Development of complications in type 1 diabetes patients can be reduced by modifying risk factors. We used a cross-sectional cohort of 1646 patients diagnosed with type 1 diabetes (T1D) to develop a clinical risk score for diabetic peripheral neuropathy (DPN), autonomic neuropathy (AN), retinopathy (DR), and nephropathy (DN). Of these patients, 199 (12.1%) had DPN, 63 (3.8%) had AN, 244 (14.9%) had DR, and 88 (5.4%) had DN. We selected five variables to include in each of the four microvascular complications risk models: age, age of T1D diagnosis, duration of T1D, and average systolic blood pressure and HbA1C over the last three clinic visits. These variables were selected for their strong evidence of association with diabetic complications in the literature and because they are modifiable risk factors. We found the optimism-corrected R2 and Harrell’s C statistic were 0.39 and 0.87 for DPN, 0.24 and 0.86 for AN, 0.49 and 0.91 for DR, and 0.22 and 0.83 for DN, respectively. This tool was built to help inform patients of their current risk of microvascular complications and to motivate patients to control their HbA1c and systolic blood pressure in order to reduce their risk of these complications. The hyperglycemic state present in type 1 diabetes is associated with both micro- and macrovascular complications . MicrovaMicrovascular complications are major predictors of macrovascular complications, such as myocardial infarctions and cerebrovascular accidents, which are the leading cause of death in the USA . The mosOne of the most important modifiable risk factors is glycemic control. Multiple randomized control trials have demonstrated that tight glycemic control is associated with decreased risk of micro- and macrovascular complications ,9. OtherOnce modifiable risk factors are identified, clinicians can educate patients on how to reduce these risk factors through lifestyle changes and medical management. Informing patients of their personal risks for developing diabetic complications helps patients set a realistic understanding of these risks and allows them to monitor how their lifestyle and/or medication changes have reduced their risks of diabetic complications . ParticuRisk scores have been reported in the past for complications of type 1 ,17,18,19These risk scores have not been implemented in clinics due to several factors. First, these scores use complex statistical approaches that are not easily accessible for patients and clinicians to use for risk calculations. Second, the scores for each complication use different clinical variables, making it more difficult for patients to collect all of the data necessary for computing clinical risk for each complication. Third, these scores do not show patients how changing their modifiable risk factors would change their risk of developing diabetic complications. Scores should be easily accessible and easy to use so that patients can use them to monitor their progress . LearninWith the increasing incidence and survival of patients with T1D ,23,24, tIndividuals diagnosed with T1D who attended the Augusta University (AU) Medical Center and/or endocrinology clinics in Augusta and Atlanta areas of Georgia between 2002 and 2010 were recruited into the Phenome and Genome of Diabetes Autoimmunity (PAGODA) study ,26. For Continuous data were presented as median and interquartile range, differences between the groups were tested by Kruskall–Wallis test. Chi-square test was used for count data. The potential differences between T1D patients with and without each complication  were initially examined using univariate logistic regression. We selected five variables that showed consistent associations with diabetic complications across multiple studies and were modifiable through lifestyle and medication management: age, age at T1D diagnosis, duration of T1D, and average HbA1C and SBP over the last three clinic visits. These five variables were used to construct four multiple logistic regression models. Each model produced a clinical risk score for each diabetic complication in a microvascular-naive T1D patient.We determined the linearity of the relationship between each continuous variable and the microvascular complication using spiked histograms for visual analysis and analysis of variance of restricted cubic spline fits of the data for the statistical test of linearity. We used the spiked histograms to pre-specify the number of knots used for restricted cubic splines appropriate for each variable. The knots are placed at equal intervals across the distribution of the variables. These variables were all modeled with restricted cubic splines with 3, 5, and 4 knots, respectively. For the DR model, duration of T1D was also modeled with a restricted cubic spline with 3 knots. Calibration plots and validation were performed using the “calibrate” and “validate” functions, respectively, in the “rms” package  with 500p-values were two-tailed, and a p < 0.05 was considered statistically significant. All statistical analyses were performed using the R language and environment for statistical computing . All data and code used to generate models, plots, and the website are available at https://github.com/pmtran5884/T1D_Complications (accessed on 14 October 2021).All n = 1026) and T1D subjects with any complications . Subjects with complications were older  and had T1D for longer duration  despite being the mainstay marker of diabetes severity.We developed multivariate models to determine the risks of a microvascular complication-naïve T1D patient for developing DPN, AN, DR, and DN based on five variables: patient age, duration of T1D, age at diagnosis of T1D, systolic blood pressure, and HbA1c. Spiked histograms demonstrated a nonlinear relationship between current age, age at diagnosis of T1D, and average HbA1c over three clinic visits and the four diabetic complications .p = 0.28) and AN (p = 0.28), but performed worse for DR (p = 3 × 10−4) and DN (p = 0.04). We compared the calibration plots for each pair of models and found the mean squared error of the bias-adjusted curves were similar for the DPN , AN , and DN . We found the removal of the duration of T1D term gave an acceptable trade-off between model predictions and model interpretability for the DPN, AN, and DN models. The DR model retained the duration of type I diabetes term.In order to decrease the model complexity, we reasoned that variability accounted for by duration of T1D may be explained by current age and age of T1D onset. Thus, we compared models with and without this variable. The models without T1D duration were comparable to the models with this variable based on the likelihood ratio test for DPN  for individuals to estimate their specific risks of diabetic microvascular complications. This interface was created to help inform patients of their personal risks of complications, motivate them to reduce their complication risk by reducing their SBP and HbA1C, and track their progress. In our models, changes in SBP and/or HbA1c levels were associated with noticeable changes in probability of having a microvascular complication ). The risk calculator is not intended to replace or support clinician diagnosis of microvascular complications. It is merely a tool to augment lifestyle counseling.We emphasize the important role of the modifiable factors HbA1c and SBP in the risk of developing microvascular complications  and of iWe characterized demographics, past medical history, blood pressure, and laboratory values associated with four diabetic microvascular complications: DPN, AN, DR, and DN. We developed a clinical risk score for each microvascular complication using four clinical variables: age, age at T1D diagnosis, average SBP, and average HbA1C. The retinopathy model also included duration of T1D. We implemented this application as a web interface for clinicians and patients to easily calculate their risks of diabetic microvascular complications.


The prevalence of chronic kidney disease (CKD) continues to increase worldwide, as well as the associated morbidity and mortality and the consequences on the patients' quality of life and countries' economies. CKD often evolves without being recognized by patients and physicians, although the diagnosis is based on two simple laboratory data: the estimated glomerular filtration rate (eGFR) and urine analysis. To measure GFR, the knowledge about the physiologic processes at the nephron level, the concept of clearance, and the identification of creatinine as a suitable endogenous marker for measuring the creatinine clearance (CrCl) had to be previously developed. On those bases, different equations to calculate CrCl , or estimated GFR  were generated. They all include creatinine and some demographic data, such as sex and age. However, to compare results throughout life or among laboratories, the creatinine determination must be standardized. In addition, the accuracy of these equations remains controversial in certain subgroups of patients. For these reasons, other mathematical models to improve CrCl estimation have been developed, such as when urine cannot be collected, in debilitated elderly patients and patients with trauma, diabetes, or obesity. Currently, eGFR in adults can be measured and reported immediately, using isotope dilution mass spectrometry traceable creatinine-based equations. In conclusion, based on knowledge obtained from renal physiology, eGFR can be used in the clinic for the diagnosis and early treatment of CKD, as well as a public instrument to estimate the prevalence. The prevalence of chronic kidney disease (CKD) continues to increase worldwide, as well as the associated morbidity and mortality and the consequences on patients' quality of life and countries' economies. In the year 2018, a joint document of the ASN, ERA-EDTA, and ISN societies estimated that over 850 million people worldwide  lived with kidney disease, about twice the number of diabetic patients estimated by the IDF (422 million) . An analAny clinical situation resulting from a reduction in the number of functioning nephrons can evolve to CKD, defined by KDIGO guidelines as “abnormalities in kidney structure or function, present for 3 months, with implications for health.” The same guideline classifies CKD based on the cause, glomerular filtration rate (GFR) category, and albuminuria .Arterial hypertension, diabetes, obesity, proteinuric nephropathies, race, family history, genetic diseases, low birth weight, aging, among others, are risk factors for the CKD , 9. EarlIn the real world, CKD is a silent disease that often evolves unrecognized by the patients and physicians, although the diagnosis is based on the two simple laboratory data: the estimated GFR (eGFR) and urine analysis  . Early dGlomerular filtration rate continues to be the best global index of kidney function, both in health and in disease, as it represents the excretory capacity of the kidney, correlates directly with the kidney functioning mass, to classify CKD in stages according to the risk of progression, and to calculate the drug dosing and preparing for the invasive studies. xxEarly diagnosis of CKD by the general practitioners and generalists would contribute to retard progression and reduce associated morbidity and mortality. Albuminuria, an important predictor of CKD progression, will not be analyzed in this article. Therefore, the evaluation of kidney function and the presence or absence of proteinuria/albuminuria should be part of any routine health evaluation, and desirable when conducting population health surveys.The present manuscript, after a brief historical description on the milestones that paved the way since the emerging physiological concepts of filtration, reabsorption, and excretion at the nephron, will focus on the present concepts of eGFR, and how it can be applied in the clinic and as a public health tool. Finally, different eGFR equations derived from creatinine and cystatin C and demographic data used for the diagnosis in patients and as a public health instrument will be described.Knowledge of kidney physiology began in the mid-19th century, when Carl Ludwig (1816–1895) developed the concept of glomerular filtration. In his thesis, he identified the glomerulus as a filter, where urine formation began; this filter was submitted to physical and chemical forces, driven by the hydrostatic pressure generated by the heart, and regulated by the contraction and vasodilatation of the afferent and efferent arterioles. He went further, speculating that the filtered volume decreased along the tubules due to reabsorption, in order to concentrate the final products at the urine , 14.In 1874, Rudolf Heidenhain (1834–1897) injected a dye, indigo carmine, in hypotensive anuric rabbits; after 15 min he removed the kidneys and identified the dye in tubular cells. He deduced that secretion from blood into the tubule occurred that meant an active tubular transport mechanism (Arthur Cushny (1866–1926) in 1917 reasoned that Ludwig's theory (the glomerulus as a filter) implied a large volume of water, and near all the filtered glucose, amino acids, sodium, and other solutes should be in the ultrafiltrate. And, as these solutes are present at different concentrations in the plasma, the reabsorption of glucose, amino acids, and others dissolved substances present in urine should happen according to their respective blood levels. He concluded that there was a threshold for differential reabsorption of some solutes .In 1924, Alfred Richards (1876–1966) and Joseph Wearns (1893–1984) published their results for the filtration process, infusing epinephrine into the glomerulus of an anesthetized frog, and observing the hemodynamic effects on the afferent and efferent arterioles and the resulting ultrafiltrate. They confirmed that the free-protein ultrafiltrate was due to filtration at the glomerular tuft, the solutes were filtered and reabsorbed at the tubular level, and there was a threshold for glucose reabsorption, corroborating the differential reabsorption of filtered solutes in the tubule .At this point, the mechanism of filtration, secretion, and reabsorption in the nephron had been proved, but to transfer the concept of GFR to the clinic, it was still necessary to find a solute removed only by filtration, and not reabsorbed or secreted in the tubule. In 1926, Paul Rehberg identified creatinine as that solute, as it was produced by the body itself, filtered and, presumably, it was not reabsorbed or excreted .Donald Van Slyke 1883–1971), in 1928, introduced the concept of “clearance,” regarding urea, as the volume of blood that would be totally cleared of it in a minute when urine flow exceeded 2 ml/min. The clearance technique was quickly applied to different solutes and became itself a fundamental tool in kidney physiology 71, in 19.The clearance concept was fundamental, not only for studying the formation of urine or kidney physiology, but because it provided a simple tool to be used in the clinic, as GFR could be measured as creatinine clearance (CrCl). Since then, over many years, CrCl has been used in the clinic to evaluate GFR.Creatinine is a waste product of muscle metabolism, generated relatively constantly. It is almost eliminated by the glomerular filtration as it is a small molecule  not bound to proteins. However, as its concentration depends on muscle mass, it is different in men and women, and may change according to the protein diet and muscle mass .In 1886, Max Jaffe (1841–1911) noticed that creatinine in contact with picric acid in an alkaline solution developed an orange-red color, proportional to creatinine concentration . Years lAt present, creatinine is one of the most frequent laboratory determinations: easy to perform, available almost everywhere, and cheap. It can be determined by enzymatic or colorimetric methods. However, as every analyte, serum creatinine measure is exposed to random error (performed by the operator) and systematic error . Standardizing its determination as a method with traceable calibration to isotope dilution mass spectrometry (IDMS) reduces biases, improving the accuracy of creatinine determination , 25.Isolated creatinine is not a good marker to evaluate kidney function, as it increases when GFR is around 50 ml/min or below. Creatinine clearance is better to estimate GFR, but it has some disadvantages when evaluating kidney function. Creatinine is not excreted only by glomerular filtration, as a small fraction is secreted at the tubular level. This fraction increases as kidney function decreases and cannot be calculated individually . Also, iDespite the limitations described, creatinine continues to be the most frequent marker used in the clinic to assess the function of kidney.In some situations, a 24-h urine collection is mandatory, and the measured creatinine clearance is preferred in some patient groups to avoid misinterpretations. This is the case of a very low protein intake, such as vegetarians, high protein intake, creatine supplementation, diet rich in meat, some muscle mass abnormalities , rapid change in kidney function, before starting dialysis or in children and pregnant women , 28.Equations to estimate GFR are widely used in day-to-day practice. More than 70 have been developed. In this publication, the most used and recent will be detailed.One of the first ones was the Cockcroft–Gault (C–G) equation, available since the mid-1970s, that (or which) includes creatinine, sex, and weight, and is not adjusted for the body surface area  29). Ho. Ho29). Similar equations require other data like patient height and/or weight; many times this information is not recorded or correctly recorded, favoring erroneous results.2  study. The equation that gave the best agreement with iothalamate-measured GFR was the six variable equation, valid for a standard body surface of 1.73 m2 :GFR = 170 × [PCr]-0.999 × [Age]-0.176 × [0.762 if women] × [1.180 if African American/black] × [SUN]-0.170 × [Alb]+0.318In 2000, Levey and coworkers proposed the simplified four-variable MDRD equation that correlates very well with the six-parameter equation proposed before  34). Th. Th34). 2, but underestimated the measured GFR at higher levels  was published, based on new methods for measuring creatinine, valid for all stages of renal insufficiency . To workThis equation is still the most accurate GFR estimating equation evaluated in large diverse populations, applicable for the general clinical use. It provides lower estimates of the prevalence of decreased eGFR, and is useful as a trial measure for decreased eGFR and to replace the MDRD Study equation for routine reporting of serum creatinine-based eGFR by clinical laboratories .2) and the MDRD equation behaved better at lower GFRs (<60 ml/min/1.73 m2). In Asian or African populations, neither equation worked as well as in the other regions  improved accuracy . It has Q) for age (children and adolescents) and gender (adolescents and adults), being Q the median serum Cr from a specific healthy subpopulation. In the validation study, 6,870 healthy and kidney disease caucasian and from the non-African origin individuals, of whom 765 were children and adolescents <18 years old and 1,748 elderly higher than 70 years old, participated. For validation, measured GFR was performed using inulin or iothalamate or iohexol clearance  equation, to estimate the GFR across all over the age spectrum since available equations lack continuity with aging . This new equation is normalized on serum Cr (SCr/learance  44). Th. ThQ) foCystatin C was described for the first time in 1961 . As creaTo improve the accuracy of eGFR several equations have now been developed using either cystatin C alone or cystatin C in combination with creatinine. Cystatin C-based equations have advantages over the creatinine-based equation as they are less influenced by age, sex, and race . The 201Despite its greater usefulness, cystatin C has not displaced creatinine for GFR estimation in clinical practice, possibly due to its higher cost and lower availability.In some clinical situations, such as patients with anorexia nervosa, cirrhosis, obesity, evaluation of living kidney donors, prescribing nephrotoxic drugs with a narrow therapeutic window, pharmacokinetic studies of drugs excreted by the kidney, or any situation in which eGFR is unreliable, it is reasonable to measure GFR (mGFR), despite the added cost and time and resources consuming , 50–52. Iohexol, a low-cost non-toxic non-ionic contrast agent, has some advantages for the plasma clearance such as simplicity, low cost, stability, and low interlaboratory variation. Besides that, it is not radioactive, is excreted almost exclusively by the kidney, is neither secreted nor reabsorbed at the tubular level, has low protein binding, and correlates with inulin renal clearance , 57. It From the knowledge that emerges from renal physiology, laboratory medicine, epidemiology, and biostatistics, have emerged equations that constitute tools not only for the clinical care of patients, but also to establish the prevalence of CKD, and consequently implementing the public health policies aimed to reduce it.The inclusion of the automatic calculation of GFR in the laboratory reports of creatinine determinations constitutes a useful tool for daily practice, and from public health perspectives for population screening for CKD.CKD–EPI Study equation continues to be the most used in general practice and from public health perspective. Recently, the FAS equation emerged as a promising option to estimate eGFR for all ages (from 2 to 100 years old).Further improvement in GFR estimating equations will require development in more broadly representative populations, such as diverse racial and ethnic groups, use of multiple filtration markers, and evaluation using statistical techniques to compare eGFR to mGFR.All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The primary outcomes were a composite outcome (50% decline in eGFR or ESRD) and ESRD. The performance of those models was assessed using discrimination, calibration, and reclassification. A total of 2,300 eligible cases were enrolled. Of them, 288 (12.5%) patients reached composite outcome and 214 (9.3%) patients reached ESRD during a median follow-up period of 30 months. Using the composite outcome for analysis, the Clinical, Limited, Full, and CKD models had relatively good performance with similar C statistics . While using ESRD as the end point, the four prediction models had better performance . Furthermore, subgroup analysis showed that the models containing clinical and pathological variables (Full model and Limited model) had better discriminatory abilities than the models including only clinical indicators  in low-risk patients characterized by higher baseline eGFR (≥60 ml/min/1.73 m2). In conclusion, we validated recently reported IgAN and CKD risk models in our Chinese IgAN cohort. Compared to pure clinical models, adding pathological variables will increase performance in predicting ESRD in low-risk IgAN patients with baseline eGFR ≥60 ml/min/1.73 m2.We aimed to validate three IgAN risk models proposed by an international collaborative study and another CKD risk model generated by an extended CKD cohort with our multicenter Chinese IgAN cohort. Biopsy-proven IgAN patients with an eGFR ≥15 ml/min/1.73 m Immunoglobulin A nephropathy (IgAN), first described by Berger in 1968, is the most common type of glomerulonephritis and an important cause of end-stage renal disease (ESRD) worldwide . BecauseIn recent decades, dozens of clinical risk factors, including proteinuria, hypertension, and estimated glomerular filtration rate (eGFR), at the time of renal biopsy have been reported to be associated with worse renal prognosis in IgAN . In addiTo date, several prediction models of IgAN progression have been established based on patients from different populations at different stages of renal function , 12–17. The objective of this study was to use our established multicenter Chinese IgAN cohort to conduct an independent external validation study of Barbour’s IgAN models and Tangri’s CKD model. We also compared the performance of pure clinical models  and combined models . We aimed to determine whether pathological parameters independently contribute to clinical models in predicting IgAN prognosis.This study was performed in accordance with the Declaration of Helsinki and approved by the Ethics Research Committee of Ruijin Hospital, Medical School of Shanghai Jiaotong University. Written informed consent was collected from all participants prior to inclusion in the study.2 at diagnosis; (4) the minimum follow-up time was 6 months; (5) the age at biopsy was more than 18 years; and (6) an informed consent form was signed.A multicenter collaborative cohort  was established to represent Chinese patients with IgAN. All patients were recruited from six renal centers from 1985 to 2018. The recruitment criteria for the IgAN patients included the following: (1) IgAN was defined by a renal biopsy demonstrating dominant IgA deposition in the mesangium of glomeruli by immuno-fluorescence microscopy; (2) IgAN was not secondary to systemic diseases, such as Henoch-Schoünlein purpura, systemic lupus erythematosus, and liver disease; (3) the eGFR was ≥15 ml/min/1.73 mAll clinical and pathologic variables at the time of renal biopsy and during follow-up were collected. Age at biopsy, mean arterial blood pressure (MAP), serum creatinine (Scr), hemoglobin, eGFR (using the EPI equation), 24-h protein excretion, and renin–angiotensin system blocker (RASB) or glucocorticoid treatments were recorded. The severity of the renal damage was scored according to the Oxford MESTC classification , and one2 or the need for dialysis/renal transplantation). Patients were censored at the time of meeting the endpoint criterion or loss to follow-up.The start of follow-up time was considered the date of renal biopsy. The primary renal outcome of our study was the combined outcome (the first occurrence of either a 50% decline in eGFR from that at biopsy or ESRD). The secondary outcome was defined as ESRD  had a renal composite outcome, and 214 patients progressed to ESRD (9.3%).A total of 2,300 IgAN patients were finally enrolled based on the inclusion criteria Figure 12, 0.23). The C statistic and R2 were not significantly improved after adding pathological indicators in the limited model  or medication and other predictors in the full model . The AIC was also similar among the clinical, limited, and full models . Moreover, continuous net reclassification improvement  indicated the significantly improved classification performance of the models that included clinical and pathological indicators compared with the models that only included clinical indicators at 5 years of follow-up  than that used to predict the composite outcome Table 2.2 (0.31) and AIC (450.11) were also similar to those of the above clinical models  and relatively good performance in predicting composite outcomes  in our IgAN patients Table 2.The IgAN models and the CKD model performed better in predicting ESRD than in predicting the composite endpoint. Considering that ESRD is a robust renal outcome, it was used for further analysis.2).A subgroup analysis of the entire cohort was used to evaluate the performance of the four models in patients from different subgroups  for the full model, 0.90  for the limited model, 0.70  for the clinical model, 0.78  for the CKD model]. Pathological variables that added predictive value to the clinical variables were observed only in low-risk IgAN patients characterized by a baseline eGFR ≥ 60 ml/min/1.73 m2 . Compared to the derivation cohort of the CKD model, our cohort had a lower proportion of patients with baseline eGFR < 30 ml/min/1.73 m2, and fewer patients progressed to kidney failure/ESRD (9.3% versus 11%) during the follow-up period.In this study, we assessed the performance of international IgAN prediction tools and another CKD model by external validation in a large, multicenter Chinese IgAN cohort. Relative to those in the derivation cohort of the international IgAN prediction tools, our follow-up time was shorter, and the incidence of a 50% decline in eGFR or development of ESRD was lower , the pathological variables could add predictive value to clinical variables, likely because the contribution of pathological indicators to ESRD prediction is diminished by the subsequent use of immunosuppressive therapy in high-risk patients characterized by lower eGFR.Considering that those laboratory and pathological markers have been associated with the progression of IgAN, risk prediction models integrate them in different combinations. Based on our data, the performances of all models according to ROC analysis were compared. The clinical models and combined models showed similar performance in predicting ESRD after 5 years of follow-up. However, for patients at low risk characterized by higher baseline eGFR , using the full model to predict ESRD at 5 years should be more precise. Additionally, both the CKD model and IgAN model exhibited similar performance in our IgAN cohort. We still need to improve the predictive ability of the models by adding IgAN-specific biomarkers, such as HAA-IgA1 levels. Alternatively, considering the genetic background of IgAN , an improvement in model performance was observed after adding histological indicators to these clinical indicators.In summary, we validated recently reported highly accurate predictive models for the progression of IgAN to kidney failure. Especially for patients at low risk characterized by higher baseline eGFR  Joint Research Program of National Natural Science Foundation of China (No:8211001014), the National Natural Science Foundation of China , “Excellent Academic Leader” by Shanghai Science and Technology Commission (No: 21XD1402000). Shanghai Jiao Tong University “Jiaotong Star” Plan Medical Engineering Cross Research Key Project , Shanghai Shenkang Hospital Development Center “Three-year Action Plan for Promoting Clinical Skills and Clinical Innovation in Municipal Hospitals” (No : SHDC2020CR6017), Science and Technology Innovation Action Plan of Shanghai Science and Technology Committee (No. 17441902200), Shanghai Municipal Education Commission, Gaofeng Clinical Medicine Grant (No. 20152207), Shanghai Jiao Tong University School of Medicine, Multi-Center Clinical Research Project (No: DLY201510), Shanghai Health and Family Planning Committee Hundred Talents Program (No: 2018BR37), and Shanghai Municipal Key Clinical Specialty (shslczdzk02502). No funding bodies had any role in study design, data collection and analysis, decision to publish, or preparation of the 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Data on how lifestyle changes due to the coronavirus disease 2019 (COVID-19) pandemic have influenced the clinical features of kidney disease patients remain scarce.This study retrospectively analyzed clinical variables in patients with stage G1–G4 chronic kidney disease (CKD) with complete or incomplete remission of proteinuria, who were managed in a nephrology outpatient clinic of a university hospital in Tokyo. The clinical variables during the COVID-19 pandemic  were compared to those one year before the pandemic . The urinary protein excretion (UPE) was used as the primary outcome measure.th–75th percentile)], respectively; the value in term 1 was 18% lower than that in term 0 (p<0.001), with no marked difference in body weight, blood pressure, protein intake or urinary salt excretion. In multivariable analyses, incomplete remission of proteinuria in term 0 , RAASi use  and decreased urinary salt excretion in term 1 vs. term 0  were identified as independent variables associated with reduced UPE in term 1 vs. term 0. No significant interactions between the variables were observed.This study included 325 patients with stage G1–G4 CKD  evaluated at term 0. The UPE at terms 0 and 1 was 247 (92–624) and 203 (84–508) mg/day [median (25In kidney disease patients receiving standard medical care from nephrologists, the UPE after the emergency declaration in relation to the COVID-19 pandemic was lower than before the declaration. The UPE reduction may be associated with reduced dietary salt intake during the pandemic in patients treated with RAASi for insufficient control of proteinuria. Our results support the current proposal to continue therapeutic approaches to these patients, which involve RAASi therapy along with optimizing dietary habits, even while dealing with the COVID-19 pandemic. Since then, most people have begun to change their lifestyle and to perform social distancing, regardless of the absence or presence of underlying diseases  and conducted according to the Declaration of Helsinki. This study was performed in accordance with the STROBE reporting guidelines.th–75th percentile) for continuous variables and frequencies and proportions (%) for categorical variables. Corresponding repeated comparisons for each clinical parameter were performed between terms 0 vs. term 1 as appropriate. Wilcoxon’s signed-rank test and McNemar’s test were used to compare changes in the UPE and the rate of patients with complete remission of proteinuria between terms 0 and 1. Univariable and multivariable (backward selection) logistic regression analyses were used to examine the variables associated with a reduced UPE in term 1 compared with term 0. As a sensitivity analysis, univariable and multivariable logistic regression analyses were performed using different definitions of UPE reduction as the dependent variable (>0% decrease or ≥10% decrease in UPE in term 1 relative to term 0). To further examine the interactions among the variables significantly associated with the UPE reduction, multivariable logistic regression analyses were performed by integrating interaction terms as the explanatory variables in the relevant statistical model. All reported p values were two-sided. P values of <0.05 were considered to indicate statistical significance. All statistical analyses were performed using the SPSS software package .Variables were presented as the mean ± standard deviation (SD) or median  of the patients were female. The distribution of the CKD stages was as follows: stage G1, 3.7%; stage G2, 32.0%; stage G3a, 31.4%; stage G3b, 20.0% and stage G4, 12.9%. Renin-angiotensin aldosterone system inhibitors (RAASis) were administered to 262 (80.6%) patients, and maintenance doses of corticosteroids and/or immunosuppressants were administered to 39 (12.0%). One hundred and seventy-six patients (54.2%) had achieved complete remission of proteinuria (UPE <300 mg/day). A histopathological evaluation of a kidney biopsy specimen was performed in 254 (78.2%) patients. IgA nephropathy (n = 140 [43.1%]) was the most common histological diagnosis.Table 2. The body weight, blood pressure, protein intake and urinary salt excretion did not differ markedly between the terms. Relative to term 0, the serum creatinine levels increased, urinary creatinine excretion decreased, and the CCr decreased in term 1. The UPE was decreased in 198 patients (60.9%) and unchanged or increased in 127 patients (39.1%) in term 1 relative to term 0. Overall, the UPE in terms 0 and 1 was 247 (92–624) and 203 (84–508) mg/day [median (25th–75th percentile)], respectively; the value in term 1 was 18% lower than that in term 0 (p<0.001) . Complete remission of proteinuria was found in 176 patients (54.2%) in term 0 and in 197 patients (60.6%) in term 1, demonstrating a statistically significant difference (p = 0.002).Comparisons of clinical factors between terms 0 and 1 are shown in Table 3 shows the results of univariable and multivariable logistic analyses of the variables associated with a reduced UPE in term 1 relative to term 0. Among the variables included, incomplete remission of proteinuria in term 0 , RAASi use , and decreased urinary salt excretion in term 1 vs. 0  were identified as significant variables by backward selection. The same analyses were performed using different definition in the UPE decrease in term 1 relative to term 0 (≥10% decrease in UPE), and similar results were obtained, except that female gender was additionally identified as an independent variable associated with UPE reduction (S1 Table in Supporting Information). As shown in Fig 4, the adjusted ORs for the UPE reduction in term 1 relative to term 0 were significantly higher in patients with any combination of the variables  than those with either of the variables. No significant interactions between the variables were observed. The detailed data of the Fig 4 was presented in S2 Table in Supporting Information.This study retrospectively analyzed the changes in clinical variables before and after the emergency declaration for the COVID-19 pandemic in patients with stage G1–G4 CKD with proteinuria remission who were treated in a nephrology outpatient clinic of a university hospital located in Tokyo. Our results showed that the UPE after the emergency declaration for COVID-19 were 18% lower than those evaluated one year before the declaration in these patients, with no marked differences noted in the body weight, blood pressure or dietary contents of protein or salt. This study highlighted, for the first time, the UPE changes in kidney disease patients during the current social crisis due to the COVID-19 pandemic.This study aimed to investigate the changes in UPE that might occur in kidney disease patients under the medical care of nephrologists during the COVID-19 pandemic. The mechanisms and factors involved in the proteinuria excretions are quite diverse . We therS1 Table in Supporting Information). One possible interpretation of this finding is that the current lifestyle during the COVID-19 pandemic may better benefit patients showing these clinical characteristics, i.e., incomplete remission of proteinuria, RAASi use, and decreased urinary salt excretion during the pandemic, with respect to UPE reduction.The COVID-19 pandemic emerged in Japan during winter, in March 2020. Seasonal changes in environmental or patient lifestyle factors may influence the clinical features of many disease conditions, including proteinuria levels in kidney diseases . Our resThe adjusted ORs for the UPE reduction were significantly higher in patients with any combination of the variables than those with either of the variables but did not show any significant interactions, suggesting the additive effects of the variables. These results are consistent with the findings showing that RAASi therapy for reducing overt proteinuria in CKD patients is more effective under salt restricted diet –14. The The present study was associated with several limitations. First, the study population was restricted to patients who underwent routine evaluations of 24-hour urine sample and maintained complete or incomplete remission of proteinuria, and who were expected to have a higher awareness of the importance of self-management for disease control. Additionally, patients were selected from those visited in term 1 when the patient visits had recovered to 84–86% relative to the corresponding months in 2019 in our hospital, which may have produced a bias in the patients’ characteristics. Second, this study indirectly indicated the effects of changes in physical activity on the proteinuria remission status, although we could not estimate the changes in physical activities before the emergency declaration or those after the declaration in this study population. Thus, possibility remains that changes in physical activity, such as changing from working in an office to telework, less effort in going to the workplace, and a longer sitting or sleeping time may have additionally influenced to the changes in the UPE levels. Finally, this study was conducted in a single institution and all patients were Japanese. In addition, the majority of the participants had been diagnosed with primary glomerular diseases. To determine the generalizability of our findings, further studies should be performed in larger populations of CKD patients, including patients of different races and countries.In conclusion, after the emergency declaration by the Japanese government in relation to the COVID-19 pandemic, the UPE in kidney disease patients with proteinuria remission who received standard medical care from nephrologists was lower than that observed before the declaration, thus indicating that lifestyle changes due to the pandemic influenced the proteinuria levels. This study also suggests that certain clinical characteristics, including incomplete remission, RAASi use and a salt-restricted diet, may be associated with the reduction in UPE observed during the COVID-19 pandemic, supporting the current proposal to continue therapeutic approaches to hypertension and kidney disease patients, which involve RAASi therapy along with optimizing dietary habits, even while dealing with the COVID-19 pandemic.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Previous large observational cohort studies showed higher blood pressure (BP) positively associated with cancer. We used Mendelian randomization (MR) to obtain less confounded estimates of BP on total and site-specific cancers.We applied replicated genetic instruments for systolic and diastolic BP to summary genetic associations with total cancer  from the UK Biobank, and 17 site-specific cancers (663–17881 cases) from a meta-analysis of the UK Biobank and the Kaiser Permanente Genetic Epidemiology Research on Adult Health and Aging. We used inverse-variance weighting with multiplicative random effects as the main analysis, and sensitivity analyses including the weighted median, MR-Egger and multivariable MR adjusted for body mass index and for smoking. For validation, we included breast , prostate  and lung  cancer from large consortia. We used asthma as a negative control outcome.Systolic and diastolic BP were unrelated to total cancer  0.89, 1.07] and OR 1.00 ) and to site-specific cancers after accounting for multiple testing, with consistent findings from consortia. BP was nominally associated with melanoma and possibly kidney cancer, and as expected, not associated with asthma. Sensitivity analyses using other MR methods gave similar results.In contrast to previous observational evidence, BP does not appear to be a risk factor for cancer, although an effect on melanoma and kidney cancer cannot be excluded. Other targets for cancer prevention might be more relevant.The online version contains supplementary material available at 10.1186/s12885-021-09067-x. Elevated blood pressure (BP), or hypertension, reduces population health globally , with 31P < 5x10-8), independent (r2 < 0.001) and externally replicated single nucleotide polymorphisms (SNPs) predicting BP from a meta-analysis of genome-wide association studies (GWAS) for BP traits totaling 757,601 participants of European ancestry  [n=372) and individuals who had withdrawn consent (n=36) [2, sex and body mass index (BMI), with genomic control applied at the study level to correct for inflation due to population stratification and cryptic relatedness [We extracted strong (% women) , consistt (n=36) , and 299t (n=36) . Indepent (n=36)  and 28,7t (n=36) . Particit (n=36) . The UK t (n=36) , adjusteatedness , followeatedness , and pot2, age2*sex and the first 10 principal components (PCs).Genetic associations with total cancer (phenocode:195) were obtained from a pan-ancestry GWAS of the UK Biobank , with lip-value [Genetic associations with site-specific cancers were obtained from the largest available pan-cancer GWAS , which pp-value , as it wFor validation of potentially small effects, we additionally included large genetic consortia of leading cancers , i.e., br2 ≥ 0.8) identified using LDlink [Estimates were aligned on the same effect allele for BP and cancer. Effect allele frequency (EAF) was not provided for pan-cancer, so we used the UK Biobank EAF which constituted 86% of the participants. Palindromic SNPs with ambiguous EAF, i.e. >0.42 and <0.58, and SNPs instrumenting BP but not available for an outcome, were replaced by proxies  used as a negative control outcome were obtained from the UK Biobank (phenocode: 495), given BP is not known to cause asthma , but bot2 to assess heterogeneity of instrument strength, an I2 < 90% suggests violation of the no measurement error (NOME) assumption and possibly invalid estimates [2 > 97% suggests minimal bias of the MR estimates by confounding of exposure on outcome in overlapping samples [2) explained by the genetic instruments was calculated as beta2*2*MAF*(1-MAF), where beta is the SNP-phenotype association standardized to the phenotypic variance and MAF is the minor allele frequency of the SNP [2 for genetic instruments on exposure [Instrument strength was assessed using the F-statistic , approxistimates . An I2 > samples , as here the SNP . Power cexposure , using aexposure .We used the inverse-variance weighted (IVW) meta-analysis, with multiplicative random effects, which assumes balanced pleiotropy , of the All analyses were performed using R . We used the R packages “TwoSampleMR”, “MedelianRandomization” and “MVMR”. Given the number of cancer outcomes considered, a two-sided p-value below the Bonferroni-corrected significance threshold 0.0014 (0.05/2 BP traits*18 cancer outcomes) was used.2 of 92.5 and 93.8%, respectively (Table P < 5x10-8) and independent (r2 < 0.001) SNPs predicting BMI and ever-smoking, respectively. Both BMI  and diastolic (hollow) blood pressure on asthma.Additional file 4: Supplementary Table S1. Genetic associations with systolic blood pressure, total and site-specific cancers. Supplementary Table S2. Genetic associations with diastolic blood pressure, total and site-specific cancers. Supplementary Table S3. Power calculations for total and site-specific cancers. Supplementary Table S4. Mendelian randomization estimates of systolic (per 10 mmHg increment) blood pressure on total and site-specific cancers. Supplementary Table S5. Mendelian randomization estimates of diastolic (per 5 mmHg increment) blood pressure on total and site-specific cancers. Supplementary Table S6. Mendelian randomization estimates of systolic (per 10 mmHg increment) and diastolic (per 5 mmHg increment) blood pressure on site-specific cancers in genetic consortia


Background: Antihypertensive treatment may have different effects on central arterial hemodynamics. The extent of the difference in effects between various antihypertensive drugs remains undefined.Methods: We conducted a systematic review and meta-analysis of randomized controlled trials that explored the effects of antihypertensive agents on both central and peripheral systolic blood pressure (SBP) and pulse pressure (PP) or central augmentation index, with a special focus on the comparison between newer [renin-angiotensin-aldosterone system (RAS) inhibitors and calcium-channel blockers (CCBs)] and older antihypertensive agents (diuretics and β- and α-blockers).Results: In total, 20 studies  were included. Compared with diuretics (10 studies), β-blockers (16 studies), or an α-blocker (1 study), RAS inhibitors (21 studies), and CCBs (6 studies) more efficaciously (P < 0.001) reduced both central and peripheral SBP by a weighted mean difference of −5.63 (−6.50 to −4.76 mmHg) and −1.97 mmHg (−2.99 to −0.95 mmHg), respectively. Compared with older agents, the newer agents also more efficaciously (P < 0.001) reduced central PP , augmentation index  and augmentation  but not peripheral PP (p ≥ 0.09). Accordingly, the newer agents reduced central-to-peripheral PP amplification significantly less than the older agents .Conclusion: Newer agents, such as RAS inhibitors and CCBs, were significantly more efficacious than older agents in their effects on central hemodynamics. When the blood flows from the central large elastic aorta to the peripheral smaller muscular arteries, systolic blood pressure (SBP) increases, without significant changes in diastolic blood pressure and mean arterial pressure, resulting in widened pulse pressure (PP). Although brachial blood pressure highly correlates with central blood pressure, substantial individual discrepancies between the central and peripheral blood pressure exist. Several studies have shown that the association between target-organ damage and SBP and PP is stronger for the central arteries than the brachial arteries . Indeed,Previous studies have shown that various classes of antihypertensive drugs may have different treatment effects between the central and peripheral arterial sites and that the newer antihypertensive agents, such as renin-angiotensin-aldosterone (RAS) inhibitors and calcium-channel blockers (CCBs), might be more efficacious than the older ones, such as diuretics, β-blockers, and α-blockers in the effect on central hemodynamics. The Conduit Artery Function Evaluation (CAFE) study, a substudy of the Anglo-Scandinavian Cardiac Outcomes Trial (ASCOT), showed that treatment with amlodipine/perindopril was more efficacious than with atenolol/bendroflume thiazide in reducing central SBP and PP by 4.3 and 3.0 mmHg, respectively, despite similar reductions in the brachial arteries . The carIn this comparative meta-analysis of randomized controlled trials, we investigated the effects of the newer agents vs. older antihypertensive agents on various central hemodynamic measurements.Preferred Reporting Items for Systematic Reviews and Meta-Analysis: The PRISMA Statement  or older agents (diuretics and β- or α-blockers) or with a combination antihypertensive therapy.Data extraction was performed using predefined data fields. Variables included author name, year of publication, study design, study population, number of patients, study intervention, duration of treatment and specifications of the blood pressure measuring device and other methods for blood pressure measurement, arterial sites, and the algorithm for augmentation index estimation. Baseline and post-intervention mean values of central and peripheral hemodynamic measurements for the experimental and control groups were extracted with standard deviation (SD), standard error of mean (SEM), or 95% confidence intervals (CIs) separately.Central hemodynamic measurements included central systolic and diastolic blood pressure (mmHg), central PP (mmHg), augmentation pressure (mmHg), and augmentation index (%). Central augmentation pressure was the absolute difference between the second peak (P2) and the first peak (P1) of the central blood pressure wave. The central augmentation index was calculated either as the ratio of the P2 to the P1, or as augmentation pressure (P2−P1) divided by PP, expressed in percent. Peripheral measurements were brachial SBP and diastolic blood pressure and PP. Central-to-peripheral PP amplification was calculated as the ratio of the central PP to the peripheral PP.When multiple usable groups were available within an individual study, the data were counted as another study in the meta-analysis. Methodological quality was assessed using the Jadad scores . Study s2). Heterogeneity of effect sizes was tested across trials using the χ2 test. If trials were homogeneous (p < 0.10), a fixed-effects model was used to calculate pooled effect sizes. Otherwise, a random-effects model was applied to calculate overall differences. Net treatment effects on central pressure and augmentation index were determined by subtracting the mean change in the experimental group from the corresponding mean change in the control group. We performed all aforementioned computations and statistical analyses in Stata version 15 . SEM was converted to SD [SE = SD/√(sample size)], and CIs were calculated [CI = mean difference ± (SEM × 1.96)], as appropriate.For each comparison within each trial, we calculated the absolute differences between the experimental and control groups. If significant between-group differences in any outcome measure were reported at baseline, we calculated the absolute difference in the mean changes over time. The pooled effect for each grouping of trials was derived from the point estimate for each separate trial weighted by the inverse of the variance , and a primary diagnosis of hypertension. All p-values were calculated from two-tailed tests of statistical significance with a type 1 error of 5%.Publication bias was assessed using the Egger’s statistic and visual inspection of funnel plots. Potential heterogeneity was further inspected by visual inspection of the data and by subgroup and sensitivity analyses. We performed subgroup analyses based on the classes of drugs, sensitivity analyses by limiting to studies with a Jadad score of ≥3, central blood pressure n = 21) or CCBs (n = 6) with diuretics, β-blockers, or an α-blocker (-blocker .n = 11),  (n = 4), or  (n = 1).These 20 trials included a total of 2,498 participants. The mean age of the study participants ranged from 35.5  to 71.6 n = 854), an ARB in nine trials , a renin inhibitor in four trials (n = 197), and a CCB in six trials (n = 490).In total, we performed analyses in 20 trials with 1,250 and 1,248 participants in the treatment groups of newer and older antihypertensive drugs, respectively . Newer an = 10), β-blockers (n = 16), or an α-blocker (n = 1), the weighted mean differences in the central SBP were statistically significant for ACEIs (n = 7) by −3.39 mmHg , for ARBs (n = 9) by −4.12 mmHg , for renin inhibitors (n = 4) by −6.67 mmHg , and for CCBs (n = 6) by −5.60 mmHg . No significant heterogeneity was noticed within all four classes of newer drugs (p ≥ 0.24). The overall weighted mean difference in the central SBP across all 20 trials was −5.63 mmHg . The weighted mean differences in central PP were statistically significant for ARBs (n = 7) by −5.52 mmHg  but not significant for ACEIs (n = 6), renin inhibitors (n = 2), or CCBs . The overall weighted mean difference in central PP across 12 studies with data was −3.27 mmHg , β-blockers (n = 15), or an α-blocker (n = 1), the weighted mean differences in the central augmentation index were statistically significant for ACEIs (n = 7) by −4.89% , for ARBs (n = 8) by −9.20% , and for CCBs (n = 6) by −5.27% . The overall weighted mean difference in the central augmentation index across 18 studies with data was −6.11% , but not for PP across 9 studies  after 12 weeks of treatment but not after 52 weeks of treatment, probably because more subjects in the olmesartan group required add-on antihypertensive therapy than in the sacubitril/valsartan group . Indeed, Schmieder found that sacubitril/valsartan reduced central aortic PP to a greater extent than olmesartan  after 52 weeks of treatment, with similar add-on treatment of amlodipine in the two groups . These observations shed some light on the potential beneficial effect of novel antihypertensive agents on central hemodynamics.A major limitation of our meta-analysis was that two recent studies on an even newer antihypertensive drug class, i.e., angiotensin receptor neprilysin inhibitor (ARNI), were not included, because the comparative drug was an ARB , which wAntihypertensive drug treatment with RAS inhibitors and CCBs was more efficacious than that with diuretics, β-blockers, and α-blockers in the central hemodynamic effects. At present, there is still no direct evidence regarding the clinical relevance of central hemodynamics for decision-making in the management of hypertension and cardiovascular prevention. Therefore, it is imperative to run adequately powered outcome trials to investigate whether central hemodynamic measurements are clinically useful in guiding antihypertensive treatment and other cardiovascular therapeutic approaches for the prevention of cardiovascular events.The original contributions presented in the study are included in the article/J-GW and Y-BC conceived the study, performed the statistical analyses, and prepared the first draft of the manuscript. Y-BC and J-HX coordinated the data extraction. All authors participated in the interpretation of the data and approved the final version of the manuscript.J-GW reports receiving lecture and consulting fees from Novartis, Omron, and Viatris. The remaining 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.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Background: Cardiovascular disease is a leading cause of heart failure (HF) and major adverse cardiac and cerebral events (MACCE). Objective: To evaluate impact of vascular resistance on HF and MACCE incidence in subjects with cardiovascular risk factors (CRF) and degenerative aortic valve stenosis (DAS). Methods: From January 2016 to December 2018, in 404 patients with cardiovascular disease, including 267 patients with moderate-to-severe DAS and 137 patients with CRF, mean values of resistive index (RI) and pulsatile index (PI) were obtained from carotid and vertebral arteries. Patients were followed-up for 2.5 years, for primary outcome of HF and MACCE episodes. Results: RI and PI values in patients with DAS compared to CRF were significantly higher, with optimal cut-offs discriminating arterial resistance of ≥0.7 for RI  and ≥1.3 for PI . Age, female gender, diabetes, and DAS were all independently associated with increased resistance. During the follow-up period, 68 (16.8%) episodes of HF-MACCE occurred. High RI  and PI  were associated with risk of HF-MACCE. Conclusions: An accurate assessment of vascular resistance may be used for HF-MACCE risk stratification in patients with DAS. With ageing, a reduction in the elastin content and an increase in the collagen content lead to increased arterial stiffness and elevated central as well as peripheral arterial blood pressure . SimilarDegenerative aortic valve stenosis (DAS) is another condition in which prevalence increases with age . DAS proUltrasonography can easily and non-invasively provide information on vascular resistance indices , that are surrogate markers of arterial stiffness. Peripheral flow parameters can be particularly important in patients with DAS, in whom severely reduced left-ventricle outflow has an impact on the altered vascular system flow pattern .Although both chronological and vascular ageing processes progress in time, they are often not parallel . In patiPatients with increased arterial stiffness tend to develop cardiovascular events at a younger age and with a higher mortality rate . HoweverWe aimed to evaluate impact of vascular resistance on HF and MACCE events in subjects with cardiovascular risk factors and degenerative aortic valve stenosis.In this single-center prospective study, from January 2016 to December 2018, 517 consecutive patients with either CRF or DAS were assessed. A flowchart of this study is presented in CRF group was enrolled from patients with suspected or known stable coronary artery disease, with preserved LVEF ≥ 50% admitted to our department for coronary angiography.2; they (2) had left ventricular ejection fraction (LVEF) ≥ 50%; and (3) underwent coronary angiography.Subjects with DAS were eligible if (1) aortic valve area was less than 1.5 cmThe exclusion criteria for both study and control groups included: significant stenosis of any carotid or vertebral artery (exceeding 50% lumen reduction), persistent atrial fibrillation or other severe arrhythmia, significant concomitant valve diseases, ongoing or recent myocardial infarction (<3 months), ischemic stroke or TIA, hemodynamic instability: NYHA class IV or acute heart failure, LVEF < 50%, aortic dissection, and lack of informed consent.Finally, in 404 study patients, including 267 patients with moderate-to-severe DAS and 137 patients with CRF, distribution of RI and PI registered at carotid and vertebral arteries was evaluated. Patients were followed-up for mean 2.5 years, with primary outcome of HF and MACCE episodes.The prevalence of CRF, including age, gender, hypertension, diabetes and dyslipidemia, and coronary artery disease was evaluated in both groups. Cardiovascular risk factors were defined as: hypertension , diabetes mellitus (treated or newly recognized > 11 mmol/l (200 mg/d) in oral glucose tolerance test, hyperlipidemia  and/or LDL > 3.0 mmol/L (115 mg/dL) and/or HDL men < 1.0 mmol/L (40 mg/dL), HDL women < 1.2 mmol/L (46 mg/dL) and/or triglycerides > 1.7 mmol/L (150 mg/dL) The averaged value of RI and PI from four arterial segments was taken into further statistical analysis.During mean observation period of 2.5 years, the incidences of HF episodes and MACCE were recorded.MACCE was defined as fatal or non-fatal ischemic stroke, myocardial infarction, acute heart failure episode, or cardiovascular death . HF episode was defined as new-onset acute HF incidence or any exacerbation of chronic heart failure requiring in-hospital stay and administration of intravenous medications such as diuretics, dopamine, adrenaline, or dobutamine.n = 4), the data on patient vital status were obtained from the national health registry.Final visit was conducted through the telephone contact with a patient or pointed family member. For patients lost to follow-up  and with R Studio 3.6.3 [Data are presented as mean ± standard deviation for continuous variables and as proportions for categorical variables. Differences between mean values were verified using the T-Student, analysis of variance (ANOVA) test, and frequencies were compared by the chi-2 test for independence, as appropriate. The normal distribution of studied variables was determined by the Shapiro–Wilk test. The Spearman’s rank-order correlation was performed for correlation between RI and PI. A receiver-operating characteristic (ROC) analysis was performed to determine the optimal cut-off values (common point of the most distant y = x line with ROC curve) for vascular resistance as potentially associated with DAS. The area under the curve (AUC), cut-offs sensitivity and specificity were calculated. The C statistic with comparison of AUCs was performed for evaluation of models with and without DAS to assess the probability of obtaining arterial stiffness parameters above thresholds. The analysis of risk factors associated with increased PI and RI values was performed with univariate regression analysis. We included age, gender, diabetes mellitus, hypertension, hyperlipidemia, coronary artery disease, LVEF, and DAS as factors potentially associated with vascular resistance. After identification of parameters potentially associated with increased vascular resistance, the multivariable logistic backward regression analysis was used to calculate odds ratio (OR) and 95% confidence interval (95% CI). We used Z-scores to standardize the raw values of age to a normal distribution. We also assessed incidence of HF-MACCE events in groups classified by high versus low PI and RI using univariate logistic regression analysis, followed by the multivariable regression models, with the PI ≥ 1.3 and the RI ≥ 0.7 as referent in all study participants. A 2-sided value of p = 0.001) and more often had hyperlipidemia , while history of myocardial infarction was more frequent in CRF group . Gender distribution, prevalence of hypertension, diabetes mellitus, and significant coronary artery disease did not differ between the CRF and DAS groups. On echocardiography, baseline LVEF was similar in both study groups, while peak and systolic aortic gradients were significantly higher in DAS vs. CRF groups.The baseline characteristics of the patients are summarized in p < 0.001).The RI values were significantly positively correlated with the PI values  and the PI  were significantly higher in patients with DAS, compared to CRF  vs. severe (n = 235) DAS, mean values of RI  and PI  differed significantly.In line, in patients with moderate  and PI value of 1.3 or higher .Univariate regression backward analysis, followed by the multivariate regression analysis, showed associations with the RI ≥ 0.7 and the PI ≥ 1.3 for age, female gender, diabetes, and DAS . There wIn multivariable logistic regression backward analysis, DAS confirmed its independent association with high RI and high PI in the multivariate analysis, both in unadjusted and Z-score age-adjusted analysis .p = 0.014) and the PI ≥ 1.3   A,B.p = 0.047.During follow-up period, 68 (16.8%) episodes of HF-MACCE occurred, including 16 (11.7%) in CRF group and 52 (19.5%) in DAS group, p < 0.001), whereas in 9 of 161 patients with PI < 1.3 vs. 59 of 245 patients with PI ≥ 1.3 .HF-MACCEs were observed in 9 out of 172 patients with RI values below 0.7, as compared to 59 of 232 with RI ≥ 0.7 , diabetes , and dyslipidemia  were all significantly associated with increased risk of developing severe DAS ,19. PatiIn contrast to overwhelming studies in favor of an independent role for arterial stiffness in predicting cardiovascular events in healthy elderly and diseased hypertensive, diabetic, or end stage renal disease subjects ,25, studIn one research study enrolling 103 asymptomatic patients with moderate-to-severe DAS, arterial stiffness assessed with femoral-carotid pulse wave velocity (PWV) method, showed significantly lower event-free survival in patients with PWV ≥10 m/s compared to those with lower PWV . In lineThere is some uncertainty about sequence of developing aortic valve calcifications, exposure to atherosclerosis risk factors, and arterial stiffening ,28. MoreIn fact, the results of our study demonstrate that both chronological and vascular age were the only independent risk predictors of HF-MACCE in multivariate analysis.It is important to realize that DAS is not only a disease of the valve (or heart), but this is a disease of the whole vascular system, and the latter contributes to adverse events. A decrease in elasticity is associated with a multitude of complications, including increased stress on the left ventricle, a gradual increase in blood pressure and, eventually, even end-organ damage through the transmission of harmful pulsation into the microcirculation. Thus, the increase in pulsatility associated with loss of elastic recoil in large blood vessels has detrimental effects on global cardiovascular health .Biological vascular age should be used to select individuals for early prevention of cardiovascular complications with intensification of pharmacotherapy and earlier intervention on the valve ,31,32. Hypothetically, the risk prediction models may help clinicians develop personalized treatments, i.e., in patients with PI ≥ 1.3 or RI ≥ 0.7, early intervention on DAS could be considered. The treatment of choice could perhaps be transcatheter aortic valve implantation in such a subset of patients, as surgical aortic valve replacement may lead to further significant increase in PWV ,32.Patients with DAS have greater vascular resistance compared to controls with cardiovascular risk factors. Moreover, RI ≥ 0.7 and PI ≥ 1.3 may be used for cardiovascular risk stratification.Our study has obvious limitations, as it consisted of a single-center observational design. Secondly, in general, DAS patients are elderly, which caused difficulties when matching with a control group. For this reason, age-adjustment in multivariate analyses was performed.


Conclusions: For PD patients, the serum OPN level was correlated with cfPWV and could play an important role in the process of AS.Background: Osteopontin (OPN) is regarded as a proinflammatory and proatherogenic molecule related to atherosclerosis. We aimed to evaluate the relationship between serum OPN and aortic stiffness (AS) of peritoneal dialysis (PD) patients. Methods: OPN and carotid-femoral pulse wave velocity (cfPWV) were measured by a commercial enzyme-linked immunosorbent assay kit and a validated tonometry system, respectively. Patients with cfPWV > 10 m/s were designated into the AS group. Results: Twenty-two patients (31.4%) were segregated into the AS group. Multivariate linear and logistic regression analysis showed that OPN was significantly related to cfPWV and was an independent predictor of AS. The receiver operating characteristic curve analysis showed that OPN was correlated with AS with an area under the curve of 0.903 (95% CI 0.809–0.961,  Cardiovascular diseases (CVD), which may be caused by traditional risk factors, such as diabetes mellitus (DM) and hypertension (HTN), as well as other specific risk factors, have been reported to be related with the worse prognosis of patients with chronic kidney disease (CKD) . Aortic Osteopontin (OPN) was initially found to be a calcium-binding glycophosphoprotein that is involved in bone remodeling, and was later known to have multiple roles in promoting the inflammatory process, such as cell recruitment to inflammatory sites, cell attachment, and wound healing. It was reported to be a mediator in regulating the pathogenesis of sepsis, and had a role in predicting the survival or recovery from renal replacement therapy in patients with acute kidney injury ,9,10. InAlthough OPN has been considered to have a role in a variety of diseases, its relationship with AS in patients on hemodialysis (HD) had been controversial . MoreoveFrom June 2015 to October 2016, with approval from the Protection of Human Subjects Institutional Review Board (IRB103-136-B), patients who underwent regular PD for more than three months at a medical center were included. Participants were excluded if they refused to sign informed consent or had an acute illness, such as infection, malignancy, stroke, heart failure, acute coronary syndrome, or amputation, at the time of blood sampling. All participants provided informed consent before participating in this study.Data on the adequacy of dialysis, which included the weekly fractional clearance index for urea (Kt/V), total clearance of creatinine, and peritoneal clearance of creatinine, were retrospectively reviewed and collected from the medical records. The morning systolic blood pressure (SBP) and diastolic BP (DBP) of all patients were measured three times at five-minute intervals by trained staff using standard mercury sphygmomanometers with appropriate cuff sizes and after having the patient rest for at least 10 min. HTN was defined as SBP ≥ 140 mmHg and/or DBP ≥ 90 mmHg, or as a receipt of any antihypertensive medication in the past two weeks. DM was defined as fasting plasma glucose > 126 mg/dL or the use of oral hypoglycemic medications or insulin.A total of 70 patients on PD were enrolled in this study. Of these patients, 50 received continuous ambulatory PD , with three to five dialysate exchanges per day; the 20 remaining patients underwent four to five dialysate exchanges each night with an automated device ).Body mass index (BMI) was calculated as the body weight in kilograms divided by the square of the height in meters. It was measured individually to the nearest half centimeter and to the nearest half kilogram, with each patient wearing light clothing and no shoes.g for 10 min. Within 1 h of collection, the serum samples were stored at 4 °C and sent for biochemical analyses. Serum levels of blood urea nitrogen, creatinine, fasting glucose, albumin, total cholesterol, triglyceride, total calcium, phosphorus, and C-reactive protein (CRP) were measured using an autoanalyzer . The serum levels of the OPN  and intact parathyroid hormone (iPTH)  were quantified by commercially available enzyme-linked immunosorbent assays [In the morning before exchanging the dialysate, approximately 5 mL of blood sample was collected from each participant and was immediately centrifuged at 3000× The cfPWV was transcutaneously measured by recording the arterial pressure pulse waveform on applanation tonometry , as previously described . Measuret-test. Variables with non-normal distribution  were expressed as median and interquartile range (IQR), and were compared between the groups using the Mann–Whitney U-test. Categorical variables were expressed as number (percentage) and were analyzed by the χ2 test. The risk factors for developing AS were determined by multivariate logistic regression analysis. The associations of cfPWV with the variables were analyzed by simple and multivariate forward stepwise linear regression analysis. The receiver operating curve (ROC) was used to calculate the area under the curve (AUC) to identify the optimal cutoff value of OPN so as to predict a high AS in patients on PD. Data were analyzed using SPSS for Windows . A p value of <0.05 was considered statistically significant.Continuous variables were analyzed for normal distribution using the Kolmogorov–Smirnov test. Variables that had a non-normal distribution were logarithmically transformed for linear regression analysis. Normally distributed continuous variables were expressed as mean ± standard deviation (SD) and were compared between the groups using two-tailed independent Student’s p = 0.001), had longer PD vintage (p = 0.024), and had higher serum levels of CRP (p = 0.005) and OPN (p < 0.001), but had a similar proportion of men and women, PD model, BMI, frequency of coexisting DM and HTN, adequacy of dialysis, and medications used, including the usage of calcium carbonate, calcitriol, and Icodextrin.The clinical characteristics of the 70 patients included in this study are presented in p < 0.001) and PD vintage  (p < 0.001)  . For the< 0.001) .r = 0.394, p = 0.001), logarithmically transformed (log) CRP , and serum log-OPN level . After adjusting for these covariates by multivariable forward stepwise linear regression analysis, the log-CRP  and log-OPN levels  were found to be independently correlated with cfPWV (For the simple linear regression analysis, cfPWV was positively correlated with age (th cfPWV .This study showed that patients on PD and with high OPN levels had a high risk of developing AS. In addition, OPN levels could be a predictor of AS, independent of age, sex, comorbidities, and medications used.Aside from the traditional CV risk factors, including DM, hyperlipidemia, and elevated BMI, as well as mineral metabolism derangements that cause elastin fragmentation and medial layer calcification in CKD, aging might contribute to the structural and functional changes in vessels and have been shown to be related with the development of AS ,22,23. IOPN is a hyperphosphorylated extracellular matrix protein that has a variety of functions in the immune system, cell viability or proliferation, and wound healing. It is a key factor in atherosclerosis and is now being regarded as an important mediator of atherosclerotic plaque formation and arterial calcification ,15,29,30The limitation of this study was its cross-sectional design with a limited number of patients on PD. Therefore, the causal relationship of serum OPN with AS and the role of OPN in the development of AS in patients on PD should be confirmed by further longitudinal studies.In conclusion, along with old age, high CRP, and long duration on PD, the serum OPN level could be a novel biomarker for predicting the development of AS in patients on PD. OPN might modulate the process of AS, but the mechanism remains to be studied.


Examine the effect of fasting during Ramadan on kidney functions in patients with chronic kidney disease.The study was conducted on 130 patients with stage III-IV chronic kidney disease (CKD), who were admitted to the Ordu University nephrology polyclinic during the month before Ramadan and one month after Ramadan in 2019. Blood samples were taken in the morning after 12 hours of fasting.post-<0.001). The eGFR was 14.826 points higher in those who fasted after Ramadan than in those who did not.There was a statistically significant difference between BUN in the fasting group before and after the month of Ramadan. The median BUN before Ramadan was 26.65 mg/dl, the median after Ramadan was 24.05 mg/dl (p=0.004).There was a statistically significant difference between the nonfasting groups before and after Ramadan with respect to creatinine level. Median creatinine before Ramadan was 1.69 mg/dl,and the median after Ramadan was 1.86 mg/dl (p <0.001).There was a statistically significant difference between the fasting groups before and after Ramadan with respect to creatinine levels. Fasting group ,the median before Ramadan was 1.5 mg/dl, and the median after Ramadan was 1.42 mg/dl (p = 0.038).The impact of independent variable of fasting, using linear regression was found to be statistically significant (pFasting during the month of Ramadan does not deteriorate kidney functions and even leads to a moderate improvement in kidney functions. Taking these results into consideration, fasting may be advised for patients with stage III-IV CKD who want to fast and remain in stable condition. Fasting from dawn to dusk during the holy month of Ramadan has been prescribed to all Muslims.6Ramadan may lead to complications such as dehydration, low blood pressure and hyperviscosity, all of which cause more kidney damage and susceptibility to thrombosis in patients with chronic kidney disease.8Some studies have suggested a temporary improvement in the estimated glomerular filtration rate (E-GFR) and the decline in proteinuria in patients with CKD or kidney transplant.To perform our study, ethical approval was obtained (No 2018/114 dated 24.05.2018) from the Ordu University Clinical Research Ethics Committee. It included 130 patients with stage III-IV CKD admitted to the Ordu University. Patients with malignancies, advanced heart failure, acute infection, diabetes mellitus using insulin as well as patients on dialysis and recipients of kidney transplants were excluded. The diagnosis of dialysis CKD was established according to the KDIGO guideline.112)).Complete blood count was examined using the CELL-DYN RUBY  device. Routine biochemical analysis were measured using the COBAS c501  module. BMI was computed in all patients (BMI = weight (kg)/height  and with respect to average body mass index (p=0.820). The comparisons of kidney function tests and all biochemical parameters are presented in Tables-There was a statistically significant difference between fasting groups before and after Ramadan with respect to BUN. The median BUN before Ramadan was 26.65 mg/dl, and the median after Ramadan was 24.05 mg/dl(p=0.004). There was a statistically significant difference between the non fasting groups before and after Ramadan with respect to creatinine level. Median creatinine before Ramadan was 1.69 mg/dl, and the median after Ramadan was 1.86 mg/dl (p<0.001). Similarly statistically significant difference was seen between the fasting groups before and after Ramadan with respect to creatinine levels. The median before Ramadan was 1.5 mg/dl, and the median after Ramadan was 1.42 mg/dl (p =0.038).Moreover, there was statistically significant difference between the groups post-Ramadan with respect to median uric acid level and between fasting groups before and after Ramadan with respect to mean uric acid level. The median uric acid level pre-Ramadan was 6.64mg/dl, and the median post-Ramadan was 6.36 mg/dl (p=0.021).There was a statistically significant difference between the fasting groups before and after Ramadan with respect to glucose level (p=0.038).The median glucose level before Ramadan was 111mg/dl, and the median after Ramadan was 102.5 mg/dl and in pre-Ramadan groups with respect to median HbA1c. The median of those who did not fast was 6%, and the median of fasted was 5.7% (p=0.016). Statistically significant difference was also seen between the post-Ramadan groups with respect to median HbA1c. The median of those who did not fast was 6.05%, and the median of those who fasted was 5.7% (p=0.011).post=25.838,ppost<0.001).The eGFR value of those who fasted after Ramadan was 14.826 points higher than that of those of who did not. When the impact of the independent variable of fasting (which affects eGFR pre-Ramadan) was examined using linear regression, the established regression model was found to be statistically significant .The eGFR value of those who fasted before Ramadan was 10.415 points higher than that of those of who did not. The results of our linear regression analysis are presented in When the impact of the independent variable of fasting (which affects E-GFR post-Ramadan) was examined using linear regression, the established regression model was found to be statistically significant  were examined in a study in the literature. After the month of Ramadan, the changes in the baseline values of eGFR between the fasting and non-fasting groups were not significantly different. These findings suggest that eGFR did not change significantly in the patients with chronic kidney disease yet fasting during Ramadan may damage the kidney tubular cells of these patients.5The changes in the kidney functions of 15 chronic kidney disease patients who fasted during Ramadan  is a standard kidney damage test, in which protein  is abnormally excreted.Chowdhury et al. did not find any significant change in HbA1c levels in their study on stage 3 CKD and Type 2 DM patients.In another study conducted by Kara et al., fasting did not affect potassium levels.14Serum uric acid levels increase in chronic kidney failure. Because hyperuricemia might occur due to decreases in kidney function with CKD, hyperuricemia itself can cause chronic kidney failure and lead to progression of the disease.The effects of fasting on lipid metabolism are not clearly known. El-Wakil et al. found that fasting had no effect on the lipid metabolism of CKD patients.Our cases are from a single region. The absence of long-term results is another limitation of our study.Fasting of CKD patients during the month of Ramadan was well-tolerated and did not disrupt kidney functions in stage III-IV CKD patients. Contrary to popular belief, fasting during the month of Ramadan does not impair kidney functions and even leads to moderate improvement in kidney functions. The same situation is true for metabolic parameters. Considering these results, patients with stable stage III-IV CKD under close monitoring can be recommended to fast.AK: Concept, Study Design, Literature review, Data collection, prepared the manuscript and is responsible for integrity of research.EC: Literature review, Data collection, Final review, Study design, Data collection.YKA: Conduct the study, Data collection and analysis.MK: Conduct the study, Data collection and analysis.BS: Literature Review, Data Collection, Final review.


Cardiac surgery is performed worldwide, and acute kidney injury (AKI) following cardiac surgery is a risk factor for mortality. However, the optimal blood pressure target to prevent AKI after cardiac surgery remains unclear. We aimed to investigate whether relative hypotension and other hemodynamic parameters after cardiac surgery are associated with subsequent AKI progression.We retrospectively enrolled adult patients admitted to 14 intensive care units after elective cardiac surgery between January and December 2018. We defined mean perfusion pressure (MPP) as the difference between mean arterial pressure (MAP) and central venous pressure (CVP). The main exposure variables were time-weighted-average MPP-deficit  and time spent with MPP-deficit > 20% within the first 24 h. We defined other pressure-related hemodynamic parameters during the initial 24 h as exploratory exposure variables. The primary outcome was AKI progression, defined as one or more AKI stages using Kidney Disease: Improving Global Outcomes’ creatinine and urine output criteria between 24 and 72 h. We used multivariable logistic regression analyses to assess the association between the exposure variables and AKI progression.Among the 746 patients enrolled, the median time-weighted-average MPP-deficit was 20% [interquartile range (IQR): 10–27%], and the median duration with MPP-deficit > 20% was 12 h (IQR: 3–20 h). One-hundred-and-twenty patients (16.1%) experienced AKI progression. In the multivariable analyses, time-weighted-average MPP-deficit or time spent with MPP-deficit > 20% was not associated with AKI progression . Likewise, time spent with MPP-deficit > 20% was not associated with AKI progression . Among exploratory exposure variables, time-weighted-average CVP, time-weighted-average MPP, and time spent with MPP < 60 mmHg were associated with AKI progression .Although higher CVP and lower MPP were associated with AKI progression, relative hypotension was not associated with AKI progression in patients after cardiac surgery. However, these findings were based on exploratory investigation, and further studies for validating them are required.Trial Registration UMIN-CTR, https://www.umin.ac.jp/ctr/index-j.htm, UMIN000037074.The online version contains supplementary material available at 10.1186/s13613-021-00969-4. Cardiac surgery is performed worldwide –5. AcuteAlthough blood pressure (BP) is a vital determinant of renal perfusion, the optimal BP target to prevent AKI progression remains unclear for intensive care unit (ICU) patients. Previous randomized controlled trials (RCTs) assessed different absolute mean arterial pressure (MAP) targets , 12. SubMoreover, relative hypotension, defined as a deficit between the premorbid and achieved BP, has been investigated as a BP target to prevent AKI progression. The Kidney Disease: Improving Global Outcome (KDIGO) guidelines suggest that the optimal BP target may vary according to the premorbid level . SeveralAccordingly, we conducted a multicenter retrospective cohort study to test whether the relative hypotension using MPP during the first 24 h would be associated with AKI progression between 24 and 72 h among postoperative cardiac surgery patients. We also explored the relationship between other BP-related parameters and subsequent AKI progression.The Blood pressure and Relative Optimal Target after Heart surgery in Epidemiologic Registry (BROTHER) study was a multicenter retrospective cohort study enrolling adult patients after cardiac surgery in 14 ICUs in Japan . All study patients were followed up until hospital discharge or 30 days after the surgery, whichever came later. The ethics committee of Kameda Medical Center (No. 19-013) and the ethics committees of all other participating hospitals approved this study with an opt-out policy from the patient or proxy. The need for informed consent was waived due to the retrospective nature of this study.We consecutively included all adult patients aged 18 years or older who were admitted to one of the ICUs after elective coronary artery bypass grafting (CABG) or valve surgery between January 1st and December 31st in 2018. We excluded (i) patients who were discharged from the ICU within 24 h; (ii) patients who underwent emergency cardiac surgery; (iii) patients on extracorporeal membrane oxygenation, intra-aortic balloon pumping, or ventricular assist device during the first 24 h after ICU admission; (iv) patients with postoperative BP recorded at an interval of longer than 1 h; (v) patients without available BP recordings within 365 days before the surgery; (vi) patients who opted out of this study; and (vii) patients censored for data collection. We defined emergency cardiac surgery as urgent surgery for a life-threatening condition to save life or prevent organ dysfunction. We excluded patients after emergency cardiac surgery because we assumed that detailed information about preoperative blood pressure was often not available, and the calculation of MPP deficiency would be inaccurate.We collected demographic data, comorbidities, Acute Physiology and Chronic Health Evaluation (APACHE) II score , SequentWe defined MPP as the difference between MAP and CVP. The preoperative BP was defined as the average of three recent BP readings recorded at least one day apart within 1 year before the surgery. We calculated preoperative MAP as diastolic BP + (systolic BP − diastolic BP)/3. The preoperative CVP was estimated using inferior vena cava data from preoperative echocardiographic findings according to the 2010 American Society of Echocardiography guidelines . When prWe collected postoperative MAP and CVP at 1-h intervals during the first 24 h after ICU admission and assumed the CVP value as the average value every 4 h. When there was no available CVP measurement within any 4-h interval, we imputed the CVP value closest to the timepoint.The primary exposure variable was time-weighted-average MPP-deficit. We defined MPP-deficit as (preoperative MPP − postoperative MPP)/preoperative MPP. We calculated the time-weighted-average MPP-deficit as an aggregate area-under-the-curve divided by 24 h, where the area-under-the-curve was measured as an integrated expression over time using a positive incremental method. When the postoperative MPP was higher than the preoperative MPP, we regarded the MPP-deficit at the timepoint as zero. The secondary exposure variable was time spent with MPP-deficit > 20%, a threshold considered as a significant relative reduction in BP , 21. We The primary outcome variable was AKI progression. We defined AKI progression as an increase of at least one AKI stage between 24 and 72 h compared to the first 24 h. We defined patients with AKI progression as the AKI group and patients without AKI progression as the Non-AKI group. We used both the creatinine and urine output criteria of KDIGO . The intAmong the patients meeting the eligibility criteria, we excluded from our analysis: (i) patients with end-stage kidney disease; (ii) patients with a preoperative serum creatinine > 3.5 mg/dL; (iii) patients who lacked urine output data during the first 24 h after ICU admission; (iv) patients with stage 3 AKI within the first 24 h after ICU admission; (v) patients with < 50% CVP recordings within the first 24 h after ICU admission, and (vi) patients who underwent reoperation during the first 24 h after ICU admission. In all variables except for CVP, we reported the number of missing data if we had missing data and excluded cases with missing data from each analysis. We described how to impute missing postoperative CVP values in “U test for continuous variables. The impact of all exposure variables on AKI progression was assessed using multivariable logistic regression analyses adjusted for age, APACHE II score, chronic hypertension, preoperative left ventricular ejection fraction, baseline serum creatinine, surgery time, cardiopulmonary bypass (CPB), intraoperative fluid balance, and postoperative red blood cell transfusion within 24 h after ICU admission. We selected these variables based on the clinical relevance and their importance as risk factors for AKI in previous studies [We presented categorical variables as numbers with percentages and continuous variables as medians with interquartile range. We compared baseline characteristics and hemodynamic parameters between AKI and Non-AKI groups using the Chi-square test or Fisher’s exact test for categorical variables and the Mann–Whitney  studies , 31–35. p value < 0.05 as statistically significant.All analyses were conducted using Stata version 16  and EZR , which is a graphical user interface for R . We considered a two-sided We conducted three sensitivity analyses. First, the type of surgery determines the necessity of CPB, which can influence intraoperative management  and is aAmong 1568 adult patients admitted to the ICUs after CABG or valve surgery between January and December 2018, we registered 870 patients on the BROTHER study. During the data collection period of this study, a pandemic of COVID-19 occurred, which made data collection difficult for some investigators, and we could not enroll 42 patients. After excluding 124 patients, we analyzed 746 patients . Among the exploratory exposure variables, time-weighted-average CVP , time-weighted-average MPP , and time spent with MPP < 60 mmHg  were statistically significantly associated with AKI progression.Multivariable logistic regression analyses  and mean arterial pressure-deficit (b) during the first 24 h after intensive care unit admission.