This study was to study the efficacy of rosuvastatin, amlodipine, and aspirin in the treatment of hypertension with coronary heart disease and its effect on platelet aggregation.  The participants included 60 patients with hypertension and coronary heart disease who were treated at our hospital between January 2020 and May 2021 and were randomly assigned to receive either rosuvastatin, amlodipine, and Ziyin Huoxue Recipe (observation group) or rosuvastatin, amlodipine, Ziyin Huoxue Recipe, and aspirin , with 30 patients in each. Outcome measures included clinical effectiveness, blood pressure indicators, blood lipid indices, plasma viscosity, platelet aggregation, cardiac function, and adverse responses. P < 0.05). The differences were found in blood pressure indices and blood lipid indices between the two groups before treatment (P > 0.05). However, after treatment, the blood pressure indices in the experimental group were significantly lower than those in the observation group (P < 0.05). After treatment, the blood lipid indices, plasma viscosity, and platelet aggregation in the experimental group were significantly lower than those in the observation group (P < 0.05). The left ventricular ejection fraction (LVEF) of patients in the experimental group after treatment was significantly higher than that of patients in the observation group (P < 0.05). There was no significant difference in the incidence of adverse reactions among patients in the two groups (P > 0.05).  The clinical efficacy in the experimental group was significantly higher than that in the observation group ( The clinical efficacy of rosuvastatin, amlodipine, and aspirin markedly reduces the blood pressure indices, blood lipid indices, plasma viscosity, and platelet aggregation of patients with hypertension and coronary heart disease, improves LVEF, and has a good safety profile. Hypertension with coronary heart disease is a common cardiovascular disease, with a high prevalence in the elderly . The cliAt present, given the absence of specific drugs for hypertension and coronary heart disease, its management is mainly performed empirically. Both hypertension and coronary heart disease damage vascular endothelial cells and increase platelet activity and blood viscosity, which aggravates illness in the coronary arteries . TreatmeRosuvastatin is a member of statins, which exerts their effects by blocking the HMG-CoA reductase enzyme in the liver. Studies have shown that rosuvastatin plays an important role in the treatment of hypercholesterolemia and hypertension . AmlodipPrevention of coronary heart disease is considered essential for the management of hypertensive patients. Aspirin is a nonsteroidal anti-inflammatory drug (NSAID) that is frequently used in the therapeutic setting. NSAIDs block the enzyme cyclooxygenase (COX) to provide analgesic, anti-inflammatory, antiplatelet, and antipyretic effects. Relevant investigations have validated the substantial antiplatelet effect of aspirin, and its involvement in the secondary prevention of coronary artery disease has received much clinical attention. . In tradhttp://www.randomizer.org/). For concealment of allocation, the randomization procedure and assignment were managed by an independent research assistant who was not involved in screening or evaluation of the participants.60 patients with hypertension and coronary heart disease treated in our hospital from January 2020 to May 2021 were recruited and randomly assigned to either the observation group or the experimental group, with 30 patients in each group. The randomization was carried out using an online web-based randomization tool  daily and 5 mg of amlodipine  dailyPatients in the experimental group additionally received aspirin. The patients received 300 mg of aspirin enteric-coated tablets  daily, and the dose was reduced to 100 mg daily after a month of treatmentTreatment efficacy: significantly effective: after treatment, the blood pressure was <140/90 mmHg, the pulse pressure was ≤50 mmHg, with a negative result on double 2-step ladder exercise testing and a normal electrocardiogram (EC G) at rest. Effective: after treatment, there was a decrease in systolic blood pressure (SBP) by less than 30 mmHg, a decrease in diastolic pressure (DBP) by less than 20 mmHg, and a pulse pressure between 50 and 100 mmHg, with a positive result on double 2-step ladder exercise testing and an improvement in the ECG at rest. Ineffective: after treatment, the blood pressure, the pulse pressure, result on double 2-step ladder exercise testing, and the resting ECG met the above stipulated criteriaThe blood pressure indices (SBP and DBP) of the two groups were measured using a sphygmomanometerBlood lipid indices: the BS-600 automatic blood biochemical analyzer (Shenzhen Mindray) was used to measure the level of total cholesterol (TC) and triacylglycerol (TG) of the two groups of patientsPlasma viscosity and platelet aggregation: an automatic blood analyzer was used to measure the plasma viscosity and platelet aggregation in all patients before and after treatmentCardiac function: Doppler ultrasound was used to measure the LVEF in patients before and after treatmentAdverse reactions: adverse reactions that may occur during treatment include dizziness, fatigue, nausea, and constipationb is unbiased and normally distributed. SPSS 22.0 software was used as the data analysis software. Measurement data were expressed as t-test. Count data were expressed as the number of cases (%) and analyzed using the X2 test. Statistical significance was indicated by P < 0.05. GraphPad Prism 8 was used to plot the graphics.If the parameter beta is either a difference of means, a log odds ratio, or a log hazard ratio, then it is reasonable to assume that P > 0.05) (The patient characteristics between the two groups were comparable ( > 0.05) .P < 0.05)  .P > 0.05). However, after treatment, patients in the experimental group had significantly lower blood pressure indices than those in the observation group (P < 0.05)  .P > 0.05). Patients in the experimental group exhibited considerably lower blood lipid indices following therapy than those in the control group (P < 0.05)  .P < 0.05)  .P > 0.05) (There was no significant difference in the incidence of adverse reactions between the two groups ( > 0.05) .In recent years, the incidence of hypertension has been increasing due to changes in diet and the development of bad habits. Ineffective control of blood pressure will lead to damage of blood vessels and various tissues and organs at all levels. Hypertension with coronary heart disease is one of the most common cardiovascular syndromes in clinical practice. It is considered a major cause of myocardial infarction and heart failure. Modern medicine shows that hypertension is an independent risk factor for the development of coronary heart disease, as it accelerates the progression of coronary atherosclerosis, leading to a rise in ventricular thickness and narrowing of coronary arteries. The hemodynamic changes produced by continuously increasing blood pressure activate platelets in the blood and contribute to atherosclerotic lesions, causing myocardial ischemia, hypoxia, or necrosis, resulting in coronary heart disease. Hypertension results in reduced blood preparation of coronary vessels, causing myocardial hypoxia and ischemia, and the incidence of coronary heart disease is considerably higher in patients with combined hypertension than in those without. Clinical research has gradually evolved from being focused on blood pressure reduction to treatment strategies that are aimed at reducing the comprehensive risk of hypertension .Ma  found thAmlodipine is a commonly used antihypertensive drug that reduces blood pressure mainly by inhibiting smooth muscle contraction, dilating peripheral blood vessels, and preventing endothelial injury . The medAspirin has remarkable antiplatelet activity and is considered effective in the prevention of thrombosis in patients with coronary heart disease .In the present, the findings revealed that clinical effectiveness in the experimental group was significantly better than that in the control group. This suggests that rosuvastatin, amlodipine, and aspirin outperform rosuvastatin and amlodipine alone, which may be attributed to the strong antiplatelet action of aspirin . In addiFurthermore, after treatment, the plasma viscosity and platelet aggregation of patients in the experimental group were considerably lower than those of patients in the observation group. It was also discovered that the LVEF of the experimental group after treatment was substantially greater than that of the observation group. This suggests that rosuvastatin, amlodipine, and aspirin are more effective than rosuvastatin and amlodipine alone in lowering plasma viscosity and platelet aggregation. And the results also found that there was no significant difference in the incidence of adverse reactions between the two groups, suggesting a high safety profile of rosuvastatin, amlodipine, and aspirin , 21.The treatment of coronary artery disease complicated with hypertension mainly focuses on vasodilatation to improve blood flow and lower blood pressure. Rosuvastatin calcium tablets reduce lipid deposition and delay the onset of atherosclerosis, amlodipine regulates blood pressure, and aspirin inhibits platelet aggregation, resulting in improved blood flow and reduced blood pressure. However, the cases in the present study were obtained from inpatients in the cardiovascular medicine department of our hospital, which is a single source and a small sample size, and the observation period is short, resulting in limitations in the clinical results. In addition, this study is a clinical study, which provides some references for future treatment and diagnosis. However, this study lacks animal tests to clarify what drug target the combination of these three drugs is based on, suggesting a lack of a more scientific basis. Future studies will further expand the source of cases and sample size, as well as design more indicators and extend the observation period and follow-up, so as to obtain more comprehensive data.The clinical efficacy of rosuvastatin, amlodipine, and aspirin markedly reduces the blood pressure indices, blood lipid indices, plasma viscosity, and platelet aggregation of patients with hypertension and coronary heart disease, improves LVEF, has a good safety profile.


Excess weight and metabolic disorders have a negative impact on male reproductive functions. The mechanisms involved are numerous and complex and epigenetic mechanisms may also be involved, notably through the small non-coding RNAs. Among them, microRNAs (miRNAs) are of particular interest. This preliminary study aimed to identify the miRNAs differentially enriched in seminal plasma related to metabolic disorders and if some are also associated with spermatic parameters alterations. One hundred and sixty men between 18 to 45 years, partners of infertile couple, were included in this cohort. The miRNAs associated with metabolism were selected from the literature and assayed by quantitative real-time PCR using TaqMan gene expression assays. A subset of those with an interesting profile in seminal plasma were secondarily tested in blood.Among the 11 selected miRNAs, seven were detected in seminal plasma . A negative correlation was observed between seminal miR19a levels and metabolic syndrome, blood glucose and C-peptide. Seminal miR19b levels were also negatively correlated with metabolic syndrome. Seminal miR34c levels were negatively correlated with body mass index (BMI) and waist circumference. Seminal miR133b levels were positively correlated with BMI, waist circumference and leptin levels. Interestingly, modifications of miRNAs in seminal plasma seem specific since highlighted above correlations were not retrieved in the blood plasma for the miR19a, 19b, 10b, 34c.Few metabolic and anthropometric disorders are correlated with the level of specific miRNAs in seminal plasma. Further studies will be required to decipher if other small non-coding RNAs may also be correlated with metabolic and anthropometric disorders and to assess their potential implication in the alteration of reproductive functions in men with obesity or metabolic disorders.NCT01974947. Registered 18 July 2013.Metabolic Syndrome and Male Infertility (Metasperme): Trial registration:  Over the last few decades, couples have seemed to face increasing difficulties conceiving children. The decline of sperm parameters observed for half a century  may be iSncRNAs present with a size generally below 200 nucleotides and are not translated in functional proteins . HoweverRecent studies also highlighted a crucial role of miRNAs in human fertility . Indeed,MiRNAs profiles can be modulated by environment and pathophysiological contexts, such as cancer, inflammation and metabolic disorders , 21. MorThe primary objective of the following study is to identify whether some miRNAs of potential interest were modulated in seminal plasma in the case of metabolic disorders, and if they were correlated with specific metabolic parameters. The secondary objective was to assess the potential association between seminal miRNA modulation and changes in sperm parameters. Finally, this work assessed whether the correlations observed for miRNAs in seminal plasma were independent or could also be retrieved in blood circulation.This study is an ancillary work of the national multicentric and transversal Metasperme study , which focused on the evaluation of metabolic status and its relationship with sperm parameters in 160 male partners of infertile couples [Male eligibility criteria were (1) partner of a couple presenting primary or secondary infertility lasting longer than 12 months; (2) aged between 18 to 45 years; (3) insured with a social security scheme; (4) have had a prior medical consultation; (5) have completed informed and written consent to participate in the research study. Exclusion criteria were (1) problems understanding French; (2) smoking more than two packs a day; (3) monitored for viral risk; (4) male with an infertility that may be explained by identifiable factors in direct questioning  or factors identified at the etiologic investigation at the sperm analysis (cytogenetic and genetic).All patients in the Metasperme study signed a consent form for the analysis of epigenetic analyses to which the microRNAs belong. Ethical approval was obtained from the Ethics Committee of the University of Paris Ile-De-France. The Germethèque biobank  of Tenon’s hospital provided blood and semen samples and their associated data. Germethèque obtained consent from each patient to use their samples (CPP 2.15.27). The Germethèque pilotage committee approved the study design on 18 December 2015. The biobank has the required declaration #DC-2014–2202 and authorisation #AC-2015–2350. The present study request number made to Germethèque is #20,151,115, and its contract is referenced under the number CHUT: 18 313 C.−2). All patients were assessed by the same trained medical investigator using the same calibrated devices.Height, weight  and waist circumference at the narrowest point between the lower border of the ribs and the iliac crest were evaluated. The body mass index (BMI) was calculated  were evaluated according to WHO guidelines . Sperm mThe remaining sperm sample was centrifuged (600G at room temperature for 10 min). The sperm pellet was used for the sperm DNA fragmentation assay and seminal samples were aliquoted and stored at − 80 °C for further miRNA analysis . Sperm DBlood samples were collected after a 12-h fasting period in dry tubes. After centrifugation 1900G at 4 °C for 10 min), the blood plasma was isolated and High-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, triglycerides and glucose concentrations were instantly measured through the standardised protocols of the hospitals’ biology laboratories. The remaining blood plasma was stored at − 80 °C for miRNA further analysis.Systolic and diastolic blood pressures were measured using a sphygmomanometer cuff around the patient’s arm after 5 min of bed rest in a supine position..Metabolic syndrome was diagnosed by the presence of at least three of the following criteria: waist circumference of more than 92 cm, triglycerides of 150 mg/dL/1.7 mmol/L or more, HDL cholesterol of less than 40 mg/dL / 1.0 mmol/L, fasting glucose of 100 mg/dL / 5.6 mmol/L or more, and arterial blood pressure of 130/85 mmHg or higher .MiRNA from 20 µL of seminal plasma and from 300 µL of blood plasma were extracted from 160 patients using of the nucleospin miRNA plasma kit  according to manufacturer instructions. The volume of seminal plasma used was adapted in view of its high concentration in miRNAs and contains a similar amount to those from the 300 µL of blood plasma . Extra-dA list of 11 miRNAs to be determined was chosen from the literature according to their associations reported in the field of male infertility  , 30 and/P value < 0.05 was considered statistically significant. All statistical analyses were performed with Prism 7 for Mac OS X software .A D’Agostino–Pearson normality test was used to assess the normality of the distribution. However, since most of the variables did not pass the normality test , we used a nonparametric test. To compare men with metabolic syndrome and men without metabolic syndrome, we used a Fisher’s exact test for qualitative variables and a nonparametric Mann–Whitney test for quantitative variables. To measure the linear relationship between miRNA expression and metabolic/fertility parameters, we used Spearman’s correlation coefficient. Strength of correlation was calculated (r) and a Of the 160 male partners of infertile couples in the Metasperme cohort, 47 presented with metabolic syndrome according to its definition (see Methods section). These subjects notably exhibited a higher BMI, waist circumference, systolic and diastolic blood pressure, triglycerides, and lower HDL cholesterol. In this cohort, some men presented with normal semen parameters while others did not. However, semen parameters in this subgroup of the Metasperme cohort do not reveal any statistically significant differences with those of the Metasperme cohort without metabolic syndrome .r =  − 0.178, p = 0.046) and C-peptide levels . MiR19a showed a tendency to negatively correlate with the other identified parameters but without reaching statistical significance. The seminal miR19b level was also decreased in seminal plasma in the case of metabolic syndrome. However, the miR19b did not present any statistically significant correlation when directly compared with identified metabolic and anthropometric parameters . The level of miR34c in seminal plasma was negatively correlated only with anthropometric parameters, namely BMI  and waist circumference . In contrast, the level of miR133b in seminal plasma was positively correlated only with anthropometric parameters, that is, BMI  and waist circumference . No statistically significant correlations were observed between seminal miR34b, miRlet7c or miR10b levels and anthropometric or metabolic parameters.Among the seven miRNAs detected in the seminal plasma , five presented decreased levels in men with metabolic syndrome Fig. .". Notabr =  − 0.185, p = 0.047). No other correlation between seminal miRNAs and conventional semen parameters was observed.Regarding semen parameters, the level of miR34b in seminal plasma was significantly negatively correlated with sperm DNA fragmentation  and LDL- cholesterol . However, levels of miR34c and miR10b in blood plasma were not significantly correlated with neither anthropometric nor metabolic status. Interestingly, no correlation was observed between the blood miRNA and semen miRNA levels (data not shown).Four miRNAs  were selected and their analysis was extended to blood plasma. As expected, all four of the miRNAs were detected in blood plasma. However, levels of miR19a, miR19b and miR10b presented a different profile in blood plasma than in seminal plasma. Indeed, the level of miR19a in blood plasma was negatively correlated with total cholesterol  and abdominal obesity (weight circumference) correlated with certain miRNAs in seminal plasma while the lipid profile did not. Although few studies have shown that dyslipidemia can have repercussions on male reproductive functions , an incrIn this study, seminal miR34b, miR34c, miR133, miR19a, miR19b seminal miRNAs were observed to be modified by metabolic disorders.MiR34 family members are located on two separate chromosomal loci (MiR34a and MiR34b/c) . They haMiR133b has been observed enriched in muscle and heart and in brown adipose tissue. It plays a critical role in pathological cardiac hypertrophy, but also in metabolic homeostasis . It is aMiR19a and miR19b belong to the miR19 family and arise from 2 clusters miR17-92 and miR106a-363 . They arIn blood, we confirm that the miR19a and miR19b were associated to the men metabolic status . InteresIn addition to sperm development and maturation, miR19a, miR19b, miR34c and miR133b, that were associated to metabolic disorders, may also be directly involved in fertilisation and contribute to embryo development. MiR34c appear crucial for the egg first divisions –52. MoreMore importantly, epididymosomes are able to convey protein cargo to the sperm  that canIn this preliminary study, we tested only 11 miRNAs to validate our hypothesis. These first results are promising and highlight the need to apply a high throughput approach, such as miRSeq, to identify miRNAs that are potentially involved. Furthermore, this study only involved male partners of infertile couples. It might be interesting to conduct a similar study on another population with different subgroups of males, regarding their metabolic status and sperm parameters.This study showed that metabolic or anthropometric disorders may be correlated with the expression of certain miRNAs in seminal plasma. Only a few miRNAs could be tested, but this pioneering study shows the usefulness of quantifying seminal sncRNAs to evaluate the impact of metabolic disorders on metabolic changes in seminal plasma. Further studies are needed to decipher whether sncRNAs are involved in reproductive function alteration in obese men with or without metabolic disorders. In addition to this impact, these deregulated miRNAs could play a role in the paternal transmission of developmental diseases (POHAD).


Levels of ET-1 and Gal-3 were strongly correlated with VS parameters . Out of 137 patients, 20 were referred to TAVR, 88 to SAVR, and 29 to OMT. In TAVR patients, the highest levels of ET-1, Gal-3, and VS were found as compared to other patients. The highest incidence of CVD was observed in patients who underwent TAVR (35%), compared to SAVR (8%) and OMT (10.3%) (p = 0.004). In a multivariate analysis, ET-1 occurred predictive of CVD risk , while Gal-3 > 11.5 ng/mL increased the risk of CHF exacerbation episodes requiring hospital admission by 12%. Conclusions: Our study indicated that ET-1 and Gal-3 levels may be associated with the outcomes in patients with DAS.Background: Although degenerative aortic valve stenosis (DAS) is the most prevalent growth-up congestive heart valve disease, still little known about relationships between DAS severity, vascular stiffness (VS), echocardiographic parameters, and serum biomarkers in patients undergoing transcatheter (TAVR) or surgical aortic valve replacement (SAVR). The objective of this study was to identify biomarkers associated with DAS severity, and those that are associated with cardiovascular death (CVD) and episodes of chronic heart failure (CHF) exacerbation. Methods: A total of 137 patients with initially moderate-to-severe DAS were prospectively evaluated for the relationship between DAS severity, baseline VS, and serum biomarkers , and were followed-up for 48 months. The prognostic significance of each variable for CVD and CHF risk was measured by hazard ratio of risk (HR), which was calculated by Cox’s proportional hazard model. Results: DAS severity showed correlations with IL-6Rα (r = 0.306,  Degenerative aortic valve stenosis (DAS) is the most prevalent growth-up heart valve disease ,2. Late Echocardiography remains the gold standard for diagnosis and evaluation of DAS severity, carrying interventional recommendations for the surgical (SAVR) or transcatheter aortic valve replacement (TAVR) . HoweverHerein, a contemporary approach to stratify cardiovascular risk and timing of intervention could be improved through the implementation of more complex work-ups. Further research might be focused on the evaluation of serum biomarkers associated with calcific DAS and imaging modalities, like magnetic resonance imaging, 3D printing, or vascular stiffness (VS) parameters ,7,8,9,10This attitude seems reasonable, since pathologic mineralization of valve leaflets in calcific DAS involves complex relationships with both innate and adaptive immunity . It was On the other hand, an inevitable DAS progression leads to myocardial damage and the left ventricle remodeling through the changes in the cellular architecture of the myocardium, hypertrophy, and eventually cardiomyocyte death. Few circulating biomarkers produced by cardiac tissue correlate with myocardial damage, including plasma B-type natriuretic peptide, growth/differentiation factor-15 (GDF-15), Endothelin 1 (ET-1), and cardiac troponin ,19,20.Although many research studies are running, still there is little known about relationships between DAS severity, VS, echocardiographic parameters, and serum biomarkers in patients referred to SAVR or TAVR.Therefore, the objective of this study was to identify biomarkers associated with DAS severity, and those that are associated with cardiovascular death (CVD) and episodes of chronic heart failure (CHF) exacerbation.2) admitted to complex diagnostic work-ups before referral to SAVR or TAVR. Additional inclusion criteria were left ventricular ejection fraction (LVEF) ≥ 50% and negative history of stroke or transient ischemic attack .The study group comprised 137 consecutive patients with moderate-to-severe DAS , persistent or chronic atrial fibrillation, concomitant mitral valve diseases, newly diagnosed or recent myocardial infarction (<3 months), hemodynamic instability, aortic dissection, and lack of informed consent.On admission, all patients underwent evaluation for cardiovascular risk factors, echocardiographic study, and examination of carotid and vertebral arteries for the assessment of vascular stiffness parameters. The biochemical blood samples for serum biomarkers were taken during the hospital stay, as soon as informed consent was obtained. Serum biomarkers included GDF-15, ET-1, IL-6Rα, urokinase activator receptor (uPAR), galectin-3 , pro-protein convertase subtilisin/kexin 9 (PCSK9), chemokine ligand 5 (RANTES/CCL5), N-terminal prohormone of brain natriuretic peptide (NT-proBNP), and high-sensitivity troponin T (hs-TnT).Based on the collected data, patients were referred to TAVR or SAVR according to the decision of the Heart Team consultation . In the Incidence of cardiovascular adverse events, including CVD and hospital re-admissions for exacerbation of CHF, were recorded prospectively during the 48-month follow-up period.The study protocol was consistent with the requirements of the Helsinki Declaration and approved by the local Institutional Ethics Committee (KBET/118/B/2014 and KBET/1072.6120.148.2018). All patients signed the informed consent to participate in the study.The prevalence of cardiovascular risk factors such as age, gender, hypertension, hyperlipidemia, smoking habit, and type 2 diabetes mellitus was evaluated in compliance with guidelines of the European Society of Cardiology ,23.All patients underwent a complete echocardiographic evaluation in compliance with guidelines of the European Association of Cardiovascular Imaging, focused on the left ventricular systolic and diastolic function, and aortic valve parameters . LVEF waVS parameters, including Resistive and Pulsatile indices , were evaluated with a high-resolution B-Mode, color Doppler, and pulse Doppler ultrasonography of both carotid and vertebral arteries with an ultrasound machine (TOSHIBA APLIO 450) equipped with a linear-array 5–10 MHz transducer on a patient lying in the supine position with the head tilted slightly backward. Bilateral peak-systolic (PSV) and the end-diastolic (EDV) velocities were measured within the internal carotid artery and proximal V2 segment of the vertebral artery. RI and PI indices were evaluated according to mathematical formulae: Resistive Index (RI) = (PSV − EDV/PSV), and Pulsatile Index (PI) = PSV − EDV/((PSV + 2 × EDV)/3). Carotid and vertebral arterial flow parameters were measured by ultrasonographers blinded to the subject’s characteristics.g at 4 °C. Collected serum aliquots were immediately stored at ≤−70 °C until analysis. Concentration of proteins in serum was measured using commercially available ELISA kits according to manufacturer instructions (no. DRN00B (RANTES/CCL5), DPC900 (PCSK9), DET100 (Endothelin 1), and DR600  from R&D Systems and BMS279-4 , EHGDF15 (GDF-15), and EHPLAUR (uPAR) from ThermoFisher Scientific). Final absorbance readings were obtained using a Synergy H4 Hybrid Multi-Mode Microplate Reader .During index hospitalization, fasting blood was collected from an antecubital vein and placed in a tube. Within 30 min of blood collection, plasma was centrifuged for 15 min at 1600× During an observation period of 48 months, aortic valve progression and the incidence of combined end-point defined as CVD and/or exacerbation episodes of CHF were recorded. CVD was defined as fatal  or other CVD . CHF episodes were defined as hospitalization for newly diagnosed exacerbated CHF requiring the administration of intravenous diuretics and/or vasoactive drugs .The final follow-up (FU) visit was performed as telephone visit with the patient or mandated family member. For all patients, data regarding patient vital status were obtained from the national health registry at the closing database.t-test and Analysis of Variance (ANOVA) test, while frequencies were compared using the Chi-squared test for independence, as appropriate.Data are presented as mean ± standard deviation or median [interquartile range] for continuous variables and as proportions for categorical variables. Normal distribution of the studied variables was determined by the Shapiro-Wilk test. Differences between mean values were verified using the Student’s p-value of less than 0.1, a multivariate Cox proportional hazards analysis was performed with the forward-backward stepwise selection method. For continuous variables, we tried receiver operating characteristic (ROC)-determined biomarker cut-points, being defined as the threshold value of the continuous covariate distribution, which best separates low- and high-risk patients with respect to the outcome. For the ‘optimal’ cut-off value, the area under the curve (AUC), 95% Confidence Intervals (95% CI), as well as a sensitivity and specificity were calculated.A univariate Cox proportional hazards analysis was used to determine risk factors for CVD and CHF exacerbation episodes, including traditional cardiovascular risk factors, echocardiographic and VS parameters, and serum biomarkers. For those parameters reaching a Statistical analyses were performed with Statistica version 13.3 software  and with R Studio 3.6.3 .2) was confirmed in 92 patients, while in 45 patients, DAS was classified as moderate (AVA between 1.01 and 1.5 cm2).Out of 137 consecutive patients admitted with the intention of TAVR or SAVR, as a result of a complex diagnostic work-up, severe DAS (AVA < 1.0 cmp = 0.04), and lower extremities arterial disease (LEAD) (p = 0.034) (p = 0.001), IL-6R ά (p < 0.001), NT-pro-BNP (p = 0.004), and uPAR (p = 0.031) were observed between patients with moderate vs. severe DAS  . There w= 0.034) . There wvere DAS .p < 0.001), uPAR , LVEF , and VS , while showing a negative correlation with NT-proBNP . We found good correlation between Gal-3 levels and VS parameters , as well as between ET-1 and VS .DAS severity showed weak, yet significant positive correlations with IL-6Rα , but not with other serum or VS biomarkers  and the observational group.p < 0.001) and presented symptoms in a higher NYHA class  patients, while an exacerbation of CHF requiring hospitalization was recorded in 23 (16.8%) patients.p = 0.004, respectively). The incidence of CHF did not differ significantly between study groups . Additionally, a comparison between the TAVR and SAVR groups showed a statistical difference in CVD rates (p = 0.003), while it showed no difference in the prevalence of CHF episodes (p = 0.683).After the intervention, the highest incidence rate of CVD was observed in patients who underwent TAVR, as compared to the SAVR and OMT groups , with a sensitivity of 57% and a specificity of 43%.In a univariate Cox proportional hazard ratio analysis, age, LEAD, NYHA class III, ET-1, IL-6Rα, NT-proBNP, hs-TnT, serum creatinine, and eGFR showed associations with risk of CVD . The ROCIn the multivariate analysis, age, LEAD, NYHA class III, ET-1, IL-6Rα, hs-TnT, serum creatinine, and eGFR retained their associations with CVD risk .p < 0.001), with a sensitivity of 87% and a specificity of 51%. For VS, the RI ≥ 0.7 and the PI ≥ 1.3 were established as optimal cut-offs (AUC 0.698 (95% CI 0.582–0.813), p < 0.001), with a sensitivity of 71% and a specificity of 63%.With regard to episodes of CHF exacerbation, in a univariate Cox analysis, biomarkers associated with CHF risk were female gender, increased VS, left atrium area, diastolic dysfunction (E/e’), Gal-3, and eGFR. The ROC-determined optimal cut-point for Gal-3 was 11.5 ng/mL (AUC 0.711 (95% CI 0.602–0.819), In a multimarker score developed using a Cox proportional hazards model for CHF exacerbation episode incidences and ROC-determined biomarker cut-points, only Gal-3 higher than 11.5 ng/mL was associated with a 12% risk increase of hospital admissions for exacerbated CHF (95% CI 1.01–1.25) .Our working hypothesis was that specific serum biomarkers and VS parameters may be of help in the decision-making processes in DAS management.The first aspect of our study concerned the relationship between DAS severity and analyzed serum and VS biomarkers. We have observed weak, yet significant associations between DAS severity and levels of IL-6Rα and uPAR. We also found a higher median level of ET-1 in patients with severe DAS, compared to lower DAS severity.Recent studies showed that the calcification extent in aortic leaflets was associated with the increased secretion of soluble uPAR, a biomarker predictive of cardiovascular outcomes after the intervention on the valve ,27.The pro-inflammatory molecule involved in vascular osteogenesis is Gal-3, which was found to be an important biomarker of DAS calcification severity . Conflicp = 0.09) [Although we did not observe a direct relationship between DAS severity and Gal-3 concentration, patients referred to TAVR had significantly higher median levels of Gal-3 as compared to other patients. Similarly, in a study by Bobrowska et al., the median Gal-3 levels were higher in patients with critically-ill aortic valve stenosis referred to balloon aortic valvuloplasty (BAV), with further prospective TAVR . In the  = 0.09) .Moreover, in our present study, Gal-3 was the only independent risk factor associated with episodes of CHF exacerbations during the follow-up period. In a multimarker score developed using a Cox proportional hazards model for CHF exacerbation episode incidence, Gal-3 levels higher than 11.5 ng/mL were associated with a 12% increase in the risk of hospital readmissions for exacerbated CHF. The possible explanation of Gal-3’s role in the worsening of CHF links Gal-3 with renal and cardiac fibrosis resulting from the cardiac and vascular remodeling, and aldosterone increase.Importantly, in experimental animal models, inhibition of Gal-3 blocked aortic valve calcification, cardiac and vascular fibrosis and inflammation ,31. ThesOn the other hand, there are data on the protective role of some biomarkers, such as the secretion of the anti-inflammatory cytokine Interleukine 10 stimulated by the expression of toll-like receptor 7 driving M2 macrophages subset activation . AdditioThe other serum biomarker involved in the endothelial to mesenchymal cells transformation, the descending regulation of vasodilation and vasoconstriction, and vascular inflammation is ET-1 . It was p = 0.004). In line, we have found that ET-1 levels were strongly and independently predictive of CVD risk  in a multivariate Cox proportional hazard analysis.As we have evidenced in the present study, the levels of ET-1 and Gal-3 were strongly correlated with VS parameters, and more importantly the highest levels of ET-1, Gal-3, and VS were found in patients referred to TAVR. Consistently, the highest incidence rate of CVD was observed in patients who underwent TAVR (35%), as compared to the SAVR (8%) and OMT (10.3%) groups (p = 0.009), while we found a negative one with NT-proBNP . It is reasonable, as progressing DAS leads eventually to left ventricle damage, NYHA symptom occurrence, and the exacerbation of CHF, resulting in the increased release of NT-proBNP.We have also found several positive correlations between DAS severity and LVEF (r = 0.223, In our present study, hs-TnT, but not NT-proBNP, occurred as an independent risk factor of CVD in patients with DAS during the follow-up period. Cardiac troponin was validated as one of several variables associated with the myocardium fibrosis, a risk factor of cardiovascular events such as CVD, and heart failure episodes with a high sensitivity and specificity ,39. AddiIn conclusion, our study indicated that ET-1 and Gal-3 levels may be associated with the outcomes in patients with DAS.However, our present study has several limitations such as single-center design and the limited number of study participants. Additionally, the other biomarkers that have a role in phosphoro-calcium bone metabolism such as osteoprotegerin and osteopontin may be worthy of investigation ,44. Addi


Ischemia-reperfusion injury affects postoperative transplanted kidney function in kidney transplant recipients. Dexmedetomidine was reported to attenuate ischemia-reperfusion injury and improve microcirculation, but its propensity to cause bradycardia and hypotension may adversely affect microcirculation. This study investigated the effect of dexmedetomidine on postoperative renal function and sublingual microcirculation in kidney recipients.The enrolled kidney transplant recipients were randomly allocated to the control group or dexmedetomidine group. After anaesthesia induction, patients in the dexmedetomidine group received dexmedetomidine infusion until 2 h after surgery. Sublingual microcirculation was recorded using an incident dark-field video microscope and analysed. The primary outcomes were the creatinine level on a postoperative day 2 and total vessel density at 2 h after surgery.p = .018). On a postoperative day 7, the creatinine levels did not differ significantly between the two groups. Total vessel density at 2 h after surgery did not differ significantly between the two groups.A total of 60 kidney recipients were analysed, and the creatinine levels on postoperative day 2 were significantly lower in the dexmedetomidine group than in the control group (1.5 (1.1–2.4) vs. 2.2 (1.7–3.0) mg/dL, median difference −0.6  mg/dL, Ischemia-reperfusion injury affects postoperative transplanted kidney function, and dexmedetomidine was reported to attenuate ischemia-reperfusion injury and improve microcirculation in other clinical conditions.This study showed that early postoperative renal function was better in kidney transplant recipients receiving dexmedetomidine.Dexmedetomidine’s side effect of bradycardia and hypotension may affect microcirculation, our results revealed that the perioperative sublingual microcirculation did not differ significantly in kidney transplant recipients receiving dexmedetomidine.We found that early postoperative renal function was better in kidney transplant recipients receiving dexmedetomidine infusion, but total vessel density was not significantly different between the intervention and control groups. End-stage kidney disease remains a global health concern; patients undergoing dialysis experience a lower quality of life and suffer increased morbidity and mortality. Kidney transplantation is the definitive treatment for patients on dialysis. However, ischemia-reperfusion injury to the transplanted kidneys may affect their postoperative function after kidney transplantation ,2. MoreoDexmedetomidine is a highly selective alpha-2 agonist with sedative and analgesic effects . It moduThis prospective, randomised, controlled, single-blinded, open-label study was approved by the Research Ethics Committee of National Taiwan University Hospital, Taipei, Taiwan . This study was registered on the ClinicalTrials.gov protocol registration system (ID: NCT02707809). Patients undergoing kidney transplants were evaluated for eligibility. We excluded patients younger than 20 years or older than 70 years, and those with an allergy to dexmedetomidine, refractory bradycardia (heart rate below 60 beats per minute after treatment), and severe atrioventricular block (Mobitz type II and III). Written informed consent was obtained from all participants. The study was conducted and reported in accordance with the CONSORT recommendations . The his2O; and end-tidal carbon dioxide partial pressure 35–40 mm Hg.The patients were allocated to a control group or dexmedetomidine group through randomised allocation using sealed opaque envelopes. The patients underwent sublingual microcirculation measurement before the induction of anaesthesia (T1). From before anaesthesia induction until 2 h after surgery, a non-invasive cardiac output monitoring system  was used for measuring cardiac index, stroke volume index, and stroke volume variation. General anaesthesia was induced with fentanyl 1.5–2.0 µg/kg, propofol 1.5–3.0 mg/kg, glycopyrrolate 0.2 mg and cisatracurium 0.15–0.20 mg/kg and maintained with desflurane at an end-tidal concentration 4.2%–7.2%. Ventilator settings were as follows: fraction of inspired oxygen 40%; tidal volume 6–8 mL/kg; positive end-expiratory pressure level, 5 cm H−1h−1 according to the individual patient’s responses in terms of cardiac index, blood pressure, and heart rate. Fluid supplementation (in the range of 30–40 ml kg−1 of predicted body weight), ephedrine, and norepinephrine were used to maintain appropriate mean arterial pressure (MAP 70–100 mm Hg), heart rate (>60 beats per minute), cardiac index (>2.5 L/min/m2), and stroke volume variation (<13%). Patients undergoing ABO-incompatible kidney transplantation received 6 units of fresh frozen plasma during the operation. Patients in the control group received conventional management with fluid supplementation (30–40 mL/kg of predicted body weight), ephedrine, and norepinephrine to meet the same hemodynamic goal. During operation, the patients received methylprednisolone (10 mg/kg) for immunosuppression. At the end of the surgery, intravenous morphine 0.1–0.2 mg/kg was administered for postoperative analgesia. Extubation was performed in the operation room, and the patients were transferred to the post-anaesthesia care unit. After arrival at the post-anaesthesia care unit, the dexmedetomidine infusion rate was reduced by one-quarter of the initial rate every 30 min and discontinued after 2 h. After blood sample and microcirculation examinations were conducted, the patients were discharged from the post-anaesthesia care unit. In the general ward, postoperative fluid was administered according to the routine post kidney transplant care protocol, adjusted according to urine output and creatinine level. Postoperative creatinine level was measured once daily in the early morning during the follow-up period.After anaesthesia induction, patients in the dexmedetomidine group received dexmedetomidine infusion until 2 h after surgery. To ensure patient safety, the titration rate of dexmedetomidine infusion was separately determined for each patient, and the infusion rate was adjusted in a range of 0.1–0.7 µg kgFor ABO-incompatible kidney transplantation, preoperative desensitisation with rituximab and double filtration plasmapheresis and preoperative immunosuppressive therapy with tacrolimus, mycophenolate mofetil, and methylprednisolone were performed according to our published protocol . Postope2 area [mm/mm2]), perfused vessel density , the proportion of perfused small vessels , and microvascular flow index  were calculated according to round table conference guidelines . Stroke volume index at T2 was lower in the dexmedetomidine group than in the control group (35 (28–39) vs. 40 (32–49) mL/m2/beat, p = .035). Daily urine output did not differ significantly between the two groups at each time point  are shown in p = .003]. Other laboratory data variables, including endocan, diamine oxidase, serum NGAL and urine NGAL levels did not differ significantly between the two groups. Tacrolimus levels at POD3 and POD7 did not differ significantly between the control and dexmedetomidine groups  vs. 6.7 (5.1–10.3) ng/mL, p = .631; POD7, 6.5 (5.0–8.5) vs. 7.0 (5.8–8.5) ng/mL, p = .610).In addition to POD2, creatinine levels were higher in the control group than in the dexmedetomidine group at POD1 and POD3 . Blood uSupplementary Table 1. The creatinine levels on POD 2 remained significantly lower in the dexmedetomidine group than in the control group (1.5 (1.1–2.4) vs 2.2 (1.6–2.7) mg/dL, median difference −0.6  mg/dL, p = .016). TVD at T6 did not differ significantly between the dexmedetomidine and control groups (24.1 (22.9–24.6) vs. 24.0 (22.9–25.1) mm/mm2, median difference 0.1  mm/mm2, p = .804). Hemodynamic variables are shown in Supplementary Figure 1. TVD and PVD did not differ significantly between the two groups . PPV and MFI did not differ significantly between the two groups.During the manuscript reviewing process, a post-hoc analysis was requested. Three patients were excluded from the post-hoc analysis as follows: two patients in the control group received cadaveric kidney transplantation and one patient in the dexmedetomidine group underwent nephrectomy of the transplanted kidney 10 days after the operation for acute rejection and infarction of the transplanted kidney. After exclusion of the three patients, the patient characteristics, operation durations, and intraoperative medications are shown in Supplementary Table 2). Blood urea nitrogen levels were higher in the control group than in the dexmedetomidine group on POD2 and POD3. Lactate levels were significantly lower in the dexmedetomidine group than in the control group at T6 (.0 (0.7–1.4) vs. 1.3 (1.0–1.9) mmol/L, median difference −0.3  mmol/L, p = .008).In addition to POD2, creatinine levels were higher in the control group than in the dexmedetomidine group at POD1 and POD3  improved sublingual microcirculation variables in patients undergoing on-pump coronary artery bypass graft surgery [Two factors may explain how microcirculation could be preserved after dexmedetomidine treatment at 2 h after surgery. First, to ensure patient safety, we did not apply a fixed dexmedetomidine infusion rate during the operation; we used blood pressure, heart rate, and cardiac index to determine the dexmedetomidine infusion rate for each patient. Mohamed  surgery . Second, surgery ,29. In o surgery . BecauseAlthough a concomitant analysis of sublingual microcirculation mirrored the findings of a contrast-enhanced ultrasound examination of the kidney in a septic animal study , the corPreoperative desensitisation and immunosuppressive therapy in ABO-incompatible kidney recipients might attenuate the anti-inflammatory effect of dexmedetomidine during the operation. The randomisation design of this study prevented the significantly unequal number of patients with ABO-incompatible transplantation between the two groups. Moreover, tacrolimus was used in this study, and it had the potential to affect renal function. We did not observe that tacrolimus levels were significantly different between the two groups.This study has several limitations. First, this was a single-centre study. Different protocols of fluid supplementation, target MAP, and cardiac output goal may have different influences on the effects of dexmedetomidine on renal function and microcirculation. Many concurrent interventions during kidney transplants make it difficult to identify a mechanism for the observed effects. Second, the use of dexmedetomidine was not blinded. There were two reasons for not blinding. One was the safety issue of living kidney transplantation, and we aimed to maintain adequate cardiac output for all participants. The other was the difficulty to blind the bradycardia effect of dexmedetomidine. Third, the sample size of this study was not designed and powered to detect the difference between the two groups on POD7. Further studies are required to investigate the longer effect of dexmedetomidine. Fourth, two patients with cadaver kidney transplants in the control group were excluded from the analysis, their creatinine levels on postoperative day 2 were 3.6 and 2.9 mg/dL respectively. Further study is required to investigate the effect of dexmedetomidine in patients with cadaver kidney transplantation. Fifth, there are many components to performing the postoperative bundle care of kidney transplant recipients, and further studies are required to investigate other interventions after kidney transplantation for early recovery or long-term preservation of renal function.In conclusion, we found that early postoperative renal function was better in kidney transplant recipients receiving perioperative dexmedetomidine infusion. The sublingual microcirculation in kidney transplant recipients of the dexmedetomidine group was preserved by maintaining adequate cardiac output and mean arterial pressure. Further studies are warranted to investigate the mechanism and effects of dexmedetomidine on other postoperative clinical outcomes in kidney transplant recipients.Click here for additional data file.


Heart failure (HF) is a progressive cardiac disorder associated with high mortality and morbidity. Previous studies have shown that sleep apnea (SA) is associated with a poor prognosis in HF patients. When HF coexists with SA, both central and obstructive respiratory events often occur. However, few studies have investigated the association between the frequency of central respiratory events coexisting with obstructive events and clinical outcomes in patients with HF and SA. This was a retrospective observational study. Patients with stable HF, defined as a left ventricular ejection fraction of ≤50%, New York Heart Association class ≥ II, and SA (apnea–hypopnea index of ≥15/h on overnight polysomnography) were enrolled. The primary endpoint was a composite of all-cause death and hospitalization for HF. Overall, 144 patients were enrolled. During a period of 23.4 ± 16 months, 45.8% of patients experienced the outcome. The cumulative event-free survival rates were higher in the central SA-predominant group. Multivariate analyses showed that a greater percentage of central respiratory events was associated with an increased risk of clinical outcomes. In patients with HF and SA, the frequency of central respiratory events was an independent factor for all-cause death and hospitalization for HF. Heart failure (HF) is an advanced stage of cardiac disease and is associated with a high rate of mortality and hospitalization due to the exacerbation of HF. The exacerbation occurs despite providing evidence-based medical and non-pharmacological therapies ,2. The iConsecutive patients with HF and moderate to severe SA who participated in the follow-up conducted at the cardiovascular center of Toranomon Hospital  between 1 January 2001 and 1 March 2005, were enrolled in the study. The inclusion criteria were as follows: (1) presence of symptomatic HF, defined as a left ventricular ejection fraction (LVEF) of ≤50% on echocardiography within one month before the diagnostic sleep study and New York Heart Association (NYHA) class II or above; (2) stable clinical status, defined as no hospital admissions within one month before study enrollment and receiving optimal medical therapy for at least one month before study enrollment; and (3) having undergone a sleep study and received a diagnosis of moderate-to-severe SA, which was defined as ≥15 apnea or hypopnea events per hour of sleep . Respiratory events were scored according to the updated American Academy of Sleep Medicine (AASM) 2020 guideline . The excRespiratory events  were scored according to the 2020 AASM scoring manual updates. Apnea, with and without ribcage and/or abdominal movement, was defined as obstructive and central apnea, respectively. Hypopnea was classified as obstructive if any of the following conditions existed: (1) paradoxical chest and abdominal movement during hypopnea events, (2) snoring during hypopnea events, or (3) flow limitation on the nasal pressure signals. Otherwise, the hypopneas were classified as central. Patients’ characteristics, polysomnography data, and clinical outcomes were assessed. Clinical outcomes, defined as a composite of all-cause death and hospitalization for HF until March 2006, were compared between the two groups.t-test or the Mann–Whitney U test for continuous variables, while the χ2 test or Fisher’s exact test were used for categorical variables. Event-free survival between the groups was compared using the Kaplan–Meier estimate with the log-rank test, and hazard ratios (HRs) were calculated using the Cox proportional hazards model. The assumption of proportional hazards was assessed by plotting a log-minus-log survival graph. Univariate analysis was based on the proportional hazards model to determine the associations between prognosis and the following pretreatment variables between the groups: age, sex, body mass index, LVEF, brain natriuretic peptide (BNP) levels, plasma norepinephrine concentration, NYHA class, systolic/diastolic blood pressure, heart rate, HF etiology, atrial fibrillation, Epworth sleepiness score, medications, total AHI, percentage of time spent at oxygen saturation (SpO2) below 90%, lowest SpO2, ratio of slow-wave sleep or rapid eye movement sleep to total sleep time, continuous positive airway pressure (CPAP) therapy, and % C/T as a categorical variable  or % C/T as a continuous variable. Variables with a p value below 0.1 in univariate analysis were included in the multivariate analysis. Statistical significance was set at p < 0.05. All statistical analyses were performed using a statistical software package .The data of all variables were presented as mean ± standard deviation. The baseline characteristics were compared using Student’s p = 0.049). Mean % C/T was 71.3 ± 22.9% in the predominant CSA group and 10.9 ± 13.5% in the counterpart   . A multi= 0.001) .In Model 1, the following variables were included as covariates: age, sex, systolic BP, LVEF, BNP, atrial fibrillation, beta blocker use, and CPAP therapy, in addition to % C/T of ≥30.1% . In Model 2, the aforementioned variables were included as covariates. Additionally, instead of % C/T of ≥30.1% , % C/T (continuous variable) was included.p = 0.02) [In this study, we demonstrated that a higher % C/T was associated with worse clinical outcomes in HF patients with SA. Previous studies reported that SA is a negative predictor in HF patients ,8,9. Rec = 0.02) . CSA was = 0.02) . In pati = 0.02) . However = 0.02) ,12. Repe = 0.02) . Moreove = 0.02) . The undIn this study, we did not elucidate whether % C/T could be an interventional target to improve prognosis in patients with HF and SA. However, CPAP therapy was proven to be associated with reduced risk for a composite of all-cause death and hospitalization for HF, although follow-up polysomnographic data after the initiation of CPAP therapy and treatment compliance to CPAP were not available. CPAP improves cardiac function in patients with HF and CSA ,16,17. PThis was a single-center observational study with a relatively small sample size. Our data should be interpreted carefully, and further studies with larger populations are required to confirm our data.Our study demonstrated that patients who had HF and a higher frequency of CSA had a higher risk of all-cause death and hospitalization for HF.


There was no significant difference in CAVI values between the MUCH and SUCH groups. Multinomial logistic regression analysis exhibited that compared with the CH group, increased CAVI levels were positively associated with the presence of MUCH and SUCH , p = 0.005; OR 2.215, 95% CI (1.310–3.747), p = 0.003) after adjusting for confounders. However, there was a similar trend of the CAVI in the MUCH and SUCH groups , p = 0.686). In summary, our findings support, for the first time, the novel notion that CAVI as an arterial stiffness parameter is an independent risk factor for MUCH, being equally important to MUCH and SUCH. When the assessed CAVI is high in hypertensive patients with normotensive office BP levels, it is necessary to further investigate with a 24 h ambulatory BP monitoring to estimate the longstanding BP control. CAVI may be used as a noninvasive indicator to identify patients with MUCH earlier.Detection of masked uncontrolled hypertension (MUCH) that was defined for treated hypertensive individuals who had normal office blood pressure (BP) but elevated ambulatory BP remains largely challenging. Arterial stiffness is one of the leading risk markers for hypertension and can be clinically assessed by the cardio-ankle vascular index (CAVI). This study aimed to evaluate the association between CAVI and MUCH. A total of 155 hypertensive patients were included with their office BP levels and ambulatory BP monitoring measurements, which were divided into controlled hypertension (CH), MUCH, and sustained uncontrolled hypertension (SUCH) groups, respectively. There were 48 patients with CH, 56 patients with MUCH, and 51 patients with SUCH. Both MUCH and SUCH groups had a significantly higher CAVI than the CH group (9.05 (8.20–9.91) vs. 8.33 (7.75–9.15),  High blood pressure (BP) is a modifiable but poorly controlled risk factor for cardiovascular morbidity and mortality in China and worldwide. Uncontrolled BP is associated with a higher incidence of hypertension-mediated target organ damage . Masked Patients with MH have a normal office BP albeit an elevated out-of-office BP while monitored using 24 h ambulatory BP monitoring (ABPM) or home BP monitoring (HBPM). ABPM measurement is more closely associated with hypertension-mediated target organ damage and the risk of cardiovascular events, is more reproducible than office BP measurement, and can help identify MUCH in treated hypertensive subjects . Howeverβ [Increased arterial stiffness is an independent predictor of cardiovascular complications , 10. Carβ . CAVI isβ –14. HoweThis was a cross-sectional study with the recruitment of the subjects being carried out in the Department of Geriatrics ward in Beijing Tongren Hospital from June 2021 to May 2022. This work was approved by the Ethics Committee of Beijing Tongren Hospital (NO. TRECKY 2021-172).2), ankle-brachial index ≤ 0.9, acute infectious diseases, and malignant neoplasms.24 h ABPM and office BP levels were examined for all patients with hypertension. The inclusion of patients was the presence of a verified diagnosis of essential hypertension and receiving antihypertensives for a year or above. The exclusion criteria were listed as follows: secondary hypertension, acute coronary syndrome, chronic heart failure, cerebrovascular disease including stroke or transient ischemic attack, peripheral arterial disease, and chronic kidney disease with a decrease in glomerular filtration rate (GFR < 45 ml/min/1.73 mAccording to the 2018 European Society of Cardiology/European Society of Hypertension (ESC/ESH) Guidelines for the Management of Arterial Hypertension [All participants received a standardized examination. Medical information regarding age, gender, tobacco smoking, drinking consumption, duration of hypertension, medications, history of diabetes mellitus, coronary heart disease, dyslipidemia, and atrial fibrillation were extracted from the hospital's electronic medical records database. Two authors reviewed the medical data separately.2)). Biochemical values included fasting blood glucose (FBG), glycated hemoglobin (HbA1c), lipid profiles including triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol, (LDL-C), lipoprotein (a) (LP (a)), uric acid (UA), creatinine, and high-sensitivity C-reactive protein (hs-CRP). Blood samples were collected from the forearm vein into vacuum tubes after an overnight fast. All blood samples were measured by an automatic biochemical analyzer  in Beijing Tongren Hospital Clinical Laboratory. The estimated glomerular filtration rate (eGFR) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation [κ, 1) α × max  − 1.209 × 0.993 age × 1.018 . In this equation, κ is 0.7 if male and 0.9 if female, α is −0.411 if male and −0.329 if female, and min and max mean the minimum and maximum values, respectively.Standard instruments were used for all measurements. Anthropometry included height, weight, and body mass index /height squared . The patient's arm was placed on the desk at the heart level. Three readings with a 1-minute interval between measurements were performed, and the last two readings were averaged as office BP [24 h ABPM measurement, belonging to out-of-office BP measurements, was performed based on the 2020 International Society of Hypertension Global Hypertension Practice Guidelines . An ambuCAVI was measured using a VaSera VS-1000 vascular screening system . The patient rested on a bed in a supine position for 10 minutes before the measurements. The CAVI examination was carried out strictly in line with the operational procedure: in a quiet environment, both ankles and brachium were secured with cuffs. Electrodes for electrocardiography were placed on both wrists, and a microphone was placed on the sternum for phonocardiography.a{(2ρ/ΔP) × ln (Ps/Pd) × PWV2} + b, where ρ is blood density, Ps refers to the systolic blood pressure, Pd refers to the diastolic blood pressure, ΔP = Ps − Pd, PWV is pulse wave velocity between the aortic and ankle values, and a and b are constants. The CAVI value was calculated as the average of the right and left CAVI measurements. The normal value of CAVI (low CAVI) is <9, and a CAVI ≥9 is defined as the abnormal value (high CAVI) [The CAVI value was based on the stiffness parameter calculated using the following formula: CAVI = gh CAVI) .p-value of less than 0.05 was considered statistically significant. Statistical analysis was conducted in SPSS 27.0 . Graphs were plotted using the GraphPad Prism software version 9.0 .The type of distribution of quantitative variables was analyzed using the Shapiro–Wilks or Kolmogorov–Smirnov tests. Continuous variables with normal distribution or with non-normal distribution were expressed as the mean ± SD or median with interquartile ranges (25th and 75th percentiles), respectively. Among the three groups, comparisons of continuous variables with normal distribution were carried out by ANOVA. The Kruskal–Wallis test was performed to compare groups with non-normal distribution. Categorical variables were expressed as the number and percentage of cases, and between-group differences were analyzed by the chi-square test or Fisher's exact test as appropriate. The Bonferroni correction was used for all pairwise comparisons. The Spearman correlation was used to identify the relations between the CAVI and BP parameters. Multinomial logistic regression analysis was performed to determine whether CAVI was independently associated with MUCH. Three models were constructed step-by-step. A After excluding 42 participants following our exclusion criteria, a total of 155 participants comprising 48 controlled hypertensive cases, 56 patients with MUCH, and 51 patients with SUCH were included in the subsequent analysis. The average age of patients was 64 years, and 110 (71%) of the patients were male.β blocker, antiplatelet agents, and statins. In addition, the values of FBG, HbA1c, creatinine, eGFR, UA, LP (a), TC, and LDL-C were comparable among the groups. But patients with MUCH were more likely to be male than the patients with SUCH. At the same time, there was a higher level of TG and a lower level of HDL-C in the MUCH group than in the CH group. Patients with MUCH and SUCH had a higher rate of the use of angiotensin-converting enzyme inhibitor (ACEI) or angiotensin II receptor blocker (ARB), while most of the patients in the SUCH group used calcium channel blocker agents (CCB). Both TG and hs-CRP values were higher in the SUCH group than those in the CH group.p < 0.001). Compared with the CH group, the MUCH group had higher levels of 24 h SBP, 24 h DBP, daytime SBP, daytime DBP, nighttime SBP, and nighttime DBP , while the levels of office BP (both office SBP and office DBP) did not differ significantly between the two groups . However, there were no significant correlations between office BP, 24 h DBP, daytime DBP, nighttime DBP, and the CAVI values.Spearman correlation analysis was used to examine the correlations between the CAVI and BP parameters including office BP levels and ABPM measurement Figures . The levp=0.017, and 9.75 (8.35–10.50) vs. 8.33 (7.75–9.15), p=0.002, respectively). However, there was no significant difference in CAVI values between the MUCH and SUCH groups . However, there was no significant difference in comparison with the SUCH group , as is illustrated in Both MUCH and SUCH groups had significantly higher CAVI values than that in the CH group (9.05 (8.20–9.91) vs. 8.33 (7.75–9.15), H groups . Of the p = 0.009, p = 0.005, p = 0.003, p = 0.686, Our findings suggested that the CAVI value is positively related to ambulatory SBP profiles but not associated with office BPs and ambulatory DBPs. In patients with MUCH, there is a higher CAVI value compared with patients with CH. However, there is no significant difference in CAVI values between the MUCH and SUCH groups. After adjusting for confounders, increased CAVI levels are positively and independently associated with the presence of MUCH, although there is a similar trend of the CAVI in the MUCH and SUCH groups.MUCH in hypertensive patients is defined as normal office BP but elevated out-of-office BP (including HBPM or ABPM), among which the risk of cardiovascular events is close to or even greater than that of SUCH. Based on the use of office BP to monitor BP control, physicians will substantially overestimate the number of patients who have well-controlled BPs, leaving many higher-risk patients at an excess risk . It is oThe clinical characteristics of patients with MH and MUCH are poorly defined . AvailabArterial stiffness is becoming increasingly important in clinical applications as an early marker of hypertension-mediated target organ damage . Some stCAVI is regarded as an arterial stiffness parameter independent of the time of its measurement, with advantages including being noninvasive, easier to obtain, and representing a global index of both central and peripheral stiffness. It thus appears to be a suitable candidate for the routine evaluation of vascular organ damage and the estimation of cardiovascular risk, especially in hypertensive subjects . 24 h ABThe current study has several limitations that must be taken into account. Firstly, the recruitment of the subjects was based on hospitalized patients, which may have unpredictable selection bias. Secondly, the participants might have some activities during ABPM, which to some extent may affect the accuracy of the measurement results. Thirdly, cross-sectional studies could not evaluate the causal relationship directly. Finally, the sample size of this work was relatively small.Our findings support, for the first time, the novel notion that CAVI as an arterial stiffness parameter is an independent risk factor for the presence of MUCH, and that it is equally important to MUCH and SUCH. In future clinical work, when the assessed CAVI is high and above the normal range in hypertensive patients with normotensive office BP, it is necessary to further investigate with a 24 h ABPM to estimate the BP control. In hypertensive patients with normotensive office BPs, CAVI might be a potential noninvasive measurement to help identify MUCH earlier. In the future, larger prospective cohort studies are needed to further confirm the causal relationship between CAVI and MUCH among the hypertensive population. The detection of MUCH using deep learning can be the new direction .


Open thoracoabdominal repair is the gold standard in the TAAA treatment. However, there are endovascular techniques, that sometimes may be an alternative, such as branched endovascular aneurysm repair (BEVAR) or implantation of the multilayer flow modulator (MFM). In this study, we aimed to assess differences in the aneurysm sac pressure (ASP) between patients undergoing BEVAR and MFM implantation. The study included 22 patients with TAAA . The pressure sensor wire was placed inside the aneurysm. A measurement of ASP and aortic pressure (AP) was performed during the procedure. The systolic pressure index (SPI), diastolic pressure index (DPI), and pulse pressure index (PPI) were calculated as a quotient of the ASP and AP values. After the procedure, SPI and PPI were lower in the BEVAR group than in the MFM group. During a procedure, a drop in SPI and PPI was noted in patients undergoing BEVAR, while no changes were revealed in the MFM group. This indicates that BEVAR, but not MFM, is associated with a reduction in systolic and pulse pressure in the aneurysm sac in patients with TAAA. A thoracoabdominal aortic aneurysm (TAAA) is a type of aneurysm that is particularly difficult to treat due to its size and involvement of the renal and visceral arteries. TAAA repair requires a technique that will exclude the aneurysm from the circulation, while maintaining perfusion in the visceral and renal arteries. Open thoracoabdominal repair with the implantation of a branched graft is the gold standard in the TAAA treatment. However, the endovascular approach is a promising and modern alternative . The steAfter implantation in the aorta, the MFM modulates blood flow by reducing local wall shear stress, while maintaining branch patency. The porosity rate of the stent for optimal flow modulation was determined at 65%, and stent implantation was reported to cause 90% reduction in flow velocity outside the stent . HoweverThe aneurysm sac pressure (ASP) measurement after stent-graft deployment is one of the promising research directions. Previous studies show that ASP can be successfully and less invasively measured during endovascular repair ,7 and prIn this study, we aimed to assess differences in the ASP between patients undergoing BEVAR and those subjected to MFM implantation. For this purpose, pressure measurements were performed during the procedure by means of an ultra-thin pressure guide wire used in interventional cardiology.This was a prospective experimental study based on the analysis of invasive pressure measurements obtained during endovascular TAAA repair.The study included 22 patients with TAAA. The group treated with BEVAR included 14 patients , while 8 patients  underwent MFM implantation. The characteristic of patients is presented in BEVAR is performed using vascular access sites in the groin . During the procedure, fluoroscopy and angiography are used to guide the accurate placement of the main stent-graft component with branches extending to the celiac trunk, superior mesenteric artery, and the right and left renal arteries. The main stent-graft component should be deployed with appropriate branches extending above the visceral and renal artery ostia. Moreover, it should be correctly placed relative to the aortic axis to ensure that the stent-graft branches are as close as possible to the ostium of the celiac trunk, superior mesenteric artery, and left and right renal arteries. After the correct deployment of the main stent-graft component, it is extended by the branched component to the iliac arteries. The ipsilateral limb of the stent-graft is extended into the common iliac artery, which ensures a complete endograft seal on this side. The contralateral limb is left without extension, with flow directed to the lower part of the aneurysm. The aim of this stage is to achieve temporary aneurysm sac perfusion through patent lumbar arteries, thus reducing the risk of spinal cord ischemia . Next, uThe second stage of the procedure is performed after 2 to 4 weeks by adding the missing component to the common iliac artery on the contralateral side. This results in complete aneurysm exclusion.In MFM  procedurIn patients undergoing BEVAR, pressure measurements were done during the second stage of the procedure, before and after the iliac branch stent-graft placement using the contralateral femoral approach. In patients undergoing MFM implantation, the measurements were done before and after stent deployment.Using local anesthesia with lidocaine, a vascular access port was implanted via the left radial artery. The port was then used to introduce a 0.014-inch pressure guide wire  with a catheter. Under fluoroscopic guidance, the guide wire was advanced to place the pressure sensor inside the aneurysm, while the distal end of the catheter was positioned in the aorta above the aneurysm. At each step of the procedure, a simultaneous measurement of ASP and aortic pressure (AP) above the aneurysm was performed, and the results were recorded in an electronic form. Diastolic blood pressure, systolic blood pressure, and pulse pressure were also recorded both for ASP and AP. Moreover, the systolic pressure index (SPI), diastolic pressure index (DPI), and pulse pressure index (PPI) were calculated as a quotient of the ASP and AP values. After the procedure, the guide wire and the catheter were removed under fluoroscopic guidance. The vascular access device was also removed, and the compression dressing was applied at the puncture site.p value of less than 0.001.For statistical analysis, the Statistica 13.3 software was used . Variables were tested for normal distribution using the Shapiro-Wilk test. The t test was used for the comparison of variables between groups. The level of significance was set at a Pressure measurements were performed in all 22 patients. The presence of a guide wire in the aneurysm sac did not affect the procedure.p < 0.001).There were no significant differences in baseline SPI, DPI, and PPI  between groups. The comparison of SPI, DPI, and PPI measurements after the procedure revealed that SPI and PPI were lower in the BEVAR group than in the MFM group (both p < 0.001), while no changes were revealed in patients undergoing MFM implantation.Changes in SPI, DPI, and PPI before and after the procedure were also assessed within each group. The results for the BEVAR group are shown in Early outcomes (30 days after the procedure) are presented in Numerous authors described the use of MFM implantation for the treatment of aortic aneurysms. These were mostly preliminary studies in a limited number of patients, concluding that further research is needed to investigate the method ,12,13,14Lowe et al.  assessedIn the multicenter STRATO trial including 20 patients, Vaislic et al.  reportedIn a systematic review of 15 studies assessing the use of MFM in a total of 171 patients with complex TAAA pathology , Hynes et al.  reportedMost studies on MFM treatment for TAAAs were conducted on small patient groups. The outcomes for vessel patency, mortality rates, progression of aneurysm diameter, and stent dislocation are satisfactory or at least promising.Most authors emphasized the need for further research; however, usually, no follow-up studies were conducted . In contIn this study, we performed invasive ASP measurements to assess the perioperative efficacy of MFM implantation. To date, there have been only a few reports of ASP measurement in patients with TAAAs. One of the studies reporting ASP measurements was by Baum et al.  in 27 paOur results confirm that MFM implantation is not associated with a reduction in ASP. In each of the eight patients treated with MFM implantation, no significant fluctuations in ASP were noted. On the other hand, patients undergoing BEVAR showed a significant reduction in ASP, indicating successful aneurysm repair.


The disease pathology for diabetes mellitus patients with chronic kidney disease (CKD) may be diabetic nephropathy (DN), non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is of significance. Renal pathological biopsy is the gold standard for diagnosing DN and NDRD. However, it is invasive and cannot be implemented in many patients due to contraindications. This article constructed a new noninvasive evaluation model for differentiating DN and NDRD.We retrospectively screened 1,030 patients with type 2 diabetes who has undergone kidney biopsy from January 2005 to March 2017 in a single center. Variables were ranked according to importance, and the machine learning methods  were then used to construct the model. The final model was validated with an external group .In total, 929 patients were assigned. Ten variables were selected for model development. The areas under the receiver operating characteristic curves (AUCROCs) for the RF and SVM methods were 0.953 and 0.947, respectively. Additionally, 329 patients were analyzed for external validation. The AUCROCs for the external validation of the RF and SVM methods were 0.920 and 0.911, respectively.We successfully constructed a predictive model for DN and NDRD using machine learning methods, which were better than our regression methods.ClinicalTrial.gov, NCT03865914. As lifestyle changes, the number of diabetes mellitus (DM) patients increases globally, particularly in those with type 2 DM (T2DM) . The latThe disease pathology for DM patients with CKD may be DN, non-diabetic renal disease (NDRD), or DN combined with NDRD. Considering that the prognosis and treatment of DN and NDRD differ, their differential diagnosis is significant . CompareSome indicators, such as diabetic retinopathy (DR), DM course, and Hb could help in identifying DN and NDRD –12. HoweIn our previous study, we used the regression method to establish the distinguishing model , 14. CurUsing renal pathological biopsy as the gold standard, we established a noninvasive differential diagnostic model based on SMM and RF to distinguish DN and NDRD patients.This retrospective study included 1,030 consecutive patients with type 2 diabetes who required kidney biopsy at our institution from January 2005 to March 2017 for model development. Additionally, we screened 338 patients from April 2017 to April 2019 at our center for external validation. The variables used for external validation were the same as the variables in the development set. This study was attached to a registered clinical trial [ClinicalTrial.gov. Registry (NCT03865914)].The study protocol was approved by the Medicine Ethics Committee of the Chinese People’s Liberation Army General Hospital . Each patient provided written informed consent before their participation in the study. All patients were screened according to the protocol shown in All patients underwent kidney biopsy after signing the informed consent form. The indications for kidney biopsy were consistent with our previous standards . The kidType 2 diabetes was defined according to the World Health Organization criteria . DN was Baseline characteristics and clinical parameters were collected from all patients before kidney biopsy. Baseline characteristics included age, sex, body mass index (BMI), blood pressure (BP), and medical history of DM and/or hypertension. Laboratory data obtained included measurements of HbA1c, hemoglobin (Hb), serum creatinine (sCr), serum albumin (ALB), estimated glomerular filtration rate (eGFR), and serum lipid levels. Variable definitions have been provided in previous studies .The variable importance of all 49 candidate variables (listed in All processes are shown in Model construction steps: the entire modeling used RF and SVM models. RF modeling used the ranger module in the R language (parameter: importance = “impurity”), and SVM modeling used the kernellab module in the R language . The detailed modeling steps are described as follows:(1) Random forest and support vector machine modeling were performed for 929 samples in the training set  (note: the steps were performed on the RF and SVM models respectively).(2) The RF model was used to screen 49 variables, and finally, 10 features were determined as variables in the final modeling.(3) The 929 samples of the training set and the 10 final selected variables were used to perform five-fold cross modeling , and the modeling results were evaluated.(4) Modeling was performed with all 929 samples.(5) The final model was constructed using all the samples, and the 329 externally reserved samples were used as the test data set; model evaluation was performed, and the receiver operating characteristic (ROC) curve was drawn.The RF machine learning algorithm is an ensemble tree method that can generate many regression trees to detect interactions. At each split, a candidate variable that maximizes the difference in cumulative hazard between the daughter nodes was chosen, and the splitting stopped at the terminal nodes when the data at hand can be split such that each terminal node has at least one unique outcome .The SVM algorithm was originally proposed by Vapnik and colleagues in 1963 . It creaLogistic regression was performed using SPSS version 20.0 . Accuracy and effectiveness were calculated using the formulas previously established by Zhou Jianhui (2008) and Liu Moyan (2014) at our center , 10, whiThe remaining statistical analyses were performed using SPSS version 20.0  and R version 3.5.1  . ClinicaIn total, 929 patients were included in the development set and assigned to one of the two groups (DN and NDRD), based on the outcomes of the kidney biopsy. Patient characteristics are shown in The results of the kidney biopsy indicated that 329 (35.41%) and 600 (64.59%) patients had DN and NDRD, respectively. Numerous pathological subtypes were observed in the NDRD group; membranous nephropathy was frequently observed (32.33%), followed by IgA nephropathy (30.83%), and then mesangial proliferative glomerulonephritis (6.00%) , sCr, and ALB levels  for RF and SVM, and the best combinations are listed in The performances of RF and SVM are shown in In total, 329 patients were enrolled for external validation, and their characteristics are presented in The comparison among the four models showed that RF and SVM do have better diagnostic performance than logistic regression models (Although some CKD patients have a clear history of diabetes and other complications (such as DR), which are clinically suspected to be diabetic nephropathy, there are still some kidney biopsy results of NDRD or DN combined with NDRD. The incidence of DN and NDRD varies greatly in different studies. The prevalence of DN ranges from 6.5 to 94% with an average of 41.3% –29; NDRDIn our study, membranous nephropathy (MN) was the most common type, accounting for 32.33% of all NDRD cases, followed by IgA nephropathy, which accounted for 30.83%. In previous studies, MN (7 to 35%) was the most common cause of NDRD –37. SomeDR, DM course, Hb levels, PP, and hematuria were among the most important indicators of diagnosis through importance ranking in our study. Same with the previous studies, which reported that the absence of DR , hematurDR ranked first in all indicators; DR was a co-occurrence in 79.3% of DN patients in this study. Previous studies ranged from 37 to 84% –51. In mThe presence of microhematuria in diabetic patients with proteinuria may range from 11 to 76–78% , 57, whiIn our study, the DN group tended to have more severe hypertension than the NDRD group. The systolic and diastolic blood pressures (SBP and DBP) of the DN group were higher than those of the NDRD group, and this result is consistent with that in our previous study, which reported that lower BP was a good predictor of NDRD , 13, 59.Kidney biopsy is the gold standard method for diagnosis, but it cannot be performed on all patients because of contraindications  and reluctance to undergo biopsy. As it is an invasive technique with certain risks, such as hematuria and perirenal hematoma, arterial embolization might be required , 62. MorThe previous non-invasive identification guidelines widely used internationally are the 2007 KDOQI guidelines , which wMachine learning has been used in many diabetes-related CKD studies, such as genotype–phenotype risk patterns  and enseThis study had several limitations. First, the time span of patients included is quite large (2005–2017); thus, the disease patterns for DM patients combined with CKD may change over this long period. Therefore, we built a new model using a new population (2015–2017), and it was verified externally. The 2015–2017 model did not show better performance  for the publication of any potentially identifiable images or data included in this article.WZ: Design of the experiment, data statistics, and model building. XL: Data collection, statistical analysis, and model building. ZD and QW: Data collection. ZP: Statistical analysis and model building. YC, YW, and YZ: Collecting clinical data. PC and ZF: Kidney biopsy. XS, GC, and XC: Design of the experiment. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.This study was supported by the National Natural Science Foundation Of China (32141005), the Science & Technology Project of Beijing China (no. D171100002817002), the Beijing Municipal Science and Technology project (no. Z181100001918015), the National Basic Research Program of China (no. 2015CB553605), the National Key R&D Program of China , the Natural Science Foundation of China , and the Specialized Scientific Program of the Hainan Province Academician Innovation Platform (YSPTZX202026).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


In the validation cohort, EHRV > 24.5% showed specificity = 100% , positive predictive value = 100%, and negative predictive value = 67.1% . The positive likelihood ratio was infinity, and odds ratio was not calculable because all the patients with EHRV > 24.5% showed ≥ 5% dehydration and/or AKI. We hypothesized that the heart rate (HR) variation in an acute setting compared with HR in wellbeing status could be a good marker of both dehydration and acute kidney injury (AKI). Since HR in wellbeing status is unknown in most cases, we assumed as reliable surrogate the 50th percentile of HR according to age and gender. We evaluated if the estimated percentage of heart rate variation in acute setting compared with 50th percentile of HR (EHRV) could be marker of dehydration and AKI in children. Two independent cohorts, one prospective comprehending 185 children at type 1 diabetes mellitus onset (derivation) and one retrospective comprehending 151 children with acute gastroenteritis and pneumonia , were used to develop and externally validate EHRV as predictor of the ≥ 5% dehydration and/or AKI composite outcome. Febrile patients were excluded. EHRV was calculated as ((HR at admission–50th percentile of HR)/HR at admission) × 100. The prevalences of ≥ 5% dehydration and AKI were 61.1% and 43.8% in the derivation and 34.4% and 24.5% in the validation cohort. For the ≥ 5% dehydration and/or AKI composite outcome, the area under receiver-operating characteristic curve of the EHRV in the derivation cohort was 0.69 (95%CI, 0.62–0.77;    Conclusions: EHRV appears a rather reliable marker of dehydration and AKI. Further validations could allow implementing EHRV in the clinical practice.The online version contains supplementary material available at 10.1007/s00431-022-04381-3. Gastroenteritis and dehydration account for a large proportion of childhood hospitalizations . Among CEarly recognition of dehydration signs and proper definition of dehydration degree could improve the care of these patients and could reduce hospital admissions for dehydration .The gold standard to classify the dehydration is the percentage of weight loss . TherefoClinical parameters that can support in the evaluation of a child with suspect of dehydration are capillary refill > 2 s, dry mucous membranes, absent tears, generally ill appearance, deep breathing, and increased thirst . UnfortuWhile clinicians may feel that they can intuitively identify which children are severely dehydrated and which ones are not, general practice physicians and nurses are likely to both over- and under-diagnose severe dehydration based on their overall clinical impression, suggesting an important role for the use of standardized scales when assessing children with suspect of dehydration .Increased heart rate (HR) is the first mechanism of compensatory adaptation to hypovolemia , and it Acute kidney injury (AKI) is often a consequence of renal hypoperfusion due to dehydration in children –12. We hSince HR in wellbeing status is an unknown parameter in most cases, we assumed as reliable surrogate the 50th percentile of HR according to age and gender . We aimeThe HR-based index to identify children with dehydration or AKI was developed by a post hoc analysis of the DiAKIdney (T1DM and AKI) cohort , a prospWe validated the findings of the derivation cohort in a separate cohort of children affected by acute gastroenteritis  and commThis cohort comprehends 300 patients, 114 (38%) with acute gastroenteritis *100.Estimated weight = estimated (from parents) weight loss at T1DM onset + weight at admission.Percentage of measured heat rate variation (MHRV) in acute setting compared with wellbeing status = ((HR at admission − HR after 14 days)/HR at admission) × 100.EHRV = [(HR at admission − 50th percentile of HR for age and sex)/HR at admission]*100. We used the percentile charts provided by Sarganas et al.  in childAKI was defined according to the Kidney Disease/Improving Global Outcomes (KDIGO) serum creatinine and/or urine output criteria . We consAccording to World Health Organization, the dehydration was classified as mild in case of < 5%, moderate in case of 5–10%, and severe in case of > 10% of MWL .Details about power calculation and statistical analyses are shown in the We calculated the crude HR value for each age which should increase the clinical suspicion of ≥ 5% dehydration and/or AKI as follows: 50th percentile of HR for age and sex + ((50th percentile of HR for age and sex/100) × the best EHRV cut-off).The study was approved by our Research Ethical Committee (protocol number 0014355/i/2020), and all parents provided written informed consent before any procedure.The mean age of derivation cohort was 9.1 years (4.1 SDS). None of the patients in this group was febrile or presented pain. Out of 185 patients, 72 (38.9%) presented with mild, 61 (32.9%) with moderate and 52 (28.2%) with severe dehydration. AKI was found in 81/185 patients (43.8%) . Out of p = 0.37)     Fig. A. On thep < 0.001)  Fig. .Fig. 2Mep = 0.001)    was a significant prognostic factor for ≥ 5% dehydration, > 10% dehydration, and AKI (Supplementary Table 01) Fig. A, > 10% 01) Fig. B, and fo01) Fig. C.Fig. 3Rp < 0.001)  and AKI .The mean age of external validation cohort was 2.9 years (2.5SDS). None of these patients presented with pain. Out of 151 patients, 52 (34.4%) showed ≥ 5% dehydration and 37 (24.5%) AKI. Patients with ≥ 5% dehydration and AKI respectively showed higher EHRV levels compared with patients without ≥ 5% dehydration . Similar findings were found when we compared the EHRV of patients with and without AKI .Comparing the characteristics of patients of both cohorts, we found that patients of the validation cohort were younger and presented lower EHRV, creatinine, highest creatinine/basal creatinine (HC/BC) ratio, sodium, chloride, and hematocrit levels and lower prevalence of AKI, ≥ 5% dehydration, and of the composite outcome defined by ≥ 5% dehydration and/or AKI compared with patients of the derivation cohort Table . When wep < 0.001)    in wellbeing status could be enough to improve our tools to define the dehydration in childhood. Until this becomes part of the current practice, the EHRV can be a useful and easily detectable sign rising the suspect of dehydration and AKI. Our one-page tool Fig.  could heAKI, especially if mild in degree, is often overlooked in children, with important future implications given the risk of later chronic kidney disease , 14, 23.Our study has some limitations. First, our results are applicable only to dehydrated children without fever. Second, a difference in age between derivation and validation cohort exists. The EHRV, however, performed best in the derivation group indicating a clinical usefulness of EHRV also in younger children. Third, the retrospective nature of the external validation cohort did not allow to accurately discriminate between patients with moderate and severe dehydration from the clinical chart review. Finally, HR is a highly variable parameter and can be affected by fear or anxiety. While in the derivation cohort comprehending a prospectively enrolled cohort of patients, we paid particular attention to the HR detection collecting it when patients were quiet, we cannot assure this attention also in the validation cohort in which the data were retrospectively collected. However, because in the retrospective validation cohort AKI and ≥ 5% dehydration have been defined on the basis of biochemical and of clinical data available from the clinical charts of the patients and because we observed a higher EHRV performance compared with derivation cohort, we can hypothesize that the fear and anxiety of the patients of the validation cohort has not significantly affected our data. In fact, if a patient has fear or anxiety, he/she presents higher HR but without clinical or biochemical anomalies suggesting dehydration and/or AKI so affecting the EHRV performance. On the other hand, the validation using a retrospective cohort could be also a strength of this study allowing us to test our findings using data collected in the daily clinical practice without the “particular attention” to data collection that could be paid in the prospective studies.In conclusion, our data suggest that the HR could play an important role in the clinical evaluation of a child with suspect of dehydration. The EHRV can predict at least moderate dehydration if > 23.2% and AKI or the composite outcome defined by at least moderate dehydration and/or AKI if > 24.5%.To avoid misleading translation of our findings in the daily clinical practice, we want to underline that the HR measurement should be taken when child is as best as possible quiet and that the clinical significance of HR should be always pondered on the basis of the clinical context. Further validation of our data in prospectively enrolled cohorts could allow implementing EHRV in the clinical practice.Supplementary file1 (DOC 34 KB)Supplementary file2 (DOC 52 KB)Below is the link to the electronic supplementary material.