicators of SEP collected in both early and adult life. The use of a single analytical framework across the 1946c and 1958c, and additionally including the 1970c, improved the available statistical power and generalisability of our investigation of the life course nature of BP inequalities. Finally, our use of quantile regression enabled us to move beyond a focus on average levels or binary outcomes to identify that such inequalities were driven by differences at the upper tail of the BP distributions. While we focused on absolute differences in BP inequality, it should be acknowledged that interpretation of trends may differ if analysed in relative terms; specifically, since average BP levels lowered across time , we were unable to fully exclude the potential that findings, and thus inferences regarding change in the SEP and BP association across time, and its attenuation after adjustment for BMI, are biased due to unobserved predictors of missing data or unobserved methodological differences between the studies. A further limitation is that the study samples were largely White; we therefore lacked power to investigate whether inequalities and their change across time are modified by ethnicity. While multiple indicators of SEP were utilised in our birth cohort analyses, we were unable to investigate unmeasured aspects of socioeconomic circumstances which may be particularly important—such as income-related food insecurity or wealth. We accounted for the expected average effects of antihypertensive medication use on BP levels by adding a constant BP value to those on treatment; while such an adjustment has been found to reduce bias in population-level estimates of exposure-BP associations , 51, it From 1989 to 2016 in Britain/England, socioeconomic inequalities in BP appear to have persisted in absolute terms, with additive associations of early life social class and own education. Indeed, studies examining inequalities in BP solely using education as a marker for SEP are likely to underestimate lifetime inequalities in BP outcomes. While our evidence is descriptive in nature, our findings suggest that prior strategies of reducing socioeconomic inequalities in these outcomes through wider use of BP-lowering treatments have been insufficiently effective. Alternative strategies, targeting the wider structural determinants of high BP are likely required, such as those which target the obesogenic environment.Additional file 1: Fig. S1. Flow diagram showing derivation of the analytical sample size: top panel (birth cohort studies), below panel . Fig. S2. Education-related difference in mean diastolic blood pressure  and hypertension prevalence  in midlife  and across adulthood . Fig. S3. Education-related differences in blood pressure lowering medication use (%) in midlife  and across adulthood . Fig. S4. Socioeconomic position across life and mean difference in systolic blood pressure (mmHg) in midlife  and across adulthood ; without adjusting for blood pressure-lowering treatment (i.e. observed rather than underlying BP). Fig. S5. Socioeconomic position and mean difference in systolic blood pressure (mmHg) in midlife  and across adulthood —before and after adjustment for body mass index (BMI). Fig. S6. Early life socioeconomic position and mean difference in systolic blood pressure (mmHg) in midlife  and across adulthood ; analyses stratified by gender. Fig. S7. Education-related difference in mean systolic blood pressure (mmHg) in those aged 25-54 years (left panel) or 55 years and older (right panel); data from repeated cross-sectional data.


Objective: There is increasing evidence that high blood pressure (BP) levels and BP variability (BPV) over 24 h or longer are associated with poor clinical outcomes in patients with intracerebral hemorrhage (ICH). The objective of this study was to examine the association between different beat-to-beat BP parameters and in-hospital outcomes.Methods: Patients with a diagnosis of acute spontaneous ICH were recruited consecutively and prospectively between September 2018 and January 2019. Beat-to-beat recordings were measured non-invasively for 5 min within the first 72 h after the onset of symptoms. BPV was analyzed by standard deviation (SD), coefficient of variation (CV), average real variability (ARV), and variation independent of mean (VIM). Outcome was assessed at discharge using the modified Rankin Scale (mRS) score. Multivariate logistic regression analysis was used to assess the association between BP levels, BPV, and clinical outcomes.Results: A total of 66 patients were included, of whom 34 had poor outcomes . Patients with poor outcomes had significantly higher National Institute of Health Stroke Scale scores , a larger ICH volume , and an increased systolic BP (SBP) -CV  and diastolic BP (DBP) -CV . After adjustment for major covariates, multivariate logistic regression analysis revealed that SBP-CV was independently associated with an increased risk of poor in-hospital outcomes . The receiver operating characteristic area for SBP-CV in predicting poor in-hospital outcome was 0.827 , and the best cutoff point was 3.551 .Conclusion: A higher beat-to-beat BPV in the first 72 h of admission was associated with unfavorable in-hospital outcomes in patients with ICH. The stabilization of BPV during the acute phase may be a therapeutic target; this could be tested in future clinical trials. Spontaneous intracerebral hemorrhage (ICH) is a major cause of disability and mortality among patients with different types of stroke, and few effective treatment options are available /2 method, where a is the greatest hemorrhage diameter by CT, b is the diameter 90° to a, and c is the approximate number of CT slices with hemorrhage multiplied by the slice thickness  of the brain. Demographic data (age and sex), medical history, and vascular risk factors, including alcohol consumption, cigarette smoking, hypertension, diabetes mellitus, previous coronary heart disease, ischemic stroke, and ICH, were documented. Antihypertensive and diabetic medications were defined as taking any drugs intravenously or orally before or after admission. The initial stroke severity was assessed using the National Institute of Health Stroke Scale (NIHSS) upon admission to the stroke unit. The primary locations of ICH were classified into the basal ganglia, thalamic, or lobar areas. The presence of intraventricular hemorrhage was also recorded. The ICH volume was calculated from the first CT scan using the  ≥2; patients who were unable to cooperate sufficiently to complete the beat-to-beat monitoring .This study was approved by the Ethics Review Committee of the First Hospital of Jilin University, and written informed consent was obtained from all participants or their direct relatives.Admission BP was measured at the brachial artery using an automatic BP monitor . Beat-to-beat recordings of SBP (in mmHg) and DBP (in mmHg) were measured noninvasively for 5 min within the first 72 h after the onset of symptoms using a servo-controlled plethysmograph  on the middle finger in a specific, quiet examination room with a controlled temperature ranging from 20 to 24°C. Because BPV was heterogeneous according to different measuring time points, all beat-to-beat BP was recorded 9:00 to 10:00 AM. Before the examination, all participants were asked to relax in a supine position for 10 min in the room.BPV on beat-to-beat monitoring was calculated for 5 min. Continuous recordings of beat-to-beat information were processed by MATLAB  using scripts developed by the research team. Ectopic beats and artifacts were automatically detected, visually reviewed, and removed by linear interpolation  to 6 (death). We defined mRS scores ≥3 as a poor outcome and mRS scores ≤2 as a favorable outcome.t-test or Mann–Whitney test for continuous variables, and the chi-squared test or Fisher's exact test for categorical variables. The variables with a univariate between-group comparison with a p < 0.1 were eligible for inclusion in the multivariate logistic regression models as the major covariates. Multivariate logistic analysis was conducted to explore the association between BPV and clinical outcome, and odds ratios (ORs) and 95% confidence intervals (CIs) were used to evaluate the risk of poor outcomes. A receiver operating characteristic (ROC) curve of the statistically significant variables associated with poor in-hospital outcome was drawn. All statistical tests were two-tailed, and p < 0.05 was considered statistically significant.Statistical Program for Social Sciences version 22.0  was used for statistical analysis. The distribution of continuous variables was assessed using a one-sample Kolmogorov-Smirnov test. Normally distributed data are presented as the means and SD, and non-normally distributed data are presented as the median and interquartile range. The clinical characteristics and BPV parameters used in this study were dichotomized into favorable and poor outcome groups. Intergroup differences were compared using the Student's Altogether, 66 patients with acute ICH were enrolled in the study, including 34 (51.5%) with poor outcomes (mRS score 3–6) and 32 (48.5%) with favorable outcomes (mRS score 0–2) at discharge. The overall characteristics of participants are shown in p < 0.001) and ICH volume  between the two groups. As for BP magnitude, the poor outcome group had a tendency toward higher admission BP and mean BP than the good outcome group. For beat-to-beat BPV, poor outcome patients had an increased SBP-CV  and DBP-CV  and the other parameters also tended to be higher, although this was not significant.A comparison of the patient characteristics between the favorable and poor groups are presented in Multivariate logistic regression analysis was performed to analyze the risk of poor in-hospital outcomes. The independent variables included in the analysis were admission NIHSS score, ICH volume, and beat-to-beat BPV . The results showed that admission NIHSS score and SBP-CV were significant independent predictors of a poor in-hospital outcome in patients with spontaneous supratentorial ICH. The ORs, 95% CIs, and p-values are presented in p < 0.001), and the best cutoff point was 3.551 . The accuracy (Youden's index), positive predictive value and negative predictive value were 0.51, 73.68 and 78.57%, respectively. The area under the ROC curve of DBP-CV was 0.679 , and the best cutoff point was 3.173 . The accuracy, positive predictive value and negative predictive value were 0.32, 63.63 and 72.73%, respectively.The ROC curve of the SBP-CV and DBP-CV is shown in This study investigated the effect of various parameters of beat-to-beat BP on the clinical outcome in patients with acute spontaneous supratentorial ICH. We demonstrated that SBP-CV and DBP-CV were significantly increased in ICH patients with poor outcomes. SBP-CV was an independent risk factor for a poor in-hospital outcome; the greater the variability, the poorer the outcome, with this relationship holding true even when admission and mean beat-to-beat BP levels were taken into consideration.To the best of our knowledge, this is the first study to evaluate the association between beat-to-beat BP parameters and in-hospital outcomes and to compare the potential prognostic differences between the various parameters of beat-to-beat BP in patients with acute spontaneous supratentorial ICH. BPV is primarily divided into the three following categories: long-term (days to months), short-term (minutes to hours), and very short-term (beat-to-beat) BPV  in the first 72 h of admission was associated with unfavorable in-hospital outcomes in patients with acute spontaneous supratentorial ICH. A greater variability was associated with a worse outcome, and this relationship remained true even when admission and mean BP levels were taken into consideration. The stabilization of BPV during the acute phase may be a therapeutic target for future clinical trials.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by the Human and Research Ethics committees of the First Hospital of Jilin University. The patients/participants provided their written informed consent to participate in this study.YY and Z-NG devised the study design and supervised study procedures. YQ, Z-NG, JL, and P-DZ analyzed the data and wrote the manuscript. HR, X-LY, and SQ collected the data. PZ provided significant statistical support. All authors provided critical review, edits, and approval of the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Diabetic kidney disease (DKD) affects approximately one-third of patients with diabetes and taking into consideration the high cardiovascular risk burden associated to this condition a multifactorial therapeutic approach is traditionally recommended, in which glucose and blood pressure control play a central role. The inhibition of renin–angiotensin–aldosterone RAAS system represent traditionally the cornerstone of DKD. Clinical outcome trials have demonstrated clinical significant benefit in slowing nephropathy progression mainly in the presence of albuminuria. Thus, international guidelines mandate their use in such patients. Given the central role of RAAS activity in the pathogenesis and progression of renal and cardiovascular damage, a more profound inhibition of the system by the use of multiple agents has been proposed in the past, especially in the presence of proteinuria, however clinical trials have failed to confirm the usefulness of this therapeutic approach. Furthermore, whether strict blood pressure control and pharmacologic RAAS inhibition entails a favorable renal outcome in non-albuminuric patients is at present unclear. This aspect is becoming an important issue in the management of DKD since nonalbuminuric DKD is currently the prevailing presenting phenotype. For these reasons it would be advisable that blood pressure management should be tailored in each subject on the basis of the renal phenotype as well as related comorbidities. This article reviews the current literature and discusses potentials and limitation of targeting the RAAS in order to provide the greatest renal protection in DKD. Throughout their lifetime, approximately one-third of patients with diabetes will eventually develop diabetic kidney disease (DKD) . FurtherIn the context of this rather complex and clinically challenging scenario a multifactorial therapeutic approach has traditionally been recommended. As a matter of fact, more than a decade ago, in the Steno-2 study an intensified multifactorial intervention with tight glucose control, the use of renin–angiotensin-aldosterone system (RAAS) blockers, aspirin, and lipid-lowering agents on top of behavior modification had been proved to effectively reduce CV morbidity and mortality over a long-term follow-up in patients with persistent microalbuminuria . NowadayHypertension is a common condition in patients with diabetes and its prevalence in subjects with DKD is significantly higher than in general population and increases gradually according to glomerular filtration rate (GFR) decline, reaching the 90% in ESKD subjects . TherefoAlbuminuria is a known marker of renal damage and has been shown to have a strong cardiovascular and renal predictive power. Furthermore, modifications of urinary albumin excretion under pharmacological treatment might impact CV and renal prognosis independent of blood pressure reduction –11. In tMore recent studies, however, have shown that DKD in both type 1 and type 2 diabetes has an heterogeneous histologic phenotype, with various involvement of glomeruli and the interstitium . On the DCRecent International Guidelines  suggest DKD is a complex disease, wherein various pathological changes including glomerular hypertrophy with progressive mesangial expansion and tubulointerstitial fibrosis are associated with multiple pathophysiological abnormalities such as inappropriate activation of the RAAS at the systemic and tissue level , 23. HypMain clinical trials that have evaluated renal protective effect of RAAS blockade across the renal continuum in DKD are reported in Table Patients with normal albuminuria In diabetic patients without microalbuminuria RAAS blockade has been studied to evaluate the effect on the transition from normoalbuminuria to microalbuminuria. Trials conducted on type 1 diabetic patients, such as Renin-Angiotensin System Study (RASS) [y (RASS)  and Diaby (RASS)  failed ty (RASS) , while iy (RASS)  the 2 ary (RASS)  the use Patients with moderately increased albuminuria As for the transition from microalbuminuria to overt proteinuria in the IRMA-2 (Effect of Irbesartan in the Development of Diabetic Nephropathy in Patients With T2DM) trial [M) trial  irbesartPatients with severely increased albuminuria More solid data support the use of RAAS inhibitors in DKD with overt albuminuria. The Collaborative study group evaluated the impact of captopril versus placebo on CKD progression in patients with type 1 diabetes and proteinuria [teinuria . Despiteteinuria  and IDNTteinuria  trials cTherefore, the use of RAAS blockers has been considered for many years the gold standard therapy to reduce cardiovascular risk and to slow the progression of diabetic nephropathy and previous guidelines recommended the use of RAAS blockers in all patients with diabetes without distinction . HoweverAccordingly, more recently, guidelines do not recommend routine use of RAAS blockers in diabetic subjects unless in the presence of nephropathy with an urinary albumin-to-creatinine ratio greater than 30 mg/g creatinine in order to reduce the risk of progressive kidney disease , 36, 37.Several studies have explored the potential benefit of maximal inhibition of the RAAS by means of high doses monotherapy or combination drug. Dual RAAS blockade is based on the pathophysiological rationale of a more profound inhibition of the RAAS cascade which may counteract the well known “aldosterone escape” phenomenon observed in patients treated with a single agent. However, disappointing results from several mega trials with hard endpoints have subsided the initial enthusiasm on the promising effects of dual RAAS blockade on surrogate outcomes. In fact, the combination of two RAAS blocking drugs did not provide considerable benefit in terms of long term renal protection and was accompanied by higher incidence of acute kidney injury and hyperkaliemia as compared to single-drug therapy –40. It iFinally, mineralocorticoid receptor inhibitors (MRI) such as spironolactone or eplerenone might offer an additional opportunity for RAAS intervention by counteracting the “aldosterone breakthrough” that occurs in a subset of patients on RAAS-inhibiting therapy. Aldosterone is known to affect volume status by the regulating renal sodium reabsorption and exert profibrotic effects through increased production of TGF-beta, reactive oxygen, species, PAI-1 and increased collagen gene expression and synthesis , 42 and,Multiple trials have demonstrated that the use of RAAS blocking drugs can slow progression to ESKD in patients with diabetic nephropathy and proteinuria > 300 mg/day, however single agent RAAS blockade is not sufficient in slowering progression in many patients. In fact, significant residual risk remains in patients with DN and many patients progress to ESKD despite standard recommended care, including optimal control of blood pressure, glycemia and lipids and the use of RAAS blockade , 50. FurGiven the steady increase in the prevalence of diabetes worldwide and the soaring costs related to its management, prevention and treatment of DKD remains an unmet clinical need. Within this context, recently developed therapeutic agents such as sodium-glucose co-transporter-2 inhibitors and glucagone like peptide-1 receptor agonist have shown promising therapeutic potential not only to reduce CV risk but also to slow the progression of kidney disease with beneficial effect on albuminuria as well as on GFR –55. As aBecause of their remarkable antiproteinuric and renoprotective activity, confirmed in many large trials, SGLT2i may soon become, in association with RAASi, the standard of care to prevent DKD and retard its progression.Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease and represent a significant cause of morbidity and mortality worldwide due to the related cardiovascular risk burden.The standard of care for management of DKD over the last three decades has been the control of cardiovascular risk factors and the pharmacologic inhibition of renin–angiotensin–aldosterone system (RAAS).Nowadays, non-albuminuric DKD is the prevailing phenotype. The nephroprotective role of intensive blood pressure control and the use of RAAS inhibitor in these patients is at present unclear.Recent evidence supports a renal protective effect of sodium-glucose cotransporter 2 (SGLT2) inhibitors independent of their hypoglycemic properties.We suggest that co-treatment with RAAS and SGLT2 inhibitors may represent the new era of therapeutic options for DKD.


Higher systolic BP , lower eGFR  and higher urine MCR  were associated with larger areas of CFD. Similar significant associations with systolic BP, eGFR and urine MCR were found with number of CFD. These findings highlight the potential role of choriocapillaris imaging using SS-OCTA as an indicator of systemic microvascular abnormalities secondary to hypertensive disease.We examined the choriocapillaris microvasculature using a non-invasive swept-source optical coherence tomography angiography (SS-OCTA) in 41 healthy controls and 71 hypertensive patients and determined possible correlations with BP and renal parameters. BP levels, serum creatinine and urine microalbumin/creatinine ratio (MCR) specimens were collected. The estimated glomerular filtration rate (eGFR) was calculated based on CKD-EPI Creatinine Equation. The main outcome was choriocapillaris flow deficits (CFD) metrics . The CFD occupied a larger area and were fewer in number in the hypertensive patients with poor BP control (407 ± 10 µm Regardless of the mechanisms that initiate the rise of blood pressure (BP), extensive structural and functional changes in the systemic microvasculature is known to occur in many tissues in patients with hypertension2. One such consequence of hypertension is the reduction in the density of the microvasculature (rarefaction) in various target organs such as the eyes and the kidneys3.Systemic hypertension remains the leading risk factor causing global mortality due to cardiovascular disease10. Recently, the introduction of spectral-domain optical coherence tomography angiography (SD-OCTA) has allowed the assessment of even smaller vessels, the capillaries12. Using SD-OCTA, the rarefaction of retinal capillaries has been reported, and found to be correlated with higher BP and poorer renal function21.The eye has two major circulatory systems: the retinal and choroidal system. Rarefaction has been observed in the retinal circulation and documented from retinal fundus photographs using computer algorithms to measure retinal arteriolar and venular diameter22, it may be susceptible to damage as a result of uncontrolled systemic hypertension. The relationship between choriocapillaris, BP control and systemic vascular risk factors in hypertension has been examined in few studies with mixed conclusions25. These studies, however, had an important limitation; they employed SD-OCT imaging with limited depth resolution, because the instrument’s central wavelength of 840 nm is strongly attenuated by the RPE26. In contrast, swept-source optical coherence tomography angiography (SS-OCTA) has a longer wavelength (~ 1060 nm) and less sensitivity roll-off, allowing for a more detailed view of the choriocapillaris26.Since the choriocapillaris network is composed of a dense network of capillariesThis study imaged the choriocapillaris using SS-OCTA, and specifically determined choriocapillaris flow deficits (CFD) in persons with hypertension with poor and good BP control compared to healthy controls and evaluated possible correlations with BP and renal parameters. We hypothesize that individuals with poorly controlled hypertension and persistent high BP or poor kidney function as a result of microvascular damage will have the most extensive CFD compared to participants with well-controlled hypertension and normal controls.P < 0.05 each).We excluded 71 participants due to eye diseases, diabetes, and poor quality OCTA images and 112 participants were available for analysis, comprising of 41 healthy controls, 53 and 18 hypertensives with well and poor controlled BP, respectively  but a fewer total number of flow deficits  compared to normal controls and well-controlled hypertensives. Figure 2, respectively  and numbers (P = 0.002) of CFD whereas diastolic BP was not associated with CFD (P = 0.226). Figure Systolic BP was also associated with the area (P = 0.003), larger in size  and lesser in numbers  and numbers (P = 0.032) of CFD  showing an impaired flow within the choriocapillaris compared to healthy controls27. Overall, the alterations in CFD as a result of systemic hypertension follows a distinct pattern and is dependent on the systolic BP. In persons with systemic hypertension, particularly those with uncontrolled BP and poorer renal function, alterations occurred in both the choriocapillaris (flow deficits were lower in absolute count and larger in average size) and retinal microvasculature (sparser vessel density)14. Hence, this finding also supports the beneficial role of strict BP control to prevent microvascular damage.We report several noteworthy findings regarding the structural and functional changes at the choriocapillaris microvasculature with systemic hypertension. First, the CFD follows a distinct pattern: in normal physiological state, there are many small flow deficits and in uncontrolled hypertension, a progressive reduction in number of CFD with increasing mean area of the CFD Fig. . Spaide 25. However, these studies have not led to clear answers; while Spaide et al.23 reported greater increase in CFD in the eyes of those with systemic hypertensions, our group24 reported a reduction in CFD with higher BP while another25 did not report a significant relationship between hypertension and normal controls. A critical reason why these studies have not produced consistent results is related to the use of SD-OCT system. In the current study, we used the SS-OCT system which offers two distinct advantages: first, the longer wavelength in the system is less scattered by the RPE; second, SS-OCTA is less susceptible to sensitivity roll-off26. Both these characteristics make SS-OCT technology less prone to low signal in the choriocapillaris region underneath the RPE. In the context of OCTA, areas of low signal can correspond to low blood flow, low OCT signal, or both26. Hence, choriocapillaris imaging using the SD-OCT may be less reliable than SS-OCT.The choriocapillaris network is one of the densest circulations in the human body and researchers have long been interested to examine the effects of systemic hypertension on the highly vascularized choroid. Previous studies have examined the relation between systemic hypertension and CFD using SD-OCTA28, leading to the breakdown of choriocapillaris capillary network, which causes blood flow impairment. Therefore, the higher the BP levels, the greater the choriocapillaris flow impairment. OCTA relies on changes between consecutive retinal B-scans, it will therefore detect flow only above a minimum threshold29. Regions that have flow below the slowest detectable flow would therefore be considered as flow deficits in OCTA29. CFD seen in response to high BP may either represent flow impairment and/or capillary dropout. We argue that reduction of blood velocity within the choriocapillaris seems unlikely because of the very focal changes resulting in increased flow deficits. This would mean localized capillary vasodilatation associated with a localized reduction of blood velocity due to the law of mass conservation and a consequent drop of the decorrelation signal below the lower limit of detection. Rather, these large CFD most likely represent capillary dropout, which is supported by animal studies. Choriocapillaris loss was reported in histologic sections in an aged non-human primate model, which was exacerbated by poorly controlled hypertension30. Furthermore, in the monkey eye’s, basal laminar deposits and hard drusen were present on areas of nonviable choriocapillaris. However, it is difficult to compare our current OCTA human study with the animal study as they only performed an observational assessment of the choriocapillaris using ICGA. This is most likely because the ICGA is unable to provide a detailed visualization of the choriocapillaris, due to the considerably higher background levels of fluorescence arising from the larger underlying choroidal vessels early in the angiogram31.A potential mechanism that contributes to choriocapillaris flow alterations in uncontrolled systemic hypertension is that in persons with chronic elevation of BP, they will develop atherosclerosis over time, where vessels narrow with age27. This suggests that size/numbers of CFD may be a more sensitive indicator of microvascular dysfunction in systemic hypertension than density.The readers may wonder why CFD density did not show any significance if there was a choriocapillaris dropout in those with poorly controlled hypertension. One potential explanation may be that CFD density requires a larger sample size to show significance whereas size/numbers of CFD requires only a small sample size. In early stage of uncontrolled BP, the CFD becomes larger and less numerous . As the BP continues to be poorly controlled, more CFD would appear and this would then have an impact on the density score of CFD. Terheyden et al. too showed that the CFD are larger and less numerous  in patients with acute hypertensive crisis32. We can therefore hypothesize that the presence of large CFD, signifying microvascular rarefaction, may mirror similar alterations in the renal microcirculation.We report changes in the choriocapillaris microvasculature that is associated with kidney function (eGFR and urine MCR levels). The arrangement of the choriocapillaris and kidney glomerular microvasculature have several structural and organizational similarities that support the concept that choriocapillaris microvascular network might reflect changes in kidney microvasculature associated with renal disease33. Our present study had some limitations. First, the relatively small sample size may limit the power for accounting for confounding parameters. Different types of BP medications may exert differing pharmacological effect on the choriocapillaris flow characteristics. However, there was no difference in the classes of BP-lowering drugs with BP control (data not shown). Second, the cross-sectional study design; SS-OCTA was only recently introduced and follow-up study is ongoing. Third, we did not collect ocular factors such as axial length and intraocular pressure measurements34. It has been shown previously that myopic eyes tended to have more flow deficits35. Nevertheless, our participants were free from any form of eye diseases such as pathological myopia.Strengths of this study included the use of ambulatory BP monitoring for the hypertensives as well as the availability of eGFR and urine MCR for objective measurements of renal function. We also excluded persons with diabetes, which is a major confounderThe ocular circulation provides a window to study the early impact of hypertension and BP changes. While the retinal vasculature has been extensively studied in the past few decades, the understanding of changes in the choroidal vasculature in hypertension has been limited, largely because it has been technically challenging to image the choriocapillaris network till the advent of SS-OCTA. Our study using SS-OCTA demonstrates clearly a relationship between choriocapillaris microvascular dysfunction with BP, eGFR and urine MCR in participants with and without systemic hypertension. Measurement of choriocapillaris microvasculature, using the SS-OCTA, is a unique non-invasive tool that has the potential to study early systemic microvascular dysfunction. Further studies are warranted to evaluate the efficacy of choriocapillaris imaging to be a novel imaging tool in the detection and monitoring of early systemic microvascular complications associated with hypertension and implications of strict BP control in reducing the risk of disease progression in target organs such as the eyes and the kidneys.36. The aim of REMODEL was to examine the role of cardiovascular magnetic resonance in patients with hypertension. Briefly, participants with essential hypertension on antihypertensive medications, aged ≥ 18 years, were recruited from a tertiary cardiac centre and primary care clinics in Singapore, from 2018 and 2019. Participants with secondary causes of hypertension, any on-going unstable medical conditions, previously diagnosed significant coronary artery disease, strokes, atrial fibrillation, women who are pregnant or breast feeding, individuals with impaired renal function of estimated glomerular filtration rate (eGFR) < 30 mL/min/1.73m2 and metallic implant were excluded.We conducted a case control study, detailed in Supplementary Figure 38. Briefly, PIONEER is a population-based study of Singaporeans aged ≥ 60 years with participants selected from a computer-generated list stratified by age and ethnicity, with 50% Chinese, 25% Malays, and 25% Indians.Normal controls were selected from a population-based study, the PopulatION HEalth and Eye Disease pRofile in Elderly Singaporeans (PIONEER) program39. Ocular conditions that might affect OCTA scans were further excluded, such as persons with glaucoma/-suspect/self-reported glaucoma40, retinopathies 41, and age-related macular degeneration42.Normal controls were defined as those free from systemic hypertension or/and diabetes) and ocular conditions. Systemic hypertension was defined as systolic BP ≥ 140 mmHg, and/or diastolic BP ≥ 90 mmHg, and/or self-reported physician diagnosed hypertension, and/or history of antihypertensive medicationAll studies were approved by the SingHealth Centralized Institutional Review Board and conducted in accordance to the Declaration of Helsinki. Written Informed consent was obtained from all participants.A questionnaire was used to collect demographic data, and medical history  and medication use. Twenty-four hour or ambulatory monitoring was performed on the hypertensive cases whereas a digital automatic BP monitor was performed on the normal controls. Hypertensive persons were stratified into two groups: well-controlled ambulatory BP defined as systolic BP < 140 mmHg and/or diastolic BP < 90 mmHg and poorly controlled BP defined as systolic BP ≥ 140 mmHg and/or diastolic BP ≥ 90 mmHg. For the normal controls, BP was measured using a digital automatic BP monitor , after participants were seated for at least five minutes. Participants’ height was measured in centimeters using a wall-mounted measuring tape, and weight was measured in kilograms using a digital scale . Body mass index (BMI) was calculated as body weight (in kilograms) divided by body height (in meters) squared.2) was calculated from plasma creatinine using the recently developed Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation43. Urine MCR was measured using immunoassay and normal MCR range was 0.2–3.3 mg/mmol creatinine, 3.4–33/9 mg/mmol creatinine implied microalbuminuria and values > 33.9 mg/mmol creatinine implied clinical albuminuria.Blood and mid-stream urine samples were collected simultaneously for analysis of serum creatinine and urine microalbumin/creatinine ratio (MCR) respectively. Bio-specimens were processed in an accredited laboratory at the Singapore General Hospital. eGFR . Participants with eye diseases  were excluded from the study.2 macular centered imaging using the SS-OCTA 44. The OCTA machine provided a signal strength index, ranging from 0 to 10, where only images with a scan quality of 8 and above were accepted. A trained grader reviewed the quality of OCTA scans. Poor quality scans were excluded from the analysis if one of the following criteria were met: (1) poor clarity images; (2) local weak signal caused by artifacts such as floaters; (3) residual motion artifacts visible as irregular vessel patterns on the en face angiogram and (4) scans with segmentation errors38.The SS-OCTA allows a high-resolution 3-dimensional visualization of perfused microvasculature in a non-invasive manner and characterizes vascular information at the retinal and choriocapillaris layers  to automatically count the number of flow deficits and measured the size of each flow deficit. The total number of flow deficits were counted, and average sizes computed as the total sizes of flow deficits divide by the total number. Flow deficits metrics showed high inter-session repeatability in normal individuals: in terms of Pearson’s R of 0.96 and intraclass correlation coefficients of 0.98 44.Images were exported from the built-in review software  and MATLAB  was used to measure CFD automatically using previously published imaging-processing algorithm 24. Chi-square test or Fisher’s exact test were used for categorical variables24. Multivariable linear regression analysis with generalized estimating equations was performed to assess the effect of systemic factors (independent variables) on each CFD metric variable (dependent variable), adjusting for age, gender, race and body mass index and accounting for inter-eye correlation. For urine MCR, we additionally adjusted for systolic BP because individuals with higher systolic BP also had higher urine MCR, and the effect of urine MCR on CFD might be confounded by the high systolic BP. For comparison between group, healthy controls were used as the reference group. Data were analyzed with statistical software .Primary outcome was CFD metrics . The Shapiro–Wilk test was used to assess the normality of the distribution of the continuous variables. To compare continuous variables between groups, one-way analysis of variance (ANOVA) test was performed for normally distributed variables, whereas the Kruskal–Wallis test was used for non-normally distributed variablesSupplementary Information


To evaluate the prevalence of albuminuria and compare its risk factors in diabetic and hypertensive patients.  This was an observational, cross-sectional, multicenter registry across China. Consecutive patients were registered with the Cardiology and Endocrine departments in 40 centers. Clinical characteristics were collected, and urinary albumin-to-creatinine ratio (UACR) was measured using the immunochemical method. P < 0.001) and in subjects with concomitant hypertension and diabetes .  Of the 2510 patients enrolled in the study, 1515 underwent UACR testing and were included in the present analysis. The prevalence of microalbuminuria was 13.0% and 16.1% while that of macroalbuminuria was 2.5% and 5.0%, in the Cardiology and Endocrinology departments, respectively. HbA1c and systolic blood pressure (SBP) were independent risk factors for albuminuria. The relationship of blood pressure (BP) and HbA1c with albuminuria was continuous and graded. Compared with the reference level of SBP 130–139 mm Hg, an SBP level of <130 mmHg was significantly associated with a lower risk of albuminuria in all subjects (OR = 0.60; 95% CI: 0.40–0.89;  In China, nearly one-fifth of patients in the Cardiology and Endocrinology departments have albuminuria although ACEI/ARB were widely used. More effective therapy is needed in this population. Albuminuria, both microalbuminuria and microalbuminuria, are important indexes in clinical practice. First, in diabetes management, microalbuminuria is one of the earliest evidences of diabetic nephropathy . BesidesTherefore, screening for albuminuria is of great importance in the Endocrinology and Cardiology departments. According to the Prevention of Renal and Vascular End-stage Disease (PREVEND) study, which involved 40,856 inhabitants of Groningen, the Netherlands .In the hypertensive population, two large-scale population surveys, the NHANES III  and PREVSo, the first aim of our study was to evaluate the prevalence of albuminuria, especially microalbuminuria in a real-world design, multicenter registry in China, in patients with diabetes as well as in patients with hypertension.In addition, previous studies have evaluated many influencing factors for albuminuria, such as age, gender, body mass index, a high-protein meal, vigorous exercise, smoking status, BP, blood glucose, hypercholesterolemia, genetic background, and metabolic syndrome –16. AmonAll the patients included in this study were from the ATTEND study, which was published previously . To be bBaseline characteristics such as body weight and body height were measured in all subjects. Body mass index (BMI) was calculated as the body weight in kilograms divided by the body height in meters squared. BP was measured using a validated Omron HEM-7201 automatic oscillometric BP monitor  at the first and second clinic visits. At both visits, three BP readings were obtained in the seated position after the patients had rested for at least 5 min. These six readings were averaged for statistical analysis.Fasting plasma glucose (FPG) levels were measured using the glucose oxidase method. HbA1c was measured using a high-performance liquid chromatography . The urinary routine test was performed on fresh urine samples, and the UACR was measured using the immunochemical method as described in the ATTEND study .t-test was used to compare continuous normally distributed variables between groups. A logistic regression analysis was used to calculate ORs, 95% CIs, and the corresponding P values. All statistical tests were performed using SAS software . A P value <0.05 was considered statistically significant.The basic statistics on study parameters were presented by number (%) and mean (SD). Student's α-receptor blocker (0.4%), antihypertensive drugs with central action (0.3%), and other antihypertensive drugs including traditional Chinese medicine (1.5%). Among them, 894 (69.3%) patients in the Cardiology department and 621 (53.2%) patients in the Endocrinology department underwent UACR testing and were included in the present analysis. The prevalence of microalbuminuria was 13.0% (116 patients) and 16.1% (100 patients), while the prevalence of macroalbuminuria was 2.5% (22 patients) and 5.0% (31 patients) in the Cardiology and Endocrinology departments, respectively.A total of 2510 patients were enrolled in the ATTEND study. The exact type and percentages of antihypertensive treatments included angiotensin II receptor blockers (ARB) (37.8%), angiotensin enzyme inhibitor (ACEI) (19.6%), beta-adrenergic receptor blocker (29.3%), diuretics (9.0%), calcium channel blockers (CCB) (55.8%), compound antihypertensive drug (7.2%), n = 1246), patients with microalbuminuria , and patients with macroalbuminuria . The clinical characteristics of these subjects in the three groups are shown in Based on their test results, all the subjects were divided into three groups: patients with normal albuminuria . The relationship of BP and HbA1c with albuminuria is relatively continuous and graded. For example, in all subjects with concomitant hypertension and diabetes, HbA1c increased by 0.5%, the risk of albuminuria increased by 14% (P < 0.001), SBP increased by 5 mmHg, and the risk of albuminuria increased by 20% (P < 0.001).A multivariate logistic analysis of albuminuria rate showed that HbA1c and SBP were independent risk factors for albuminuria in all subjects as shown in We then analyzed the relationship between albuminuria rate and SBP and HbA1c by performing a univariate logistic analysis. A reference level of BP 130–140 mmHg was used, and the risk of albuminuria in the low-BP group (<130 mmHg) and the high-BP group (≥140 mmHg) was evaluated. Similarly, a reference level of HbA1c 6.5–7.0% and the risk of albuminuria in the low-HbA1c group (<6.5%) and the high-HbA1c group (≥7%) was analyzed. The risk of albuminuria in the BP ≥ 140 mmHg group reached 2.17 times as compared with the reference. The risk of albuminuria in the HbA1c ≥ 7% group was the highest and reached 3.17 times compared with reference as shown in In a stratified analysis, we analyzed the prevalence of albuminuria in relation to SBP and HbA1c in all the participants as well as in the Cardiology and Endocrinology departments separately. The results are presented in In this real-world, multicenter registry study in China, we found that  the prevIn this study, the prevalence of microalbuminuria in hypertensive patients was found to be 13.0%, similar to the two large-scale population surveys, namely, the NHANES III study 16%)  and the %  and thP < 0.001), SBP increased by 5 mmHg, and the risk of albuminuria increased by 20% (P < 0.001). More importantly, we also found that compared with the reference level of SBP 130–140 mmHg, an alternative level of less than 130 mmHg could significantly lower the risk of albuminuria by 40%  in all subjects and lower the risk of albuminuria by 52%  in subjects with concomitant hypertension and diabetes. This finding added more evidences for the new definition of high BP (≥130/80 mmHg) in 2017 High Blood Pressure Clinical Practice Guideline [Our findings that HbA1c and SBP were independent risk factors for albuminuria were in line with the results of previous studies , 17, 21.uideline .P < 0.001) [P < 0.001) [We also compared risk factors for albuminuria in a population of hypertensive patients with hyperglycemic patients. In the Endocrinology department, the influence of SBP on albuminuria was more than that in the Cardiology department. SBP in the Endocrinology department was not so high, but all patients had a history of significant hyperglycemia  . This hi< 0.001) . HoweverTo conclude, in China, nearly one-fifth of patients in the Cardiology and Endocrinology departments have albuminuria although ACEI/ARB were widely used. HbA1c and SBP were independent risk factors for albuminuria, and the relationship of BP and HbA1c with albuminuria is relatively continuous and graded. More effective therapy is needed in patients with albuminuria.