Long-term dialysis vintage is a predictor of persistent hyperparathyroidism (HPT) after kidney transplantation (KTx). Recently, preemptive kidney transplantation (PKT) has increased. However, the incidence, predictors, and clinical implications of HPT after PKT are unclear. Here, we aimed to elucidate these considerations.In this retrospective cohort study, we enrolled patients who underwent PKT between 2000 and 2016. Those who lost their graft within 1 year posttransplant were excluded. HPT was defined as an intact parathyroid hormone (PTH) level exceeding 80 pg/mL or hypercalcemia unexplained by causes other than HPT. Patients were divided into two groups based on the presence of HPT 1 year after PKT. The primary outcome was the predictors of HPT after PKT, and the secondary outcome was graft survival.P < 0.001; odds ratio [OR], 5.480; 95% confidence interval [CI], 2.070–14.50) and preoperative donor-estimated glomerular filtration rate  were independent predictors of HPT after PKT. Death-censored graft survival was significantly lower in the HPT group than that in the HPT-free group .Among the 340 consecutive patients who underwent PKT, 188 did not have HPT (HPT-free group) and 152 had HPT (HPT group). Multivariate logistic regression analysis revealed that pretransplant PTH level (Pretransplant PTH levels and donor kidney function were independent predictors of HPT after PKT. In addition, HPT was associated with worse graft outcomes even after PKT.The online version contains supplementary material available at 10.1007/s10157-023-02371-9. Hyperparathyroidism (HPT) is a typical complication of chronic kidney disease (CKD) often associated with mortality and various complications . Althoug2. The exclusion criteria were as follows: patients who underwent chronic dialysis before KTx, those who underwent parathyroidectomy before KTx, those for whom data were lacking, those who had lost their kidney graft within 1 year of KTx, and those who were under 16 years of age at the time of KTx. HPT was defined as intact parathyroid hormone (PTH) levels of > 80 pg/mL or hypercalcemia unexplained by causes other than HPT 1 year after KTx; intact PTH level has been reported to be ≤ 80 pg/mL in over 98% of healthy individuals irrespective of vitamin D status in both PTH assays used in this study  before KTx), number of human leukocyte antigen (HLA) mismatches, positivity of donor-specific HLA antibody (DSA), treatment with vitamin D supplementation and calcimimetics before PKT, eGFR and laboratory data before and 1 year post-PKT, mean blood pressure (MBP) 1 year after PKT, and graft survival were documented. In addition, Ca deposition and interstitial fibrosis and tubular atrophy (IFTA) in the kidney graft were assessed by reviewing the reports of protocol biopsy performed 1 h and 1 year after KTx. IFTA was graded by an experienced transplant pathologist according to the Banff classification system. The primary outcome was the predictor of HPT after PKT, and the secondary outcome was death-censored graft survival. Pretransplant blood sample analyses were performed on all patients within 3 months before KTx, and posttransplant blood sample analyses were performed every month for 1 year after KTx and every second month thereafter. All samples were collected from fasting patients. The values of serum Ca and intact PTH obtained from blood samples 1 year after PKT were used for patient enrollment and classification. This study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.www.srl-group.co.jp, reference range [10–65 pg/mL]) or an enzyme immunoassay . When serum albumin values were < 4.0 g/dL, all serum Ca values were corrected for serum albumin values as follows ) because of their non-normal distribution, as confirmed by the Shapiro–Wilk normality test and histogram. The Spearman’s rank correlation coefficient was used to evaluate the correlations among the variables (Online Resource 1). Multivariate logistic regression analysis was performed to identify predictors of persistent HPT after PKT. Age ,, U test PKT. Age  before PPKT. Age  were useA total of 340 patients met the inclusion criteria . Of 340 patients, 188 and 152 were assigned to the HPT-free and HPT groups, respectively , donor age , donor hypertension , and preoperative donor eGFR  were significantly associated with HPT after PKT  and preoperative donor eGFR  were significantly associated with HPT after PKT       Supplementary file2 (TIF 1317 KB)Supplementary file3 (PDF 117 KB)Supplementary file4 (TIF 913 KB)Supplementary file5 (PDF 123 KB)Below is the link to the electronic supplementary material.


Introduction: Hypertension is a well-known risk factor for aneurysms, as high blood pressure can worsen the development and rupture of aneurysms. Ginsenoside, derived from ginseng and widely used in traditional herbal medicine, is believed to have antihypertensive properties. Recent research has also shown a connection between gut microbiota and various diseases, including hypertension. However, the relationship between ginsenosides, gut microbiota, blood pressure, and intracranial aneurysms needs further exploration.Methods: In this study, a rat model was used to investigate the effects of ginsenosides on both blood pressure and intracranial arteries. Comparative analysis was conducted, and 16S rRNA sequencing was employed to identify marker genera within the gut microbiota. Metabolites were also analyzed to uncover potential mediators of blood pressure regulation.Results and Discussion: The results of this study revealed that ginsenosides, particularly ginsenoside Rb1, demonstrated positive effects in reducing both blood pressure and the development of intracranial aneurysms in rats. Furthermore, the analysis of gut microbiota showed that certain genera, including Clostridium, Roseburia, Ruminococcus, and Treponema, were significantly influenced by ginsenoside treatment. Several metabolites, such as behenic acid, N-Acetylserotonin, Prostaglandin F2a, and Vitamin D2, were also detected, all of which play a role in regulating blood pressure. These findings provide valuable insights into the potential benefits of ginsenosides in hypertension and atheroma development. Furthermore, they suggest a possible link between ginsenosides, gut microbiota, and blood pressure regulation. Further research is needed to fully understand the mechanisms underlying these effects and to determine the clinical implications for treating hypertension and reducing the risk of aneurysm development. Intracranial aneurysm (IA) is a localized, aneurysmal dilatation of an intracranial artery, and it is a serious cerebrovascular disease with high morbidity and mortality . EffectiHypertension is one of the significant risk factors for IA . IA refeGinsenosides are active ingredients extracted from ginseng and are widely used in traditional herbal medicine . Studiesbifidobacteria and lactobacilli, which play a crucial protective role in maintaining intestinal balance, as well as promoting nutrient absorption and digestion. Nevertheless, it should be noted that numerous unknown factors still surround the effects of ginseng and ginsenosides on gut microbiome. As such, a definitive understanding of the association between ginsenosides, gut microbiome, blood pressure, and intracranial aneurysms is presently lacking.Gut microbiome, symbiotically coexist with the human body and significantly influence human health . ResearcTherefore, in this study, we explored the changes in blood pressure, gut microbiome and peripheral blood metabolome in aneurysmal rats under ginsenoside treatment by using a rat model to preliminarily investigate the relationship between them.Eighteen male SD rats (200–250 g) were randomly divided into four groups: the model group, the amlodipine group, the ginsenoside group, and the control group of WKY rats. Animals in the model and treatment groups were anesthetized and underwent an abdominal incision, and the posterior branches of the renal arteries were isolated bilaterally using a microscope and then electrocoagulated by electrocoagulation. One week after surgery, the left common carotid artery was then electrocoagulated and severed. The rats in the treatment group were given 60 mg/kg-d of ginsenoside Rb1 per day, which was dissolved in saline to formulate the appropriate concentration and given by intraperitoneal injection, and body weight measurements were taken once a week, and the dosage was adjusted according to body weight. The control group was given the same normal feed after the simulated surgery. Twelve weeks after surgery, the animals were executed by perfusion with 4% paraformaldehyde solution, followed by craniotomy to remove the brain, and the ring of arteries at the base of the skull and its main branches were carefully observed under a dissecting microscope and stripped off, and finally stored at 4°C for spare parts.Arterial blood pressure was measured in different groups of rats using the tail-cuff method before treatment and at the 12th week of treatment. Measurements were made in a quiet place with few people, keeping the room temperature between 25°C and 26°C. The systolic blood pressure of the tail artery of rats in the awake state was measured using a BP-98A rat non-invasive sphygmomanometer, and each measurement was averaged three times.Fresh feces were placed in a special fecal preservation tube in the early morning in the fasting state. The tubes were then quickly placed in a tank of liquid nitrogen for snap freezing, and stored in a −80°C refrigerator. DNA was extracted by commercial kit , and total DNA quality control was performed by NanoDrop  and 1% agarose gel electrophoresis.The V3-V4 region of 16S rDNA was selected, and the universal primers were designed as 341F and 806R. The primer design was as follows: forward primer (5′-3′): CCTACGGGRSGCAGCAG (341F); reverse primer (5′-3′): GGACTACVVGGGGTATCTAATC (806R). PCR amplification was carried out with PCR kit  using diluted genomic DNA as template After passing the quality control, the libraries were quantified using Qubit. Sequencing was carried out with Illumina Miseq PE250 by Biotree company. Raw data were deposited in NCBI database as PRJNA1010153.p diversity indices were calculated using an iterative algorithm using QIIME software and differences were calculated under weighted species taxonomic abundance information and unweighted species taxonomic abundance information, respectively.To facilitate the subsequent analysis of species diversity, clustering of long Reads was performed with 97% similarity using Usearch software, and the sequences were divided into operational taxonomic units (OTUs) based on similarity. The diversity indices of the samples were calculated using QIIME software and the corresponding dilution curves were generated. Values of Linear discriminant analysis of effect sizes (LEfSe) was used to estimate the magnitude of the effect of different component abundances on the effect of differences and to identify communities or species that significantly differed in the delineation of the samples. LEfSe Tools was used to perform this analysis. Significant difference analyses were performed using the rank sum test to identify species that produced significantly different effects on group delineation.Metabolite extraction, Chromatographic conditions, Mass spectrometry conditions were performed by Biotree company.The effects of ginsenoside Rb1 treatment on IA rats were investigated, specifically focusing on blood pressure regulation and arterial abnormalities. After 12 weeks of treatment, both the ginsenoside Rb1 and amlodipine groups exhibited a more significant reduction in blood pressure compared to the model group. The decrease in blood pressure was not as pronounced in the ginsenoside Rb1 group as in the amlodipine group, which served as the positive control drug. While both high-dose ginsenoside Rb1 and amlodipine effectively reduced blood pressure in the spontaneously hypertensive rats (SHR), the ginsenoside Rb1 group did not fully restore blood pressure to the level of normotensive WKY rats .In this study, an average of over 5,000 operational taxonomic units (OTUs) were identified per sample. The OTU Venn diagram illustrates the overlap and uniqueness of OTUs among the groups. Among the total OTUs, 520 OTUs were found to be shared by all four groups, while 4,884 were unique to the modeling group, 2,811 were exclusive to the amlodipine group, 4,517 were specific to the WKY group, and 5,467 were exclusive to the ginsenoside group .Firmicutes, Bacteroidetes, Tenericutes, and Proteobacteria. At the genus level, four dominant genera were identified: Ruminococcus, Prevotella, Lactobacillus, and Allobaculum.To gain further insights into the taxonomic distribution of species within each region of the Venn diagram, the number of corresponding amplicon sequence variants (ASVs) or OTUs in each region was analyzed at the phylum and genus level, and the results were presented using bar charts . The anaTo further investigate changes in the diversity of the gut microbiome within each group, several indexes were calculated. These indexes describe both the species richness and diversity of the gut microbiome . SpecifiIn the study, the principal coordinate analysis (PCoA), a dimensionality reduction technique, was used to visualize the differences between samples in a two-dimensional coordinate system based on their similarity distance . The disFirmicutes, Bacteroidetes, Tenericutes, and Proteobacteria. Additionally, four genera, namely, Ruminiococcus, Prevotella, Lactobacillus, and Allobaculum, were predominant in the samples  analysis to identify robust differential species between subgroups . The anaLactobacillus, Clostridiales, and Ruminococcaceae, respectively.After analyzing the abundance data of bacterial groups in each metabolic pathway, we can focus on identifying the metabolic pathways that exhibit significant differences among the groups . In compp < 0.05) were carefully selected for the construction of the RDA analysis plot (Treponema, unclassified_Rikenellaceae, unidentified_Peptostreptococcaceae, Allobaculum, unclassified_Clostridiaceae, Clostridium, 02d06, unclassified_Enterobacteriaceae, Flexispira, Prevotella, unclassified_Bacteroidales. The metabolites associated with these genera comprised of 4-Hydroxyphenylpyruvic acid, Beta-Tyrosine, Brassinolide, 3-Dehydroecdysone, Behenic acid, Arabidiol, UMP, and other unidentified compounds (In order to analyze the flora at the genus level, variables with significant correlation coefficients (sis plot . In thisompounds .Clostridium, Ruminococcus, and Treponema have significantly related metabolites, including 4-Hydroxyphenylpyruvic acid, UMP, and Vitamin D2 (Representative genera of the ginsenoside Rb1 group tamin D2 .Hypertension, characterized by excessive blood pressure in the arteries, has a complex mechanistic impact on the development and progression of aneurysms . SeveralWhile hypertension plays a crucial role in aneurysm formation, other factors, such as genetic factors, structural abnormalities of the vessel wall, and tumor vascular supply, may also contribute to aneurysm development and progression. Studies examined the effects of ginsenoside Rb1 treatment on hypertension and aneurysm and found that it relieved both conditions, consistent with previous published studies . Ginsenobifidobacteria, while decreasing harmful bacteria (Recent studies have revealed that ginsenosides can influence the intestinal flora in hypertensive patients . The gutbacteria . This alClostridium, Roseburia, Ruminococcus, and Treponema (Aristophanes, Lactobacillus, and Butyric acidophilus, while decreasing Ruminococcaceae, Streptococcus, and Turbotobacteria (Vibrio lachnosus spp. and high-density lipoprotein cholesterol but a negative association with systolic and diastolic blood pressure (Treponema pallidum was positively correlated with blood pressure. Another study exploring the effects of a low-carbohydrate diet and exercise training found positive correlations between changes in Ruminococcus spp, Escherichia coli spp., Rosella spp, and blood pressure (Clostridium butyricum pMTL007 GLP 1, improved blood pressure by producing GLP 1 and influencing the gut microbiota in a rat model of hypertension (In a study, the ginsenoside Rb1 group exhibited marked increases in the genera reponema . Anotherbacteria . Furtherpressure . Althougpressure . Moreovertension . These fOn the other hand, we have identified a series of metabolites that are associated with the abundance of gut bacteria in the ginsenoside Rb1 group. Several metabolites have been extensively reported as strongly correlated with blood pressure. Notably, one study has confirmed the association between lauric acid found in circulating saturated fatty acids and the risk of pregnancy-induced hypertension . AdditioIn conclusion, hypertension has a multifaceted impact on aneurysm development, involving arterial wall weakening, vascular inflammation, altered blood flow, and abnormal vascular smooth muscle cell proliferation. While ginsenosides have shown potential in alleviating hypertension and aneurysms, further research is needed to elucidate their precise therapeutic effects. Additionally, ginsenosides have been found to modulate the intestinal flora in hypertensive patients, potentially influencing hypertension through immune modulation and inflammation regulation. Although the specific role of gut flora in aneurysm treatment remains unclear, an association between intestinal dysbiosis and aneurysms can be hypothesized. However, comprehensive studies are required to validate this hypothesis.


Extracellular matrix (ECM) is an integral player in the pathophysiology of a variety of cardiac diseases. Cardiac ECM is composed mainly of collagen, of which type 1 is the most abundant with procollagen type 1 N-terminal Propeptide (P1NP) as a formation marker. P1NP is associated with mortality in the general population, however, its role in myocardial infarction (MI) is still uncertain, and P1NP has not been investigated in acute chest pain. The objective of the current study was to assess the role of P1NP in undifferentiated acute chest pain of suspected coronary origin.813 patients from the Risk in Acute Coronary Syndromes study were included. This was a single-center study investigating biomarkers in consecutively enrolled patients with acute chest pain of suspected coronary origin, with a follow-up for up to 7 years. Outcome measures were a composite endpoint of all-cause death, new MI or stroke, as well as its individual components at 1, 2, and 7 years, and cardiac death at 1 and 2 years. In multivariable Cox regression analysis, quartiles of P1NP were significantly associated with the composite endpoint at 1 year of follow-up with a hazard ratio for Q4 of 1.82 . There was no other significant association with outcomes at any time points.P1NP was found to be an independent biomarker significantly associated with adverse clinical outcome at one year in patients admitted to hospital for acute chest pain of suspected coronary origin. This is the first report in the literature on the prognostic value of P1NP in this clinical setting.NCT00521976. The most common serious cause of chest pain is acute coronary syndrome (ACS), which in the aftermath induces a remodeling process with both positive adaptation and scar healing, but also with a potential for development of heart failure (HF) . This reFibrillar collagen is the predominant component of cardiac ECM, with ∼85% being collagen type 1, conferring tensile strength , 4. CardThe prognostic value of P1NP has been investigated in myocardial infarction (MI) and as a potential marker of ischemic heart disease in apparently healthy individuals, but the results are mixed, with some series showing association with risk, while others found no association –8. Only In this study, we wanted to investigate the prognostic value of P1NP with respect to adverse clinical outcome including morbidity and mortality, in an undifferentiated acute chest pain cohort.2.2.1.This study is an extension of the single center prospective cohort study Risk in Acute Coronary Syndrome . Consecutive patients presenting to Stavanger University Hospital, Norway, with acute chest pain suggestive of ACS were included from November 2002 to October 2003 . Exclusi2.2.The main outcome measure of the current study was a combination of all-cause death, new MI or stroke within 1 year. Other outcomes included the combined endpoint at 2— and 7-years follow-up, as well as its individual components at 1, 2, and 7 years. Cardiac death at 1 and 2 years, and the combination of cardiac death, MI or stroke at 1 and 2 years were also analyzed.Cardiac death was defined as death after a definite MI or chest pain lasting more than 20 min, or a history of ischemic heart disease and no other clear cause of death. ACS incorporates ST-elevation MI (STEMI), Non-ST-elevation MI (NSTEMI), and unstable angina pectoris (UAP). MI was defined as symptoms of coronary ischemia with or without ST-segment changes on ECG and a typical rise and fall of Troponin T (TnT) with levels ≥0.05 ng/ml. As opposed to NSTEMI, STEMI required ST-segment elevation. UAP was diagnosed in acute chest pain with clinically suspected ACS, with or without ST-segment changes and serial TnT levels below 0.05 ng/ml. All other cases were defined as non-ACS, and included conditions such as arrhythmia or unspecified chest pain. Prespecified analyses were performed in the TnT-positive subgroup. In these analyses a lower level  were chosen as cut-off to adjust for the diagnostic difference using a contemporary analytical assay.2.3.Venous blood samples were obtained immediately following admission to hospital. After centrifugation, Ethylenediaminetetraacetic Acid (EDTA) plasma and serum were stored at −80°C until analyses. Hematology and other baseline laboratory data were collected from the individual hospital records. Analysis of TnT, Brain Natriuretic peptide (BNP), and high-sensitivity C-Reactive Protein (hsCRP) have been described previously .P1NP was measured in duplicate by an enzyme immunoassay (EIA) with matched antibodies from MyBioSource  in a 384-format using a combination of a SELMA  pipetting robot and a Biotek  dispenser/washer. Absorption was read at 450 nm with wavelength correction set to 540 nm using an ELISA plate reader . PINP intra- and inter-assay coefficients of variation were 6.9% and 8.9%, respectively.2.4.p-value of <0.05 was considered statistically significant. Categorical variables in the model with >2 levels were tested both for the equality of the hazard ratio (HR) across levels, and for each level against the reference level. A likelihood ratio (LR)-test was conducted to assess if the addition of P1NP quartiles significantly improved the multivariable model. Only variables with p < 0.05 in both  or all three tests  were considered significant. We included only cases with complete data in our analyses. Patients that did not experience the endpoint before our defined time-points of 1, 2 and 7years follow-up were censored in the respective analyses. We did not have any loss to follow-up and hence have no discontinuations in our data set. As this study is purely exploratory in origin, no adjustments were made for multiple comparisons and no power calculations were performed. We used all available samples from the biobank of the RACS study and the sample size was dictated by this. All statistical analyses were performed using SPSS version 25 .Baseline characteristics are presented by quartiles of P1NP. Continuous variables are presented as median and interquartile range, and analyzed across quartiles of P1NP by the Kruskal–Wallis test. Categorical variables are presented as frequency and percentage, and analyzed across quartiles of P1NP by Chi-square tests. Biomarkers were analyzed as quartiles, except for TnT which was analyzed as a binary detectable variable . Survival analyses are presented as Kaplan–Meier plots and tested using Log-Rank tests. Receiver Operator Characteristics (ROC)-curves and Area under ROC (AUROC) were estimated to test the ability of P1NP to predict outcome. Associations between P1NP and outcomes were assessed by both univariable Cox proportional hazards analysis and by a multivariable Cox analysis with a stepwise inclusion of common confounding variables. First, the multivariable Cox analysis was adjusted for significant confounding variables, thereafter P1NP was introduced in a second step. Significant confounding variables were selected from the baseline characteristics; age, sex, diabetes mellitus, hypertension (HT), current smoking, dyslipidemia, prior heart disease (Angina or MI), HF, prior medication , discharge diagnosis (STEMI/NSTEMI/UAP/Non-ACS), primary revascularization within 50 days of index event, as well as biomarkers . A two-sided 3.P1NP measurements were available for 813 patients, and a flow chart for the study participants is shown in 3.1.p = 0.017), with consistent significance in testing for both model change and equality of HR. Kaplan–Meier plot for this endpoint is shown in p = 0.021), although not in testing for equality of hazards ratios. For the combined outcome of cardiac death, new MI or stroke at 1 year follow-up there was an association found in both univariable and multivariable Cox analysis , although it did not reach statistical significance for equality of HR in either case. The same was observed for the association with all-cause death at 1-year follow-up in both univariable and multivariable cox analysis  without significance in the analysis of equality of HR. No association could be found for the individual endpoints of MI, stroke, or cardiac death, nor for the combined endpoints or all-cause death at other time-points. Detailed results of the Cox analyses are given in Quartiles of P1NP was significantly associated with the combined endpoint of all-cause death, new MI or stroke at 1-year follow-up in multivariable Cox analysis, HR (Q4 vs. Q1) of 1.82 . An association with the combined endpoint was seen with significance in univariable cox (p = 0.028), but without reaching significance for equality of HR. There was no other significant association between P1NP and any endpoint at any time, neither in univariable nor in multivariable testing. Details of the cox analyses are shown in P1NP significantly discriminated patients with and without the combined endpoint of all-cause death, new MI or stroke at 1-year in this subpopulation  is regulated by Tissue Inhibitors of MMPs (TIMPs). The ultimate results of either buildup or breakdown of collagens are dependent on the ratio of synthesis to degradation. Degradation is in turn dependent on the ratio of MMPs to TIMPs . This woA significant difference was seen in the use of ACEI/ARB and diuretics between quartiles of P1NP in our TnT positive subpopulation despite no difference in number of cases with previous history of hypertension or heart failure across the quartiles. This pattern was not seen in the full study population. ACEI is shown to lower levels of P1NP, while different diuretics have variable effects on levels of P1NP , 38–42. The dynamics of P1NP suggest that blood sampled at different time points may reflect variable phases of disease and healing. Although the sampling time varies in the literature, no sampling time for optimal risk stratification has been defined. In this study, blood samples were taken at hospital admission, as close as possible to symptom onset. Impact of timing on our results remains uncertain. As medication prior to hospital admission could affect levels of P1NP we have included this information in baseline characteristics and in our multivariable analyses. Furthermore, our study patients were enrolled in 2002 to 2003 and were treated according to the guidelines of that time. This raises the question of how more current therapies may influence P1NP levels and its association with clinical outcome. We still believe that from a mechanistic perspective, our study and significant findings are valuable. One potential limitation of our study is the long storage of the blood samples in a biobank before the P1NP analysis. Sample stability in freezer and during multiple freeze-thaw cycles has been demonstrated for P1NP for up to at least 2 years, but no studies have investigated stability for a more extended period of time . Howeverp-value in one or two of the tests were above the significance level. Being an exploratory study not adjusted for multiple comparisons, we chose a conservative approach and interpreted mixed test results as non-significant.Our main finding of a significant association between P1NP and the composite endpoint of all-cause death, MI or stroke within 1 year was backed by consistently significant results in the Cox analyses on all three levels, namely LR test for model change, equality of quartile HR, and HR Q4 compared to Q1. The interpretation was more uncertain for several of the other endpoints as the 5.In our material, P1NP was found to be an independent biomarker significantly associated with adverse clinical outcome in patients admitted to hospital for acute chest pain of suspected coronary origin. This is the first report in the literature on the prognostic value of P1NP in this clinical setting, and the results needs further documentation in independent series. Future studies are warranted in order to clarify the definite role of P1NP as a predictor of adverse outcome in this and other clinical conditions related to cardiovascular disease.


Autonomic nervous system (ANS) dysfunction and vascular stiffness increase cardiovascular risk in people with chronic kidney disease (CKD). Chronic elevations in sympathetic activity can lead to increased arterial stiffness; however, the relationship between these variables is unknown in CKD.To explore the association between measures of autonomic function and arterial stiffness in patients with moderate-to-severe CKD.This study was a prespecified secondary analysis of a randomized controlled trial. This included the following measures: 24-hour ambulatory blood pressure (BP), carotid-femoral and carotid-radial pulse wave velocity (PWV), and postexercise heart rate recovery (HRR). We used mixed effect linear regression models with Bayesian information criteria (BIC) to assess the contribution of ANS measurements.Forty-four patients were included in the analysis. Mean carotid-femoral and carotid-radial PWV were 7.12 m/s  and 8.51 m/s , respectively. Mean systolic dipping, calculated as percentage change in mean systolic readings from day to night, was 10.0% . Systolic dipping was independently associated with carotid-radial PWV, MD −0.09 m/s  and had the lowest BIC.Systolic dipping was associated with carotid-radial PWV in people with moderate-to-severe CKD; however, there was no association with carotid-femoral PWV. Systolic dipping may be a feasible surrogate of ANS function, as the association with carotid-radial PWV was consistent with the minimal clinically important difference (MCID). Future studies are needed to define the relationship between ANS function, arterial stiffness, and CV events over time in people with CKD. Arterial stiffness is increased in people with CKD and is independently associated with cardiovascular (CV) risk.24 Autonomic nervous system (ANS) dysfunction is prevalent in CKD and contributes to the progression of CKD and increased CVD risk.6 The hallmark of ANS dysfunction is increased sympathetic nervous system (SNS) activity and blunted parasympathetic nervous system function. Elevations in SNS activity acutely increase blood pressure (BP), but also play a role in the long-term regulation of BP by altering vascular function . An association between markers of SNS activity and vascular stiffness has been reported in other in chronic disease populations;1013 however, there is limited data in people with non-dialysis-dependent CKD. In one study, coexisting comorbidities explained the relationship between stiffness and SNS measures.The risk of cardiovascular disease (CVD) in people with chronic kidney disease (CKD) is significantly higher than in the general population. However, there are several other noninvasive, clinically available measures that are established surrogates of ANS function, including measures of blood pressure (BP) variability and heart rate recovery (HRR) from exercise. BP variability is defined as the short-term fluctuations in BP measured during 24-hour ambulatory blood pressure monitoring (ABPM). Accordingly, the daytime standard deviation and coefficient of variation (CV) of systolic BP are potential screening tools for assessing ANS function.19 One-minute HRR, defined as the change in heart rate from peak exercise to 1-minute postexercise, is also a powerful prognostic indicator of CV risk and events21 and can be obtained following cardiopulmonary exercise testing (CPET). Chronotropic incompetence is another potential surrogate of autonomic dysfunction obtained from CPET that independently predicts all-cause mortality, and is defined as the attenuated heart rate response to exercise (achieving <80%-85% of the maximum predicted heart rate [MPHR]). However, the association between the above measures and arterial stiffness is unknown in CKD.Sympathetic nervous system activity can be assessed directly with muscle sympathetic nerve activity (MSNA) and plasma catecholamines.The primary objective of this study is to determine the association between non-invasive measures of ANS, , and art Participants were eligible for inclusion if they were 18 years or older, hypertensive (defined as resting systolic blood pressure [SBP] greater than 130 mm Hg on screening measurement) and had an estimated glomerular filtration rate (eGFR) of 15 to 44 mL/min per 1.73 m2 on at least 2 occasions in the past year. Participants were recruited from both academic and community-based CKD clinics within the Alberta Kidney Care North program in Edmonton, Alberta. Written informed consent was obtained. The University of Alberta Research Ethics Board approved this study (Pro00078564). The study was registered with the Clinical Trials.gov registry (NCT03551119). The full details of the trial protocol have been reported elsewhere.This was a prespecified secondary analysis of data from a randomized controlled trial “PAIRED” .24-hour ABPM was completed using a validated device  worn on the nondominant arm for a 24-hour period. Readings were obtained at 20-minute intervals from 6 a.m. to 10 p.m. and at 30-min intervals from 10 p.m. to 6 a.m. Participants were advised to perform their regular daily routine, but not to exercise during the 24-hour ABPM period. As the SD is also correlated with mean BP, we reported the CV.Mean 24-hour SBP and diastolic blood pressure (DBP); daytime SBP and DBP; and systolic dipping were reported. Systolic dipping was calculated as the difference between daytime mean systolic pressure and nighttime mean systolic pressure, expressed as a percentage of the day value. In addition, we calculated the standard deviation (SD) for 24-hour and daytime BP measures. Mean PWV was calculated as the average of at least 10 consecutive beats to cover a full respiratory cycle.Central and peripheral arterial stiffness were estimated with tonometry  with sensors placed at the carotid-femoral and carotid-radial arterial pulse sites. The distance between measuring sites was divided by the time difference between the upslope of the pulse-waves at each measuring site, and arterial stiffness was expressed as PWV.2peak was determined by breath-by-breath indirect calorimetry using a cardiorespiratory metabolic measurement system  and recorded as the peak 20-second average VO2 during the final minute of exercise. Peak exercise was defined as achieving one or more of the following criteria: respiratory exchange ratio ≥1, an intensity rating of breathlessness or leg discomfort of ≥5 on the 0 to 10 modified Borg scale, or a peak HR no less than 10 beats/minute of the age-predicted maximum of 220-age. HRR was defined as the difference in HR measured in beats per minute at peak to one-minute postexercise during unloaded cycling at a slow cadence (50–60 revolutions per minute).Participants completed a standardized maximal CPET on an upright cycle ergometer (Ergoselect II 1200 Ergoline). After 5 minutes of rest, participants began cycling at 20 Watts with an increasing stepped workload of 20 Watts every 2 minutes until volitional exhaustion. 12-lead electrocardiogram recordings  were taken at rest, during exercise, and 5 minutes into recovery. VOhttps://www.stata.com) and reported baseline descriptive statistics as counts and percentages, or medians and inter-quartile ranges, as appropriate. Mean values and 95% confidence intervals were calculated for arterial stiffness and autonomic function by averaging over all 3 time points  using a clustered sandwich estimator to account for repeated measures from the participants. Carotid-femoral and carotid-radial PWV were regressed onto potential measures of ANS function using mixed effect linear regression models; participant was modeled as a random effect. Unadjusted and adjusted associations were expressed as mean differences  with 95% confidence intervals. Two-sided P-values < .05 were considered statistically significant. Because the sample size was small, we used a forward stepwise approach. The candidate variables for the adjusted models were intervention, timepoint, age, sex, non-Caucasian ethnicity, current smoking status, diabetes, baseline body mass index (BMI), eGFR, the number of antihypertensive medications, resting HR, and 24-hour MAP. The selection of covariates and the relative contribution of the ANS function measures were quantitatively assessed using Bayesian information criterion (BIC) estimates. As described by Raftery, the BIC is an approach to model selection that helps overcome the difficulties with P-values and standard model selection procedures. With several candidate independent variables , results from standard models can be misleading. However, the BIC adds a penalty based on the number of parameters being estimated in the model, with the preferred model being that which has the minimum BIC value. Thus, we sought which unadjusted and adjusted associations had the lowest BIC.All analyses were completed in Stata/MP 17.0 , which was 77.3%  of their predicted VO2peak. Participants achieved 88.9%  of their MPHR. The percentage of tests that were completed during which the participant both (1) exercised to volitional exhaustion and (2) met VO2 peak criteria was 90% (95% CI 81–95), value not indicated in table. Five tests were terminated by physician due participant meeting ECG criteria (asymptomatic). Five tests were terminated by the exercise physiologist/research staff due to participant inability to maintain cycling cadence above 50 revolutions per minute, with a mean respiratory exchange ratio of 1.2  and a mean Borg rating of perceived exertion of 8.0 .Diabetes was associated with carotid-femoral PWV in the unadjusted model, 2.03 m/s ; however, the association was not significant after adjustment. 24-hour DBP SD, daytime SBP SD and CV, and daytime DBP SD were associated with carotid-femoral PWV 0.31 m/s , 0.27 m/s , 0.32 m/s , and 0.37 m/s , respectively.In this study, we explored the association between clinical measures of ANS function and central and peripheral stiffness in people with CKD. Our analysis revealed that systolic dipping, a measure of the day to night change in systolic BP, was most highly associated with PWV, both in the unadjusted and adjusted models. Specifically, for every 1% increase in systolic dipping, there was a 0.09-m/s decrease in carotid-radial PWV. Furthermore, measures of daytime BP variability were associated with carotid-femoral PWV in the adjusted model, which supports our hypothesis that patients with greater BP variability (as a surrogate measure of ANS function) would have greater arterial stiffness. In people with CKD, higher MSNA was associated with reduced systolic dipping and endothelial dysfunction. Jeong et al demonstrated that individuals with CKD who had higher MSNA burst incidence also had higher nighttime BP and non-dipping patterns . Non-dipping was also associated with endothelial dysfunction, flow-mediated dilation (FMD)  in non-dippers compared to dippers. One of the potential mechanisms to explain this relationship is nocturnal hypoxia induced by sleep apnea, which is prevalent among people with CKD. Intermittent hypoxia has been associated with increased inflammation, oxidative stress, and sympathetic activity, leading to increased blood pressure and heart rate as well as endothelial dysfunction. In a recent study, individuals who had more severe sleep apnea also had greater arterial stiffness, particularly in those with nocturnal non-dipping BP patterns. Obstructive sleep apnea is an important link between hypertension, SNS activity, and arterial stiffness; however, further study in people with CKD is needed.Our finding that systolic dipping is associated with measures of vascular stiffness is supported elsewhere in the literature. In a previous study of men and women with normal BP, high-normal BP, and stage 1 hypertension, there was an association between non-dipping and attenuated reduction of norepinephrine (NE) and epinephrine (EPI) in non-dippers compared with dippers. However, recent evidence suggests SNS activity may modulate arterial stiffness independently of changes in BP.40 A review of cross-sectional studies in healthy men and women showed increased MSNA was directly associated with increased arterial stiffness after adjustment for age and BP. In healthy individuals, Faconti et al demonstrated a dissociation between changes in BP and PWV. Lower limb venous occlusion led to a 1.8 mm Hg  reduction in MAP, yet aortic and carotid-femoral PWV increased acutely by 0.8 m/s  and 0.7 m/s . In another study of healthy adults, lower body negative pressure had no significant effect on HR, BP, stroke volume, cardiac output, or total peripheral resistance, yet MSNA burst frequency, total MSNA, and carotid-femoral PWV all increased significantly. It is important to note, however, that these studies included healthy individuals and measured short-term changes in PWV from interventions that cause reflex sympathetic activation, rather than the chronic effects of elevated sympathetic activity. Although the pressure-independent relationship remains unclear in CKD, we found a significant association between carotid-radial PWV and systolic dipping that remained after adjustment for MAP and anti-hypertensive use.The role of pressure independent mechanisms in mediating the relationship between SNS activity and vascular stiffness remains unclear. A traditional mechanistic explanation of the association between blood pressure and arterial stiffness is that arterial stiffness precedes increases in central pulse pressure and SBP. and is lower than that reported in another study of people with stage 3 and 4 CKD (16.3 ± 9.3 bpm). On average, our study sample achieved 87.3%  of the MPHR, suggesting borderline chronotropic incompetence. An important consideration, however, is the potential effect of beta blocker use on HRR, which we did not include in our adjusted model due to nonsignificance. In a study of patients with known or suspected coronary artery disease, HRR was attenuated in patients using beta blockers. Conversely, a study of patients with hypertension showed no effect of beta blocker use on HRR. Others have also shown HRR retains its prognostic value independent of beta blocker use.47 Although an attenuated HRR alone might suggest elevated SNS activity in our study sample, whether it contributes to or is a consequence of stiffness remains unknown. Yang et al showed HRR was inversely associated with ultrasound carotid stiffness index after treadmill exercise with adjustment for established cardiovascular risk factors, resting SBP, and metabolic equivalent of task scores, but not with carotid stiffness index at rest. HRR was also weakly associated with brachial-ankle PWV; however, it is important to note these findings were in young, normotensive participants and may not be applicable to people with CKD.While the increase in heart rate during exercise is considered a function of parasympathetic withdrawal and SNS activation, the decrease in heart rate postexercise involves reactivation of the parasympathetic nervous system. Thus, blunted HRR is thought to reflect sympathetic over-activation. Participants in our study had a mean HRR of 7.1 bpm (95% CI 4.9–9.3), which falls below the <12 bpm cut-off that has been used to predict mortality,50 we did not find an association between VO2peak and PWV. Although we acknowledge this could be due to sample size, it is important to consider the lack of association could be attributed to the uniformly low cardiorespiratory fitness (CRF) of our study sample, mean VO2peak of 17.9 mL/kg/min, which is lower than the baseline VO2peak in several other studies of patients with non-dialysis CKD.5154 Other work has shown peak peripheral oxygen extraction is a more important determinant of VO2peak in CKD and that PWV does not change in CKD despite significant improvements in VO2peak. We also reported different associations between peripheral versus central measures of arterial stiffness and ANS function. Previous studies have focused primarily on central PWV, and whether elevated SNS activity disproportionally affects peripheral stiffness is an area for future study.In contrast to other studies in CKD, The association we found between systolic dipping and carotid-radial PWV was consistent with the minimal clinically important difference (MCID) for PWV (1 m/s). For every 1% increase in systolic dipping, there was a 0.09 m/s decrease in carotid-radial PWV, ie, for a 10% increase in systolic dipping, there was a 0.9 m/s decrease in carotid-radial PWV. 24-hour ABPM is also an established, readily available clinical tool for measuring BP in CKD, thus systolic dipping would be a relatively simple measure of ANS function to obtain. However, our study also has important limitations. First, we cannot infer the associations between variables determine causality. We cannot exclude residual confounding due to bias from confounding by indication, but this was mitigated by adjusting for number of antihypertensives. Second, we used indirect measures of ANS function, and we did not specifically measure SNS activity . However, given the complexity of the ANS, there is no singular, gold standard test that accurately represents ANS function as whole; BP variability and HRR are therefore both practical and valid surrogates of ANS function and CV risk. Third, we did not attempt to quantitate vascular calcification, which is present in moderate-to-severe CKD and may contribute to arterial stiffening and reduced baroreflex sensitivity. Medial calcification in the artery wall may alter baroreceptor function and could explain the differences we observed between central and peripheral PWV. Finally, while the patients in our study had low cardiorespiratory fitness and low kidney function, they had high-normal levels of arterial stiffness and modestly elevated SBP, thus we cannot say whether the associations we found would exist in people with higher SBP and arterial stiffness.We included central and peripheral measures of arterial stiffness using PWV and reported an association between systolic dipping and carotid-radial PWV, including adjustment for resting HR and MAP. Previous studies comparing ANS function and vascular stiffness have not adjusted for these variables and are an important consideration for understanding the mechanistic relationship between vascular stiffness and ANS function.Describing the factors related to ANS function could provide greater insight into the mechanisms that contribute to CVD in people with CKD. Longitudinal studies enrolling people at earlier stages of CKD with repeated measures of aortic stiffness and SNS activity are required to better understand these mechanistic relationships. However, large scale studies measuring MSNA are less practical; thus, to facilitate the advancement of this research, identifying valid, non-invasive surrogates of ANS function is needed. It is also undetermined whether non-pharmaceutical interventions such as exercise or lifestyle modifications can adequately attenuate SNS activity in CKD. Future studies using randomized designs should evaluate whether interventions known to reduce SNS activity, such as exercise, are effective in CKD and whether these autonomic adaptations result in improved vascular stiffness.This exploratory analysis revealed systolic dipping was associated with increased carotid-radial stiffness in people with moderate-to-severe CKD. Although it is highly desirable to identify measures of autonomic function in this patient population, there is not a universal gold-standard measure of autonomic function, and thus assessments may be limited by what is clinically available. Systolic dipping warrants further investigation as it is a potential non-invasive surrogate for SNS activity and can be obtained clinically. Systolic dipping may then be a useful target for treatment with exercise and lifestyle interventions to examine whether it is both modifiable and may improve cardiovascular risk and mortality. Future studies are also needed to describe the mechanisms that underlie the relationship between ANS function, vascular stiffness, and clinical outcomes in CKD.


Markers on chromosome 17  and 11 (D11S1999) also correlated with diastolic pressure. These results illustrate the successful use of discordant sib pair analysis to detect linkage within relatively small numbers of pedigrees with hypertension. Further analysis of this cohort may be valuable in complementing findings from the large genome wide scans in affected sib pairs.Genome-wide scans performed in affected sib pairs have revealed small and often inconsistent clues to the loci responsible for the inherited components of hypertension. Since blood pressure is a quantitative trait regulated by many loci, two siblings at opposite extremes of the blood pressure distribution are more likely to have inherited different alleles at any given locus. Hence, we investigated an extreme discordant sib pair strategy to analyse markers from two previous loci of interest: (1) the Gordons syndrome locus that includes the WNK4 gene and (2) the ROMK locus identified in our first genome-wide scan. For this study, 24 sib pairs with strong family histories of essential hypertension were selected from the top and bottom 10% of the blood pressure distribution and genotyped for highly polymorphic microsatellite markers on chromosomes 11 and 17. The mean age of the population was 39.8 ± 7.8 years. A significant inverse correlation was found between the squared difference in pulse pressure and the number of alleles shared by IBD between the siblings for the DS11925 marker (r = −0.44,  High blood pressure is a common condition affecting one in four adults in the UK, and it is an important modifiable risk factor for cardiovascular, cerebrovascular and renal diseases globally . GeneticIn the mid-1990s, one approach received particular attention for dissecting polygenic traits including obesity, asthma, and age-related macular degeneration ,14,15, aWNK4 gene [ROMK locus on chromosome 11 which was identified in our first GWS for hypertension [WNK kinases [Our aim was to recruit the untreated offspring of affected sibling pairs with essential hypertension from the East Anglia Region community  and deteNK4 gene ,23, and rtension . The twortension  due to o kinases ,24,25.In total, 140 families with two or more untreated siblings with a family history of essential hypertension were recruited, of which 47 offspring pairs, referred to herein as sib pairs, had blood pressure (BP) differences of greater than 15/14 mmHg. Of the 47 sib pairs, 24 sib pairs  fitted the strictest definition of extreme discordance. Establishing the genetic architecture in individuals with extreme trait values is important because these individuals are at an increased risk of disease and are also the most likely to harbour rare variants of large effects due to natural selection. In these sib pairs, either one sib had high blood pressure (SBP >139 mmHg or DBP >85 mmHg) and the other sib had low blood pressure (SBP <112 mmHg or DBP <66 mmHg) or there was a difference of at least >25/20 mmHg in blood pressure between the sibs. Centiles of BP were defined from reference data previously gathered from 35,000 healthy subjects registered at their general practitioners and recruited to for cardiovascular risk screenings in the CLEAREST (Cholesterol Levels in the East Anglia Region Effective Screening and Treatment) study . Ethical2. Peripheral blood pressure was recorded in the brachial artery of the non-dominant arm using a validated oscillometric technique . Blood pressure was measured twice unless there was discrepancy in the two measurements (>10 mmHg); in this case, a third reading was taken, and the average value was used in the subsequent analysis. All the sib pairs were healthy and were not taking any hypertensive or cardiovascular drugs. Peripheral venous blood samples were obtained for biochemical and genetic analysis.At each participant’s clinic visit, basic demographic information  was acquired and a family history questionnaire was completed. Height and weight were recorded using standard methods in kilograms, and the body mass index was calculated in kg/m2  and 50–100 ng of template gDNA. The polymerase chain reactions were carried out for 34 cycles at 94 °C for three minutes, 55 °C for 1 min and 72 °C for 45 s. The fluorescent-labelled PCR products were pooled and loaded onto an ABI 377 semi-automated sequencer (Perkin Elmer). The sizes of the markers, which reflected differences in the number of CA repeats, were assigned using version 2 of ABI Genotyper® software and corrected manually if necessary. To identify if any genetic polymorphisms in the WNK4 gene exons were involved in this cohort (n = 24 sib pairs), a mutation analysis of exons 7 and 17 was performed via a single-strand conformation polymorphism (SSCP) analysis and direct sequencing on an ABI 377 sequencer, and the data were analysed using Genescan and Genotyper software from ABI (Perkin Elmer).Genomic DNA (gDNA) was isolated from whole blood in all 47 sib pairs recruited, but only individuals who fitted the strictest BP criteria i.e., 24 sib pairs, were genotyped for highly polymorphic microsatellite markers  from the MRC panel and Gordon’s markers located on chromosomes 11 and 17, as listed in p-value of <0.05 was considered statistically significant.A statistical analysis was performed using SPSS software (version 28.0) to determine the relationship between blood pressure and the microsatellite markers  and for graphical illustration. The data were also analysed using the Haseman–Elston quantitative trait loci regression method in which the squared difference in the phenotype  between sibs is regressed to the number of alleles shared by identity-by-descent (IBD) and by the use of the SPLINK package, a non-parametric likelihood ratio method. Since this was a small study of 24 sib pairs, correlation coefficients and unadjusted p-values are presented, and a The demographic details of this cohort are provided in p = 0.011) and D17S250  markers, as illustrated in p = 0.04; p = 0.05; p = 0.04, p = 0.025; p = 0.031), a surrogate marker of arterial compliance and an independent predictor of cardiovascular complications.Blood pressure levels correlated with chromosome 17 and 11 microsatellite markers, suggesting evidence of linkage. Significant inverse correlations were identified between the squared difference in the systolic blood pressure and the number of alleles shared between the siblings for the D17S799 , there were no common polymorphisms in the coding region of the WNK4 gene that influenced the blood pressure level.However, we did not find any polymorphisms in exons 7 and 17 of the High blood pressure affects over 25% of adults and is the major cause of cardiovascular morbidity and mortality. Despite over half a century of multiple lines of investigations, the genetic basis remains poorly understood, with each genetic loci contributing to a minor proportion of blood pressure inheritance. We investigated the feasibility of exploiting the continuous nature of the blood pressure distribution, using extreme discordant sib pairs rather than regarding hypertension as a categorical abnormality. This strategy is widely used in experimental hypertension genetics in which two rodent strains of opposite phenotypes are crossed. However, this approach is most useful when there are large differences in the continuous variable between sib pairs. The extreme discordant strategy, in which a lack of alleles at contributing loci is sought, is predicted to reduce the number of sib ships required by several orders of magnitude (from 10- to 40-fold) ,17 but dFor the first time, we were able to identify that extreme discordant sib pairs do indeed exist in the general population, although their identification is even more labour intensive clinically because of the low return for each proband when compared to that of the concordant sibs required for affected sib pair studies. In theory, our present cohort approached the number required in humans, when the number of loci responsible for hypertension is itself unknown. We were able to recruit double the minimum target proposed by Risch. However, the identification and phenotyping process carried out to identify 24 sib pairs with extreme blood pressure differences took 2 years. Our East Anglian population also has a low prevalence of cardiovascular risk compared to London and other parts of the UK. All the sib pairs studied, including the original probands (parents), were local residents from a region of low CV risk with little or no influence of environmental factors. Nevertheless, this resource will be useful to replicate loci of modest linkage on genome-wide scans and will help to exclude false positives.p = 0.004) in the affected sib-pairs [ROMK gene that encodes the KCNJ1 potassium channel and is mutated in Bartter’s syndrome (type 2), a monogenic hypertension disorder [ROMK does not influence blood pressure in our East Anglian population, although other genes in the region around D11S934 may be operating. In fact, we found several other highly polymorphic genomic markers in the chromosome 11 region associated with diastolic pressure  and pulse pressure (D11S925) phenotypes.In our previously published genome-wide search for the susceptibility loci of hypertension in affected sib pairs (ASPs) , we idenib-pairs . This redisorder . In our Similarly, two of the markers investigated for chromosome 17 correlated with systolic blood pressure (D17S799 and D17S250) suggesting genetic linkage. We previously demonstrated evidence of linkage for the D17S250 marker (with a maximum LOD score of around 2.3) with Gordon syndrome in a large, well-characterised Brisbane family with seven offspring . This suSignificant inverse correlations between blood pressure  and several microsatellite markers suggests evidence of linkage on chromosomes 11 and 17, as noted previously in our studies on affected sib pairs with essential hypertension and the Brisbane family with Gordon’s syndrome. The results also illustrate the use of a discordant sib pair analysis to detect linkage within small numbers of pedigrees with essential hypertension. Further analysis of this cohort may be valuable in complementing findings from large genome-wide scans in affected sib pairs.


The Kidney Failure Risk Equations (KFRE) are accurate and validated to predict the risk of kidney failure in individuals with chronic kidney disease (CKD), but their potential to predict health care costs in the US health care system is unknown. We assessed the association of kidney failure risk from the 4-variable and 8-variable 2-year KFRE models with monthly health care costs in US patients with CKD stages G3 and G4.This was an ancillary study to a larger observational, retrospective cohort study examining the association between serum bicarbonate and adverse kidney outcomes. Monthly medical costs were calculated from individual health care insurance claims. Generalized linear regression models were used to examine the association of KFRE score with health care costs.P < 0.001) and 4.1% (P < 0.001) higher monthly costs for patients with CKD stage G3 and G4, respectively. For 4-variable KFRE, a 1% increase in risk was associated with 6.7% (P = 0.016) and 2.9% (P= 0.014) increase in monthly costs for patients with CKD stage G3 and G4, respectively.A total of 1721 patients qualified for the study . For 8-variable KFRE, each 1% (absolute) increase in risk was associated with 13.5% (Higher risks of kidney failure as predicted by the 4-variable or 8-variable KFRE were associated with higher 2-year medical costs for patients with CKD stages G3 and G4. The KFRE may be a useful tool to anticipate medical costs and target cost-reducing interventions for patients at risk of kidney failure.  The program, the Advancing American Kidney Health executive order has 3 goals that are as follows: (i) reducing kidney failure risk, (ii) improving access and quality of treatment options, and (iii) increasing optimal kidney failure transition .,,,Tools to classify the risk of progression of patients with CKD can help to align the goals in the aforementioned care models. One such tool, the KFRE, is an internationally validated prediction tool that estimates the risk of progression to kidney failure and is highly accurate for prediction of kidney failure at 2 years and 5 years.In a Canadian study, patients classified as high-risk of progression with the KFRE (5-year risk >15%) have been demonstrated to have approximately twice the costs of hospital admissions and physician visits and a 30% increase in drug dispensation expenses over a 5-year period compared with the low-risk group.This observational, retrospective cohort study of US patients with advanced nondialysis-dependent CKD was conducted using Optum’s deidentified Integrated Claims-Clinical data set of US patients (2007–2017). The Optum database is a longitudinal repository of electronic health record (EHR) data that included >81 million patients as of 2017 from all insurance types or statuses and a subset of patients linked by unique patient identifiers to a health care claims database of private and Medicare Advantage health care insurance plans.2 and at least 3 serum bicarbonate results, with at least 1 result between 12 and 29 mEq/l, plus linked claims data  were excluded, so were patients’ missing data on baseline albumin-to-creatinine ratio (ACR). Patients were classified by baseline CKD stages G3 or G4 using baseline eGFR. Definition details including code lists are provided in This was an ancillary study of a larger observational, retrospective study to determine the association of serum bicarbonate levels with clinical outcomes. Patients included in the database extract with claims data had at least 1 year of EHR activity with at least 3 estimated glomerular filtration rate (eGFR) results <60 ml/min per 1.73 mims data . To qualTo ensure sufficient representation at low serum bicarbonate levels, an iterative selection algorithm was used to oversample the number of patients with metabolic acidosis by initially selecting qualifying pairs of serum bicarbonate in the 12 to <22 mEq/l range before examining bicarbonate values between 22 and 29 mEq/l. This methodology is further explained in a previous publication, along with sensitivity analyses showing that primary clinical findings were sustained in the absence of oversampling.,,The primary variable of interest was the predicted risk of kidney failure within 2 years, calculated for each patient using the 8-variable and 4-variable versions of the KFRE.Additional descriptive statistics were provided for sex and race, as well as diabetes and hypertension, which were identified by single occurrence of an International Classification of Diseases-9 and 10-Clinical Modification diagnosis code in all available preindex data, excluding codes with a status of “possible” or “indicative of personal or family history”.Serum calcium was missing in 5% of patients in CKD stage 3 and 0% of patients in CKD stage 4, and serum albumin was missing in 21% of patients in CKD stage 3 and 13% of patients in CKD stage 4. Missing data for serum calcium and serum albumin were imputed 10 times by multiple imputation using the Markov chain Monte Carlo method and reported at the mean of 10 imputations in descriptive results.The outcome was all-cause medical costs per month, assessed during the 2-year outcome period. Outpatient pharmacy costs were not included in this analysis. Medical costs in the Optum data set were obtained from medical insurance claims for inpatient and outpatient services of all types and provided from the payer perspective  as Optum-defined “standard cost,” an approximated cost per service based on private insurance payment levels in 2015 US dollars. This methodology accounts for service quantity, relative resource costs, and the nature of the service rendered to reduce variation in payment amounts to similar providers for the same service. For inpatient confinements missing cost data, costs were imputed at the average per-diem rate for other admissions for the same patient or (for 3 patients) at the per-diem mean of the total cohort. Costs were inflated to 2021 US dollars at 3% per annum.Medical cost per month was calculated as the 2-year total of costs for inpatient and outpatient medical claims, divided by the number of months in the observation period . To address typical skew in health care costs, patient-level medical cost per month was adjusted with a 98% winsorization, setting all results less than the first percentile of medical cost per month to zero and all costs greater than the 99th percentile of medical cost per month to that 99th percentile.Patient characteristics were reported at mean values with standard deviation or as percentages. Results for imputed laboratory variables were reported at the mean of 10 imputations. For descriptive analyses, patients in each CKD stage (G3 and G4), and overall, were ranked highest to lowest in risk of kidney failure by the 8-variable KFRE and assigned to risk quartiles within stage. Average cost per month in 2021 US dollars was calculated by risk quartile within each stage and evaluated pairwise between risk quartiles by a generalized linear model comparison of least squares means.Generalized linear models were run within CKD stage G3 and stage G4 groups, equating log-transformed medical cost per month with the calculated risk score with both the 8-variable and 4-variable KFREs. Because the 8-variable KFRE risk score models contained missing serum calcium and serum albumin data, multiple imputation was implemented 10 times to generate 10 complete datasets. These 10 complete datasets were then analyzed separately using the 8-variable KFRE risk score as the sole predictor of medical cost per month (log-transformed). The results of the 10 analyses were combined in the SAS PROC MIANALYZE procedure to derive valid inferences. Similar sets of generalized linear model analyses were run on models that evaluated each component of the 4-variable and 8-variable KFRE equations as individual covariates as follows: (i) a model with age, sex, eGFR, and log-transformed urine ACR (4 variable) and (ii) a model with age, sex, eGFR, log-transformed urine ACR, serum bicarbonate, serum albumin, and serum calcium .P-values <0.05 were considered statistically significant.All statistical analyses were performed using SAS/STAT software, version 9.2 . The Optum database contained longitudinal records of approximately 81 million patients, of which 29,831 met the criteria for inclusion in the database extract with claims. Within this extract, 1721 patients qualified for the study cohort as follows: 1475 in CKD stage G3 and 246 in CKD stage G4 .Mean (standard deviation) age was 75.3 (9.8) years in the CKD stage G3 group and 76.2 (9.1) years in the CKD stage G4 group . The CKDP = 0.003), $7700 (P = 0.002), and $11,505 (P = 0.8) for patients in the second-highest quartile of kidney failure risk, respectively  and 4.1%  increase in predicted monthly health care costs in patients with CKD stages G3 and G4, respectively  increase in the predicted risk score was associated with a 13.5%  and 2.9%  increase in monthly medical costs in patients with CKD stages G3 and G4, respectively  versus approximately $76,000 for those at low risk of progression (Canadian dollars).,The primary components associated with cost from the 8-variable KFRE were serum bicarbonate and serum albumin. Each of these variables, when modified by 1 standard deviation from their means, represented a 30% change in estimated monthly costs. These biomarkers likely affect costs because of their association with adverse outcomes. Serum albumin is a marker of nutritional status and has been shown to be associated with physical function decline and failure to thrive. This study had several strengths. It analyzed costs from a large population health repository and therefore improves upon previous studies examining cost by risk that were limited to patients enrolled in multidisciplinary CKD care and is likely generalizable to a wider population of patients with CKD. It also further builds on the evidence for the utility of the KFRE in managing CKD care in the US health system, providing additional evidence that risk scores predicting progression of CKD are associated with increase in health-related expenses.This analysis also had several limitations. First, the cost data was obtained from patients with 2 types of common insurance (private and Medicare Advantage) and may not be representative of other payment types . Urine ACR and serum bicarbonate were required for inclusion in the study for assessment of the KFRE (measured directly or by transforming a urine protein-to-creatinine ratio/urine dipstick result), and therefore may not be representative of patients in whom no such measurement was available. Although these findings confirm a previous study in the Canadian health system,In conclusion, higher risk of progression to kidney failure as measured by the KFRE is associated with higher all-cause health care costs in patients with private insurance and Medicare Advantage in the United States. Use of risk stratification equations to identify patients at the highest risk of progression and subsequent use of health care resources may help to effectively target resources.NLR, SEF, VM, TWF, JL, and NT were paid consultants to Tricida, Inc. in connection with the development of this manuscript. NLR, VM, and NT report consultancy, personal fees, and equity ownership from Tricida, Inc., related to the submitted work. SEF and TWF report consultancy and personal fees from Tricida, Inc. VM and NT are members of advisory boards at Tricida. VM is listed on patents related to work for Tricida. VM reports additional consulting fees from Tricida, Equillium, Myovant, Rigel, Corvidia, Acuta, Frazier, Intarcia, PTC Bio, Escient, RallyBio, Unicycive, Galderma, and Sanifit outside the submitted work.


BackgroundSevere acute pancreatitis (SAP) has a mortality rate as high as 40%. Early identification of SAP is required to appropriately triage and direct initial therapies. The purpose of this study was to develop a prognostic model that identifies patients at risk for developing SAP of patients managed according to a guideline-based standardized early medical management (EMM) protocol.MethodsThis single-center study included all patients diagnosed with acute pancreatitis (AP) and managed with the EMM protocol Methodist Acute Pancreatitis Protocol (MAPP) between April 2017 and September 2022. Classification and regression tree , univariate, and logistic regression analyses were performed to develop a scoring system for AP severity prediction. The accuracy of the scoring system was measured by the area under the receiver operating characteristic curve.Results9/L), procalcitonin (PCT) (0.155 ng/mL), and systemic inflammatory response system (SIRS). The prediction model was built with a multivariable logistic regression analysis, which identified CR, WBC, PCT, and SIRS as the main predictors of severity. When CR and only one other predictor value  met thresholds, then the probability of predicting SAP was >30%. The probability of predicting SAP was 72% (95%CI: 0.59-0.82) if all four of the main predictors were greater than the cutoff values.A total of 516 patients with mild (n=436) or moderately severe and severe (n=80) AP were analyzed. CART analysis identified the cutoff values: creatinine (CR) (1.15 mg/dL), white blood cells (WBC) (10.5 × 10ConclusionsBaseline laboratory cutoff values were identified and a logistic regression-based prognostic model was developed to identify patients treated with a standardized EMM who were at risk for SAP. Acute pancreatitis (AP) is the third most common gastrointestinal reason for hospitalization in the United States and accounts for approximately 300,000 hospitalizations annually and nearly three billion dollars in direct healthcare costs . The RevClassification of final AP severity is necessary for benchmarking outcomes. It is more important, however, to identify at baseline those patients at risk for poor outcomes. Unfortunately, highly accurate predictive models to identify SAP in patients on presentation do not exist -9. WhileFortunately, most AP cases are mild and can be accurately identified as such on presentation . Early pStudy design and patientsThe MAPP was initiated in January 2015. MAPP is a multidisciplinary EMM quality initiative that implements computerized physician orders, physician/nursing education, and patient navigator-directed care to optimize adherence to AP published guidelines (APPG) . Data frAnalysis in the current study included data from all patients in the registry diagnosed with AP from April 2017 to September 2022 who were managed per the MAPP. Patients were included in the analysis if they met APPG diagnostic criteria: pain consistent with AP, serum amylase and/or lipase >3X the upper limit of normal, and/or characteristic imaging findings. Exclusion criteria included age <18 years, transfers from outside hospitals, post-endoscopic retrograde cholangiopancreatography AP, and trauma-related AP.The study was approved by the WCG Institutional Review Board and was found to meet the requirements for a waiver of consent under 45 CFR 46 116(f) (2018 Requirements).Data collection and outcomesBaseline data (from admission in the emergency department) and measured outcomes included age, body mass index (BMI), white blood cell (WBC) count, hematocrit (HCT), creatinine (CR), C-reactive protein (CRP), procalcitonin (PCT), systemic inflammatory response syndrome (SIRS), presence of pleural effusion on imaging, bedside index of severity in acute pancreatitis (BISAP) score , and harStatistical analysisAll statistical analyses were carried out using SAS on Demand for Academics  and Minitab Statistical Software . Normally distributed variables are presented as means and standard deviations (SD). Non-normally distributed variables are presented as medians and minimum and maximum values. These variables were compared using t-tests or Wilcoxon tests, as appropriate. Categorical variables were summarized with percentages and compared using Pearson's chi-square test.The cutoff values of continuous variables were established using classification and regression tree (CART®) analysis , providing equal probability for mild and SAP, and obtaining the highest sensitivity and specificity of each cutoff point. The cutoff values were used to convert continuous variables into binary variables. When the value of the predictor was lower than or equal to the cutoff value, it was assigned a value of zero. If the value of the predictor was greater than the cutoff value, it was assigned a value of one.CART analysis utilizes two basic principles, classification and regression, to formulate a simple output that can be easily interpreted. Classification trees are used when the dependent variable is categorical. Regression trees are used when the dependent variable is continuous. The classification tree consists of categorical target variables, and the tree identifies the “class” into which the target variable would best fit. The optimal tree was selected according to its predictive accuracy and clinical relevance. The class probability function was used as the splitting rule for tree building: the node would not be split if the sample number was <30, and the terminal node would not be split if the sample number was <10. We used a 10-fold cross-validation method for validating the tree model, the overall performance of which was validated in the test sample using the area under the receiver operating characteristic curve. The CART analysis was also used to create a model that was compared to a logistic regression model.Separately, logistic regression analysis was used to establish the association between baseline predictors and the severity of AP. A multivariable logistic regression model was constructed with backward variable selection, including those variables that were not highly correlated according to Pearson’s correlation analysis to avoid multicollinearity. The concordance (c) statistic and Hosmer-Lemeshow test were used to validate and calibrate the model. Additional models with two and three variables were included and reported with the c statistics. Missing values were handled with listwise deletion, and a p value<0.05 was considered statistically significant.As shown in Table 2 developed SAP during the study period), showed a significantly increased risk of SAP (p<0.05). Patients with hypertriglyceridemia had 3.8 times the risk of SAP compared to other etiologies .Table Cutoff values and CART analysisThe predictor variable cutoff values, sensitivity, specificity, and area under the curve (AUC) are found in Table Patients with a CR level >1.15 mg/dL had a 47% probability of having SAP, regardless of the value of the other variables included in the model Figure . The subLogistic regression2 developed SAP during the study period. In this bivariate analysis, all predictors with values exceeding their respective established cutoff values were significantly associated with SAP.The association between demographic characteristics, baseline predictors , and AP severity was assessed by logistic regression analysis Figure . No patiIn the multivariate logistic analysis, BISAP and HAPS were excluded to avoid redundancy with SIRS, CR, and HCT. After adjustment for the covariates included in the model, CR , PCT , WBC , and SIRS  were the main predictors of severity. The analysis showed that having a CR >1.15 mg/dL increased the probability of SAP by 7.5 times compared to a CR ≤1.15 mg/dL when the other covariates are held constant. Similar interpretations can be made for the other predictors. The AUC was 0.824 Figure , and theThe formula for the model is as follows:Probability of severity (SAP) = exp(Y’)/(1=exp(Y’)Y’ = -3.368 + 0.0 CR_0 + 2.022 CR_1 + 0.0 PCT_0 + 0.635 PCT_1 + 0.0 WBC_0 + 0.678 WBC_1 + 0.0 SIRS_0 + 0.915 SIRS_1Figure Additional logistic regression models were constructed including only two variables, with CR (>1.15 mg/dL) always as one of the variables, for example, CR+PCT (>0.155 ng/mL), CR+WBC (>11 x 109/L), or CR+SIRS. These models all showed an AUC >71%. Table While the incidence of AP, including outpatient encounters , may be We found that four objective baseline variables can predict the likelihood of developing SAP. The probability of developing SAP was <5% if none of the four baseline parameters were met, but as high as nearly 75% if all four baseline parameters were met. When baseline CR was >1.15 mg/dL and any one of the other baseline parameters  were met, the probability of SAP was at least 30%. The probability for SAP was 20% when only the CR threshold was met, and <10% when only any of either WBC, PCT, or SIRS threshold criteria were met. Furthermore, additional logistic regression models were constructed with only two variables, where one was commonly CR . These models showed an AUC >71%. When both predictors have values greater than their cutoff points, the probability of SAP was >50%. This further underscores the ability of CR plus any one of the other baseline parameters to predict SAP. We believe that a probability of 30% in the multivariate logistic regression model is a clinically relevant parameter to identify patients at risk of developing SAP.Several AP severity scoring systems (APSSS) have been developed to assist in predicting patient clinical outcomes. When comparing existing APSSS statistically, the AUC for severity predicted by BISAP was 0.793, APACHE II was 0.836, Ranson score was 0.903 , and BALMany APSSS were developed without defining severity outcomes according to the RAC. The Glasgow criteria defined SAP as either fatal or associated with a complication that required a length of stay >20 days . While tThus, current methods for predicting AP severity have reached maximum utility, and there has been a call for new approaches with practical utility ,8,54-59.Our analysis of a prospective study registry is differentiated from previous assessments of potential individual biomarkers and various scoring systems. The data analyzed in this cohort were collected from a population of patients in which the EMM adhered to a standardized evidenced-based protocol. We used a computerized physician order set that guided early aggressive fluid resuscitation and early enteral feeding, as well as a patient navigator, to optimize adherence to APPG. These factors minimized confounders stemming from variable management. Lastly, we excluded variables that introduced subjectivity in interpretation . Our study identified variables that could be easily obtained and utilized clinically.Other groups have used CART analysis to assess severity in AP. There are principle differences between these and our study. They were retrospective analyses of patients not managed by a standard EMM and did not use the RAC for the definition of SAP. The BISAP severity system was the first APSSS developed using CART analysis . Though We used logistic regression as a robust strategy to develop a reliable clinical decision rule that could be used to classify patients by AP severity. There are numerous benefits of utilizing logistic regression modeling as an analytical tool as opposed to CART analysis. Logistic regression is a traditional statistics method, easier to implement and interpret, and very efficient to train. The sample size makes minimal modification of the coefficients, and it makes no assumptions about distributions of classes in feature space. Logistic regression also has minimal overfitting problems with small to moderate sample sizes. The logistic regression model not only provides a measure of how appropriate a predictor (coefficient size) but also its direction of association (positive or negative).Our logistic regression analysis identified four baseline predictors: CR, WBC, PCT, and SIRS. A number of other studies have evaluated the importance of these variables for assessing the severity of AP. Increased serum CR during the first 48 hrs after admission was reported by Muddana et al. as associated with pancreatic necrosis . In a stThe early APSSS models considered elevated WBC as a prognostic factor for SAP. A WBC >16K was associated with SAP in the Ranson criteria . The thrEarly studies suggested that PCT, the 116 amino acid peptide precursor of calcitonin that is elevated early (3-24 hours) in severe inflammation and sepsis , can accMeeting SIRS criteria was an important variable in our analyses. Initiation of local inflammation associated with AP may lead to SIRS as a result of high circulating levels of proinflammatory cytokines that induce activated leukocytes, oxygen free radicals, ischemia-reperfusion, and organ injury -93. PropMeeting SIRS criteria at baseline and persistent SIRS has been commonly studied in AP. Some prospective studies reported that baseline SIRS correlated with AP severity -99, whilThe strengths of our study are derived from having a standardized cohort in which patients were all managed in a very deliberate, evidence-based manner. This minimized the confounders that are inevitably present in retrospective studies of cohorts that have been managed at the discretion of varied providers. Another strength of our study was the utilization of both logistic regression and CART analyses to identify the baseline variables most important in predicting AP severity, determine cutoffs, and create a decision tree model that physicians can implement easily in their clinical practice. Logistic regression as a traditional statistics method is easier to implement, interpret, and very efficient to train, whereas CART model calculations can be far more complex compared to other algorithms.Our study is limited to the smaller population of patients with SAP in our cohort. This is perhaps explained by the standardized EMM by which all patients were treated. There is also perhaps some variability from symptom onset to admit as these data were not collected.Our severity of AP prediction (SAPP) model, namely, CR + WBC, PCT, and/or SIRS, will be based on easy-to-collect on admission, simple, and objective variables to predict severity. The next step is to validate these results in other patient populations that may not have been treated with a standardized EMM. Moreover, the SAPP could be used now to triage patients on admission to different EMM protocols and for proper disposition to ward or ICU care.