TMAO clearances were not significantly different from mGFR, with a mean ± SD TMAO fractional excretion of 105% ± 32%. This suggests a complete renal excretion of TMAO by glomerular filtration with a negligible participation of tubular secretion or reabsorption, during all stages of CKD. Moreover, TMAO was effectively removed within 4 h of hemodiafiltration, showing a higher fractional reduction value than that of urea . This study reports a strong correlation between plasma TMAO levels and mGFR, in CKD, that can be mainly related to a decrease in TMAO glomerular filtration. Clearance data did not support a significant role for tubular secretion in TMAO renal elimination.Gut microbiota-dependent Trimethylamine-N-oxide (TMAO) has been reported to be strongly linked to renal function and to increased cardiovascular events in the general population and in Chronic Kidney Disease (CKD) patients. Considering the lack of data assessing renal handling of TMAO, we conducted this study to explore renal excretion and mechanisms of accumulation of TMAO during CKD. We prospectively measured glomerular filtration rate (mGFR) with gold standard methods and plasma concentrations of trimethylamine (TMA), TMAO, choline, betaine, and carnitine by LC-MS/MS in 124 controls, CKD, and hemodialysis (HD) patients. Renal clearance of each metabolite was assessed in a sub-group of 32 patients. Plasma TMAO was inversely correlated with mGFR ( Trimethylamine-N-oxide (TMAO) is a small amine plasma compound of 75.1 Da derived from intestinal microbial metabolism. Gut flora produces trimethylamine (TMA) either from foods containing TMA or TMAO, or from diet precursors that are identified as choline, phosphatidylcholine, betaine, and carnitine ,3. TMA iConversely, over the last two decades, several large clinical studies have shown that plasma TMAO levels associate with cardiovascular risk ,9,10,11,Although numerous studies have reported increased TMAO levels in CKD, data assessing renal metabolism (filtration and excretion) of TMAO is still lacking. We therefore conducted a prospective study to address this question. More specifically, we aimed to determine TMA, TMAO, choline, betaine, and carnitine concentrations in all stages of CKD, using gold standard measured glomerular filtration rate (mGFR) and renal clearance measures in order to assess the role of decreased GFR in TMAO increase. Moreover, we measured concentrations of these solutes before and after hemodialysis treatment to assess the effect of hemodialysis on their removal.A total of 124 patients, including 11 hemodialysis patients, were recruited in our study. The main characteristics of the patients are shown in n = 18), CKD stages 1–2 (n = 49), CKD stages 3a–3b (n = 31), and CKD stages 4–5 (n = 15). There were significant differences between groups in sex ratio, age, and data concerning renal function, plasma bicarbonate, proteins, triglycerides, total cholesterol, LDL-cholesterol, and proportion of lipid lowering treatments. Plasma TMAO concentration was significantly increased in patients with mGFR < 60 mL/min.1.73 m2 according to the CKD stages, with an increase of median concentration by 3 (CKD 3a–b), 7 (CKD 4–5), and 28 (CKD 5D) fold compared to controls  (and these were separated into four groups: controls (controls A–C. mGFR 0.0001) B. In uni 0.0001) .p = 0.168). Plasma concentrations of choline, betaine, carnitine, and TMA for all groups and according to CKD subgroups, are shown in sr = −0.26, p = 0.0059 and sr = −0.32, p = 0.0005 respectively). In addition, hemodialysis participants exhibited significantly higher concentrations of choline and significantly lower concentration of carnitine than all CKD participants (p < 0.0001).No correlation was found between plasma TMAO and BMI, triglycerides, LDL-cholesterol, HDL-cholesterol, or estimated protein intake. Plasma TMAO was not correlated with gender with a median  concentration of 6.98 µmol/L [3.08–14.40] in males and 4.60 µmol/L [2.82–10.01] in females , whereas there was no relationship between betaine and mGFR. Among precursors of TMAO, only carnitine was weakly correlated with plasma concentrations of TMAO .TMA was positively correlated to renal function (p < 0.0001), with a mean ± SD value of FE of 137% ± 25%. Inversely, clearance of urea was significantly lower than mGFR (p < 0.0001), with a mean ± SD FE of 58% ± 19%. In contrast to urea or creatinine, TMAO FE was not significantly different from mGFR . Clearances and FE of uric acid, choline, betaine and carnitine were also calculated .Among participants, a subgroup of 32 patients  underwent urinary clearance tests for TMAO, creatinine, uric acid, urea, and other TMAO precursors to calculate their fractional excretion (FE). Baseline characteristics of these patients are shown in lculated . Data shp < 0.0001) (see p = 0.04). Compared to urea FR, choline and betaine FR were significantly lower  whereas carnitine FR was not significantly different (p = 0.064) . All patients were treated for 4 h with hemodiafiltration. Clinical and biological characteristics of hemodialysis patients are shown in 001) see . TMAO FR= 0.064) .Identified mechanisms for target molecule elevation in CKD patients are either a decrease in renal excretion, an increase in endogenous production or both. Thus, TMAO levels could result from variations in production levels  or from its renal excretion. This study was therefore designed to assess the exact changes in TMAO values according to CKD stages as determined by gold standard measurements of GFR and its potential modifications during renal metabolism.2r = 0.388) between plasma TMAO and mGFR. Surprisingly, in all stages of CKD, we did not find any correlation between TMAO levels and its precursors, except a weak correlation with carnitine. Measured clearances of TMAO showed a complete renal excretion of TMAO by glomerular filtration with a steady FE of 105% during CKD, regardless of the stage. Unlike previous studies, we reported no evidence for effective contribution of tubular excretion or reabsorption during renal clearance of TMAO. In hemodialysis patients, we confirmed a greater increase in TMAO even though FR was similar to that of urea.In the present study, we confirmed that TMAO is increased in CKD based on an inverse, although weak, correlation  patients, as has been previously described ,18,19. DThe discrepancy between urea and TMAO increases in HD patients could also be explained by the different metabolic pathways involved. For instance, the mitochondrial cycle for urea which is impaired in CKD , could lElevation of TMAO levels in CKD is mostly related to the decrease of mGFR and may be in part due to an enhanced production of TMAO by FMO3 and/or by the promotion of TMAO production pathway rather than that of urea. This latter will have to be confirmed and should be the aim of futures studies. Renal elimination of TMAO seems to be poorly influenced by tubular secretion or reabsorption, suggesting that therapeutic target research to reduce TMAO levels should focus on its production mechanisms rather than its renal elimination.From October 2012 to December 2016, 124 subjects were prospectively recruited from the Nephrology and Renal Functional Explorations Department in the Lyon teaching hospitals . Hemodialysis or CKD patients who were referred for GFR measurement were recruited to participate in the study. Renal transplant recipients and patients with systemic active inflammatory disease or known active malignant diseases were excluded. Controls subjects consisted of patients referred to the renal unit for kidney donation or for exploration of kidney stone and with normal kidney function. This research was approved by the local institutional review committee  and conducted in accordance with its ethical standards and the principles of the Declaration of Helsinki. All subjects involved in the research signed written informed consent forms prior to enrolment. 0.425 × height (centimeters) 0.725). Body weight was measured in light clothing without shoes to the nearest 100 g on a digital scale, in order to determine dry weights for HD patients. Body mass index (BMI) was calculated as body weight divided by squared height. Body Surface Area (BSA) was assessed following the Dubois and Dubois BSA formula: BSA =  g for 10 min to isolate plasma supernatant which was snap frozen in liquid nitrogen and stored at −20 °C until analysis.After an overnight fast, blood samples were obtained by venipuncture, except for dialysis blood samples that were obtained immediately before and after dialysis from the arterial line of the mechanical bloodstream. Blood samples were centrifuged at 3500× 2) or iohexol clearance. Inulin clearance measurement  was performed with a loading dose of 30 mg/kg injected over 10 min, followed by a maintenance inulin dose infusion of 40 mg/kg/h. Urine was collected every 30 min (3–4 collection periods of 30 min), and blood tests were performed between urine collection time points. Inulin clearance was calculated for each period to determine mean GFR for each subject, based on the following Equation (1):GFR was measured using gold standard methods, i.e., urinary clearance of inulin  and by weighing the syringe before and after the injection. Blood collection was performed at 120, 180, and 240 min. Serum iohexol concentration was measured by High Performance Liquid Chromatography (HPLC). GFR was calculated using the following Equation (2):The concentration at time 0 was corrected using the Bröchner–Mortensen equation. eGFR was estimated using the CKD EPI (Chronic Kidney. Disease - Epidemiology) formula  and CKD Urinary clearance of creatinine, urea, uric acid, TMA, TMAO, choline, betaine, and carnitine was calculated by the following Equation (3):2. Fractional Excretion (FE) was calculated using the following Equation (4): Urine was collected for a precisely measured time to calculate urinary debits. All the clearance and GFR measurements were indexed to the BSA and expressed by 1.73 m2H9-choline, 2H9-carnitine, 13C2-betaine, -TMA and 2H9-TMAO) were added to 20 µL of standard solutions, plasma, and diluted urine samples. All samples were then treated with 75 µL of tert-butyl-bromoacetate (TMA derivatization) diluted at 50 mmol/L in acetonitrile and 10 µL of 70% ammonium hydroxide solution before mixing and incubation in the dark, at room temperature, for 30 min. Then, 50 µL of acetonitrile containing 1% formic acid were then added and samples were centrifuged for 10 min at 10,000× g (20 °C). Supernatants were then transferred to vials for LC-MS/MS analyses, performed on a Xevo® TQD mass spectrometer with an electrospray interface and an Acquity H-Class® UPLCTM device . Samples (5 µL) were injected onto an HILIC-BEH column  held at 35 °C. Compounds were separated using a linear gradient of mobile phase B  in mobile phase A  at a flow rate of 400 µL/min. Mobile phase A was kept constant for 1 min at 1%, linearly increased from 1% to 45% for 6.5 min, kept constant for 1 min, returned to the initial condition over 1 min, and kept constant for 1.5 min before the next injection. Targeted compounds were then detected by the mass spectrometer with the electrospray interface operating in the positive ion mode  flow and temperature, 650 L/h and 350 °C; source temperature, 150 °C). The multiple reaction monitoring mode was applied for MS/MS detection as detailed in r² which was greater than 0.997 for all compounds . The intra- and inter-assay imprecisions of the analytical method were assessed throughout experiments in spiked samples with known concentrations , and were below 11.4% for all compounds.Trimethylamine N-oxide (TMAO), trimethylamine (TMA), betaine, choline, and carnitine concentrations were determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS). All solvents used were LC-MS grade and purchased from Biosolve . Standard compounds were obtained from Sigma Aldrich . A pool of reference standard solutions was prepared and serially diluted in acetonitrile to obtain seven standard solutions ranging from 0.05 to 100 µmol/L. Urine samples were diluted 10-fold in distillated water prior to analysis. Exogenous internal standards (10 µL) diluted at 25 µmol/L in acetonitrile  concentrations were measured using enzymatic test kits . HDL cholesterol concentrations (HDL-C) were measured using a specific assay kit allowing apoB-containing lipoprotein precipitation . LDL cholesterol concentrations (LDL-C) were then deducted using the Friedewald equation . PatientFor HD patients, protein intake was estimated by normalized protein catabolic rate (nPCR) with the following Equation 6 : nPCR = Post dialysis values of TMAO, choline, betaine, carnitine and urea were normalized according to the hemoconcentration  of each patient.p < 0.05 was considered as statistically significant in all analyses.Data are expressed as mean ± standard deviation (SD) or as median  when variables were not normally distributed. Data were analyzed using Graphpad Prism version 8.2.1, . Normality was tested using d’Agostino–Pearson test. Differences between groups were assessed with one-way ANOVA or a Kruskal–Wallis test, when variables were not normally distributed, completed by post-hoc multiple comparisons. Sex ratio and medications between groups were compared using Fisher exact test. Univariate analysis was performed using the Spearman rank correlation method. A


Compared with the initial phase of surgery, correlation coefficients were significantly lower during the reperfusion period . The correlation between PSV and PPV showed similar variation according to the surgical phases . Conclusions: Continuous monitoring of intraoperative PST with an esophageal stethoscope has the potential to act as an indirect estimator of beat-to-beat arterial PP. Moreover, PSV appears to exhibit a trend similar to that of PPV with moderate accuracy. However, variation according to the surgical phase limits the merit of the current results, thereby necessitating cautious interpretation.Purpose: To investigate the possibility of esophageal phonocardiography as a monitor for invasively measured pulse pressure (PP) and its respiratory variation (PPV) in patients undergoing liver transplantation. Methods: In 24 liver transplantation recipients, all hemodynamic parameters, including PP and PPV, were measured during five predetermined surgical phases. Simultaneously, signals of esophageal heart sounds  were identified, and S1–S2 interval  and its respiratory variation (PSV) within a 20-s window were calculated. Beat-to-beat correlation between PP and its corresponding PST was assessed during each time window, according to the surgical phases. To compare PPV and PSV along with 5 phases , Pearson correlation was conducted. Results: Beat-to-beat PST values were closely correlated with their corresponding 3360 pairs of PP values (median  Heart sounds result from the interplay of the dynamic events associated with the contraction and relaxation of the atria and ventricles, valve movement, and blood flow. A graphic recording of heart sounds, phonocardiography, provides valuable information concerning the function and integrity of the heart valves and on the hemodynamics of the heart, and has a high potential for detecting various heart diseases ,2,3. AltIn our previous study, we suggested that intra-operative monitoring of the phonocardiogram may provide useful clinical information as a non-invasive hemodynamic index . In thatThis study was approved by the Institutional Review Board of Asan Medical Center (No. 2015-1371). The requirement for written informed consent was waived because of minimal risk to participants in this study. We reviewed electronic health records and routinely collected biosignal data of patients who underwent liver transplantation from June to September 2015. Patients with preoperative arrhythmia, valvular heart disease, reduced ventricular function (ejection fraction <40%), intracardiac shunt, hepatopulmonary syndrome, or pulmonary hypertension were excluded. Patients with incomplete signal data records were also excluded. The preoperative Child-Turcotte-Pugh class and Model for End-Stage Liver Disease (MELD) score were recorded.All the patients were subjected to our institutional standard anesthetic management protocol for living donor liver transplantation ,10,11,12After electrocardiography was applied, invasive radial arterial pressure was measured. The FloTrac/Vigileo device  was used to analyze invasive arterial pressure waveform data over 20-s intervals, with a recalibration interval of 1 min. A 7.5-Fr pulmonary arterial catheter , which was inserted via a 9-Fr introducer sheath into the internal jugular vein, was advanced to a wedged position under the guidance of a pressure curve recording. The pulmonary artery catheter was connected to a Vigilance device . The Vigileo device computed stroke volume variation (SVV) from its relationship to the difference between the maximal and minimal values of stroke volume over a 20-s interval. We used a Multi-Data Logger  to capture and store patient data simultaneously from the Vigilance II and Vigileo devices. An 18 Fr esophageal stethoscope  was inserted to monitor heart sound continuously during the operation. The esophageal stethoscope was positioned at the depth of 28–32 cm from upper incisor where the S1 sound was heard loudest, the location reported to be the best position to listen to heart sounds during the operation . The depHemodynamic parameters including blood pressure, heart rate (HR), central venous pressure (CVP), femoral venous pressure (FVP), pulmonary artery pressure, SV, cardiac output (CO), right ventricular end-diastolic volume index (RVEDVI), systemic vascular resistance (SVR) and phonocardiogram (PCG) signal were obtained. SV and CO were collected from STAT mode screen of the Vigilance monitor, which displayed them every 30–60 s. Based on our previous study , all datWhen acquiring intraoperative PCG signal, a custom-built replica of a phonocardiography amplifier  was used. The collection of data was conducted in a Windaq application  after which the data were stored on a database of the operating room. Raw PCG signal is not suitable for signal analysis because of various kinds of noises, including high frequency electrocautery signal and respiratory crackles during mechanical ventilation. Band-pass filtering 8–100 Hz) was applied using Matlab programming to remove white noise, and Hilbert transformation of the signal was performed to detect actual points of maximal amplitude of S1 and S2 heart sounds for appropriate digital signal analysis ). Compared with the correlation coefficients at I + 60, the correlation coefficients at R + 30 were significantly lower   . In all r = 0.510, p < 0.001; R + 30, r = 0.290, p = 0.170) , the correlation was weaker than that between PPV and PSV, and there was no significant correlation between SVV and PSV at timepoints after reperfusion   . In Blan= 0.170) . Althoug= 0.797) .In this study, we hypothesized that heart sound signal monitoring using an esophageal stethoscope would be a useful non-invasive hemodynamic index. Specifically, the S1–S2 interval, measured as the PST, was closely correlated with corresponding beat-to-beat arterial PP, and the correlation was more evident at the other timepoints than at the post-reperfusion period. Furthermore, respiratory variation of S1–S2 interval (PSV) has similar incremental/decremental pattern according to hemodynamic fluctuation compared with PPV as well. Although esophageal stethoscopes have been used for 60 years for continuous auscultation during general anesthesia ,15,16,175 at each timepoint) in this patient. It has been known that the PP depends not only on SV but also on properties of arterial circulation such as aortic compliance [5 at each time point). In this case, the individual characteristics of the patient, an error in measurement, or a limitation of the signal processing method may be considered as the cause.Our results show that the performance in tracking the beat-to-beat PP varies depending on the surgical phases and individual characteristics. In most patients, PST and PP showed good correlation before graft reperfusion, but the correlations were significantly lower at the timepoints after reperfusion. In addition, there were two patients who showed unfavorable correlations in most timepoints, regardless of the surgical phase (patient #5 and #13 on mpliance . These fmpliance  (low SVRmpliance ,21. For mpliance ,23. The mpliance ,23. FurtThere were several limitations to our study. First, the patient population of the present study was only limited to cirrhotic patients undergoing liver transplantation. As patients with end-stage liver disease usually show altered hemodynamic characteristics such as low SVR and underlying cirrhotic cardiomyopathy ,25, the In conclusion, non-invasive determination of PST and PSV parameters using heart sounds can provide useful continuous hemodynamic index during liver transplantation. Intraoperative monitoring of PST and PSV will enable the clinicians in estimating the cardiovascular status of surgical patients and eventually reduce uncertainties in the bedside assessment of preload status. Further research and development of this technique is warranted.


Successful renal transplant and consequent good graft function depend on agood surgical technique, an anesthetic that ensures the hemodynamicstability of the receiver, and appropriate conditions of graft andrecipient. Several factors can interfere with the perfusion of the graft andcompromise its viability. The objective of this study was to evaluateperioperative factors associated with delayed graft function (DGF) in renaltransplantation patients.This is a historical cohort study of patients who underwent renaltransplantation between 2011 and 2013. Three hundred and ten transplantswere analyzed. DGF was defined as the need for dialysis during the firstweek post-transplant. Logistic regression with a stepwise technique was usedto build statistical models.-1 , dialysis for morethan 60 months , basiliximab , cold ischemia time > 12 hour , living donor , and earlydiuresis . The accuracy of this model was92.6%, calculated using the area under the ROC curve. The incidence of DGFin the study population was 76.1%.Multivariate analysis revealed the following risk factor for DGF: combinedanesthesia technique , a fluid regimen <50 mL·kgCombined anesthesia technique, dialysis for more than 60 months, basiliximab,and cold ischemia time > 12 hours are risk factor for DGF, while liberalfluid regimens and kidneys from living donors are protective factors. Renal transplantation is the treatment of choice for patients with end-stage kidneydisease and is associated with better quality of life, a greater cost/benefit ratio,and longer survival.Early diuresis is a good marker of successful renal transplantation as it reflectsthe re-establishment of graft function.The aim of this study was to evaluate the perioperative factors associated withdelayed graft function in patients who underwent renal transplantation.Following approval by the hospital ethics committee, this historical cohort study wasconducted on patients aged 18-60 years who were scheduled for renal transplantationat our institution in Recife, Brazil between 2011 and 2013. Patients with cardiacdisease (ejection fraction < 30), kidney-pancreas transplantation, and kidneyretransplantation were excluded from this study.-1. There are many definitions ofDGF in the literature; one of the most well established and adopted in our researchwas the need for dialysis during the first week post-transplant. Immediate graftfunction (IGF) is defined as serum creatinine decrease less than 70% of preoperativevalue in the first week.Hemodynamic instability was considered to be a drop in systolic blood pressure (SBP)of at least 30% compared to the initial blood pressure in the operating room and/orrequiring vasoactive drugs for a period equal to or greater than 15 minutes.-1.Expanded criteria deceased organ donors (ECD) are a source of kidneys that permitmore patients to benefit from transplantation. ECD is defined as all deceased donorsolder than 60 years or donors older than 50 years with two of the followingconditions: hypertension, stroke as the cause of death, or preretrieval serumcreatinine greater than 1.5 mg/dLStandard monitoring included continuous electrocardiography, heart rate (HR),peripheral oxygen saturation, and noninvasive blood pressure measurement. Inductionand maintenance of general anesthesia were performed using sevoflurane inconcentrations of 1 to 2% in a mixture of 50% oxygen and 50% air. The most commonlyused intravenous anesthetics were fentanyl, propofol and atracurium. Patientsunderwent balanced general anesthesia (GA) or combined anesthesia (CA), defined bythe assistant anesthesiologist depending on hemodynamic stability, comorbidities,and coagulation profile. Regional anesthesia was performed by lumbar epiduralinjection of bupivacaine 0.125%, follow by general anesthesia. The protocol ofimmunosuppressive drugs used in our institution is Thymoglobulin and Basiliximab.Thymoglobulin is generally used when the patient has a panel reactive antibody (PRA)> 25% and Basiliximab when the PRA < 25%.Data were collected from patients' pre-anesthesia evaluation form, intraoperativeanesthesia records, and nephrology medical records. The independent variablesincluded anesthesia technique, intraoperative hydration regimen, CIT, durationand type of dialysis, PRA, living or deceased donor, hemodynamic instability,traumatic or non-traumatic death of the donor, receptor comorbidities, type ofimmunosuppressant used, and weight and age of the donor and receptor. Thedependent variable was DGF.2) tests to comparecategorical variables and the Student's t and Mann-Whitneytests for mean comparisons .Of 310 patients, 67.7% were male, 89% received kidneys from deceased donors, and 112(36%) received general anesthesia. Upon univariate analysis , only thp-value = 0.44). Traumatic death occurred in 42.7% (120) ofthe donors. Stroke was the cause of death of 46.3% (130) and death from otherscauses was 11%.ECD organs were present in 109 transplanted patients, 56 in the DGF group. Analysis of recipient factors revealed associations ofDGF with dialysis time > 60 months . During theintraoperative time, a restrictive fluid regime ,and the use of combined anesthesia  were related toDGF. Cold ischemia time > 12 hours  andbasiliximab  were risk factors to DGF. Among donorfactors, living donor was a protective factor against DGF  and patients with early diuresis had a lower risk of DGF . To assess the performance of the multiple logistic regressionanalysis, we calculated the area under ROC curve, which yielded accuracies of 92.6%.In this retrospective study conducted in 310 kidney transplant patients, weidentified several factors related with delayed graft function. Although causalitycannot be established, our data suggested associations in agreement with otherreports.et al.DGF is one of the most common complications following renal transplantation and isoften associated with acute rejection and increased risk of graft loss. Theincidence of DGF in our study was 76.1%, with rates of 0.01% for living donorkidneys and 83.4% for deceased donor kidneys. In a Brazilian multicenter study of 6transplantation centers, totaling 612 kidney transplants with grafts of deceaseddonors carried out between 2000 and 2002, revealed an incidence of DGF of 53.9,62.3, and 51.6% in 2000, 2001, and 2002, respectively.et al.Living donor kidneys and early diuresis were identified as protective factors forDGF. The short cold ischemia time and the consequent less pronouncedischemia-reperfusion injury (IRI) produce fewer cytokines and free radicals, whichlimit the deleterious effects of IRI. A similar association between graft origin andDGF was reported by Ojo DGF rates were also affected by the type of anesthesia used. Combined anesthesiashowed a three-fold increased risk of graft dysfunction in our study. This is thefirst study to correlate anesthetic technique with DGF. The association may beexplained by the reduction in catecholamine levels and vasodilatation followingneuraxial blockade, which reduces graft perfusion.et al.A restrictive fluid regimen increased the risk of DGF approximately 4-fold. Kidneyperfusion depends linearly on mean arterial pressure, which is influenced byintravascular volume, sympathetic tone, and renal autoregulation.et al.Duration of dialysis pre-transplantation was also identified as a risk factor for DGFin our study. In a retrospective study of 30,294 kidney transplant patients, Keithp-value= 0.03201). Similarly, in a retrospective cohort study of 327 patients, Chenet al.p-value = 0.035). Accordingto Lebranchu et al.,Basiliximab was identified as risk factor for DGF (OR 3.34, The current study had a few limitations. First, some unmeasured variables may haveaffected the accuracy of our models. Second, perioperative care practices may bedifferent in other institutions, potentially accounting for the differences inoutcomes. Third, the lack of water balance, which would be the ideal variable tocharacterize peri-operative volume management. Our study has several strengths: thisis the first study to examine the effect of anesthesia on DGF, and our end-pointsare statistically relevant for clinical practice. Future controlled prospectivestudies should be conducted to further evaluate these results.In summary, this study showed that liberal fluid regimens, kidneys from livingdonors, and cold ischemia of less than 12 hours are protective factors for DGF.Dialysis pre-transplantation > 60 months and combined anesthesia are riskfactors. Basiliximab is a risk factors for DGF.


To investigate the changes of polyunsaturated fatty acids (PUFAs) and their downstream eicosanoids in patients with asthma, the levels of erythrocyte membrane lipids and plasma lipid metabolites were examined.2, TXA2, LTB4, PGE1, 6-k-PGFα1 and PGFα2 in plasma were measured by ELISA.Erythrocyte membrane lipids were extracted and esterificated, and then fatty acid compositions were determined by gas chromatography. The concentrations of six eicosanoids of PGEp < 0.01), showing statistically significant differences. ELISA results showed that the levels of plasma PGE2, TXB2, and PGE1 in patients were higher than health persons; and the levels of eicosanoids of PGF2α and 6-k-PGF1α were significantly lower in patient group than healthy group (p < 0.05), but LTB4 was no obvious difference (p = 0.09). Increased ratio of n-6/n-3 PUFAs is consistent to the increased levels of pro-inflammatory PGE2 and TXB2 and anti-inflammatory PGE1 originated from C20:4(n-6) and C18:2(n-6), indicating that increased ratio of n-6/n-3 PUFAs and eicosanoids from n-6 PUFAs might promote the progress of airway inflammation of asthma.The results showed that the contents of erythrocyte membrane fatty acids in patients with asthma were mainly composed of C16:0, C18:0, C18:1, C18:2(n-6), and C20:4(n-6). The ratio n-6/n-3 PUFAs in patients and health persons were (4.42 ± 1.33):1 and (3.21 ± 0.79):1 (2, TXB2, and PGE1 in patients with asthma were relevant to airway inflammation in some extent. Therefore, it could be proposed that increase of n-3/n-6 PUFAs ratio by diet supplementation of n-3 PUFAs might effectively improve airway inflammation in asthma.Changes of erythrocyte fatty acids, n-6/n-3 PUFAs ratio and the levels of plasma PGE Asthma is an allergic disease of the airways associated with airway hyperresponsiveness to various bronchoconstrictor stimuli , 2. The PUFAs are important components of cellular membrane and functional lipid mediators, which can be divided into n-6 PUFAs and n-3 PUFAs . PUFAs c2), prostaglandin E1 (PGE1), thromboxane B2 (TXB2), leukotriene B4 (LTB4), prostaglandin F1a (PGF1a), prostaglandin F2a (PGF2a) /methanol (MeOH) (Sigma-Aldrich) were added to silica tube. Tricosanic acid (C17:0)  was also added to each tube as internal standard. Air was purged with a gentle stream of nitrogen. Samples were methylated for 1 h at 100 °C and the reaction stopped with the addition of 1 ml double deionized water. After centrifugation for 10 min at 3000 g, the upper hexane layer containing the fatty acid methyl esters was transferred to a 2 ml GC vial [0.5 ml of heparinized venous blood samples were centrifuged for 20 min in 3000 rpm/min at 4 °C, and then the supernatants were removed in order to remove leukocytes and platelets. The lower layer cells were washed by double deionized water, and then centrifuged for 10 min in 3000 rpm/min to remove the supernatants. This was repeated three times to collect the lower layer of erythrocytes. In order to analyze the compositions of erythrocyte fatty acids, a simplified method for analysis of PUFAs was used to extract total lipids and fatty acid methylation [ GC vial .Fatty acid methyl esters were separated on a Shimadzu Scientific Instruments, GC-2010 gas chromatograph equipped with a flame ionization detector and 30 m × 0.25 mm × 0.25 m Omega-WAX capillary column . Helium was used as the carrier at a constant flow rate of 10.1 ml/min. One microliter fatty acid methyl esters were injected into the column in split mode. Fatty acid methyl esters were eluted using a temperature program from 100 to 250 °C. The initial temperature of 100 °C ramped to 220 °C at 15 °C/min and held for 12 min, then ramped to 250 °C at 10 °C/min and held for 13 min. Fatty acid peaks were identified by comparing the retention time of each peak against the retention times of validated fatty acid standards  , respectively. Plasma samples were assayed according to the manufacturer’s instructions. Briefly, plasma samples and controls were added to ELISA plates pre-coated with the capture antibody, then incubated in 37 °C for 60 min, washed and detected based on a colorimetric reaction between a horseradish peroxidase-labeled detection antibody and the tetramethyl benzidine substrate solution. The color absorbance at 450 nm was measured using a spectrophotometer (Bio-Rad).Six kinds of eicosanoids derived from C18:2 and C20:4 were detected. Immunoassays for PGEp < 0.05 was considered statistically significant.T-test and one-way ANOVA analyses were used to evaluate differences in mean erythrocyte fatty acids and mean eicosanoids’ concentrations. Spearman’s correlation coefficient and partial correlation coefficient were used to describe the concentrations of erythrocyte fatty acid and plasma eicosanoids Tables  and 2. AOverall, 31 patients and 31 healthy persons were included in this study, with a mean age of 58 ± 6.5 years old (patients group) and 25 ± 2.3 years old , respectively. In the patients group, there were 13 men (41.90%), 5 patients in 27–29 years old (16.10%), 9 in 30–39 years old (26.03%), 5 in 40–49 years old (16.10%), 6 in 50–59 years old (19.35%), 5 in 60–69 years old (16.10%), 1 in 70–79 years old (3.22%). Meanwhile, the healthy group was 15 healthy men (48.4%) who aged> 16 years old, with no prior history of asthma or other respiratory diseases, allergic diseases, and other chronic diseases.Comparison of the contents of fatty acids in the erythrocyte membrane between patients group and healthy group was given in Table p < 0.01).The percentages of n-6 and n-3 PUFAs in total erythrocyte fatty acids in patients were 30.49 ± 3.03 and 7.56 ± 2.37, while in healthy group, the percentages of n-6 and n-3 PUFAs were 32.33 ± 1.57 and 10.52 ± 2.05, respectively. The contents of n-6 and n-3 PUFAs were significantly decreased in patients group compared to the healthy group, while the ratio of n-6/n-3 PUFAs in patients group were significantly higher than those in healthy group , while the levels of PGF2α and 6-k-PGF1α in patient group were lower than the healthy group   Fig. .Fig. 3CoOur study showed that erythrocyte fatty acids were mainly composed of C16:0, C18:0, C18:1, C18:2(n-6), and C20:4(n-6) in patients with asthma and healthy persons. The contents of fatty acids from the high to low were SFA, PUFA, and MUFA in patients group, respectively, while the healthy group was PUFA, SFA, and MUFA. The proportion of SFAs in erythrocytes in patients with asthma was higher than that in healthy persons. The contents of C14:0, C16:0, and C24:0 in patients were higher than healthy persons. It is known that accumulation of fatty acids due to altered metabolism could induce cell death, cytokine secretion and activation of inflammatory processes. SFAs have been described as ligands of Toll-like receptor 4 to induce fatty acid-mediated cytotoxicity by activation of nuclear factor kappa B and C-jun N-terminal kinase in murine macrophages and adipocytes . Accumulp < 0.01). n-6 PUFAs could regulate the inflammatory responses of the body by their metabolites [PUFAs could exert various functions through directly mechanisms or their metabolites. In this study, the proportion of PUFAs in erythrocytes in patients with asthma was lower than that in healthy persons, indicating that increased consumption of PUFAs in asthma might induce the lower level of PUFAs in patients than the healthy persons. As for the significantly difference (58 ± 6.5 vs 25 ± 2.3) in ages from two groups in this study, a number of clinical trials, including patients with asthma, have investigated the changs in the ratio of n-3/n-6 PUFAs ranged from 3 to 72 years old, showing that the age may not influence the results of study . Our databolites . n-3 PUFabolites . Observaabolites , 22. The2 and TXB2 produced by the action of COX on AA are the predominant pro-inflammatory eicosanoids, were higher in asthma patients than that in healthy persons (Table 1α was lower in patients than that in healthy persons. It is consistent to previous study of the higher level of PGE2 and TXB2 in the plasma of asthma patients than that of healthy persons, and the concentration of 6-K-PGF1α in patients was lower than healthy persons [4, the downstream metabolites of AA produced by the action of 5-LOX, has been considered as a pro-inflammatory mediator and induce airway hyper-reactivity [4 in BALF fluid or blood from severe asthma were higher than moderate symptomatic asthma patients and normal [4 in two groups showed no statistical difference in this study. PGF2α have been also demonstrated to be involved in acute or chronic inflammation in several situations such as asthma [2α in patients was lower than the healthy group. Furthermore, the concentration of PGE1, a typical anti-inflammatory factor, was also higher in asthma patients than that in healthy persons. PGE1 could dilate blood vessels, inhibit oxygen radicals and macrophage activation [PUFAs could be metabolized to PGs, TXs, and LTs through COX and LOX pathways to involve in regulating inflammatory responses . In our  persons . LTB4, tactivity , 26. LTBd normal , 28. Howtivation . Our dat2, TXB2, and PGE1 might be the potential biomarkers associated with the inflammatory responses of asthma, and the treatment of asthma using n-3 PUFAs may be useful to improve the symptoms of asthma [Asthma is a complex syndrome with different clinical phenotypes, airway inflammation is a response companied with the pro-inflammatory and anti-inflammatory reactions in the body. In the initial stage of airway inflammation, the contents of pro-inflammatory mediators might be high, while with the progress of inflammatory responses, the contents of anti-inflammatory mediators were also produced to involve in inflammatory responses. Eicosanoids of PGEf asthma .2, TXB2, PGE1, and the ratio of n-6/n-3 PUFAs in patients with asthma than healthy persons, might be due to the airway inflammation. It provides the basis for studying the association of fatty acids and its metabolites with airway inflammation of asthma.In conclusion, we investigated the compositions of erythrocyte fatty acids and plasma eicosanoids in patients with asthma from Zhanjiang. Changes in fatty acids and eicosanoids level, especially the higher level of PGE


The crude and adjusted hazard ratios for mortality were 0.55 and 0.52 in patients with KT (both p < 0.001). Mortality was insignificantly higher for patients who were on dialysis for longer than 1 year prior to KT compared with those on dialysis for less than 1 year. Conclusion: This study used a propensity score-matched cohort to confirm that KT is associated with lower risk of mortality than dialysis alone in patients newly diagnosed with ESRD.Background: Several comparison studies have suggested that kidney transplantation (KT) could reduce mortality in patients with end-stage renal disease (ESRD). Selection criteria bias is common in the selection of dialysis patients for control groups. In this study, we compared the survival outcome between KT recipients and comparable propensity score-matched dialysis patients. Methods: We used Taiwan’s National Health Insurance Research Database to identify patients newly diagnosed with ESRD between 2000 and 2010. We separated them into two groups: a KT group and non-KT dialysis-only group. To evaluate the survival outcome, we compared each patient with KT to a patient on dialysis without KT using propensity score matching. Results: In total, 1276 KT recipients and 1276 propensity score-matched dialysis patients were identified. Compared with the propensity score-matched dialysis patients, the patients who underwent KT exhibited significantly higher 5-year and 10-year survival rates (88% vs. 92% and 74% vs. 87%, both  Because populations are aging and diabetes mellitus has become more prevalent, the incidence of end-stage renal disease (ESRD) has increased worldwide. ESRD often causes mortality and disability and thus represents a growing public health problem . ConsequBecause most kidney transplant recipients are younger and have fewer comorbidities compared with the dialysis population, the survival rate between all dialysis patients and kidney transplant recipients cannot be directly compared. However, ethical issues preclude the performance of randomized control trials comparing dialysis patients and kidney transplant recipients. Those on transplant waiting lists may be better candidates for inclusion in an investigative study into the difference between the survival rates of dialysis and kidney transplant patients. To further limit the effect of biases caused by confounding variables, we consider forming an adjusted cohort through propensity score matching, as well as implementing equal age and sex categories, to be the best study design for clearly identifying the difference between the survival outcome of each renal replacement therapy. Although it cannot replace a truly randomized trial, propensity score matching is a powerful tool for adjusting confounding variables and reducing the number of treatment selection biases ,17. In tWe conducted a retrospective nationwide cohort study by analyzing the Registry for Catastrophic Illness Patients Database (RCIPD) of the National Health Insurance (NHI) program in Taiwan. The NHI program, which covers 99% of the 23 million inhabitants of Taiwan, was launched on 1 March 1995. The RCIPD contains the medical records for each patient diagnosed with a catastrophic illness from 1996 to 2011. Being listed in the RCIPD exempts patients, including dialysis patients, from copayments for the medical services related to their conditions. The Research Ethics Committee of China Medical University and Hospital in Taiwan approved this study (CMUH104-REC2-115-CR3). We identified patients first listed in the RCIPD from 2000 to 2010 with catastrophic illness registration cards for ESRD who underwent regular dialysis (ICD-9-CM Code 585) and were evaluated for kidney transplantation. We separated these patients into two groups: a kidney transplantation group (ICD-9-CM Code V42.0) and a comparison group of patients receiving dialysis but not transplants. The study index date was defined as the date on which a kidney transplant recipient underwent the transplant procedure, and the corresponding comparison dialysis patients were followed from a randomly assigned date in the same year. Patients diagnosed with cancer (ICD-9-CM Codes 140–208) and those younger than 18 years old or with missing demographic data were also excluded. For each kidney transplant patient, a dialysis patient who did not receive a transplant was selected for comparison; the dialysis-only patients were selected and frequency matched according to age (in 5-year increments), sex, and year of index date on the basis of the same exclusion criteria. A second method of comparison matched the kidney transplantation group and dialysis group with propensity scores at a 1:1 ratio to minimize selection bias. Propensity scores were calculated using logistic regression to estimate the probability of receiving a kidney transplant based on the baseline variables of age, sex, index date, and comorbidities , hepatitis B virus, hepatitis C virus, and peripheral vessel disease). All patients were followed until death, withdrawal from the NHI program, or 31 December 2011 (whichever occurred first). The cumulative censoring rate over 12 years was 7.55% in the kidney transplantation cohort, which was slightly lower than that in the comparison cohort (13.1%). The possible reasons for the discontinuity of national health insurance include death, withdrawal of insurance, immigration, prison sentence, etc.t test for the continuous variables in the age- and sex-matched groups. A standardized difference of ≤0.10 indicates a negligible difference between the two propensity score-matched cohorts. The cumulative incidence of mortality was calculated using the Kaplan–Meier method, and the log-rank test was used to examine the differences between the two groups that were propensity score matched. We calculated the incidence density of mortality according to person-years in each group. Univariable and multivariable Cox proportional-hazard regression models were used to determine the effect of kidney transplantation on the risk of mortality by using a hazard ratio (HR) and its 95% confidence interval (CI). The multivariable models were simultaneously adjusted for age, sex, and the existence of hypertension, hyperlipidemia, diabetes, coronary artery disease, atrial fibrillation, heart disease, hepatitis B virus, hepatitis C virus, and peripheral vessel disease. Based on propensity score matching, Cox proportional hazards models stratifying on the matched pairs were performed to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of developing mortality associated with kidney transplantation, compared with the comparison cohort. Patients were stratified according to age, sex, comorbidity, and follow-up duration, and the relative risk of mortality in the kidney transplantation group compared with the dialysis-only group was analyzed using Cox models. We conducted further data analysis to assess the effect of the dialysis treatment period before kidney transplantation on the risk of mortality, comparing patients receiving dialysis for less than 1 year and for more than 1 year. We also compared the risk of mortality between two groups using different propensity score methods for sensitivity analysis. All analyses were conducted using SAS software version 9.4 , and the two-tailed statistical significance level was set at p < 0.05.Demographic characteristics and the prevalence of comorbidities were compared between the groups using the chi-square test for categorical variables and a two-sample p < 0.001). The 5-year patient survival rate was 92% in the kidney transplantation group and 88% in the dialysis-only group, and the 10-year patient survival rate was 87% in the kidney transplantation group and 74% in the dialysis-only group (both p < 0.05). The mean follow-up periods for the age- and sex-matched patients who died during the study period in the kidney transplantation group and the dialysis-only group were 5.31 ± 3.07 and 5.02 ± 2.96 years, respectively . The oveThe survival benefit for kidney transplant recipients among the patients with ESRD and with different ages, sexes, follow-up durations, and comorbidities was consistent, except in those patients with peripheral vessel disease and atrial fibrillation . The relp > 0.05). We next assessed the effect of the duration of pretransplant dialysis on the risk of mortality in all propensity score-matched kidney transplant patients . CompareSimilar results were observed for mortality through different propensity score methods; the kidney transplant cohort had a lower risk of mortality than the comparison cohort .This 12-year follow-up study is the first large-scale propensity score-matching investigation of the survival benefit of kidney transplantation for patients newly diagnosed with ESRD and undergoing dialysis in Taiwan, a region with a very high prevalence of ESRD. We made three major findings. First, we demonstrated a significantly lower risk of mortality (adjusted HR = 0.52 with 95% CI = 0.43–0.70) for patients with ESRD who received a kidney transplant compared to those who did not. In 2008, Huang CC and colleagues reported overall 10-year patient survival rates of 35% for peritoneal dialysis patients and 33.8% for hemodialysis patients . HoweverSecond, our findings confirmed that selection biases affected earlier survival analysis studies. Previous Taiwanese national data reported by Wu PH and colleagues indicated a mean age of 60.96 ± 13.92 years among 79,645 dialysis patients and that 51.2% of these patients were diabetic . The meaWe also determined the HRs of mortality in dialysis populations across different age ranges, sexes, comorbidities, and follow-up durations . The surStudies have found that a lengthier duration of pretransplant dialysis was an independent risk factor for patient death after kidney transplantation ,24,25. TThe cumulative regular dialysis population in Taiwan was more than 80,000 at the end of 2017. The transplant rate is relatively low in Taiwan. According to the online data from the Taiwan Organ Registry and Sharing Center, less than 10% regular dialysis patients are on the waiting list for kidney transplantation. Moreover, the indication for the waiting list for cadaveric kidney transplantation, such as age and comorbidities, widely varies between different transplant centers. Thus, we suggest that matching from the waitlist could be more difficult than propensity score-matching a dialysis population.The data compiled in the RCIPD limited what could be done in our study. The dataset does not distinguish between live and cadaveric kidney transplantation, but a live kidney transplantation results in a considerably higher long-term survival rate than a cadaveric kidney transplantation. Additionally, we were unable to assess the effect of the condition of the donor kidney. Using a kidney from a donor who has diabetes mellitus, is geriatric, or has viral hepatitis is no longer contraindicated for kidney transplantation. The waiting list criteria for kidney transplantation have also changed over the past few decades ,27,28,29This study confirms the survival benefit of kidney transplantation in patients with ESRD. In light of the survival data presented, we conclude that it is reasonable to perform kidney transplantation on all dialysis patients without contraindication.


Hypertension management in rural, resource-poor settings is difficult. Detailed understanding of patient, clinician and logistic factors which pose barriers to effective blood pressure control could enable strategies to improve control to be implemented.This cross-sectional, multifactorial, observational study was conducted at four rural Rwandan district hospitals, examining patient, clinician and logistic factors. Questionnaires were administered to consenting adult outpatient hypertensive patients, obtaining information on sociodemographic factors, past management for hypertension, and adherence . Treating clinicians identified local difficulties in providing hypertension management from a standard World Health Organisation list and nominated their preferred treatment regimens. Blood pressure measurements and other clinical data were collected during the study visit and used to determine blood pressure control, according to goals from JNC-8 guidelines. Medication availability and cost at each hospital’s pharmacy were reviewed as logistic barriers to treatment.p < 0.05). However, of 89 patients with blood pressure data, only 26 (29%) had achieved goal blood pressure. No patient factor were statistically associated with poor blood pressure control. Among 30 participating clinicians, deficiencies in knowledge were evident; 43% (13/30) and 37% (11/30) chose a loop diuretic as their prescribed medication and as an ideal medication, respectively, for a newly diagnosed hypertensive patient without comorbidities, counter to JNC 8 recommendations, and 50% (15/30) identified clinician non-adherence to hypertension guidelines as a barrier. In the pharmacies, common anti-hypertensive medications were affordably available ; however, clinicians perceived medication cost and availability to be barriers to care.The 112 participating patients were 80% female, with only 41% having completed primary education. Self-reported adherence by the MMAS-8 was high in 77% (86/112) and significantly associated) with literacy, lack of medication side effects and the particular hospital and pharmacy attended (all Clinician-based factors are a major barrier to blood pressure control in rural district hospitals in Rwanda, and blood pressure control overall was poor. Patient and logistic barriers to blood pressure were not evident in this study. The management of hypertension poses many challenges in countries with limited resources , 2. and In considering the relative importance of these factors in Rwanda, several specific features of the health system are relevant. Rwanda has a community based health insurance system that helps to offset medication cost for patients. Rwanda also has a process for central allocation of newly graduated doctors to rural district hospitals, possibly reducing urban-rural disparities seen elsewhere , 10–12. We hypothesized that in the current context of Rwandan rural hospitals, patient barriers would be more important than clinician and logistic barriers in successful treatment of hypertension, due to the system now in place. The knowledge of which factors limit care is vital if resources are to be appropriately allocated. In a cross-sectional study, we analyzed patient, clinician and logistic factors (including medication availability and cost) in four rural district hospitals (DH) and documented blood pressure control among patients in the same rural district hospitals.Prior to study commencement, consent was sought from the Directors General of the four hospitals, and the Head of Pharmacy at each centre. The study was approved by the Faculty of Medicine Ethics Committee at the National University of Rwanda in March 22nd 2014. Written informed consent was received directly from all (patient and clinician) participants prior to study enrolment.In order to investigate the barriers to adequate hypertensive treatment in rural Rwanda, we conducted a cross-sectional, multifactorial observational study at 4 district hospitals: Gitwe, Kabgayi, Kabutare, and Ruhango; all located in the Southern Province of Rwanda. These hospitals were selected for their rural setting, their accessibility by the principal investigator and their relatively high patient volumes. Gitwe and Ruhango DH are located in relatively more remote settings compared with Kabgayi and Kabutare; however, all 4 DH are staffed by general practitioners in internal medicine and treat primarily local subsistence farmers and their families. The four study sites were assigned to anonymous letter identifications  so as to minimize bias in data interpretation and to help anonymize facility-level results.Over the 4-month study period, study staff spent 4 weeks at each hospital recruiting patients (one day a week). All consenting, consecutive patients with hypertension were recruited by medical providers at each DH, who were informed about the purpose and general methodology of the study without disclosure of the specific objectives under investigation. Patients with known hypertension followed and managed in adult outpatient setting, were eligible for enrollment. Patients who were not able to communicate with study staff (due to language or communication difficulties) were excluded from our study. All eligible patients who agreed to participate in the study were included, and no patient was recruited more than once. Approximately 20-30% of patients requested to participate refused, mainly due to the need to depart immediately after the consultation to return home. No sample size targets were applied to recruitment at any individual site. We estimated we would need a sample size of 112 patients to establish the prevalence of hypertension control (estimated to be 40%) with a 10% margin of error at a 95% confidence level, allowing a 20% margin for patient loss or consent withdrawal.Study data were collected via self-reported questionnaires ; literacy level; tobacco and alcohol history; and features of their clinical history of hypertension  and of the patient experience at the clinical encounter . Literacy level was based upon the patient’s own report of their ability to read and write; alcohol and tobacco consumption were considered as dichotomous variables with any reported lifetime habitual consumption being considered positive; other sociodemographic details were considered as reported on the patient questionnaire. In addition, they completed the Morisky Medication Adherence 8-item Scale (MMAS), a validated , 15 toolVital signs, including height, weight and blood pressure, were measured by a trained nurse before a patient entered the office to meet the clinician, as per the clinics’ usual practice. In all hospitals, weight was recorded by using a mechanical bathroom scale after participants removed shoes and any heavy clothing; height was determined with a rigid measure against a vertical wall; and blood pressure was recorded using electronic sphygmomanometers in a seated position, with the lower of two readings accepted. Neither the nurse nor patients were briefed on the later use of measurements. Blood pressure goals were determined according to JNC 8 guidelines [In order to minimize potential bias, such as changing in prescribing behaviors due to priming by the study materials and purpose, all clinicians who were available at each hospital on the last day of data collection were asked to complete a questionnaire. Clinicians were asked to identify barriers to blood pressure control in their patients, including patient, clinician and environment barriers; factors influencing the medication of choice prescribed to their patients; their most prescribed antihypertensive medication in monotherapy; and the best medication to start with to a newly diagnosed hypertension without comorbidities  was given to clinicians, with a request for the clinicians to estimate the monthly cost of treatment. Costs were categorized as “Do not know”, “Less than 50 Rwandan Francs (RWF)”, “Between 50 and 200 RWF”, “Between 200 and 500 RWF”, “Between 500 and 1000 RWF” and “More than 1000 RWF”, after considering the 90% price reduction provided by community health insurance coverage. For comparison purposes, at the time of study 700 RWF were approximately equal in value to one United States dollar.The real cost and availability of antihypertensive medication over the 4-month study period were checked by an in-person review of the hospital pharmacies’ shelves, supply register, price list and dispensing records by a study investigator at each visit to each study site.p < 0.05 was used to compare patient demographic and clinical data with adherence, defined as “high” or “low-moderate” by the MMAS. All statistical analysis was performed with SPSS .Patient demographic and clinical data, patient responses to the MMAS, and clinician responses to the questionnaire on perceived barriers to hypertensive care and medication cost and availability were tabulated categorically. Cross tabulation with use of the Chi squared test, or Fishers’ exact test for expected cell frequencies < 5, at a significance level of Over the 4-month study period, a total of 112 patients  were enrolled across the 4 district hospitals. One hundred and two enrolled patients were subsistence farmers (91%) and 106 were covered by community health insurance (95%). Among the 89 patients in which patient encounter blood pressure levels were obtained, the mean systolic blood pressure was 153 mmHg and mean diastolic blood pressure was 91 mmHg. Only 26 (29%) had achieved the goal blood pressure. Further details about patient demographic factors, and their association with adherence, are presented in Table The study also enrolled 30 clinicians from the same 4 DH. Twenty-five clinicians were general practitioners, a term that in Rwanda denotes a lack of formal postgraduate subspecialty training (83%). Many were in their first year of practice (33%), and a small proportion had greater than 10 years’ experience (13%). Most clinicians perceived patients’ lack of knowledge about hypertension (77%), inability to change their lifestyle (77%) and medication nonadherence (63%), as well as pharmacies’ lack of medication supply (77%) and medication expense (63%) to be the key barriers to blood pressure control, as shown in Table Self-reported patient adherence, as measured by the MMAS, demonstrated 77% of patients to have high adherence Table . AdherenAlthough many clinicians believed medication cost and availability to be major impediments to achieving target blood pressure, most clinicians we unable to accurately estimate medication cost in their respective hospitals . Based upon the review of hospital pharmacies conducted, multiple antihypertensive medications were available at low cost in all hospitals throughout the study period (supplementary data). Monthly medication costs varied between 15 RwF (US$ 0.02) and 315 RwF (US$ 0.38). Captopril, furosemide, nifedipine, spironolactone, methyldopa and propranolol were available at all hospitals throughout the study period. In addition, hydrochlorothiazide was available at hospital C, and atenolol was available at hospitals A and B.Reflecting on the role of the medical provider in the control of blood pressure, 50% of clinicians identified lack of availability of hypertension treatment guidelines as a barrier to care, suggesting clinicians were not confident in selecting anti-hypertensive medications for their patients without the use of guidelines. In support of this perception, a loop diuretic was selected as the most prescribed medication and as the preferred medication to give a newly diagnosed hypertensive patients without comorbidities, by 44 and 37% of clinicians, respectively , and the study’s applicability to other populations. As the patients were selected in non-probabilistic fashion from hypertension clinics, their responses and blood pressure control may not reflect that of the general Rwandan hypertensive population. In addition, we relied upon the clinicians’ diagnosis of hypertension and the blood pressure measurements obtained during routine clinical care to ascertain study eligibility and blood pressure control. This pragmatic approach may have systematically biased the study to include more severe hypertension, due to ascertainment bias. Because permission was sought from each hospital and pharmacy prior to data collection and because study interviews were carried out in the hospital clinics, clinicians may have suspected that patients would be questioned after their clinic visit. This could have influenced clinicians’ education of patients, contributed to the observed high rate of change in prescriptions, and affected patients’ answers to questions related to clinicians. While patients were briefed on the purpose of the study, surveyed clinicians were left unaware of the questions asked to patients, limiting their ability to tailor their management to the survey. In addition, medication availability was assessed only over the 4-month study period, by examining each pharmacy’s registry of medication supply and distribution. It is possible that some doctors had been primed by medication non-availability prior to the study period and therefore underestimated medication availability. However, as many doctors were quite junior in their clinical experience, the effect of any such priming is likely to be small.The MMAS has not been specifically validated in Rwanda. However, it has been validated in many studies in other populations around the world –16. It sExtrapolating the findings of this study to other rural sub-Saharan African hospitals is somewhat challenging, as the Rwandan health system has several features  that are likely to materially affect the results observed. While other rural sub-Saharan African communities may currently have greater financial and logistic barriers to hypertension treatment, this study shows that even when such barriers have been overcome, care may be sub-optimal. It is important to conduct similar surveys in multiple sub-Saharan African sites before concluding that the barriers observed in this study are similar to those elsewhere in the region.Patients attending Rwandan district hospital hypertension clinics have poor attainment of goal blood pressure, with clinician factors appearing more important barriers than patient or logistic factors. In a health care system which has succeeded in making medication available and affordable, deviation of clinicians from standard guidelines for the management of hypertension and low clinician awareness of medication availability and cost appear to be significant barriers to hypertension management and are promising areas for targeted clinician educational interventions.Additional file 1. “Full Questionnaire” including data collected from patients, clinicians and pharmacy drug audit.


Brain natriuretic peptide (BNP) is an important biomarker for patients with heart failure, hypertension and cardiac hypertrophy. Although it is known that BNP levels are relatively higher in patients with chronic kidney disease and no heart disease, the mechanism remains unknown. Here, we review the functions and the roles of BNP in the heart-kidney interaction. In addition, we discuss the relevant molecular mechanisms that suggest BNP is protective against chronic kidney diseases and heart failure, especially in terms of the counterparts of the renin-angiotensin-aldosterone system (RAAS). The renal medulla has been reported to express depressor substances. The extract of the papillary tips from kidneys may induce the expression and secretion of BNP from cardiomyocytes. A better understanding of these processes will help accelerate pharmacological treatments for heart-kidney disease. The Brain natriuretic peptide (BNP), which is a component of the natriuretic peptide (NP) system and also known as B-type NP, is mainly secreted from the cardiomyocytes in response to cardiac stretch and ischemia, and plays an important role in cardiorenal protection ,2,3,4. TCongestive heart failure (CHF) is a complex syndrome characterized by sodium and water retention through the activation of different neurohormonal systems, such as the RAAS and the sympathetic nervous system (SNS), and also importantly, the NP system. Several experimental and clinical studies have implicated BNP in the pathophysiology of the unbalanced cardiorenal axis in CHF. In CHF patients, BNP plasma levels are in excess of 100 pg/mL . Due to Growing evidence suggests that in CHF, coronary artery disease and/or left ventricular hypertrophy etc., are increasingly associated with CKD patients. More recently, the cardiorenal syndrome (CRS), which is a complex pathophysiological condition that involves an association between acute heart failure (AHF) or CHF and renal impairment, has received much more attention. However, this condition is more than just a simultaneous cardiac and renal disease . A recenBNP acts as a compensating agent in the early stages of disease progression by inducing natriuresis and dieresis, and reducing RAAS and SNS. Similar to that seen with severe disease states like HF or CRS and despite high levels, endogenous BNP becomes resistant and is no longer able to compensate for volume overload in such cases. Thus, the supportive role of BNP in counteracting the unwanted effects of activated RAAS and SNS in these diseases provides the rationale for using this peptide as a potential therapeutic agent ,24. As iHuman BNP mRNA is translated to preproBNP of 134 amino acids, from which proBNP of 108 amino acids is processed and cleaved by the serine proteases corin and/or furin, yielding a biological inactive amino-terminal fragment, 76-amino acid proBNP (NT-proBNP) and an active carboxy-terminal fragment, 32-amino acid BNP . It has It has been well established that BNP plays important roles in the kidneys, and provides multiple beneficial effects involving renal function . AbnormaThe functions of NPs are mediated by their interactions with specific surface receptors on the target cells. In the kidney, BNP increases GFR by relaxing the mesangial cells and inhibits the tubular fractional reabsorption of sodium ,35 Figu. BNP alsBNP infusion may play an important role in preventing the development of CKD. McKie et al. recently examined BNP’s role in the pathophysiology of cardiorenal dysfunction and found that in asymptomatic systolic HF patients, chronic subcutaneous BNP therapy for 12 weeks improved renal function along with favourable hemodynamic effects in response to volume expansion . A recenThe vascular effects of NPs are site-specific . ImportaIn CKD patients, impaired renal function restricts the use of NPs, as plasma BNP levels are elevated to ~200 pg/mL in CKD patients without HF. Whether these elevated BNP levels in CKD promote the activation of the NP system and have an effect on the target organ still remains unclear. Downregulation of NPR-A and upregulation of NPR-C expression in the renal medulla and renal cortex, respectively, may be responsible for the resistance of NPs including BNP in CKD, thereby resulting in its limited use in treating CKD patients with HF ,65.BNP clearance is associated with two major pathways. The first involves binding to the NPR-C receptor, while the second one is involved with the degradation by neprilysin (NEP), a zinc metallopeptidase. NPR-C, which is devoid of any guanylyl cyclase activity and coupled to the adenylyl cyclase inhibition , plays aSympathetic stimulation activates the RAAS, including the augmentation of angiotensin II (Ang II) and aldosterone production, as a result of the elevation of vasopressin and norepinephrine plasma levels, as well as the secretion of renin. SNS and RAAS augment the cardiac output by increasing heart rate, contractibility, preload and afterload at the expense of increased oxygen consumption . InhibitBNP has been shown to directly inhibit renin production from the kidney before affecting RBF or GFR , similarExperimental studies using rat cardiomyocytes reported that both endogenous and exogenous BNP reduced aldosterone synthase (CYP11B2) mRNA expression, which may lead to the inhibition of the RAAS and attenuation of cardiac hypertrophy and fibrosis . Further2 has demonstrated that over 12 months, the combination of sacubitril and valsartan was well tolerated and had similar effects on kidney function and albuminuria compared to ARB irbesartan, with a BP and cardiac biomarker lowering effect, suggested that this combination could have the potential for reducing cardiovascular risk in CKD [Although BNP is progressively activated in HF, its response may often be insufficient to counteract the sodium retention and vascular constriction due to activation of RAAS and SNS. Therefore, more thorough approaches were undertaken both experimentally and clinically in an attempt to minimize the dysregulation of these neurohormonal systems. Ongoing strategies in promoting NP include synthesis or using agonists to increase its bioactivity and inhibition of NEP to reduce its catabolism ,91. Nesik in CKD .LCZ696 lowered BP more effectively than valsartan in hypertensive patients . The PARIn spite of having numerous benefits of ARNi so far, however, some concerns raised that limits its clinical use, such as the elevation of bradykinin levels with ARB, the development of angioedema , and theKidneys play an important role in regulating blood pressure. In addition to volume control via urination with balanced water and electrolytes excretion, the kidneys possess several substances that are used to control blood pressure  Figure . The mosEndothelin-1 (ET-1), a 21 amino acid vasoconstrictor, is also produced by the endothelial cells, tubular cells and inner medullary collecting duct cells . In physProstaglandin (PG) is a lipid mediator involved in a variety of physiological and pathological processes in the kidneys . PGE2 isTissue kallikrein is mainly expressed in the submandibular gland, pancreas and kidneys. Kallikreins are primarily produced in the distal convoluted tubule ,119, theIt has been reported by several independent groups that the renal medulla possesses a depressor substance that acts as a counterpart to RAAS ,127. ThiNPPB gene from −1000 to +136 and demonstrated that this promoter was specifically activated in the papillary tips of the kidneys and was not accompanied by the BNP mRNA expression [We recently developed a BNP reporter mouse carrying tdTomato under the mouse promoter of the 1136-bp fragment of the mouse pression . No evidpression ,133,134.pression .The pBNP-tdTomato-positive cells were interstitial cells and were not proliferative. The papillary medulla has been reported to possess the ability to decrease blood pressure due to its vasodilatory activity ,127. To BNP plays an important role as a major player in the heart-kidney connection via its inhibitory effect on the RAAS, especially in the heart and the kidneys. Kidneys possess several substances involved in regulating the blood pressure in addition to volume control via urination. Furthermore, the papillary tips may play important roles in regulating the BNP expression from cardiomyocytes. Additional investigations will need to be undertaken in order to determine the relationship between the renal depressor system and BNP regulation, especially in terms of cardiovascular diseases, such as heart failure, hypertension and CKD.


HR) when after two years the subject either died or suffered life-threatening complications, and as low risk (IDCLR) when the subject remained stable during this period. Values were extracted from ECG and BP signals, the beat-to-beat interval, and systolic and diastolic blood pressure, and analyzed using the segmented Poincaré plot analysis (SPPA), the high-resolution joint symbolic dynamics (HRJSD) and the normalized short time partial directed coherence methods. Support vector machine (SVM) models were built to classify these patients according to SCD risk. IDCHR patients presented lowered HRV and increased BPV compared to both IDCLR patients and the control subjects, suggesting a decrease in their vagal activity and a compensation of sympathetic activity. Both, the cardio -systolic and -diastolic coupling strength was stronger in high-risk patients when comparing with low-risk patients. The cardio-systolic coupling analysis revealed that the systolic influence on heart rate gets weaker as the risk increases. The SVM IDCLR vs. IDCHR model achieved 98.9% accuracy with an area under the curve (AUC) of 0.96. The IDC and the CON groups obtained 93.6% and 0.94 accuracy and AUC, respectively. To simulate a circumstance in which the original status of the subject is unknown, a cascade model was built fusing the aforementioned models, and achieved 94.4% accuracy. In conclusion, this study introduced a novel method for SCD risk stratification for IDC patients based on new indices from coupling analysis and non-linear HRV and BPV. We have uncovered some of the complex interactions within the autonomic regulation in this type of patient.Cardiovascular diseases are one of the most common causes of death; however, the early detection of patients at high risk of sudden cardiac death (SCD) remains an issue. The aim of this study was to analyze the cardio-vascular couplings based on heart rate variability (HRV) and blood pressure variability (BPV) analyses in order to introduce new indices for noninvasive risk stratification in idiopathic dilated cardiomyopathy patients (IDC). High-resolution electrocardiogram (ECG) and continuous noninvasive blood pressure (BP) signals were recorded in 91 IDC patients and 49 healthy subjects (CON). The patients were stratified by their SCD risk as high risk (IDC According to the 2015 update of the heart disease and stroke statistics of the American Heart Association  lower or equal to 35%. Currently, there is no effective means to stratify SCD risk in patients with EF above the risk threshold, who constitutes at least 70% of the patients who will suffer SCD Chugh, . AdditioPrevious studies have hypothesized various strategies to assess SCD risk based on clinical tests and data, imaging techniques, and signal processing methods, among others. The corrected QT interval was tested in elderly subjects and was associated with SCD risk  in predicting an appropriate ICD therapy in cardiomyopathy patients  has been studied as a measurement of autonomic tone. Higher vagal tone activity is related to increased spontaneous variations in heart rate, and multiple non-linear techniques have been applied to study it  study, oriented to evaluate risk predictors of SCD and to improve the risk stratification in IDC patients. Signals from 220 IDC patients were recorded in two hospitals: the Friedrich-Schiller University Hospital in Jena (44 patients) and the Franz-Volhard Clinic in Berlin (176 patients). All participants provided their written informed consent to a protocol approved by the local ethics committee of the two hospitals. This study complies with the Declaration of Helsinki. The study was approved by the local Ethics Committee (No. 0986-11/02).In the acquisition protocol, the ECG signals  and blood pressure  were synchronously recorded for 30 min. The ECG recordings were performed with a Porti system , and the blood pressure recordings with the Portapress NIBP monitor . All patients were recorded under resting conditions in supine position.The inclusion criteria for the IDC patients were LVEF <45% and/or fractional shortening <25%, and the left ventricle end-diastolic diameter (LVEDD) >117%. Additionally, the New York heart association index (NYHA) of each patient was included. The exclusion criteria were systemic hypertension at rest, coronary artery disease, congenital heart disease, pericardial diseases, valvular heart diseases, systemic disease known to cause dilated cardiomyopathy, chronic alcoholism, sustained ventricular tachycardia, atrial fibrillation, diabetes mellitus, renal failure, and active permanent cardiac pacemaker as well as patients without sinus rhythm  percentage of ectopic beats or artifacts, 19 with atrial fibrillation, four because of technical problems, two suffered from hypertrophic non-obstructive cardiomyopathy, one patient with arrhythmogenic right ventricular cardiomyopathy, and another patient who was clinically unstable due to acute decomposition . The remaining patients, who either died of SCD or needed resuscitation because of a life-threatening tachyarrhythmia, were categorized as high risk for cardiac sudden death (IDCHR). None of these patients died from a non-cardiac disease. Additionally, 49 healthy subjects  were used as control group (CON). After a median follow-up period of 28 months (range: 17–38 months), the patients were classified into two groups according to their SCD risk. The group of patients that remained in stable physical condition were considered as low risk for cardiovascular sudden death ] from the ECG signal.- Time series consisting of the maximum successive end-systolic blood pressure amplitude values over time in relation to the previous R-peak  from the BP signal.- Time series consisting of the minimum successive end-diastolic blood pressure amplitude values over time in relation to the previous R-peak  from the BP signal.In order to characterize autonomous regulation of the cardiovascular systems, the following time series from ECG  and BP signals were extracted using in-house software (programming environment Delphi 3 and MATLAB® R2011b):All extracted time series  were filtered by applying an adaptive variance estimation algorithm , segmented Poincaré plot analysis (SPPA) and normalized short-time partial directed coherence (NSTPDC).Xis defined as a bivariate sample vector that contains two out of the three time series, for all their possible combinations , as expressed in Equation (1),The joint symbolic dynamics (JSD) method , were the threshold l is set equal to 0  an 8 ×8 vector matrix can be derived, taking values from T to T.Sequences of symbols are considered words of length Wmatrix .In order to obtain JSD indices that are more robust against noise, fluctuations and artifacts, the comparison threshold should be something other than 0. There are several advantages for choosing a non-zero threshold. For instance, a state will be generated that will help to distinguish between small and large changes in the system's variability. It is also possible to differentiate between decrements and equilibrium because both states are no longer coded with the same symbols. Lastly, the number of word types including “0” will not be the most prevalent within the Winto a vector matrix family (Wf). These indices were analyzed by their occurrence probabilities. Afterwards, these indices were grouped according to their family description (The new space is composed of combinations of 27 different possible types of words (from 000 to 222) and a total of 729 indices. All the word types were grouped into eight pattern families, transforming the vector matrix cription . These pcription . Additiocription  was calcThe thresholds applied were 5 ms and 1 mmHg on the BBI and the blood pressure time series, respectively. These threshold values were successfully applied in earlier work  = x1, x2, x3, …, xn, the Poincaré plot is obtained by plotting X(n) vs. X(n+1). The typical representation is an elongated scatter of plots through the line of identity with all the points whose values are near the mean placed toward the center. Long- and short-term variability indices can be by fitting an ellipse to the shape of the plot and measuring the dispersion along the minor (SD1) and major (SD2) axis of the ellipse, corresponding to their standard deviation  is used to quantify self-similarity in processes by plotting the data into a higher dimensional state space. Considering a time series Although PPA is a non-linear characterization method, indices SD1 and SD2 can be correlated with the linear behavior of the system, hence making them a suboptimal way to explore information about the non-linear part of the process  is an enhanced pseudo-phase space quantification method that yields indices that also represent the non-linear information of the system. In SPPA the SD1 and SD2 indices are calculated similarly to PPA. Then, the scatter points are rotated α degrees around the main focus of the plot as defined in Equation (4),x and y axis correspond to X(t) and X(t + 1) values, Xtime series respectively, and z is the axis of the rotation  the single probability (ρij) is calculated considering the number of points contained by the total number of points in the series. Afterwards, the probabilities of each row (ρri) and column (ρcj) are calculated as the sum of their single probabilities, as shown in Equation (5):Finally, for each rectangle in position (feedback and feedforward aspects.The directed coherence method (DC) describes how and whether two complex physiological signals are functionally connected  determines the either direct or indirect causality between the systems analyzed. The PDC is limited to work on stationary signals and is unable to yield information about the partial correlative short-time interaction properties  process with model order p to determine Granger causality in the frequency domain. For the selection of the optimal model order popt of the AR(p) model and for the estimation of its coefficients, the stepwise least squares algorithm ) providing information about the partial correlative short-time interaction properties of non-stationary signals, with f as the frequency and n the number of windows  with the covariate z , a coupling factor (CF) was introduced. CF was obtained by dividing the mean value πxy by the mean value of πyx, defined asTo quantify the coupling direction between two time series, These results were normalized to become a specific set of values leading to the  factor NF representing the coupling direction, given byxBBI and ySBP) as a function of frequency f. NF takes the following values: NF = {−2, −1, 0, 1, 2}. Strong unidirectional coupling is indicated if NF is −2 or 2 (where −2 denotes ySBP as the driver), bidirectional coupling if NF = −1 or 1 (−1 denotes ySBP as the driver), and an equal influence in both directions and/or no coupling if NF = 0 in respect to coupling strengths .A normalization procedure was applied to CF leading to the normalized factor (NF). NF determinates the direction of the causal connections between the investigated time series (xBBI and ySBP with covariate (zDBP), the areas (ABBI → SBP(DBP), ASBP → BBI(DBP), [a.u.]) generated in space by CF were estimated in each window within the frequency band f = 0–2 Hz, and afterwards, averaged. ABBI → SBP(DBP) and ASBP → BBI(DBP) ranges between 0 to 1 . Hereby, 1 indicates that all causal influence originating from time series Xare directed toward (arrows: →) time series Y.For determining the coupling strength between two time series, e.g., i of the BBI-, SBP-, or DBP- time series X = {xi, i = 1, …N} and Y = {yi, i = 1, …N} with N as the maximal number of samples i  was first normalized by subtracting the mean of Xor Y, respectively. The normalized time series xnorm and ynorm (zero mean and unit variance) were thus obtained as seen in (8)In order to take advantage of the aspect of stationarity and scale-invariance for NSTPDC analyses, a normalization (zero mean and unit variance) of the time series BBI, SBP, and DBP was performed . The analysis of the tachycardic fluctuations (tslope) provides additional information about autonomous cardiovascular regulation  is the sequence method .- The standard deviation of BBI, SBP, and DBP time series .- The proportion derived by dividing NN50  by the total number of NN intervals .- The square root of the mean squared differences of BBI, SBP, and DBP time series .- The power of the low frequency components (0.04–0.15 Hz) of BBI, SBP, and DBP time series .- The power of the high frequency components (0.15–0.4 Hz) of BBI, SBP, and DBP time series .- The ratio between the low and high frequency power components of BBI, SBP, and DBP time series .The HRV and the blood pressure variability (BPV) were quantified using the standard indices from time and frequency domain. The following indices were calculated from the BBI, SBP, and DBP time series, with NN being the normal-to-normal intervals:A total number of 621 indices were extracted to analyze the interaction between the coupling across all signals . The “cd” label represents the cardiac and diastolic coupling, “cs” label indicates the cardiac and systolic coupling, and “ds” label the diastolic and systolic coupling.The distribution of these indices is as follows: 264 indices from the HRJSD, 216 from the SPPA, 97 from the JSD, 12 from the PPA, 9 from the NSTPDC, 21 from the standard HRV and BPV indices, and 2 from the DSMs. Summary descriptions of the indices are shown in In order to reduce dataset dimensionality, Mann Whitney non-parametric statistical test was used to determine the statistical significance of the indices obtained in the characterization process. The results were analyzed for different levels of significance, including the Bonferroni criterion, considering:Additionally, a correlation analysis was performed on the statistically significant indices. The ones with high correlation (ρ ≥ 0.7) and relative lower significance were discarded.The leave-one-out cross-validation procedure was used to validate the results. The classification results are presented in terms of accuracy (Acc), sensitivity (Sn), specificity (Sp), and area under the curve (AUC).The objective of the support vector machines (SVM) method is to find a higher dimensional space where a classification problem can be more easily solved than in the original space. The vectors that defines the hyperplane are called support vectors. This technique allows separating groups of data that are not originally possible using linear classifiers ,Being w is the normal vector to the hyperplane. The function K(xiyi) is the Kernel function that will shape the hyperplane and αi and b define the efficiency of the classifier on the optimal values. In this study we evaluated the Gaussian, Laplace, and ANOVA kernels.where The Gaussian kernel is useful to model radially distributed data, and is defined in Equation (10), where σ is a penalization term,Laplace kernel is a less σ influenced version of the Gaussian kernel, given by Equation (11)d are the optimization indices of its function,The ANOVA kernel works well on multidimensional support vector regression models  in order to avoid scaling biases. For each iteration of features, the model was built by optimizing the value of IDCHR) vs. the low risk IDC patients(IDCLR).The high risk IDC patients (IDC patients vs. the CON subjects.The IDCHR) vs. the CON subjects.The high risk IDC patients (IDCLR) vs. the CON subjects.The low risk IDC patients  and diastolic-systolic (DBP-SBP) couplings. LR and , 2B,D IDLR patient, and .IDCHR and IDCLR groups, 96 indices presented statistically significant differences, corresponding to: 76 indices from the HRJSD, 12 from the SPPA, and 7 from the NSTPDC. After the correlation analysis, a total of 36 statistically significant indices were chosen for the classification process. Some of the most relevant indices, expressed in a mean value and 95% confidence interval, are shown in When comparing the When comparing IDC patients vs. CON subjects, 261 indices presented statistically significant differences between the two groups: 169 from the HRJSD, 76 from the SPPA, and 13 from NSTPDC. A total of 82 indices remained after discarding the highly correlated indices. IDCHR patients vs. CON subjects and IDCLR patients vs. CON subjects, the differences were found in 182 and 247 indices, respectively. After the correlation analysis, 61 and 85 remaining indices were chosen for the classification step. A summary of the most relevant indices is shown in When comparing HR vs. IDCLR comparison, no statistically significant indices were found. In the remaining comparisons, seven indices presented statistical significances: two from the sequence analysis and five from the HRV and BPV standard indices. A summary of these results is shown in When the HRV and BPV standard indices and the DSM were evaluated in the IDCIDCHR vs. IDCLR comparison. The HRJSDds-E0d and NSTPDCcs_Area_c-s allowed us to classify IDC patients from the CON group with an accuracy of 93.6 % and an AUC of 0.94 using the Laplace kernel. Meanwhile, the HRJSDds_LD1-V and the NSTPDCcs_Area_c-s were able to discriminate between IDCHR patients and the CON group with an accuracy of 96.9% and AUC of 0.95 applying the Gaussian kernel. Finally, the HRJSDds-E1d and the NSTPDCcs_Area_c-s were found to be the best indices to classify IDCLR patients from the CON group, obtaining 89.6 % accuracy and a 0.85 AUC with the Laplace kernel. The classification plots and the results are shown in After the SVM classification step, the PPAs_SD1/SD2 and HRJSDds_LU1-P indices were deemed the optimal choices for the Laplace kernel SVM model, achieving an accuracy of 98.9% and an AUC of 0.96 for the HR vs. IDCLR models  and systolic and diastolic blood pressure (BP) temporal series using linear and non-linear univariate and bivariate  techniques. The indices extracted from these techniques revealed patterns that behave differently in patients at high risk of SCD. These indices  were used to train several SVM models in order to classify the subjects based on different levels of SCD risk.LR patients. Additionally, the coupling strength from cardiac activity over both the systolic and diastolic blood pressure  gets stronger when the patients are at high risk, suggesting that the cardiac activity is significantly dominating the blood pressure. This type of relationship has been observed before in congestive heart failure patients  is bidirectional with the diastolic activity as a driver in IDCOur results also revealed that there is a significant increase in systolic pressure activity as a response to the alternant activity of diastolic pressure in patients at risk of SCD (HRJSDds_P-LU1). Similar patterns were also observed in the cardio-diastolic coupling (HRJSDcd_LD1-P), suggesting that the deterioration of autonomic regulation is more severe in patients at high risk of SCD. Earlier studies indicated that symmetric patterns in the HRJSD could be related to baroreflex-like response patterns. This suggests that this kind of behavior is also more pronounced in patients at high risk  occurred more frequently and were more concentrated in low risk patients, suggesting that these patients present a higher HRV compared to patients at higher risk of SCD. The viability of HRV as a reliable predictor of SCD in IDC patients was questioned in an earlier study  in response to decreasing patterns in diastolic blood pressure (LD1). This may be a result of the vagal response, causing less frequent parasympathetic activity, leading to a less effective control of the blood pressure, and consequently the heart rate, in patients at higher risk conditions.These results were consistent when CON subjects were compared with IDC patients: decreasing patterns (E0) in diastolic BPV were reflected in decreasing heart rates at higher frequencies in CON subjects. The DIA_LF/HF was higher in the patients when compared to the CON group. Higher levels of this index reflects efferent sympathetic activity  and low decreasing (LD1) diastolic blood pressure patterns, independent from all BBI patterns, are more frequent in CON subjects. These indices suggest a worsened circulatory homeostasis in IDC patients and support the idea of the influence of baroreflex activity in pathological conditions Kishi, .Earlier studies . Further, this study allowed us to uncover, for the first time, some of the complex interactions that take place within autonomic regulation, leading to a more accurate modeling, and interpretation of these processes in pathological conditions. Our findings revealed that there is a gradual decrease of HRV and an increase of BPV as the SCD risk increases. We conclude that patients at high risk of SCD can no longer maintain circulatory homeostasis consistently, leading to states of stress that worsens the condition over time.With this study we suggest that indices from coupling analysis and non-linear HRV and BPV can contribute to the development of risk stratification in IDC patients. We have introduced a novel cascade model that successfully classified subjects into different levels of SCD risk  study, oriented to evaluate risk predictors of SCD and to improve the risk stratification in IDC patients. Signals from 220 IDC patients were recorded in two hospitals: the Friedrich-Schiller University Hospital in Jena (44 patients) and the Franz-Volhard Clinic in Berlin (176 patients). Each study was performed following the recommendations of the Declaration of Helsinki and patient consent was granted. The study was approved by the local Ethics Committee (No. 0986-11/02).BG and AV: conceptualization. JR, SS, BG, and AV: methodology, validation, writing—original draft preparation, writing—review and editing, and final version approval. BG, JR, and SS: software and data analysis. AV: data acquisition.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.