Expanded criteria donor (ECD) kidneys are commonly used but are associated with increased graft failure. Graft failure is in turn related to rehospitalization within thirty days post transplant. Our goal was to determine whether ECD kidneys independently lead to rehospitalization within 30 days, 1 year, and 2 years after transplant.  All adult first-time recipients of deceased donor kidneys transplanted from 2003–2012 at our center were reviewed. Models included demographics, medical comorbidities, center for disease control high-risk kidney, ECD kidney, ischemia times, cause of renal failure, immunosuppressive regimen, positive psychiatric screening, alcoholism, surgeon, year the transplant was performed, years on dialysis before transplant, and the number of inpatient hospitalizations within 6 months prior to transplant. We conducted Andersen–Gill modeling and propensity score matching followed by logistic regression. We also used multivariable linear regression to predict average length of stay during rehospitalization. p=0.014). Thirty-day and 2-year time marks were not significant. Andersen–Gill models predicting successive hospitalizations yielded HR of 1.42 (p=0.002) and 1.32 (p=0.015) for ECD patients at 1 and 2 years of after transplantation, respectively. Propensity score matching and logistic regression showed a significant relative risk of 1.630 at one year (p=0.033) and 1.313 at two years (p=0.268). There was no significant association between ECD and subsequent lengths of hospital stay.  More ECD patients had a rehospitalization at 1 year (70.3% versus 59%, log-rank test  Receiving an ECD kidney is independently associated with multiple readmissions within 2 years of transplant but unrelated to length of stay. Driven by the increasing waiting list and coupled with a diminution in deceased organ donation, kidneys previously considered unacceptable for transplantation have come into widespread use under the sobriquet of “Expanded criteria donor” (ECD) . RecipieAfter institutional review board approval was obtained from Albert Einstein College of Medicine (IRB number 2014–3276), we utilized the transplant database at the Montefiore Medical Center to identify all patients who had received a deceased donor kidney transplant from January 1, 2003, through December 31, 2012. Pediatric recipients were excluded from the study because they do not receive ECD kidneys at our center. Repeated transplants and multiorgan recipients were also excluded from the study because we did not want prior transplants or other organs to alter the risk for rehospitalization via immune sensitization. HLA mismatch is not a determinant in our institution for determining organ acceptance, and therefore, these data were not analyzed. Patient data were obtained through Clinical Looking Glass , the Montefiore Transplant Database, and direct review of the electronic medical record . Death wRehospitalization is defined as any inpatient admission occurring after discharge from kidney transplantation. The Charlson Comorbidity Index is the summation of the patient's medical comorbidities prior to transplant aggregated into one numeric value. The value increases with increasing age from 40 and also increases with the number of medical comorbidities patients had prior to surgery. For further descriptions of weights of different comorbidities, refer , 11. TheThe occurrence of a readmission at one and two years after kidney transplant (KT) was demonstrated by cumulative incidence curves (inverse of a Kaplan–Meier). We used the log-rank test at 30 days, 1 year, and 2 years to determine whether there was a significant difference in readmissions at those time points. We used a Bonferroni correction for multiple tests within the same survival plot, with an adjusted alpha of 0.05/3 = 0.0167. Multivariable analysis of readmission was modeled using an Andersen–Gill (AG) analysis, which allowed us to model the proportional effect of covariates on multiple readmissions, not just the hazard ratio for one readmission . For AG,The following variables were considered as potential covariates in AG: age of recipient (dichotomized using an age threshold of 65), race, diabetes, peripheral vascular disease, BMI, center for disease control high-risk kidney, Charlson Comorbidity Index, cold ischemia time, warm ischemia time, ECD kidney, causes of end stage renal disease (ESRD), hepatitis C virus status, induction type (basiliximab or thymoglobulin), immunosuppressive regimen (mycophenolate mofetil (MMF), tacrolimus, and sirolimus), surgeon who performed the transplant, years on dialysis before transplant, year the transplant was performed, and the number of inpatient hospitalizations 6 months before transplant.For further verification of the AG results, nearest neighbor propensity score matching without replacement or discard was carried out. The ratio of SCDs to ECDs for matching was 3 : 1. The following covariates were used a priori for matching: years on dialysis before transplant, age and cause of ESRD as outlined above, BMI, year transplant was performed, the number of inpatient hospitalizations within 6 months of transplant, race, and Charlson Comorbidity Index. After matching, the resulting weights were used in logistic regression models to predict rehospitalization at 1 and 2 years after transplant.To examine which covariates were most predictive of mean length of stay (LOS) for all subsequent hospitalizations in the following two years, we used the Leaps algorithm. This algorithm uses an exhaustive search function to find the best covariates to include in a model according to the Bayesian information criterion . For modAll of the covariates from the AG models were considered potential covariates for LOS model inclusion, except for whether or not the patient was rehospitalized. The ECD status was “forced-into” the algorithm, meaning that all results would include the ECD status.p value of 0.05 or less statistically significant unless otherwise stated. All confidence intervals are 95%, and all tests are two-tailed unless otherwise noted. Categorical variables were described by absolute numbers and percentages. Continuous variables were described using the mean and standard deviation, or the median if the data were skewed. We employed use of the Mann–Whitney U test for some univariate analyses when our data did not appear to fit a normal distribution. All analyses were performed using R, an open source statistical computing software, along with associated packages [We considered a packages . Tables packages . The surpackages , 21. Propackages . The Leapackages .From January 1, 2003, to December 31, 2012, 746 kidney transplants were performed at our institution. After excluding pediatric recipients (79 patients), multiple organ recipients (2 patients), and patients previously transplanted (118 patients), 547 patients were included in our study. In our cohort, the median recipient age was 54 years; 164 (30.01%) patients in our cohort received an ECD kidney. Our cohort was 41.0% Black, 36.7% Hispanic, 10.3% White, and 11.6% other. Median time on dialysis was 4.13 years prior to transplant. Median BMI was 26.72. The median cold ischemia and warm ischemia times were 1285.0 minutes and 40.0 minutes, respectively. Median LOS immediately after transplant was 7.00 days. Comparisons of recipient and donor variables among patients who received ECD and SCD kidneys are shown in . There wp=0.877) nor the number of days missed  varied significantly between the ECD and SCD groups. These same tests also failed to reach significance when only studying patient deaths .There were 74 patients with incomplete follow-up during the study leading to an overall loss of 5.30% of potential follow-up days. Of the 74 patients with incomplete follow-ups, 47 were due to graft failure and 27 were due to early death. Of the 74 patients with incomplete follow-ups, there was no difference between ECD and SCD patient groups for both graft failure and patient death. The other patients in our cohort, including the ECD patient group, were readmitted due to various other reasons. Neither the number of patients with incomplete follow-up . However, 1 year following KT there was a greater prevalence of rehospitalization among patients who received ECD kidneys . This p value remained significant after Bonferroni correction for multiple tests . This significant difference was no longer observed 2 years after KT .Cumulative incidence curves were used to analyze the number of patients rehospitalized after KT. Thirty days after KT, there was no difference in rehospitalization between ECD and SCD recipients  and two years (p=0.002), ECDs had a greater number of total readmissions. We further analyzed the effect of the ECD status and other covariates on the risk of multiple successive hospitalizations using Andersen–Gill (AG) models (p=0.002) and 2 years of 1.32 (p=0.015). Other significant variables in our 1-year AG model were time spent on dialysis prior to transplantation and total number of admissions 6 months before transplantation (p=0.065). The AG model we employed has the same required assumptions as a Cox proportional-hazards model, mainly that variables affect the outcome proportionally over time. We tested this assumption of proportionality by graphing the Schoenfeld residuals and also by performing chi-squared goodness of fit tests between each covariate and time, transformed according to the Kaplan–Meier curve. There was a statistically significant departure from proportionality for both ECD (p=0.023) and number of admissions 6 months prior to transplant (p ≤ 0.001). Therefore, the hazard ratios for ECD and previous admissions were not constant with time. To further validate that the differences in rehospitalization at 1 and 2 years were in fact due to ECD status and not the other variables, and propensity-score matched logistic regression was performed to isolate the effect of the ECD status alone. The relative risk (RR) for rehospitalization was found to be significant for the ECD status at 1 year  but insignificant at 2 years .When considering the potential influence of ECD kidneys on multiple readmissions, we used a one-tailed Mann–Whitney ) models . AG modeantation . Time ofOur study demonstrated that receipt of an ECD kidney led to a 63% increase in risk for rehospitalization within the first year. All inpatient readmissions occurred exclusively at our center. A statistically significant association was present irrespective of whether an AG model or a propensity score matched logistic regression model was used. We however found a statistically significant departure from the proportional hazards assumption in our AG model. While this does not invalidate our results, it suggests that the effect of those variables is more complex than the assumption of proportionality would allow. Put differently, the strength of the effect these variables have on rehospitalization changes with time. This makes sense because ECDs were significantly associated with rehospitalization at 1 year, but not 30 days or 2 years after transplant according to our log-rank tests.This study highlights the importance of considering alternative metrics when evaluating the equivalence of ECD kidneys to SCD kidneys. Many studies have compared the two kidney groups on the basis of delayed graft function and overall graft survival. We believe that rehospitalization is a worthy metric in its own right. The various reasons for readmission and/or hospital charges for all readmitted patients are not available. By 2006, rehospitalization after kidney transplant already cost an average of 13,678 dollars . In addiStudies have shown that patients over the age of 60 take longer time to recover from surgery than previously believed –28. In aThere are few studies which compared ECD versus SCD in relation to rehospitalization. A study combining retrospective and prospective data conducted by Stratta et al. in 2006 found no association between ECDs and rehospitalization with just 77% of patients followed for a year or more . We beliAlthough the ECD status was significantly associated with rehospitalization, it did not reach statistical significance for predicting mean LOS. Mean LOS was significantly associated with a history of alcoholism, taking sirolimus, or having a longer initial length of stay. The most clinically significant of these would be alcoholism and initial length of stay, as they had larger effect sizes.A recent study reinforced the risk of using ECD kidneys, finding adjusted hazard ratios of 1.46 to 1.20 for all-cause mortality in different age groups up to age 70 . Other sThis study has important limitations, one of which is the retrospective design. Although every effort was made to include confounding factors into the multivariable analysis, it is possible that there is a confounding variable which influences both ECD/SCD status and rehospitalization rates. Only a randomized controlled trial can fully eliminate unforeseen biases. Another limitation of our study was missing data. Although the vast majority of patients in our study had complete follow-up time and follow-up time did not differ between ECD and SCD recipients, it is possible that those patients lost to follow-up could be vastly different from the patients who completed the study, hence affecting our results. HLA mismatch data were not analyzed for our study, and therefore, recipient immunological risk at transplant might be incompletely controlled in our study.This study utilized a unique patient population . We have a higher proportion of Black and Hispanic patients than other transplant centers . FurtherImportantly, our results use an aging metric to assess kidney quality. The Kidney Donor Profile Index (KDPI) and Kidney Donor Risk Index (KDRI) have recently supplanted the classification of ECD/SCD . Our conAfter extensive multivariable modeling and propensity score matching, we observed an association between receipt of an ECD kidney and increased risk for multiple rehospitalizations within 1–2 years after transplant. This effect should be replicated and further characterized. Patients should fully understand their risks before choosing an ECD kidney.


Background: Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability through Motor Evoked Potential (MEP) amplitude measurements. The input-output (I/O) curve is a sigmoid-shaped relation between the MEP amplitude at incremented TMS intensities. The aim of this study was to examine the relationships between seven parameters derived from the sigmoid function.Methods: Principal Component Analysis and Spearman's rank correlation matrices were used to determine if the seven I/O curve parameters capture similar or, conversely, different aspects of the corticospinal excitability in 24 healthy subjects and 40 stroke survivors with a hand motor impairment.Results: Maximum amplitude (MEPmax), peak slope, area under the I/O curve (AUC), and MEP amplitude recorded at 140% of the resting motor threshold showed strong linear relationships with each other . Results were found to be similar in healthy subjects and in both hemispheres of stroke patients. Our results did not support an added benefit of sampling entire I/O curves in both healthy subjects and stroke patients, with the exception of S50, the stimulus intensity needed to obtain half of MEPmax amplitude.Conclusions: This demonstrates that MEP elicited at a single stimulus intensity allows to capture the same characteristics of the corticospinal excitability as measured by the AUC, MEPmax and the peak slope, which may be of interest in both clinical and research settings. However, it is still necessary to plot I/O curves if an effect or a difference is expected at S50. Transcranial magnetic stimulation (TMS) is widely used to probe corticospinal excitability in both healthy subjects and in a broad range of neuropsychiatric conditions. A common approach from basic research to pivotal clinical trials is to compare recruitment curves of TMS-induced motor evoked potentials (MEPs) between groups of subjects or before and after different types of interventions aimed at promoting brain plasticity .vs. stimulus intensity and fitting the data with the following sigmoid function equation (MEP(s) is the MEP amplitude at the stimulation intensity s, MEPmax is the maximum MEP amplitude, S50 is the stimulus intensity needed to obtain 50% of MEPmax amplitude, and m is the slope parameter of the sigmoid function, i.e., the global slope of the function  the x-intercept (Xint) of the tangent at S50, and (3) the area under the I/O curve (AUC) usually calculated using the trapezoidal area method (The input-output (I/O) relation in the corticospinal pathway is assessed by plotting MEP amplitude equation –4: MEP(sfunction . Three a/(1+expmS0-s), whemax, it does not mean these three parameters are correlated together. Same for Xint, which depends on m parameter and S50. The question arises whether these variables capture similar or, conversely, different aspects of the corticospinal excitability and if so, how each of them relates to one other. To clarify the interdependency between these parameters, we estimated I/O curves from the dominant hemisphere of healthy volunteers and performed Principal Component Analyses (PCA) in addition to correlation matrices to summarize the most important linear relationships between variables. PCA is a tool capable of summarizing the most important linear relationships between variables and computing synthetic variables from the original variables named principal components (PCs). PCA provides a visual and geometric representation of the correlation matrix  and were collected before the intervention stage of the study. The study was approved by the appropriate legal and ethical authority  in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.Inclusion criteria for healthy participants were (1) no history of neurological or psychiatric disorders, (2) Mini-Mental State Examination ≥27, (3) age older than 18 years, (4) no contraindications to TMS and, (5) no use of psychoactive medication or recreational drugs.Patients were recruited according the following inclusion criteria: (1) ischemic stroke >1 month old, (2) no history of psychiatric disorders as determined through an interview by a trained neurologist, (3) Mini-Mental Status Examination ≥27, (4) age older than 18 years, (5) no contra-indications for TMS, and (6) presence of an upper-limb deficit  with some preserved hand movement (maximum finger flexors voluntary contraction >0 Newton).All subjects were tested with the Edinburgh handedness inventory (EHI) with a cut-off of 0.2 to be considered as right-handed , 9.offline analysis with the Signal software . Anatomical T1-weighted Magnetic Resonance images were entered into a computerized frameless stereotaxic system . MEPs were elicited using a MAGSTIM 2002 stimulator  connected to a figure-of-eight-shaped coil with an internal wing diameter of 7 cm. The handle of the coil was held pointing postero-laterally in order to induce a current in the brain from the posterior-lateral to the anterior-medial (PA) orientation. The coil was first held tangentially to the scalp over the presumed hand knob area as determined by the anatomical 3D reconstruction of each participant's brain. The optimal coil position was then determined as the site where TMS at a suprathreshold intensity consistently produced the largest MEPs in the contralateral FDI muscle. The coil position was continuously monitored using a neuronavigation system to ensure its constant position over the “hotspot” tangentially to the head surface. TMS pulses were delivered at 0.2 Hz. The resting motor threshold (rMT) was defined in both hemispheres as the minimum stimulation intensity needed to elicit recordable MEPs in the relaxed FDI of >50 μV in 5 out of 10 consecutive trials  muscles of both hands at rest, in a belly-tendon montage using Ag/AgCl surface electrodes . EMG signals were amplified ×1000), filtered with a band pass of 0.02–2 kHz , digitalized at 5 kHz via a Power 1401 data acquisition interface  and stored for 00, filteoffline and those showing voluntary EMG activity in the 100 ms prior to stimulus artifact resulting in MEP amplitude facilitation (>2 SD of mean MEP amplitude without EMG) were discarded and peak-to-peak MEP amplitudes were measured in the remaining trials  in an incremental order with steps of 10% rMT according to the IFCN guidelines  for subsequent statistical analysis: MEPmax, S50, m, PS, Xint, AUC and MEP amplitude at 140% rMT derived from the I/O curve (IO140) according to the IFCN recommendations (R2) of the I/O curve were also calculated.This procedure was carried out in the dominant hemisphere of healthy subjects and in both the affected and unaffected hemispheres in stroke patients. The following seven electrophysiological parameters were computed ndations . The coeTo examine the relationships between the seven different electrophysiological variables, Principal Component Analysis (PCA) were performed separately for the dominant hemisphere of the healthy subjects and for each hemisphere of stroke patients with the seven electrophysiological variables , 7. AddiBecause of the non-normal distribution of the data, as assessed by Shapiro-Wilk's tests, Spearman's rank coefficient matrices were used to examine relationships between electrophysiological variables. Confidence intervals were obtained through bootstrapping with 5,000 iterations .Furthermore, we tested the absence/presence of multicollinearity to demonstrate equivalence. To that purpose, the variance inflation factor (VIF) was computed using JASP . By convention, multicollinearity is considered present if the VIF of one variable is higher than 10 .Wilcoxon paired signed-rank tests were employed to assess statistical differences in I/O curve parameters between hemispheres in stroke patients.P-values for each correlation matrix were adjusted using the Benjamini-Hochberg method ], median age:  and forty stroke patients [14 females (35%)], median age: , median time since stroke: 106 days [48–276], min-max: 31–1,764) with upper limb motor impairment were enrolled in the study.All subjects but two healthy participants and one patient, were right-handed. Electrophysiological parameters in the 24 healthy subjects are summarized in max, PS, AUC, and IO140 showed strong positive correlations with each other. 50 since (i) the arrow of the PCA was perpendicular to others and, (ii) the correlations were not significant. Because Xint and m were not well-explained by the two first principal components, their relation with the other variables could not be interpreted from the correlation circle.The first two principal components explained 79% of the total variance of the seven electrophysiological variables  in healtElectrophysiological parameters in 40 stroke patients are summarized in max, PS, AUC, and IO140 strongly intercorrelated, regardless of the hemisphere considered .max, PS, and AUC. However, it confirmed that the S50 was independent and showed also that m and Xint were not highly correlated.The variance inflation factor (VIF) is reported for each I/O parameter in the healthy subjects, unaffected and affected hemispheres of the stroke patients in Interestingly, in healthy subjects and stroke patients (unaffected hemisphere), the relationships between the seven electrophysiological variables were similar for MEP amplitudes ranging from 120 to 160% rMT but not when MEP were collected at 110% rMT max, PS, and AUC, were clustered in healthy participants independently from S50. (2) Despite brain damage, I/O curve-derived parameters were similarly clustered and thus intercorrelated in both hemispheres of stroke patients independently from the time post-stroke or the lesion location.There are two new findings in our results. (1) Four I/O curve-derived parameters, namely MEP amplitude recorded at 140% rMT, MEPmax, PS, and AUC) to a single measure of MEP amplitude collected at a given intensity (140% rMT) would provide further information when assessing corticospinal excitability. However, this notion is challenged by the high degree of correlation found between MEPmax, PS and AUC from the I/O curve and MEP amplitude at 140% rMT. Additionally, this relationship exists when MEPs are collected between 120 and 160% rMT; this means that the AUC, MEPmax, and PS can be dropped when measuring MEPs at those intensities.One could expect that adding parameters from the I/O curve . This was also expected for AUC, which is seen as a surrogate marker of the overall corticospinal output and is derived from the gradual summation of outputs as inputs increase. Its value should therefore also strongly relate to the maximum output   , 19–21.max, and the peak slope after stroke. Moreover, this method of assessing corticospinal excitability requires fewer pulses and is thus by far much faster than sampling the full I/O curve, which may be useful in a clinical setting or in research protocols when accounting for patient fatigue .Importantly, even if these four variables are highly intercorrelated, our results do not imply that interventions  will affect all of these parameters similarly. For example, it has been shown that low and high frequency rTMS exerts a more complex influence on cortical network excitability, as assessed by an I/O curve, than simple inhibitory and facilitatory effects, usually assessed with MEP amplitudes collected at a single intensity . Similar/O curve , 26, sugFinally, using a single stimulus intensity does not allow the operator to know how large is the portion of the motoneuronal pool activated. However, as displayed in Considering the short interstimuli interval (5 s), the incremental order of stimulus intensity may induce a hysteresis effect with a systematic rightward shift of the I/O curve . HoweverR2 values were excellent in both healthy subjects and stroke patients. Finally, given that our parameters were collected at rest only, we cannot extrapolate our observations to data collected under an active condition.Our study has several limitations. First, we did not study the test-retest reliability of each metric of the I/O curve, which can be another deciding factor beyond redundancy to determine which variable to drop. However, in previous studies, the intraclass coefficients of the IO parameters for the FDI muscle has been shown to be good to excellent (>0.6), indicating a good reliability in healthy subjects , 30 and 50. However, to what extent our results rely on individual characteristics in neuronal function or anatomy such as the number or the coherence of corticospinal tract fibers is not clear and unknown. Nevertheless, this finding may raise doubts about the pertinence of systematically acquiring such measurements, especially in both clinical and research settings.We examined the relationship between I/O curve parameters and MEP amplitude recorded at a single intensity. Although I/O curve analysis can convey some additional information, our results did not overall support an added benefit of sampling entire recruitment curves in both healthy subjects and stroke patients, except if an effect or a difference is expected at SThe study was approved by the appropriate legal and ethical authority  in accordance with the Declaration of Helsinki. Written informed consent was obtained from all participants.J-CL and CR were involved in the conception and the design of the project. They also participated in the data collection with EM, SL, and CK. CK has analyzed the data with MH and drafted the manuscript with CR and J-CL. SM was involved in the interpretation of the results and has revised it critically for important intellectual content. EM, native English speaker, has also proofread the text.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.


IN vitro, primary cultured human ovary granulosa cells (GCs) were isolated from the follicular fluid (FF) extracting from PCOS patients and controls. FF, especially which extracted from PCOS patients with a high expression of serum testosterone, significantly induced cell apoptosis and inflammation in human GCs. To examine the communication between PCOS and kidney injury, a human proximal tubular epithelial cell line (HKC‐8) was cultured and administered FF. Interestingly, FF from PCOS patients with a higher level of serum testosterone induced fibrotic lesions in HKC‐8 cells. These data suggest serum testosterone plays a critical role in PCOS and PCOS‐associated kidney injury. Serum testosterone may serve as a promising indicator for kidney fibrotic injury outcomes in PCOS patients.Polycystic ovary syndrome (PCOS) is closely related with the onset and development of metabolic abnormalities. However, the correlation between PCOS and kidney injury has not been clarified, and the underlying mechanism remains unknown. Herein, we performed a prospective survey in 55 PCOS and 69 healthy participants. Furthermore, the correlation analyses between serum testosterone and renal functional manifestations of patients and healthy subjects, including urinary albumin to creatinine ratio (UACR), urinary κ‐light chains (KapU), urinary λ‐light chains (LamU), urinary α1‐microglobulin (α1‐MU), and urinary β2‐microglobulin (β2‐MU), were analyzed. Compared with that in normal subjects, the levels of serum testosterone and UACR were significantly higher in PCOS patients. Serum testosterone is significantly correlated with the disease severity of PCOS. Although urinary excretions of KapU, LamU, α1‐MU, and β2‐MU did not increase in PCOS patients, they had a significantly positive correlation with the extent of serum testosterone in PCOS patients.  Polycystic ovary syndrome (PCOS) is the most common type of endocrine disorders in women of reproductive age. Up to 20% in women of childbearing age worldwide are suffering PCOS , dyslipidemia, hypertension, anxiety, depression, obstructive sleep apnea, endometrial cancer, fatty liver, and cardiovascular diseases  is a gradual loss of kidney function over months to years. Without early preventing and treatment, CKD could eventually progress into the disease state of uremia, an end‐stage kidney disease with significantly increased mortality , λ‐light chains (LamU), α1‐microglobulin (α1‐MU), and β2‐microglobulin (β2‐MU), the markers of tubular proteinuria  were obtained from additional five PCOS patients with hyperandrogenism, five PCOS patients with normal expression of testosterone and five control participants. FF was collected from the PCOS patients with hyperandrogenism and controls.PCOS was diagnosed according to the 2003 Rotterdam Criteria, with at least two of the following symptoms: (1) oligomenorrhea/amenorrhea; (2) polycystic ovaries (PCO) on ultrasonography; (3) clinical and/or biochemical signs of hyperandrogenism (hirsutism or acne) and exclusion of other etiologies . Clinical features including menstrual cycle, the number of antral follicles (AFC), body mass index (BMI), mean arterial pressure (MAP) as well as endocrine and biochemical parameters  were recorded. The demographic and clinical data of the patients with PCOS are presented in Tables g for 10 min, and supernatants were obtained and stored at −80°C until further analysis. The urinary albumin to creatinine ratio (UACR), KapU, LamU, α1‐MU, β2‐MU, and urinary creatinine (UCr) were measured by automatic‐specific protein analyzers  in National Clinical Research Center of Kidney Disease in Nanfang Hospital, Southern Medical University. The kits were purchased from SIMENS9. The value of the UACR as well as KapU, LamU, α1‐MU, and β2‐MU were normalized to UCr.One hundred and twenty‐four urine samples from 55 PCOS patients and 69 control subjects were collected before participants were treated with assistant reproductive technology. The urine samples were centrifuged at 3000in vitro fertilization and embryo transfer. In brief, ovarian hyperstimulation was achieved with the use of recombinant follicle‐stimulating hormone (FSH) from the third day of menstruation and adjusted as needed according to the ovarian response. Gonadotropin‐releasing hormone antagonist (GnRHant) was started in patients until they were triggered after the fifth day of COH. Transvaginal ultrasound‐guided oocyte retrieval was performed 35 h after the injection of human chorionic gonadotropin (hCG). The follicular fluid (FF) samples were obtained from the first‐punctured follicle (18−25 mm in diameter) during the oocyte aspiration. The samples were then centrifuged at 800g for 10 min, and the supernatants were stored at −80°C until further analysis. The testosterone expression in FF was analyzed. The GCs were isolated from FF obtained during oocyte retrieval for IVF from each subject. Briefly, FF was first centrifuged at 400g for 10 min. The pellet was resuspended with PBS, and then layered on 50% Percoll and centrifuged at 400g for 20 min. The volume ratio between PBS and 50% Percoll was 3:2. Three layers could then be distinguished, and the middle white layer was collected and washed with PBS at 600 g for 8 min at least twice. One milliliter of TRIzol reagent was added to the collected GCs  until RNA analysis.An antagonist protocol for controlled ovarian hyperstimulation (COH) was used in the cycle of HKC‐8 cells, a human kidney proximal tubular cell line, were cultured in DMEM–Ham’s F12 medium containing 10% fetal bovine serum. HKC‐8 cells were treated with DMEM medium containing 10% FF for 24 h. The cells were then collected for various analyses.−ΔΔCT). Relative levels of mRNA were reported after normalization with β‐actin. The composition of the primers was as follows: caspase3: forward 5’‐GAAATTGTGGAATTGATGCGTGA‐3’, reverse 5’‐CTACAACGATCCCCTCTGAAAAA‐3’; NLRP3: forward 5’‐CGTGAGTCCCATTAAGATGGAGT‐3’, reverse 5’‐CGACCCTGTCCCTCAAATCC‐3’; actin: forward 5’‐CTCACCATGGATGATGATATCGC‐3’, 5’‐AGGAATCCTTCTGACCCATGC‐3’.The mRNA expression levels of caspase 3 and NLRP3 in GCs were analyzed by qRT‐PCR. Total RNA was extracted with TRIzol reagent  and cDNA was synthesized with the Reverse Transcription System kit . qRT‐PCR was performed using SYBR Green PCR MasterMix (Applied Biosystems), according to the kit instructions by an ABI PRISM 7000 Sequence Detection System . The PCR reaction system contained 12.5µL SYBR Green PCR MasterMix (Applied Biosystems), 5µL diluted RT product (1:10), and 0.5 mmol/L sense and antisense primer sets. The expression levels of various genes were determined by the comparative CT method . After separation on 10% SDS‐PAGE gels, the protein was transferred to membranes, which were later incubated with primary antibodies: anti‐fibronectin , anti‐α‐SMA , and α‐tubulin  overnight at 4°C. The signals were visualized using the enhanced chemiluminescence system . Relative protein abundance was calculated after normalizing with α‐tubulin.HKC‐8 cells were cultured on coverslips and fixed with 4% paraformaldehyde for 15 min at room temperature and immersed in 0.2% Triton X‐100 for 10 min. After blocking with 10% donkey serum for 30 min, the cells were immunostained with primary antibodies against fibronectin  and a Cy3‐conjugated secondary antibody . Photos were taken with fluorescence microscopy .n (%). Student’s t test and the Mann–Whitney U test were used to compare normally and non‐normally distributed variables, respectively. Correlations were conducted using Spearman’s correlation coefficient for non‐normally distributed data. Continuous variables among groups were compared using one‐way analysis of variance, followed by the LSD test. Statistical analyses were conducted with SPSS 22.0 software. A value of P < 0.05 was considered statistically significant.Continuous variables are shown as the means ± SD, and categorical variables are expressed as A total of 124 participants aged between 23 and 40 were enrolled. Among 55 patients with PCOS, hyperandrogenism  was observed in 24 (43.64%) patients.2), and testosterone (T) in the PCOS group were significantly higher compared to controls. There were no significant differences in GLU, FSH, and prolactin (PRL) between two groups (Table Two PCOS patients (3.64%) showed a slight increase in blood pressure  and higher BMI index . While the blood pressure in each of 69 controls was normal. One control subject showed slight increases in fasting glucose (GLU) (6.42 mmol/L) and BMI index 26). None was diagnosed hyperglycemia among 55 PCOS patients. Due to the small proportion of participants with the abnormal rate of BP and GLU, hierarchical analysis was not performed. The groups were matched in terms of age. Whereas, the BMI, length of the menstrual cycle, number of total antral follicles , basal levels of luteinizing hormone (LH), estradiol (EP < 0.05) in PCOS patients compared with controls. However, SCr and BUN showed no significant difference. Although no significant differences in the levels of KapU, LamU, α1‐MU, and β2‐MU, there was a rising trend for these tubular proteinuria markers in PCOS patients. Additionally, the proportion of patients with UACR higher than 7 mg/g was 45.45% in PCOS patients and 44.93% in controls.Previous studies have shown that PCOS links to abnormalities including obesity, DM, and cardiovascular disease. Notably, all these abnormalities are major risk factors for the progression of CKD  , and metabolic dysfunction. Notably, PCOS patients often complicate with hyperandrogenism. To further clarify the responsibility of testosterone for the disease severity of PCOS, we analyzed the correlation between serum testosterone and the length of the menstrual cycle or number of total antral follicles . We also assessed the association of testosterone with BMI, MAP, and GLU, the three metabolic symptoms that commonly display in PCOS. As shown in Table 1) Table . HoweverTo identify the role of serum testosterone in PCOS‐associated kidney injury, we performed Spearman’s correlation analysis in two groups. First, the correlation between serum testosterone and UACR in two groups was analyzed. There was no correlation between them in two groups (data not shown). We next assessed the urinary levels of KapU, LamU, α1‐MU, and β2‐MU, which represent the proteinuria originated from renal tubular epithelia cell injury. All of them were performed correlation test with serum testosterone. As shown in Table P < 0.01), suggesting the important role of testosterone in GCs injury.To further confirm the effects of testosterone on PCOS injury, we cultured primary GCs. The cells were collected from the follicular fluid (FF) samples of five PCOS patients with hyperandrogenism (with high testosterone), five PCOS patients with non‐hyperandrogenism  and five healthy controls. First, the levels of testosterone in FF were analyzed Fig. A. We nexTo further identity the correlation between PCOS and kidney injury, we cultured HKC‐8 cells and treated cells with FF from PCOS patients with hyperandrogenism and healthy controls. The fibrotic injury markers of fibronectin and α‐SMA were assessed by western blot analyses. As shown in Figure PCOS has a close association with the progression of metabolic abnormalities such as obesity, diabetes and hypertension, which are the major causes of kidney disease  in our study. We then explored the association between serum testosterone and the disease severity of PCOS. Abnormality of the menstrual cycle is one of the critical characteristics in PCOS patients. The prolongation of the menstrual cycle could result in the high frequency of anovulation, which would lead to amenorrhea, infertility, endometrial hyperproliferation and even carcinogenesis (Barry et al., .64% in oOther studies have revealed testosterone in the FF in PCOS patients is higher than that in controls (Qu et al., We further investigated the role of testosterone in PCOS‐associated kidney injury. We performed correlation analyses of serum testosterone with the urinary excretion levels of KapU, LamU, α1‐MU, and β2‐MU, the markers of kidney tubular injury (Yu et al., To the best of our knowledge, this is the first study that demonstrates a definitive relationship between PCOS and kidney injury. First, our clinical analysis showed that UACR is higher in PCOS patients than controls, suggesting that PCOS is closely associated with kidney injury. Second, we found that serum testosterone in PCOS patients are positively correlated with the urinary protein excretion levels of which reflect the injury in kidney tubules. These results demonstrate that testosterone plays an important role in PCOS‐associated kidney injury. Third, we analyzed the effects of FF from PCOS patients with hyperandrogenism on HKC‐8 cells. We found the upregulated fibrotic lesions in PCOS FF‐treated HKC‐8 cells, suggesting that testosterone mediates PCOS‐related kidney injury through promoting the fibrosis in tubular epithelial cells.In this study, because mass spectrometry has not yet been established in our clinics, we tested the total testosterone in serum by the chemiluminescence immunoassay but not the “gold standard” testing method of testosterone status such as liquid chromatography‐tandem mass spectrometry. Future studies should be designed to analyze testosterone by multiple methods. Furthermore, a larger sample size including various ethnic backgrounds from different regions should be recruited to verify the conclusion and deeply explore the underlying mechanisms. Specially, studying a prospective cohort of women with PCOS and BMI more than 30 would be more meaningful to assess the association between PCOS and renal injury.Although more studies are needed, these results provide proof of principle that serum testosterone plays a pivotal role in the onset and development of PCOS and PCOS‐associated kidney disease. Continued monitoring and early intervention of serum testosterone would be of great value to prevent the high risk of kidney injury for PCOS patients. Overall, serum testosterone may be regarded as a novel indicative marker for clinical prevention and treatment of PCOS and the related kidney diseases.The authors declare that there are no competing interests associated with the manuscript.This study was approved by the Ethical Committee Faculty of Nanfang Hospital, Southern Medical University, and informed consent was obtained from all of the participants recruited into this study and was carried out in accordance with the World Medical Association Declaration of Helsinki. All methods were performed in accordance with the relevant guidelines and regulations. The number of ethical approvals is NFEC‐2018‐154.Table S1. Demographic characteristics of the participants in the study.Table S2. Parameter values of control subjects and PCOS patients.Table S3. Parameter values in isolated human granulosa cells.Click here for additional data file.


P> 0.05). After adjusting for confounding factors, the nonsignificant tendencies for high risk of type 2 diabetes mellitus and impaired fasting glucose/high risk of type 2 diabetes mellitus to associate with hypertension persisted . Unlike earlier studies, the present study suggests that the level of fasting blood glucose may not be significantly related to hypertension in aging patients with benign prostatic hyperplasia.Evidence suggests there maybe an association among abnormal fasting blood glucose, hypertension and benign prostatic hyperplasia. In this study, we investigated whether abnormal fasting blood glucose correlates with hypertension in aging benign prostatic hyperplasia patients. Ultimately, 612 benign prostatic hyperplasia patients, including 230 hypertensive patients and 382 normotensive patients, were included. Univariate and multivariate logistic regression analyses were used to evaluate the associations. The results indicated that neither impaired fasting glucose/high risk of type 2 diabetes mellitus nor high risk of type 2 diabetes mellitus were associated with an increased risk of hypertension. When patients were stratified based on the severity of their hypertension, similar results were obtained (all  Hypertension is a global problem with high morbidity. In China, the prevalence of hypertension has reached 29.6%, along with an increasing rate of obesity . MetabolP<0.001)  after measuring the largest anteroposterior , transverse , and cephalocaudal  prostate diameters.IFG in this study was defined as a blood glucose level ≥5.60 mmol/L (100.80 mg/dL) and <7.00 mmol/L (126 mg/dL); a FBG level >2.8mmol/L (50.40 mg/dL) and <5.60 mmol/L was defined as normal FBG (4.00-5.59 mmol/L23), and HR-T2DM was defined as a FBG level > 7.00 mmol/L (126 mg/dL) with one of the other indexes  from the national clinical practice guideline in China (2017 version), which was developed by the Chinese Diabetes Society –34. HypeThe patients were classified into two groups (0 for the normotensive group and >0 for the hypertensive group), and the statuses of the hypertensive participants were presented as four levels, from healthy to severe. FBG levels were graded as normal, IFG and HR-T2DM, and were further categorized into normal and abnormal groups. Basic characteristics were examined in the overall population and subgroups. Categorical variables were shown as counts (percentage) while continuous variables were shown as the mean ± standard deviation (SD). Comparisons of continuous variables between the normotensive and hypertensive groups were made using t-tests for continuous variables and chi-squared tests or Fisher exact test for categorical variables.Logistic regression was implemented to explore the potential relationship between FBG level and hypertension level, and Ors with their corresponding 95% CIs were calculated. Binary logistic regression was conducted with normotensive and hypertensive groups as a dependent outcome. Ordinal logistic regression was performed for the four ordinal levels of hypertension. In these models, the effects of two types of FBG estimation was done: polytomous  and binary . The confounders adjusted for in models included age, BMI, t-PSA, IPSS, resting heart rate, marital status, history of alcohol drinking and cigarette smoking, complicating disease (yes or no), and hemoglobin level. Missing values for the drinking and smoking status were coded as unknown in multiple models. Two forest plots were constructed to clearly represent the results.Sensitivity analysis was done to determine the robustness of the results by performing nominal logistic regression. All statistical analyses were done using SPSS 19.0 software. Statistically significant tests were two-sided, and a value of P < 0.05 was considered significant.


Patterns and determinants of long‐term oral corticosteroid (OCS) use in asthma and related morbidity and mortality are not well‐described. In a nationwide asthma cohort in Sweden, we evaluated the patterns and determinants of OCS use and risks of OCS‐related morbidities and mortality.Data for 217 993 asthma patients (aged ≥ 6 years) in secondary care were identified between 2007 and 2014 using Swedish national health registries. OCS use at baseline was categorized: regular users ; periodic users ; and nonusers . Relative risks of becoming a regular OCS user and for morbidity and mortality were analysed using multivariable Cox regression.At baseline, 24% of asthma patients had used OCS during the last year and 1.5% were regular users. Of those not using OCS at baseline, 26% collected at least one OCS prescription and 1.3% became regular OCS users for at least 1 year during the median follow‐up of 5.3 years. Age at asthma diagnosis, increasing GINA severity and Charlson Comorbidity Index were associated with regular OCS use. Compared to periodic and non‐OCS use, regular use was associated with increased incidence of OCS‐related morbidities and greater all‐cause mortality, adjusted HR 1.34 (95% CI 1.24‐1.45).Oral corticosteroids use is frequent for asthma patients, and many are regular users. Regular OCS use is associated with increased risk of morbidity and mortality. These findings indicate that there is a need of other treatment options for patients with severe asthma who are using regular OCS. Annually, almost one in seven asthma patients used oral corticosteroids, which was stable over the 10‐year study period. Oral corticosteroids are still a substantial part of current asthma management for many patients and are associated with severe side effects and mortality risk. There is a need for other treatments for severe asthma patients who are using regular oral corticosteroids. This may be due to limited number of countries with access to complete nationwide data. Sweden, with its nationwide, longitudinal and mandatory registers is an ideal setting to study OCS treatment in asthma from a whole population perspective.The aim of this study was to evaluate the patterns of OCS use and its potential determinants, and the associations between OCS use and the risk of OCS‐related morbidities and all‐cause and cause‐specific mortality for asthma patients diagnosed in secondary care.22.1This was a prospective, longitudinal, observational cohort study utilizing national Swedish health registries: (a) The National Patient Register (NPR) covering all hospital admissions since 1987 and outpatient specialist visits since 2001; (b) the Prescribed Drug Registry, covering all collected outpatient drug prescriptions since July 2005 using the anatomical Therapeutic Chemical (ATC) codes; and (c) the Cause of Death Register.2.2The study population included all asthma patients between 12 and 45 years in Sweden during 2007‐2014 in outpatient or inpatient secondary care, and a drug claim for obstructive lung disease (ATC R03). A defined index date and baseline period was utilized to classify patients into different OCS usage groups. The index date was the date of first asthma diagnosis and the baseline period was from the index date up to 365 days post index.asthma diagnosis only before the age of 6 years,patients with <365 days of follow‐up from index date,drug claim of oral glucocorticoid other than prednisolone (ATC H02AB06) and betamethasone (ATC H2AB01) any time prior to index date or during the baseline period.The following exclusion criteria were used:The reason for this is that prednisolone and betamethasone are the only OCS recommended for treatment of asthma in the Swedish Asthma Guidelines.Use of OCS equivalent to >20 mg/d of prednisolone during the full 1‐year baseline period as a higher dose would typically be used for conditions other than asthma.Patients with other conditions for which systemic corticosteroids may be prescribed  were excluded.Medical history data were retrieved from the NPR by ICD‐10 codes during 10 years prior to the date of asthma diagnosis and during the baseline period, except for current malignancies which was retrieved within 12 months prior asthma diagnosis and during the baseline period.2.32.3.1Oral corticosteroids use during the baseline period was classified using the collected mean daily dosage per year  of prednisolone or betamethasone: regular users ; periodic users ; and nonusers . During follow‐up, OCS nonusers at baseline who subsequently collected OCS were further classified as regular OCS users (average ≥ 5 mg/d/y); ≥1 OCS collected; and patients dispensing ≥2 OCS.2.3.2Data on potential determinants of OCS use was collected at index date: age, sex, severity of asthma  and Charlson Comorbidity Index.2.3.3Patients were followed prospectively for OCS use and death from the first day after the baseline period until date of death, emigration, dispense of OCS other than prednisolone and betamethasone, date of diagnosis of conditions for which systemic corticosteroids may be prescribed (see exclusions criteria), malignancies or end of follow‐up (31 December 2016), whichever occurred first. Assessment of comorbidity and mortality was performed prospectively from the end of the baseline period until date of death, emigration or end of follow‐up (31 December 2016), whichever occurred first.2.4Primary outcomes were OCS‐related morbidity and mortality. For morbidity, we considered the following OCS‐related complications that occurred during follow‐up: diabetes, osteoporosis, fractures, glaucoma, ischaemic heart disease, hypertension, psychiatric conditions, hypercholesterolaemia and sleep disorders. For mortality, we considered death from all causes during follow‐up, as well as cause‐specific mortality categorized using the underlying cause of death: respiratory related (ICD‐10: J as main cause of death), cardiovascular related (ICD‐10: I), cancer related (ICD‐10: C) and other.2.5Baseline characteristics were described as mean (standard deviation [SD]) for continuous variables and absolute and relative frequencies for categorical variables. For continuous variables the Kruskal‐Wallis rank sum test and for categorical variables the chi‐squared test were applied to test for difference between baseline OCS exposure groups. Regular OCS use during follow‐up was assessed through a sliding window of 365 days with patients collecting at least 1825 mg of prednisolone equivalent classified as regular OCS users. Cox proportional hazard models were applied to estimate hazard ratios (HR) with 95% confidence intervals (CI) of possible risk factors for becoming a regular OCS user for non‐OCS users at baseline. Age at asthma diagnosis, sex, asthma severity (GINA steps) and comorbidity (Charlson Comorbidity Index) were explored individually as well as in multivariable adjusted analysis. Potential OCS‐related morbidities were presented as age‐ and sex‐adjusted rates during follow‐up. Risk factors for all‐cause mortality were analysed using Cox proportional hazard regression, including baseline OCS exposure, age at asthma diagnosis, sex and comorbidity (Charlson index) explored individually and in mutually adjusted analysis. OCS use, risks of morbidities and cause‐specific mortality were analysed using Fine‐Gray regression accounting for competing risks of death.3.Overall, 356 446 patients with a diagnosis of asthma and a collected asthma drug were identified, of whom 217 993 fulfilled the eligibility criteria during the observation period and were included in the study .Each year, approximately 15% of the patients collected at least one OCS, which was relatively stable during the follow‐up period Figure . Mean daP < 0.001).During follow‐up, more regular OCS users were hospitalized with asthma as the main reason for contact. Age‐adjusted hospitalization rate was 3.66 (3.22‐4.09) per 100‐patient‐years, compared with 1.48 (1.42‐1.54) in the periodic users and 0.51 (0.49‐0.53) in non‐OCS users. The proportion of patients seen in specialist care was similar between regular OCS users (41.3%) and periodic (42.2%) and nonusers (40.1%), although statistically significant different , and 20.1%  had collected two or more OCS prescriptions Figure . Of the 3.2Of the non‐OCS users at baseline, older age at asthma diagnosis was the strongest independent risk factor for becoming a regular OCS user during follow‐up: people 65+ had a 19 times greater risk  compared with people <18 years  adjusted for age, sex and Charlson Comorbidity Index , that may also be indications for OCS treatment in severe asthma patients. As our intention was to describe the OCS use directly related to asthma, we utilized a conservative approach and excluded patients with bronchiectasis in order not to overestimate the OCS use that is directly related to asthma. We did, however, include rhinitis and rhinosinusitis as regular OCS treatment is seldom use in these conditions. Furthermore, there is always a risk that some of the patients have a COPD component together with their asthma diagnosis. However, we have excluded patients with COPD at baseline, and patients were censored if/when a COPD diagnosis was recorded during follow‐up. In addition, few patients were treated with typical COPD therapy alone at baseline (LABA as monotherapy without ICS [1.0%] or fixed LABA/LAMA monotherapy without ICS [<0.1%]), thus the impact of a potential COPD component is limited.A potential source of underreporting of OCS use could be the exclusion of other OCS medications than the ones we have included in the analyses. However, only 1.3% of the patients collected other types of OCS during follow‐up, thus the impact of the exclusion of other OCS medications can be regarded as limited Figure . AnotherThere are few comparable studies having a nationwide population perspective on OCS use in an asthma population. Some reports describe the overall OCS use for patients in primary care, and there are reports on determinants for OCS use and OCS‐related adverse events in different asthma populations.Our results indicated that, annually, almost one in seven asthma patients had used OCS, which was stable over the 10‐year study period. Of the non‐OCS users at baseline, a cumulative risk of 35% and 20% for prescribing one or more than one OCS prescriptions during follow‐up was observed. OCS use is considered to be a marker of uncontrolled asthma, either as exacerbation treatment or as a regular maintenance treatment to prevent disease deterioration.A large proportion of the regular OCS users continued with regular therapy during the 10‐year study period, with a mean daily dosage of 5.5 mg, a dosage which in many countries is considered to be a low maintenance dosage and in line with GINA recommendations.Compared with periodic and non‐OCS use, regular use was associated with greater all‐cause mortality. This observation persisted even after adjusting for sex and age. There were more deaths among the regular OCS users compared to non‐OCS users particularly related to cardiovascular disease, malignancies, other reasons (mainly dementia related) and respiratory diseases. We cannot rule out that patients with severe and terminal illness might have been prescribed regular OCS therapy without a related diagnosis in a hospital setting. However, we think that it is unlikely that such patients would have received regular OCS therapy over a full calendar year. Our findings of increased risk of deaths among regular OCS users when compared to nonusers agree with reports from other previous studies.The present findings have several potential clinical implications. The GINA guidelines recommend assessment, life style counselling and regular monitoring of patients with asthma who receive OCS as maintenance therapy with treatment lengths for 3 or more months.The GINA guidelines also recommend that patients with severe asthma should be managed by asthma specialists.In conclusion, the present findings demonstrate that OCS therapy is still a substantial part of current asthma management for a high percentage of patients and that regular OCS use is associated with severe side effects and mortality risk. The study indicates that there is a need for use of other treatment options for patients with severe asthma who are using regular OCS.PH and GT are employed by AstraZeneca. FW is employed at Statisticon for which AstraZeneca is a client. ME, BN and CJ report no conflict of interest relevant to this article.Data collection was performed by JB. Statistical analysis was conducted by FW and ME. Analysis, interpretation and drafting of the manuscript were conducted by ME and PH and in cooperation with the other authors. All authors approved the manuscript before submission.The study was approved by the Stockholm regional ethics committee (registration number 2017/4:2). The linkage of registers data was approved and performed by the Swedish National Board of Health and Welfare. Patients do not need to give consent for use of public register data in Sweden.All authors read and approved the final manuscript. All authors gave consent to publish these data. Click here for additional data file.


Although invasively measured blood pressure (invBP) is regarded as a “gold standard” in critically ill cardiac patients, the non-invasive BP is still widely used, at least at the initiation of medical care. The erroneous interpretation of BP can lead to clinical errors. We therefore investigated the agreement of both methods with respect to some common clinical situation.diastolic pressure + (pulse pressure ÷ 3)). We used Bland-Altman analysis and we calculated concordance correlation coefficients to assess agreement between different BP methods.We included 85 patients hospitalized for cardiogenic shock. We measured BP every 6 h for the first 72 h of hospitalization, in all patients. Each set of BP measurements included two invasive (invBP), two auscultatory (auscBP), and two oscillometric (oscBP) BP measurements. InvBP was considered as a gold standard. Mean non-invasive arterial pressure (MAP) was calculated as  contains supplementary material, which is available to authorized users. Invasively measured arterial blood pressure (invBP) measurement is an integral part of the management of critically ill patients and is considered to be the gold standard for blood pressure (BP) measurement. However, at least at the initiation of medical care (before other more urgent measures are taken), BP is measured non-invasively. Indeed, some data suggest that in real clinical practice it is not unusual for BP to be assessed non-invasively in critically ill patients . We mighSeveral papers have reported data showing agreement between invBP and non-invasive auscultatory (auscBP) or oscillometric (oscBP) BP measurements in patients hospitalized in intensive care units. These reports included patients admitted for a variety of conditions  as summarized by Lakhal . HoweverDifferences in BP measurement methods have the potential to impact clinical outcomes. In a large intensive care unit (ICU) database, severe, non-invasively assessed, systolic hypotension was associated with a significantly higher prevalence of acute kidney injury and ICU mortality than invasive systolic BP readings within the same BP range . During In the present study we therefore investigated how non-invasive BP measurements agree with invasive BP measurements and which clinical conditions or factors can influence the accuracy of auscultatory and oscillometric measurements in patients with cardiogenic shock.2), use of extracorporeal membrane oxygenation, intra-aortic balloon counter-pulsation, and cannula insertion into other than the left or right radial artery.This prospective study included 85 patients with cardiogenic shock hospitalized at the Coronary-Care Unit (CCU) of the University Hospital in Pilsen, Czech Republic between March 2017 and April 2018. We used following criteria for cardiogenic shock: (i) systolic blood pressure < 90 mmHg for > 30 min or vasopressors required to achieve a blood pressure ≥ 90 mmHg; (ii) pulmonary congestion or elevated left-ventricular filling pressures; (iii) signs of impaired organ perfusion with at least one of the following criteria: (a) altered mental status; (b) cold, clammy skin; (c) oliguria; (d) increased serum-lactate. We included patients in whom invasive blood pressure monitoring was indicated. None of the patients received an intra-arterial catheter only for the purpose of the study. The management of the patient was guided exclusively by invBP with the target invasive mean arterial pressure (invMAP) value ≥70 mmHg. Exclusion criteria were as follows: extreme obesity .First was the invasive BP value; next were two auscultatory BP measurements; followed by two oscillometric measurements; and lastly the second invasive BP measurement was recorded. For BP comparisons, the mean values of each pair of BP measurements were used. BP measurements were repeated in the same patient every six hours for 72 h; thus we expected to obtain12 sets of BP measurements for each patient (1020 sets of measurement). However, seven patients were dismissed from the CCU before end of the study. Moreover, in four cases we were not able to measure oscillometric BP. The values of invasive and auscultatory BP in these cases were: 108/79 and 110/70; 50/20 and 40/20; 105/78 and 110/70; 102/65 and 100/60 mmHg. In two times atrial fibrillation was present, in other two cases frequent supraventricular of ventricular extrasystoles were present. Therefore, number of BP sets totaled 967. In non-invasive measurements, systolic (SBP) and diastolic BP (DBP) were recorded and mean arterial pressure (MAP) calculated according to the formula: MAP = DBP + ((SBP-DBP) ÷ 3). For invasive measurements, we directly recorded MAP, SBP, and DBP. Only nine experienced nurses  were responsible for taking all BP measurements. At the time of each BP measurement, the following were are also recorded: the patient’s Glasgow coma score, body temperature, electrocardiogram, Richmond Agitation-Sedation Scale (RASS), information on patient sedation, and whether the patient had received (was receiving) vasopressive or inotropic medications.A 20-gauge cannula was inserted into the right or left radial artery and connected to a disposable pressure transducer ; B. Braun Melsungen AG, Germany) using 100-cm-long tubing. The transducer system was set up by an experienced nurse and checked by a physician in all cases. The forearm was at the same level as the brachial cuff  to eliminate hydrostatic pressure. Air bubbles were carefully flushed from the system before data collection. The zero level for the arterial blood pressure was taken at the right atrium  and the arterial waveform was displayed on a Solar 8000i monitor . The average resonance frequency of the catheter tubing-transducer system was 20 Hz , combined with a damping coefficient of 0.3. In addition, the correct shape of the BP waveform was ascertained using the “fast flush” test. BP values were measured at the end of expiration assessed using capnography waveform and with the help of monitor freezing at the time of BP reading to minimize the effect of changing intrathoracic pressure on invasively measured BP values . Thus, the higher invasive BP the lower oscillometric BP. Similar finding was observed for auscultatory BP.In a regression analysis accounting for repeated measurements, determinants of mean bias between oscillometric and invasive measurement were invBP . While the patient’s core body temperature was lower than 36 °C 148 sets of measurements were taken. SBP and MAP were lower in hypothermic patients compared to patients with body temperatures higher than 36 °C . Systolic and mean blood pressures where lower when arrhythmia was present. According to BHS protocol both subgroups achieved grade D for oscillometric SBP. However, patients with sinus rhythm achieved grade B for mean arterial pressure, while patients with arrhythmia present achieved grade C . MoreoveThe maximal left ventricle ejection fraction assessed within the first twelve hour after admission was 40%. Eighteen patients, in whom 200 sets of measurement were done, had left ventricle ejection fraction (EF) lower than 30%. Patients with severely reduced EF had lower BP compared to patients with milder systolic dysfunction ; Addijtional file 1 FigureS1). As above mentioned clinical situations which tended to achieve lower reliability assessed as CCC had in general lower BP, it is quite possible that underlying mechanism for this observation is indeed the level of blood pressure . Only MAP reached good agreement according British Hypertension Society protocol . MoreoveLehman et al. recently used a large ICU database to compare invasive arterial and oscillometric BP and demonstrated clinically significant discrepancies between the methods . In concIn our settings, mean bias for systolic and diastolic pressures were in agreement with results of recently published meta-analysis comparing non-invasively and invasively measured blood pressure in more than 3000 subjects . We obseMean arterial pressure reflects perfusion pressure and is the main hemodynamic parameter monitored by the neurohormonal system to control BP. During treatment of shock, MAP is the key pressure. In our study we showed that in hypotensive patients invSBP < 100 mmHg), the mean pressure values obtained by both auscBP and oscBP were inaccurate , which leads to a rise in BP, per se, but also affects radial-brachial pressure relationships .We also observed that mechanical ventilation did not worsen agreement between invasive and non-invasive BP measurement. On the contrary, in mechanically ventilated patients, agreement between invasive and oscillometric (but not auscultatory) DBP and MAP was higher than in spontaneously breathing patients. Mechanical ventilation leads to changes in intrathoracic pressure and thus directly affects monitored BP . Since cMoreover, we did not observe lower agreement between oscillometric BP and invBP compared to auscultatory BP. Although influence of an irregular heart rhythm on the reliability of oscillometric BP measurements is well known and generally accepted , severalFirst, this was a single-center study on a limited number of patients. However, we applied strict quality control of BP measurements and only nine of the most experienced nurses (shift supervisors) performed all BP measurements. Moreover, we used a dual BP tonometer (DM-3000) for both auscultatory and oscillometric measurements. Therefore, we eliminated measurement errors that might have resulted from different types of arm cuffs or cuff positioning. Second, our results, which are based on patients admitted for cardiac shock, might not be extrapolatable to the general population or other critically ill patients. Third, we used calculated non-invasive MAPs  for our analyses. However, we tried to mirror frequent clinical practice as majority of oscillometric tonometers do not give MAP value. It was shown that calculated MAP using broadly used 1/3 rule underestimates real MAP , 16. In Mean arterial pressure  measured non-invasively appears to be in good agreement with invasively measured MAP in patients with cardiogenic shock. From a practical point of view, it is important to acknowledge that several clinical conditions associated with hypotension affect the accuracy of non-invasive MAP or SBP measurements, e.g., presence of shock and therapeutic hypothermia. In these situations, use of invasive measurements should be recommended.Additional file 1:Figure S1. Scatter plots for auscultatory vs. invasive measurements (left panels) and oscillometric vs. invasive (right panels) blood pressure measurements. Figure S2. Effect of severe hypotension on accuracy of non-invasive MAP measurements. Upper panels show scatter plots between invasive and non-invasive measurements in those cases where invSBP < 100 mmHg (n = 80), lower panels for those with invSBP ≥ than 100 mmHg (n = 887). Table S1. BHS grade of agreement between noninvasive and invasive methods: cumulative percentage of absolute difference (mmHg) between invasive BP and other studied methods (auscBP and oscBP). Table S2. Effect of current cardiogenic shock on accuracy of non-invasive BP measurement. Table S3. Effect of therapeutic hypothermia on accuracy of non-invasive BP measurement. Table S4. Effect of mechanical ventilation on accuracy of non-invasive BP measurement. Table S5. Effect of arrhythmia on accuracy of non-invasive BP measurement. Table S6. Effect of severe left ventricular dysfunction on accuracy of non-invasive BP measurement. Table S7. Frequency of potential factors affecting accuracy of non-invasive BP measurement in respect to hypotension (invSBP<100mmHg). (DOCX 464 kb)


We aimed to investigate the relationship between the perioperative hemodynamic parameters and the occurrence of cardiac surgery-associated acute kidney injury.A retrospective study was performed in patients who underwent cardiac surgery at a tertiary referral teaching hospital. Acute kidney injury was determined according to the KDIGO criteria. We investigated the association between the perioperative hemodynamic parameters and cardiac surgery-associated acute kidney injury to identify the independent hemodynamic predictors for acute kidney injury. Subgroup analysis was further performed in patients with chronic hypertension.P = 0.045). Subgroup analyses in hypertensive subjects (n = 91) showed the postoperative nadir diastolic perfusion pressure and peak central venous pressure were both independently related to the development of acute kidney injury .Among 300 patients, 29.3% developed acute kidney injury during postoperative intensive care unit period. Multivariate logistic analysis showed the postoperative nadir diastolic perfusion pressure, but not mean arterial pressure, central venous pressure and mean perfusion pressure, was independently linked to the development of acute kidney injury after cardiac surgery (odds ratio 0.945, Postoperative nadir diastolic perfusion pressure was independently associated with the development of cardiac surgery-associated acute kidney injury. Furthermore, central venous pressure should be considered as a potential hemodynamic target for hypertensive patients undergoing cardiac surgery. Acute kidney injury (AKI) is a frequent and severe complication after cardiac surgery, which has shown to be related to the increased morbidity, mortality and resource utilization –4. The AHowever, hemodynamic parameters, as modifiable risk factors, may be related to the progression of AKI in high-risk patients –11. A nuTo date, a paucity of research has extensively studied the potential links between the systemic hemodynamic parameters, including postoperative extreme values (peak and nadir) of CVP, mean perfusion pressure (MPP), systolic perfusion pressure (SPP), diastolic perfusion pressure (DPP), and the development of AKI in cardiac surgery patients.Accordingly, we investigated potential relationships between profound hemodynamic parameters  and CSA-AKI to establish if patients with AKI exhibited a lower perfusion pressure and higher CVP compared to patients not suffering from AKI.We included all patients admitted in our ICU after cardiac surgery for a period of 3-months (June 1st-Septemper 1st 2015). The Institutional Ethics Committee of Zhongshan Hospital granted permission to study design and data collection, and the need for informed consents were waived because of the noninterventional design of the study.The inclusion criteria were: adult patients (age ≥ 18 years) who underwent elective cardiac surgery with or without CPB and stayed in the intensive care unit (ICU) for ≥24 h following surgery. Exclusion criteria were: patients who underwent cardiac transplantation or emergency operations; patients who had a history of previous renal replacement therapy or kidney transplantation; patients who were deceased ≤24 h after they were admitted to the ICU.Baseline blood pressure (BP) were measured at least three times prior to surgery and averaged for estimation of baseline hemodynamic values. Baseline MAP was estimated from diastolic arterial pressure (DAP) and systolic arterial pressure (SAP) using the standard formula: MAP = DAP + (SAP - DAP) / 3.Intraoperative BP values were measured every 10 min during the surgical period using a radial artery line, which was routinely positioned for hemodynamic monitoring. Time-weighted average (TWA) of intraoperative MAP values during CPB period were estimated as well. Systolic blood pressure values > 299 mmHg or < 25 mmHg were regarded as errors and excluded from the analysis as in the previous study .Differences between the baseline MAP and intraoperative TWA-MAP were presented as absolute delta MAP (baseline MAP – intraoperative TWA-MAP) as well as relative delta MAP (absolute delta MAP/baseline MAP × 100%), respectively.Postoperative BP values were measured every 15 min for 24 h during the ICU period, and postoperative TWA-MAP was estimated over 24 h during such period. Given that hemodynamic parameters variates during the initial phase of ICU admission, the upper limits of the range (ULR) and lower limits of the range (LLR) over the first 24 h were recorded as well. The ULR of each hemodynamic parameter was defined as the highest value achieved within 24 h whereas the LLR was defined as the lowest value achieved within 24 h after ICU admission. The ULR and LLR of CVP within 24 h after surgery were also measured. Postoperative MPP was then calculated from postoperative TWA-MAP within 24 h and extrema (ULR or LLR) values of CVP (MPP = MAP – CVP). Similarly, postoperative DPP and SPP were calculated from postoperative TWA-DAP or TWA-SAP and extrema (ULR or LLR) values of CVP, respectively  .An estimate of the glomerular filtration rate (eGFR) was calculated by the Modification of Diet in Renal Disease (MDRD) formula based on the patient characteristics and baseline serum creatinine, which was defined as the latest measurement prior to surgery. Serum creatinine was measured at least once a day during the postoperative ICU period as a standard of care. All of the subjects were separated into two groups depending on whether they suffered from AKI, defined according to the criteria published in the KDIGO guidelines .Demographic data including gender, age, body weight, height, comorbidities and surgery type, surgical variables, vasopressin administration, fluid administration, erythrocytes transfusion, plasma transfusion, estimated intraoperative blood loss, intraoperative and postoperative urine output, mechanical ventilation time, length of ICU stay, and hospitalization time were obtained from the anesthetic database or electronic medical records.t-test or Mann-Whitney U-test whereas changes in categorical variables were compared using Fisher’s exact test or chi-squared tests in patients with or without CSA-AKI.Continuous data were shown as means ± standard deviation or as a median (interquartile range) whereas categorical data were presented as numbers (%). Potential differences between continuous variables were assessed using a P value of < 0.05 considered to be predictive for CSA-AKI. Given that CPB duration and cross-clamp time were colinear factors, we enrolled only CPB duration in the multivariable analysis. After adjusting for the confounding factors  for the occurrence of AKI, we established independent hemodynamic predictors for AKI development. Subgroup analyses were further performed in hypertensive subjects to establish the independent hemodynamic risk factors for CSA-AKI. Statistical significance was considered to be a two-tailed P value ≤0.05. All of the analyses were conducted using SPSS Statistics for Windows .Patient characteristics, intraoperative variables and postoperative variables were compared using the univariable logistic regression analysis to determine the risk factors for CSA-AKI. We calculated the odds ratio (OR) with 95% confidence interval (CI) for the predictors for AKI. The multivariable logistic regression analysis was further performed using the forward stepwise selection for the hemodynamic variables with a P = 0.003). Acute Physiology and Chronic Health Evaluation III (APACHE III) score, EuroSCORE II at ICU admission, and surgery types were comparable in different patient groups. CPB duration as well as cross-clamp time in AKI group was remarkably longer than non-AKI group . The length of ICU stay and total hospitalization time were statistically longer in AKI patients (both P < 0.05). In-hospital mortality rate was significantly higher in AKI patients   were enrolled in our study. Eighty-eight (29.3%) patients developed CSA-AKI based on the KDIGO criteria . Baseline serum creatinine levels were significantly higher in AKI patients when compared to non-AKI patients , and higher ULR and LLR values of postoperative CVP  in comparison to the non-AKI patients. During the postoperative period, TWA-MAP at 6 h and 12 h was significantly reduced in the AKI groups . In addition, ULR and LLR values of DPP as well as LLR value of MPP in AKI patients were statistically less than non-AKI patients  (Table Table P < 0.05) (Table P = 0.045)  Table . Neverthn = 91). After adjusting for risk factors for AKI , the ULR value of CVP and the LLR value of DPP were both significantly and independently associated with AKI occurrence   at the end of cardiac surgery was independently associated with AKI [Subgroups analyses indicated that the peak value of postoperative CVP also independently contributed to the development of AKI in patients with chronic hypertension. The link between AKI and CVP was most notable in patients with cardiovascular disease , 13. Morwith AKI . Incremewith AKI , 26. HenAs far as we know, the present research is the first to have investigated the relationship between perioperative extensive hemodynamic parameters and CSA-AKI. Based on our results, we suggest the nadir level of DPP may serve as a surrogate for indicating the risk of AKI development. In cardiac surgery patients with decreased DPP, excessive fluid resuscitation should be under deliberation in patients with chronic hypertension. Further interventional studies should be carried out to clarify whether potential therapeutic manipulations such as increasing DPP or limiting CVP may prevent AKI development in cardiac surgery patients.However, our investigation still confers some limitations. First, it was a single-center retrospective study with a relatively small cohort of patients. Our study only enrolled patients who underwent cardiac surgery, limiting the applicability of our findings to general settings. Second, since preoperative CVP values were not available in our database, premorbid perfusion pressure was not taken into account in the analysis. Finally, a causal relationship between relevant hemodynamic variables and the development of AKI may not be established due to the inherent bias of the study design. Therefore, further interventional studies should be carried out to establish possible causal connections between hemodynamic parameters and AKI, which will be beneficial for the hemodynamic management in patients undergoing cardiac surgery.Postoperative nadir DPP was independently associated with the development of AKI. Postoperative peak CVP was significant for AKI in patients with chronic hypertension. Further investigations are needed in the future to verify whether advanced hemodynamic management  may reduce the incidence of CSA-AKI.


After an adjusted analysis, only the waist circumference (odds ratios (OR) = 1.16; confidence intervals(CI)95%: 1.03–1.30), triglyceride , systolic blood pressure  and Chronic Kidney Disease Epidemiology  remained related to urinary sodium excretion. African descendants had a high rate of sodium excretion, especially among those who had hypertension. Abdominal adiposity, triglyceride and systolic blood pressure levels and renal function by CKD-EPI equation were associated to urinary sodium excretion.In most countries, salt intake has been excessive and constitutes one of the main risk factors for disease development, especially hypertension. Factors such as age, gender, sedentary lifestyle, smoking, African descent, obesity, dietary habits and family history of hypertension may be associated with high blood pressure. Studies show a positive association between the excretion of sodium and increased blood pressure. We evaluated the urinary excretion of sodium and associated factors in isolated urine samples of African descendants from remaining Quilombos. We performed a cross-sectional, population-based study with 1162 African descendants living in remaining quilombos in Alcântara, Maranhão, Brazil. Demographic, nutritional, clinical and laboratory data were analyzed. Urinary sodium excretion was estimated using the Kawasaki equation. A multivariate linear regression model was used to identify the variables related to sodium excretion. The average age was 37.6 ± 11.8 years and 51.2% were women. The prevalence of hypertension was 21.3%. The average urinary excretion of sodium was high, especially among the hypertensive (217.9 ± 90.1 vs. 199.2 ± 83.0 mmol/d;  High sodium intake is one of the main risk factors for the development of diseases such as strokes, left ventricular hypertrophy, chronic kidney disease and especially hypertension . AssociaThe excessive consumption of salt has been observed worldwide, ranging from 9 to 12 g per person per day . The WHOSodium excretion in a 24 h urinary sample is considered the gold standard for evaluation of sodium intake. However, the difficulties associated with the accuracy of urine collection may interfere with the results, especially in population studies. Thus, the estimate of sodium intake from the collection of random urine, at a population level, has been increasingly used as a convenient and affordable alternative. Several formulas have been proposed to convert sodium in spot urine into a 24 h excretion estimation using creatinine to monitor urinary concentration .Kawasaki et al.  and TanaBrazilian studies that evaluate the consumption of salt are scarce, mainly in minority groups where there are differences in the amount of salt intake. These differences may be attributed partly to the evidence of changes in eating habits and the westernization. These factors may result in diseases and death by hypertension and other cardiovascular diseases in future . Thus, wThis is a cross-sectional population-based study that included African descendants living in the city of Alcântara, Maranhão, Brazil. This study was part of the research project ‘Prevalence of chronic kidney disease in quilombo communities of Alcântara, Maranhão state(PREVRENAL)’. The PREVRENAL is a population-based cohort which evaluated, during July 2012 to April 2013, 1162 African descent individuals in 32 remaining Quilombo communities from Alcântara, Northern Maranhão. This study was approved by the research ethics committee at University Hospital, Federal University of Maranhão (HUUFMA), São Luís, Maranhão, Brazil.Quilombos can be defined as ethnic and racial groups according to self-award criteria, with its own historical trajectory, endowed with specific territorial relations with presumption of descent from Afro-Brazilian slaves. In general, Quilombos have a certain degree of geographical isolation and cultural practices that have a strong relationship with the past .The participants were selected by probabilistic sampling, per conglomerates in two phases. The first consisted of the identification of the census sectors (139 Quilombos); 32 of these sectors were then selected. The homes in each sector were chosen at random sampling, based on the calculation of the sample size. From the selected houses, all individuals aged 18 y or above were invited to participate in study. To those who accepted, explanations about the purpose of the study were given and they signed an informed consent (IC).As a non-inclusion criteria, the following was adopted: individuals under 18 and over 59 y of age, pregnant women, patients with consumptive chronic diseases (cancer or acquired immunodeficiency syndrome), hematological diseases, autoimmune diseases, systemic infection or genitourinary tract infection, chronic and/or acute kidney disease under dialysis and those using immunosuppressive drugs or with thyroid disorders based on clinical history and physical examination.In order to calculate the sample size, a pilot study with 76 African descendants from the studied population was conducted to estimate the average rate of sodium excretion. Assuming an average sodium excretion rate of 211.4 mmol/d, standard deviation of 71.4 mmol/d and a sampling error of 7 mmol/d, we obtained a sample size of 810 individuals. Considering eventual losses, the sample was increased by 10%. Nevertheless, owing to this study makes part of the PREVRENAL project, 1162 African descent people who met the inclusion criteria composed the sample.The data collection occurred in two stages and was conducted by a multidisciplinary team. All directly involved researchers who were trained on implementation procedures, such as filling out forms, informed consent, measurement of blood pressure, anthropometric measurements, collection of laboratory tests and confidential information.The initial stage of the study consisted of collecting household data through interviews using a structured questionnaire regarding demographic and socioeconomic data, lifestyle, previous medical history, medication consumption, use of health services and blood pressure measurements.For the evaluation of the economic condition, the family monthly income was categorized into multiples of minimum wages (which in Brazil was approximately $US 296.19) and also the Criterion of Brazilian Economic Classification (CCEB), defining classes in metropolitan areas, were considered. The CCEB divides the population into seven classes: A1 and A2, B1 and B2, C, D and E, from best to worst . The eduAfter the questionnaire, the blood pressure (BP) was measured on the individual’s right arm while seated, resting for at least five minutes, using a digital sphygmomanometer , with an appropriate cuff covering approximately 80% of the arm area. Three measurements were made with a minimum interval of three minutes each. The first measurement was discarded and the average of the other two was obtained. To classify the BP, the proposal made by the VI Brazilian Guidelines on Hypertension was used .After BP measurements, two collectors of urine, each previously identified by the name and numbers one and two, for the first and second urine of the collection day, respectively, were delivered to individuals. The first sample was used for urine sediment and the second for analysis of creatinine and sodium excretion. The subjects were instructed on collection procedures and storage. The need to fast for blood collection and clinical exams were also explained. They were also instructed to attend a location pre-determined by researchers the next day to deliver the urine samples and to collect blood.®, Brazil) and height (meters) with a stadiometer , both following the recommended techniques.In the second stage, one day after the interview, the collection of biological material and anthropometric measurements were conducted. Weight (Kg) was measured on a portable digital scale (Plena2). The classification recommended by the WHO was used. The following was considered: underweight, BMI <18.5 kg/m2; normal weight, BMI ≥18.5 and <25 kg/m2; overweight, BMI ≥25 and <30 kg/m2 and obese, BMI ≥30 kg/m2. The waist circumference (WC) in centimeters (cm) was measured at the midpoint between the last rib and the iliac crest at expiry, using a non-extensible anthropometric tape . The adopted cutoff point was high risk, WC ≥94 cm for men and ≥80 cm for women and very high risk, WC ≥102 cm for men and ≥88 cm for women  – 79.9 ;24 h PrCr (mg) = [ +  - (4.72 × age)] – 74.95 ;0.5.24 hour urine Na excretion estimation (mg) = 23 × 16.3 × {[Na (mEq/L) in the spot urine/Cr (mg/dL) in the spot urine × 10] × PrUCr24h}The excretion estimation of the 24 h urinary creatinine (24 hPrCr) and the ratio Na/Cr in the spot voiding urine (SUNa/SUCr) were obtained for estimating the 24-h urinary Na (NaUr-24 h) and from the sodium/creatinine ratio in the casual urine (NaUr) were obtained for the estimation of sodium excretion of 24 h (Na24 h) in random urine sample by the Kawasaki Equations  that wer2 was considered , after adjustment for confounding factors, showed a significant trend between salt intake and an increased energy consumption from all macronutrients. The increase of body fat was 0.24 kg and the WC of 0.18 cm per 100 mmol of 24 h urinary sodium excretion, during the six-year study period [p < .001) [Our study found a positive association between hypertriglyceridemia and the estimation of urinary sodium excretion (OR = 1.13). According to the results from the KNHANES , from 2007 to 2013, the prevalence of high-TG in the population aged over 30 years had increased, reaching 17.1% in 2013 . The rel < .001) .2/min presented a 24% risk of excreting more sodium when compared to those with lower GFR (OR = 1.24).In this current study, Afro-descendants with GFR >60 mL/1.73 mAfrican Americans are more prone to sodium retention and salt-sensitive hypertension than Caucasians . AccordiImpaired excretion of sodium is often present in patients with CKD, which leads to elevation of blood pressure and proteinuria, glomerular hyperfiltration as well as low response to rennin angiotensin aldosterone system (RAAS) blockade. In order to preserve renal function, lowering the intake of sodium to less than 2 g per day is recommended (corresponding to 5 g of sodium chloride) in adults, unless contraindicated, that is, patients with salt-losing nephropathies, postural hypotension and volume contraction who do not have heart failure .Our findings also reveal a direct relation between systolic blood pressure and the estimate of urinary sodium excretion (OR = 1.19). The literature reports a positive association of salt intake, urinary sodium excretion and prevalence of hypertension .r = 0.16, p = .01). Each 100 mmol/day in sodium intake was associated with a of 4.0 mmHg increase in systolic blood pressure.Law et al.  showed aThe Prospective Urban Rural Epidemiology (PURE) Study involving 157,543 adults showed increases of 2.11 mmHg in the systolic blood pressure (SBP) and 0.78 mmHg in the diastolic blood pressure (DBP) for each 1 g increase in the estimate of sodium excreted. The tendency of this association was stronger with an increased sodium intake. An increase of 2.58 mmHg in SBP per excretion gram >5 g/d was observed .According to Forman et al. , in a poOtherwise, in a meta-analysis, it was shown that the reduction in dietary salt intake has no effect on blood pressure and that the greater the restriction, the greater the pressure drop . In a raThe estimate of sodium intake from the collection of random urine, at a population level, is increasingly used as a convenient and affordable alternative, although the 24 h urine collection is the ‘gold standard’. Nevertheless, there are limitations regarding the fact that random urine samples may indicate poor 24 h urinary excretion according to individual variations .Thus, Ji et al. , suggestMany formulas have been proposed to convert sodium in random urine into 24 h excretion estimation by using creatinine to monitor urinary concentration. A formula, based on random urine of 591 Japanese individuals from an international multicenter epidemiological (INTERSALT) study, was proposed by Tanaka et al. . A similIn New Zealand, two formulas, one proposed by the Pan American Health Organization (PAHO) and the other derived from INTERSALT data, were tested on a sample with 101 healthy volunteers from a random and a 24 h urine sample. Estimates of urinary sodium excretion using these formulas were close to those of the 24 h excretion. The authors concluded that the collection of random urine is a suitable alternative to the 24 h urine collection in population surveys .p < .001 and p = .02, respectively) [A study performed in different populations showed a higher intra-class correlation coefficient (ICC) between estimated and measured sodium excretion with Kawasaki equation compared to INTERSALT and Tanaka. The degree of bias for estimated and measured sodium was lower with Kawasaki  compared to INTERSALT  and Tanaka  formulae (ctively) . A studyctively) .The strengths of this study include the large representative sample, the random selection of participants, which, in addition, are a vulnerable population. This was the first population-based study with African-descendant communities of Maranhão and Brazil that evaluated sodium excretion and associated factors.The limitation of this study was the use of a cross-sectional design. Although the gold standard for measuring sodium excretion was not used, we utilized another equation validated in Brazil, where the population has a high degree of admixture as well as strong influence of Africans.Whereas there is individual variation in sodium excretion during the day, the random sample tends to underestimate or overestimate its excretion. However, the estimate of urinary sodium can be a mean to monitor dietary sodium intake in population studies and low-income individuals, where the 24 h collection can be logistically difficult due to several factors .The sodium excretion estimation was high in random urine samples. Furthermore, WC, TG, SBP and estimated GFR by CKD-EPI equation were associated with urinary sodium excretion. These findings show that much greater attention should be given to the sodium intake because of health risks related to high intake of sodium.