Obstructive sleep apnea (OSA) is a sleep disorder characterized by intermittent hypoxia, chronic inflammation, and oxidative stress and is associated with cardiometabolic disease. Several biological substrates have been associated with OSA such as nephroblastoma overexpressed (NOV), endothelial progenitor cells (EPC), and circulating endothelial cells (CEC). Few studies have looked at the association of NOV with OSA while the EPC/CEC relationships with OSA are unclear. In this study, we hypothesize that (1) NOV is associated with the severity of OSA independent of BMI, identifying a protein that may play a role in the biogenesis of OSA complications, and (2) EPCs and CECs are also associated with the severity of OSA and are biomarkers of endothelial dysfunction in OSA.  61 subjects underwent overnight polysomnography (PSG), clinical evaluation, and blood analysis for NOV, EPC, CEC, interleukin 6 (IL-6), and other potential biomarkers. p = 0.032; EPC p = 0.001). EPC was also independently associated with AHI after adjusting for BMI, age, and sex (p = 0.017). IL-6 was independently associated with AHI, but not with ODI.  NOV and EPCs were independently associated with the oxygen desaturation index (ODI) after adjusting for potential confounders including body mass index (BMI), age, and sex (NOV  NOV and EPC levels correlate with the degree of OSA independent of BMI, indicating that these biomarkers could potentially further elucidate the relationship between OSA patients and their risk of the subsequent development of cardiovascular disease. Obstructive sleep apnea (OSA) is a highly prevalent disorder, ranging from 3% to 17% in the general population depending on age and gender . The res.NOV is a multifunctional protein that plays a role in inflammation, cancer, and fibrosis through its involvement in adhesion and mitosis pathways  and has .CECs and EPCs are involved with vascular injury and repair. CECs are essentially “sloughed endothelial cells” resulting from systemic inflammation, which are replaced by EPCs that are expected to increase as inflammation-induced CECs sloughing increase . When thIn the current study, we sought to demonstrate that in a sample of well-characterized OSA subjects at increased risk for cardiovascular disease, baseline inflammation in OSA, as demonstrated by changes in known and novel inflammatory biomarkers, may help to risk stratify this population and further elucidate a pathogenic link between OSA and cardiovascular disease. This manuscript is a follow-up study to our previous work  with a lStudy subjects and controls were enrolled at New York-Presbyterian Brooklyn Methodist Hospital (NYPBMH), and laboratory analysis of blood samples was analyzed at New York Medical College (NYMC). Subjects were drawn from individuals presenting to the Center for Sleep Disorders at NYPBMH for evaluation of possible OSA and from faculty and staff of NYMBMH who were not at risk for OSA to serve as controls. Subjects were considered for enrollment only in the absence of a known history (chart review) of coronary artery disease, atherosclerosis, or congestive heart failure. Only adults (age > 18 years old) were recruited. All subjects provided informed consent. A total of 61 subjects were enrolled. IRB approval at the clinical site (NYPBMH) was obtained prior to enrollment. All data were collected prospectively.All recruited patients had a complete history and physical examination. Patient demographics were collected including age, gender, and race. Patients underwent measurement of systolic and diastolic blood pressure, height and weight for BMI determination, neck circumference, and waist and hip circumference for waist-hip ratio determination by standard methods. Patients were also queried, and medication lists were evaluated to determine the presence of comorbid medical conditions .All patients underwent nocturnal polysomnography (PSG) either by (1) conventional full-montage in-laboratory PSG or (2) home sleep testing; studies were performed in accordance with American Academy of Sleep Medicine (AASM) guidelines. Conventional full-montage in-laboratory PSG was performed using Compumedics  software: standard 10-20 electroencephalography (EEG), electrocardiography (ECG), electromyography (EMG) of the chin and anterior tibialis muscle, electrooculography (EOG), snore, and pulse oximetry monitoring were utilized. Oral and nasal airflow were measured by pressure transducer and thermocouple. Respiratory effort was measured with respiratory impedance plethysmography bands at the chest and the abdomen including summation channel. Home sleep testing was performed using ResMed ApneaLink Air . An apnea was defined as a reduction in peak thermal sensor  excursion by ≥90% of baseline, in which there is continued or increased inspiratory effort throughout the entire period of absent airflow lasting at least 10 seconds. Desaturation and/or arousal were not required. A hypopnea was defined as an abnormal respiratory event lasting at least 10 seconds with at least a ≥30% reduction in the nasal pressure signal excursion  accompanied by a ≥4% oxyhemoglobin desaturation. The AHI is a measure of OSA severity and derived from the number of apneas and hypopneas per hour of sleep (in-lab determination) or per hour of recording time (home sleep testing). OSA was defined as AHI ≥ 5/hr for analysis purposed. Further analysis with AHI ≥ 15/hr was also explored.Venous blood was drawn from antecubital vein into a serum separator tube and a tube containing EDTA. Each SST sample was centrifuged at a force of 1600 g for 10 minutes after blood draw. The tubes were placed in an insulated container with dry ice until analysis.Subjects frozen plasma was suspended in buffer . Immunoblotting for NOV was performed as previously described . NOV levAfter overnight fasting, venous blood was drawn from an antecubital vein to measure serum levels of inflammatory cytokines, Leptin, and EPC testing (blood was drawn in heparinized tubes). Serum samples were frozen at -80°C before analysis. IL-6 was determined using ELISA.μl of anti-CD146 coated 45 μm Dynabeads (1.4 × 108 beads/ml) overnight at 4°C in a Dynal mixer  at 50 rpm. Cells bound to anti-CD146 coupled beads were separated from blood in a Dynal magnet, washed , and dissolved in 100 μl buffer. Side-by-side assays were performed with Dynabeads coated with human antibodies against mouse IgG but without an antiendothelial antibody to check for nonspecific binding to the Dynabeads. The cells were mixed with acridine and visualized by light and fluorescence microscopy.A 10 ml sample of peripheral blood was obtained and used for CEC and EPC experiments. One ml of blood was incubated with 100 6 cells per well. After 48 hours, the nonadherent cells were collected and replated onto fibronectin-coated 24-well plates. EPC colonies were counted using an inverted microscope 7 days after plating. An EPC colony was defined as a cluster of at least 100 flat cells surrounding a cluster of rounded cells, as previously described [Peripheral mononuclear cells (PMNCs) were fractionated using Ficoll density-gradient centrifugation. Isolated PMNCs were resuspended in CFU-Hill Medium  and plated on 6-well plates, coated with human fibronectin at a concentration of 5 × 10escribed . Resultst-test or Mann–Whitney/Wilcoxon paired test as appropriate. Categorical variables were compared with the chi-square test for independence. The relationship between NOV and OSA was compared in several different categories including ODI quartiles, AHI quartiles, and categories of OSA  as defined by the AASM; these relationships were determined both between groups and overall trends. Due to nonnormal distribution of dependent variables, the cube-root transformation of NOV (and ODI/AHI when dependent variables), which approximated normality, was used in both multivariable models and between group comparisons (Student's t-test) to ensure validity of the model. All analyses were performed in Stata 15.1.We summarized continuous variables using means and standard deviations and summarized categorical variables as frequencies and percentages. Continuous variables were compared with Student's p = 0.018). BMI was greater in OSA vs. no OSA subjects . 67% of subjects demonstrated OSA on sleep testing with an AHI ≥ 5/hr while 41% of subjects had OSA under more stringent criteria of AHI ≥ 15/hr . There was a similar proportion of OSA among men and women (66%). Black race accounted for 54% of the study population, while white race accounted for 31%. Among comorbid conditions, hypertension was the most common at 31%; hypertension was seen more frequently in OSA vs. no OSA subjects  (p = 0.002) and AHI (p = 0.039) increase. Within group differences were observed (p = 0.028), quartiles 1 and 4 (p = 0.009), and quartiles 2 and 4 (p = 0.033), while NOV was different among AHI quartiles 2 and 4 (p = 0.033). NOV levels increase as OSA severity categories  increase (p = 0.013); within group differences in NOV were only seen comparing mild and severe OSA (p = 0.011).NOV levels were greater among those with OSA (3.3 ± 2.9 vs. 2.2 ± 2-fold increase in OSA vs. no OSA ( = 0.02) ). NOV leobserved : NOV wasp = 0.015; IL-6 4.4 ± 2.7 vs. 2.5 ± 2.7 ng/mL, p = 0.006; p = 0.017) but not with AHI quartiles or by OSA severity categories. In exploratory analysis, EPC levels were higher in OSA when OSA was classified as AHI ≥ 15 hr   . These rp = 0.032). NOV was not independently associated with AHI. EPCs were independently associated with both ODI (p = 0.001) and AHI (p = 0.017). Leptin was independently associated with both ODI and AHI in model 2; however, when BMI was added, leptin was no longer associated with either parameter indicative that BMI is a strong confounding variable. IL-6 was independently associated with ODI (p < 0.0001) and AHI (p < 0.0001) in model 2; however, when BMI was added, it was no longer associated with ODI but maintained significance with AHI (p = 0.049), which supports that BMI confounded IL-6 as well.In multivariable analysis , after aWe have shown for the first time that measures of obstructive sleep apnea (OSA) are independently associated with the novel adipokine matricellular protein nephroblastoma overexpressed (NOV) and endothelial progenitor cells (EPC) after adjusting for baseline demographics and BMI. Specifically, NOV levels were higher in those with OSA compared to those without OSA in univariate analysis. Further, multivariable methods showed that NOV is associated with the oxygen desaturation index (ODI) after adjusting for age, gender, and BMI; this finding was not seen in association with the apnea hypopnea index, suggesting that intermittent hypoxia, as specifically measured by the ODI, is central to this relationship, and that the more general measure of sleep-disordered breathing (AHI), which may also include nonhypoxic arousal events, is not. EPCs, in contrast, are independently associated with both the ODI and AHI, suggesting that overall mechanisms of OSA including intermittent hypoxia and other pathophysiologic variables are important in this relationship. Leptin and IL-6 levels related to OSA measures appear to be modified by BMI.Inflammation in OSA is driven by intermittent hypoxia and fragmented sleep leading to oxidative stress, manifested by increased formation of ROS and elevated adipocytokines , 17. Oxiα (PGC-1 α) reversed these findings and blocking the nuclear coactivator of HO-1 suggested that HO-1 upregulation was the mechanism involved. These findings propose that NOV may play a role in the OSA-related risk of developing cardiac disease and may be a target for potential therapy. This was shown again by administration of an EET agonist that increased PGC-1 α, which induced the HO-1 increase, improved mitochondrial function, and induced a change in the pericardial and epicardial adipocyte phenotype from white to beige; the improved insulin receptor phosphorylation improved insulin sensitivity and resulted in reversal of heart failure [α [NOV, a member of the CCN multifunctional proteins, plays a role in inflammation, cancer, and fibrosis through its involvement in adhesion and mitosis pathways . It has  failure . Thymoquilure [α . NOV indilure [α . White ailure [α . In addiilure [α –32. The ilure [α , 20. Theilure [α , 33.Other potential predictive markers such as CECs and EPCs are of interest in proinflammatory disease states as well. CECs are accepted and reliable indicators of vascular damage . CECs arQuantification of CEC and EPC has correlated with cardiovascular disease. Studies show increased levels of CECs in the acute coronary syndrome spectrum, stable angina, ischemic cerebrovascular accident (CVA), and critical limb ischemia . CEC quap = 0.001) and AHI (p = 0.017)  . There wp = 0.003), but the relationship was weakened when adjusted for BMI (p = 0.049), suggesting the inflammatory state of obesity acts as an effect modifier. Similar findings are well established in OSA patients, in which several inflammatory markers are known to be elevated in OSA, including leptin, CRP, TNF-a, and IL-6 [The proinflammatory state of OSA was confirmed in our subjects by increased levels of IL-6. There was an overall positive correlation between AHI and IL-6 (I p = 0.0, suggestThere are several limitations in our study. Although we feel that the findings are generalizable, the fact that we had a large percentage of black subjects makes this less so. Known racial differences in cardiovascular disease  may indiThe subjects of our study demonstrated that OSA is independently correlated with NOV after adjusting for BMI, age, and sex when compared to control. NOV appeared to be driven by intermittent hypoxia rather than general obstructive episodes as the correlation was with ODI and not AHI. EPCs were independently associated with both ODI and AHI, while CECs did not demonstrate an association with OSA. IL-6 was elevated in OSA subjects based on AHI, but BMI appeared to be a strong modifier of this relationship. Leptin was not associated with OSA after fully adjusting for BMI. In summary, the inflammatory adipokine NOV and EPC represent potential biomarkers that may help identify OSA patients at a current or future increased risk of cardiovascular disease from oxidative stress and may be a potential target to prevent the vascular downstream consequences of this systemic inflammatory cascade.


Depending on the person, cervical spondylosis may have no clinical symptoms, but cervical spondylosis will definitely cause changes in people's blood pressure, which will further affect physical and mental health.This study aims to explore the effect and safety of mind-body exercise intervention on the blood pressure in middle-aged and elderly patients with hypertension through meta-analysis.This meta-analysis searched studies from 4 research databases: the China National Knowledge Infrastructure (from 1979), Web of Science (from 1950), PubMed (from 1965), and Cochrane (from 1991), Date of retrieval: January 22, 2021, Two authors will independently search literature records, scan titles, abstracts, and full texts, collect data, and assess materials for risk of bias. The data will be analyzed by Stata 14.0 software.The present study is a systematic review and meta-analysis program with no results. Data analysis will be completed after the program has been completed.This meta-analysis may provide clinical practice with more reliable evidence-based medical evidence that mind-body exercise can benefit the blood pressure of middle-aged and elderly hypertensive patients.INPLASY202130072. Studies have demonstrated that there is a certain correlation between the symptoms of hypertension and the level of blood pressure. When hypertension symptoms are serious, confusion and convulsions will occur, which is not difficult to cause irreversible pathological changes and damage to the heart, brain, kidney, and other target organs in a short time. Data from the Lancet showed that the number of patients with hypertension in the world had exceeded 1.1 billion, seriously endangering people's health. Ezzati et al of the School of Public Health at Imperial College, UK, stated: “High blood pressure was a great risk factor for stroke and heart disease, with about 7.5 million deaths worldwide each year.” Therefore, how to actively treat hypertension is worthy of research and discussion in this century.The symptoms of hypertension vary from person to person. There may be no symptoms or symptoms that are not obvious in the early stage, and there will be occasional symptoms such as fatigue and palpitation, but these conditions generally only occur after fatigue, mental tension, and mood-swings and can quickly return to normal following rest. In addition, studies have proved that Baduanjin and Qigong have positive effects on blood pressure in patients with hypertension, which provides a specified reference basis. However, the subjects’ ages in these studies are between 18 and 75. According to the clinical observation, middle-aged and elderly people are the multi-incidence patient populations with hypertension, Despite this, the existing research results do not have the related research characteristics aimed at this population. However, Mind-body exercise, as low-cost exercise therapy, may be a good choice for middle-aged and elderly patients with hypertension.Mind-body exercise originates from the East and includes Taijiquan, Baduanjin, and Qigong, among others. It has been proven that mind-body exercise is beneficial to health and can improve happiness and satisfaction. The existing research takes mind-body exercise  as a scheme to improve blood pressure, but the existing research has not reached a unified consensus among the related results of research design, exercise time, exercise frequency, exercise volume, and other variables, which is not conducive to the wide range of Mind-body exercise to the treatment of patients with hypertension. The purpose of this study is to evaluate the efficacy and safety of mind-body exercise in improving blood pressure in middle-aged and elderly patients with hypertension and to provide operative suggestions for middle-aged and elderly patients with hypertension and clinicians to improve blood pressure.Compared with traditional experimental research, meta-analysis is a systematic review method with a combination of quantitative and qualitative analysis, which contributes to expand the sample size of this research topic and obtain more objective and scientific results.22.1In this study, the following research databases were searched: the China National Knowledge Infrastructure (from 1979), Web of Science (from 1950), PubMed (from 1965), and Cochrane (from 1991). Because mind-body exercise originated in the East, and China has the largest number of people practicing oriental mind-body exercise, this study also searched the CNKI. The end date of the consistent retrieval of this study is January 22, 2021. At the same time, the references included in the literature are searched manually, and the relevant literature is achieved by contacting the original author. This study uses 2 groups of keywords: mind-body exercise, Taijiquan, Baduanjin, and Qigong; blood pressure, essential hypertension, hypertension. Literature retrieval is conducted by two authors (LXH and CH) and confirmed by another collaborator (GBH) to ensure data retrieval accuracy. for systematic reviews and meta-analysis, and completed the research registration on the INPLASY platform (registration number: INPLASY202130072).We conducted this systematic review in accordance with the Guidelines for the Preferred Reporting Project (PRISMA)2.22.2.12.2.1.1We included randomized controlled trials (RCTs).2.2.1.2The experimental subjects included in this study are all hypertensive patients ≥45 years old.2.2.1.3In general, there are 2 ways to include the intervention subjects in this study: the intervention group simply adopted Mind-body exercise: the intervention group adopted Taijiquan or Baduanjin or Qigong, and the control group adopted other measures  other than Mind-body exercise; the intervention group adopted the Mind-body exercise method plus other measures: the intervention group adopted Mind-body exercise (Taijiquan or Baduanjin or Qigong) plus other measures , the control group simply adopted other measures (mentioned above).2.2.1.4; diastolic blood pressure.The purpose of this study is to measure the blood pressure of hypertensive patients. At this stage, the most intuitive way to evaluate blood pressure is to observe its systolic and diastolic blood pressure. Therefore, the main results of this study are: systolic blood pressure2.2.2To complete this study accurately, this article has the following exclusion criteria:(1)RCTs not in peer-reviewed journals;(2)compared with the control group, Mind-body exercise is not the main factor in the intervention group measures;(3)subjects are <45 years’ old, are not hypertensive or essential hypertension patients, or have a history of myocardial infarction or stroke;(4)publication of meetings, publication of abstracts, reviews, publication of no detailed data, repeated publications, low-level academic literature, among others.2.3 If there is any dispute, it will discuss with the third researcher (CH). The widely accepted methodological quality assessment tool includes 11 items: description of the inclusion conditions of the subjects; subjects are randomly assigned to each group; the mode of distribution is hidden; there is no significant difference in the baseline between the experimental group and the control group; all the subjects were blind; all the physiotherapists were blind; all the evaluators of at least one major result were blind; at least 85% of the subjects had major measurement results; all the participants were treated according to a randomly assigned scheme; the intragroup statistical results of at least one major result were reported; the study provided point measurements and variation measurements of at least one major result. However, during the actual mind-body intervention, it is not realistic to blind the participants in item 5 and the therapists in item 6. Therefore, these 2 items are not required in the quality evaluation of this study. In the end, there are 9 evaluation items, each of which is 1 point. If the evaluation literature meets the standard, the score will be 0.To evaluate the methodology of the included studies independently, the 2 authors (LXH and GBH) utilized the Physiotherapy Evidence Database (PEDro) scale,2.4Each article was extracted by 2 independent researchers (LXH and GBH), the third researcher (CH) confirmed, and transformed into 2 standard forms: descriptive data, including the first author and year of publication, research location and language, subjects’ health status, sample size, average age and age range, intervention schemes between the intervention group and the control group, and main measurement results; quantitative data, including the randomly assigned number of subjects, the mean ± standard deviation (SD) of the baseline data between the intervention group and the control group, and the mean ± standard deviation (SD) of the data after intervention between the intervention group and the control group.2.5P value and I2. If P > .10, there was no heterogeneity among the studies. If P < .10, there was heterogeneity among the studies. If I2 < 25%, then the heterogeneity between studies is considered small. If I2 > 50%, then the studies were considered to be noticeably heterogeneous. Subgroup analysis was utilized to explore the potential influencing factors of the outcome index of essential hypertension in the middle-aged and elderly.Stata 14.0 software was used to analysis the heterogeneity, sensitivity, and publication bias of all the outcome indicators included in the literature, and forest and funnel maps were drawn. Literature outcome indicators included in this articles belong to continuous variables, and the test units of each index are the same; therefore, the mean ± standard deviation (SD) is selected for statistics, and 95% CI is determined by the same time. The heterogeneity test was performed by 33.1The research included in this review solely involved RCT studies that used combined effect size, subgroup analysis, sensitivity analysis, publication bias tests, and other methods to evaluate the effect and safety of mind-body exercise intervention on the blood pressure in middle-aged and elderly patients with hypertension.3.2 Most of the patients with hypertension are older people, which is a more economical and less side-effect treatment in addition to drug treatment. Reviewing previous studies, researchers on the therapeutic effects of Taijiquan or Qigong or Baduanjin on hypertension are mainly from China and South Korea. Chinese researchers believe that Taijiquan and Qigong may be supplementary and effective treatments for lowering blood pressure, but the therapeutic effect may be related to the increase of NO and the decrease of ET-1 in the blood. The researchers believe that Qigong is effective in the treatment of hypertension. In order to further verify the study's conclusions, it is necessary to design a higher intensity of evidence to prove it.,18It has been proved that the quality of life of patients with hypertension is often worse than that of normal people. and 40 to 70 years’ old. It may be necessary to design RCT experiments to prove the therapeutic effect of people aged 30 to 40 years and to eliminate other possible biased factors. From the perspective of mechanism, researchers from South Korea believe that the effect of Qigong is not to reduce blood pressure directly but to stabilise the sympathetic nervous system and thus lower the blood pressure of patients. It is believed that Qigong is a complementary and irrational way to treat hypertension.However, the ages included in the 2 studies are different, 30 to 70 years’ oldThe authors acknowledge the participants for taking part in the study .Conceptualization: Xianhui Liao, Beihai Ge.Data Curation: Xianhui Liao, Beihai Ge, Hao Chen.Funding acquisition: Beihai Ge.Funding: Beihai Ge.Methodology: Xianhui Liao, Beihai Ge, Hao Chen.Project Administration: Xianhui Liao, Beihai Ge.Resources: Xianhui Liao, Beihai Ge, Hao Chen.Supervision: Xianhui Liao.Writing – original draft: Beihai Ge, Hao Chen, Xianhui Liao.Writing – review & editing: Beihai Ge, Hao Chen, Xianhui Liao.


This study was designed to verify whether early posttransplant standardized phase angle (SPhA) determines nutrition status of hemodialysis patients in regard to different nutritional markers and predicts handgrip strength (HGS) 6 months after kidney transplantation.A total of 82 kidney transplant recipients on maintenance hemodialysis treatment entered the study. Nutritional status was evaluated before kidney transplantation, at the hospital discharge date, and 6 months after. We used bioelectrical impedance analysis (BIA), three different malnutrition screening tools, HGS, and anthropometric measurements. Demographic profiles and biochemical nutritional markers were collected. SPhA values, adjusted for age and BMI, were used in our study.dis [the SPhA (at discharge) adjusted for hospitalization time and the baseline SPhA] displayed lower values of albumin concentration , hemoglobin , GNRI , and HGS . These patients had higher ferritin concentrations , longer inpatient stays , and higher MIS scores .In the early posttransplant period, kidney transplant recipients lost muscle mass, gained fat mass, and developed mostly negative SPhA, accompanied by significantly lower albumin levels. The subjects with lower than median (<-1.46) SPhAAt the moment of hospital discharge, lower than the median SPhA is related to protein-energy wasting, represented as lower concentrations of nutrition biomarkers and an active inflammatory response. Higher SPhA before kidney transplantation predicts HGS 6 months after kidney transplantation, especially in women. Kidney transplantation is considered as the optimal treatment option for end-stage kidney disease. It enables greater longevity and better quality of life compared to peritoneal dialysis and hemodialysis , 2. The During the last decade, nutritional status is shown to be a relevant clinical factor in patients with chronic kidney disease (CKD), as malnutrition and sarcopenia are strongly associated with prolonged hospitalization, increased risk of complications, infections, morbidity, and mortality . Kidney A number of nutrition assessment tools are available on the market. One of them is bioelectrical impedance analysis (BIA). BIA has been advocated as a simple, safe, and non-invasive technique. It measures body composition by determining the resistance and reactance of the body against an alternating electrical current . The meaCurrently, a limited number of studies have investigated PhA measurement importance in kidney transplant recipients. To our knowledge, none of them provided standardized PhA values for either CKD population or for patients after kidney transplant. Therefore, in this study, we aimed to verify whether standardized PhA (SPhA) measured during the early posttransplant—at the discharge from the hospital and then after 6 months of follow-up—reflects on other compartments of body composition, biochemical nutritional markers, and handgrip strength (HGS).A longitudinal observational study was conducted in a tertiary referral university hospital between January 2018 and March 2020. The aim of this study was to measure BIA-derived PhA and to investigate its associations with other BIA-derived nutritional parameters: fat mass (FM), fat-free mass (FFM), skeletal lean mass (SLM), skeletal muscle mass (SMM), HGS, patient demographics, and biochemical markers at the baseline (before KT), at the discharge day and 6 months posttransplant.The eligibility criteria were as follows: (1) undergoing hemodialysis (HD) > 3 months, (2) age ≥ 18 years, and (3) signed informed consent form. Exclusion criteria included limbless patients, pacemakers, and patients who refused to participate in the study.In our hospital, the recipients after kidney transplant surgery are transferred to the intensive care unit for 24–48 h, and then, they are moved to the urology department for a week and the rest of time they recover in the kidney transplantation department. The patients remain in the hospital for a total of about 14–21 days. Dietary therapy during recovery period consists of high protein, fiber, and low salt intake.The flow chart of patient selection.Permissions from the regional research ethics committee  and the research ethics committee of the hospital were acquired. Informed consent was obtained from all patients prior to enrollment in the study. The study was conducted in accordance with the principles of Declaration of Helsinki.Two times during the course of the study [at the baseline (before KT) and 6 months later], blood samples were collected to assess the following parameters: serum albumin, prealbumin, ferritin, transferrin, and high-sensitivity C-reactive protein (hs-CRP). The blood samples were collected into BD Vacutainer SST-II Advance Serum Separator Tubes  by venipuncture from all participants after a 12-h overnight fasting period. Samples for all biochemical markers were centrifuged at the local clinical chemistry laboratory  and analyzed the same day using standard automated methods. The CKD-EPI formula was used for estimating glomerular filtration rate (eGFR).2). Waist and hip circumferences (cm) were examined using a measuring tape, and the waist-to-hip ratio was calculated.A trained nephrologist performed the anthropometric measurements for all participants. Height (cm) and weight (kg) were measured using an automatic scale with a sensitivity of 0.1 cm and a resolution of 0.1 kg. BMI was calculated as a ratio between weight and height in meters squared (kg/mHandgrip strength was measured using a Saehan hydraulic hand dynamometer (Model SH5002) with a scale of strength up to 100 kg. HGS was evaluated on the non-fistula dialysis arm or, if there was no fistula, on the dominant arm, as the arteriovenous fistula (AVF) is usually located in the non-dominant arm . Three mThe 2020 Updated Clinical Practice Guideline for Nutrition in CKD published by the National Kidney Foundation/Kidney Disease Outcome Quality Initiative recommended the 7-point subjective global assessment (SGA) (7p-SGA) and malnutrition inflammation score (MIS) for the assessment of nutritional status in patients with CKD on HD. We have chosen to use SGA and MIS, which were administered through face-to-face interviews and have been previously reported to be applicable tools in this population .The SGA scores patients on a scale ranging; A—well nourished, B—mild-to-moderately malnourished, C—severely malnourished .For the MIS, the cutoff proposed by Yamada et al. was used to classify the nutritional status: 0 to 5—well-nourished; 6 to 10—mild protein-energy wasting (PEW), and ≥11—moderate-to-severe PEW .Bioelectrical impedance analysis was performed to obtain the measurements of resistance (R) and reactance (Xc) using a calibrated body composition analyzer , which applies a single frequency of 50 kHz. The analysis was conducted for patients in a reclining posture and according to all recommendations from ESPEN and the manufacturers .The PhA was calculated automatically by the BIA device from these two components according to the following formula: phase angle (°) = (reactance/resistance) × 180°/π) (0°/π (8).Interestingly, many authors focus on the calculation of a standardized phase angle (SPhA), which aims to account for confounding factors when determining PhA. An SPhA is calculated as a z-score that may be based on established population reference values and allows assessment of individual deviations from age-, sex-, and BMI-specific population . We usedSD, standard deviation.dis.”Then, the SPhA (at discharge) was adjusted for hospitalization time and the baseline SPhA and labeled as the “SPhAPhA and SPhA values for each study patient are provided in the t-test or a two-sample Wilcoxon test were applied, and for categorical variables, a chi-square test was used. Multivariate linear regression analysis was used to evaluate potency of SPhA at the baseline and at discharge to predict HGS 6 months after kidney transplantation following corrections for age, sex, and baseline HGS. Since in men, these associations were absent, and we reported only data on women.Data were analyzed using R commander (Rcmdr) version 3.3.2. Continuous variables are expressed as the mean ± standard deviation (SD), discrete variables as medians with min–max values in parentheses, and categorical variables as percentages. To check the equality of two populations, an F-test and, if appropriate, Student's p-values lower than 0.05 were considered as statistically significant.We enrolled 82 kidney transplant patients who received standard immunosuppressive treatment, which includes methylprednisolone, calcineurin inhibitor, and mofetil mycophenolate, after deceased-donor kidney transplantation. Baseline characteristics are presented in dis accompanied by significantly lower plasma albumin levels.The prevalence of protein-energy wasting (PEW) before kidney transplantation was 44% and decreased to 7% after surgery. We compared nutrition-related variables during early posttransplant period , that isThe overlap of SPhA histograms at the baseline, at the discharge day from hospital, and 6 months after kidney transplant is presented in dis displayed lower values for the following variables 6 months after kidney transplant: plasma albumin concentration , hemoglobin , GNRI , and handgrip strength . Conversely, these patients had higher ferritin concentrations , longer inpatient stay , and higher MIS scores . The SGA nutrition questionnaire could not reveal these differences.The subjects with lower than median (<-1.46) SPhAWe analyzed whether the calculation of SPhA values before kidney transplant and at the hospital discharge could predict HGS 6 months after kidney transplant. The scatterplots on the association between HGS and SPhA are visualized in Multivariate linear regression revealed that only in women, baseline SPhA could predict HGS following adjustments for age and baseline HGS . We faillower than the median SPhA at the hospital discharge is related to protein-energy wasting, represented as lower concentrations of nutrition biomarkers , an active inflammatory response , whereas higher SPhA before kidney transplantation predicts HGS 6 months after kidney transplantation. In addition, this finding is specific to women.This study aimed to evaluate whether early posttransplant standardized phase angle (SPhA) determines nutritional status regarding different nutrition markers and predicts HGS 6 months after kidney transplantation. The main finding of this study indicates that One potential explanation of our results could be the longer hospital stay of the patients with lower SPhA caused by surgical and/or infectious complications . FurtherIn line with previous studies, a low PhA is related to lower HGS, a criterion for diagnosing sarcopenia, which results from loss of SMM and strength . We alsoPassadakis et al. found that in continuous ambulatory peritoneal dialysis patients, PhA was only significantly different between well-nourished and severely malnourished groups, with a weak correlation between SGA and PhA . Varan eKidney transplantation, as a major surgical procedure, causes protein catabolism, which leads to the loss of muscle tissue, decreased albumin concentration, and impaired nutritional status. However, the use of immunosuppressive therapy and often abnormal renal function can affect the body composition of renal recipients, particularly causing the loss of muscle mass. In general, an increase in body weight is observed after renal transplantation, but at least initial posttransplant weight gain appears to be predominant due to an increase in fat mass . TherefoFor example, patients with a lower functional capacity at discharge are at risk of maintaining posttransplant physical inactivity . Both aeA major advantage is that we analyzed not raw but standardized PhA values to detect the relationship between PhA and nutrition status during the follow-up. To our knowledge, this study is the first that has investigated the role of SPhA in the assessment of nutritional status in the very early period after kidney transplantation.The main limitations of this study are the single-center design, the small sample size, and the absence of CT/MRI data for sarcopenia evaluation.lower than the median standardized PhA regarding PEW and an active inflammatory response, whereas higher SphA prognosticate HGS within 6 months following transplant. There is an emerging need for standardized PhA values, not specific to the general population but to CKD patients.In summary, our study shows the predictive potential of Future studies may examine the utility of PhA alone or in combination with other prognostic tools and how PhA may inform prognosis-based clinical decision-making in the kidney transplant setting.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Lithuanian Bioethics Committee. The patients/participants provided their written informed consent to participate in this study.DS, MM, and LR were responsible for study design, data collection, and wrote the paper. DS performed the statistical analysis and analyzed data. All authors critically reviewed the manuscript and approved the final draft.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.


Introduction: Muscle mass depletion, overhydration, and inflammatory state have been related to impaired physical function in chronic kidney disease patients. The relationship between bioelectrical impedance analysis (BIA) parameters, such as hydration status and phase angle (PhA), with physical function in peritoneal dialysis (PD), is still not well-established. Therefore, the objective was to evaluate the association of BIA parameters (overhydration index and PhA) and inflammatory markers with physical function in patients on PD.Methods: The present cross-sectional study enrolled PD patients. Multifrequency BIA was performed to obtain overhydration index and PhA. The Short Physical Performance Battery (SPPB) test battery was applied to assess physical function. The time to complete the 4-m gait test and sit-to-stand test was also considered for physical function assessment. The inflammatory markers tumor necrosis factor-alpha and C-reactive protein levels were determined. Multiple linear regression models were performed, with the physical function variables as dependent variables, adjusted for age, diabetes, and sex.Results: Forty-nine PD patients were enrolled, 53.1% (n = 26) women; mean age, 55.5 ± 16.3 years. There were significant correlations between PhA and SPPB , time of 4-m gait test  and sit-to-stand test and . Overhydration index was significantly correlated with SPPB, 4-m gait test , and sit-to-stand test . Inflammatory markers were not significantly correlated with physical function parameters. In the multiple linear regression analysis, PhA was associated with physical function parameters, even after adjustments. Overhydration index was associated with all physical function tests only in the models with no adjustments.Conclusion: PhA was independently associated with physical function in PD patients. Inflammatory markers and overhydration index were not associated with physical function. Bioelectrical impedance analysis (BIA) has been used in clinical practice to assess patients with chronic kidney disease (CKD) on dialysis. BIA provides raw data regarding electrical current conductivity through the body tissues, such as resistance and reactance. The relation among these parameters may be converted into physiological parameters related to body composition and hydration status .BIA was recommended by the National Kidney Foundation–Kidney Disease Outcomes Quality Initiative in the Nutrition Guideline in CKD, as a method capable of assessing body composition in patients on hemodialysis. However, there is insufficient evidence to suggest using BIA to assess body composition in peritoneal dialysis (PD) patients .Regarding hydration status evaluation, one of the parameters obtained by BIA is the overhydration index (OH), which assesses fluid overload by the difference between measured and expected extracellular water in normal situations . OH is cPhase angle (PhA), a measure of the relationship between resistance and reactance, reflects cell membranes integrity, cellularity, and cell function . PhA hasCKD is characterized by metabolic and hormonal disturbances, which culminates in skeletal muscle wasting and disfunction. Decreased physical function has been associated with poor outcomes, such as disability, falls, fracture, hospitalization, and mortality . In dialHowever, the relationship between BIA parameters, such as hydration status and PhA, with physical function in PD is still not well-established. Therefore, the objective of the study is to evaluate the association of BIA parameters (OH and PhA) and inflammatory markers with physical function in patients with CKD on PD.This was a secondary analysis of data from a study previously published , which eClinical, demographic data, and routine laboratory tests were collected from medical records .Blood collection was performed in the morning, after PD. C-reactive protein levels were determined by immunoassay  at the specialized chemistry laboratory of the Hospital of Botucatu Medical School. Blood samples were centrifuged, aliquoted, and kept frozen at −80°C for tumor necrosis factor-alpha (TNF-α) levels determination, using an enzyme-linked immunosorbent assay according to the manufacturer's instructions .All the patients underwent anthropometric and bioimpedance assessment with no dialysate in the peritoneal cavity in the morning, after PD. Measurements of body weight, height, and calculation of body mass index were carried out.Multifrequency BIA  was performed with the patients in the recumbent position and all metal accessories removed. The BCM measures body resistance and reactance to electrical currents of 50 discrete frequencies, ranging from 5 to 1,000 kHz. Values of OH and PhA in the frequency of 50 kHz were considered. The OH was obtained by the BCM device, considering the difference between the measured extracellular water (ECW) and the predicted values based on fixed hydration on lean and adipose tissue mass.To assess physical function, the Short Physical Performance Battery (SPPB) was used. This assessment was performed at the same day of BIA, after PD. SPPB is composed of a set of three tests: balance, a 4-m gait and sit-to-stand tests. These tests are useful to predict the performance of the lower limbs. The scores were assigned to each test, ranging from zero to four , 16.Besides the SPPB total score, the time to complete the 4-m gait test and sit-to-stand test was considered for physical function assessment.The Kolmogorov-Smirnov test was performed to assess the normality of the data. Data were expressed as mean and standard deviation, median, and interquartile variation, according to the distribution. Frequencies were expressed as percentages.t or Mann–Whitney tests.Comparisons between male and female, and between diabetic and non-diabetic patients were performed using Student's post-hoc or Kruskal–Wallis with Dunn post-hoc test.The patients were grouped according to OH and PhA tertiles. Tertiles were compared, using one-way ANOVA with Tukey Correlations between physical function parameters and other variables were assessed. For this, Pearson and Spearman coefficient correlations were used.Multiple linear regression models were performed, with the physical function variables as dependent variables, adjusted for age, diabetes, and sex.p < 0.05.The analyses were performed, using IBM SPSS Statistics V22.0 . The level of significance was set at n = 26) female. The patients in different modalities of PD were included, 61.2% (n = 30) in continuous cyclic PD, 34.7% (n = 17) in night intermittent PD, and 4.1% (n = 2) in continuous ambulatory PD. The most prevalent comorbidities were arterial hypertension  and diabetes . The main underlying diseases were glomerulonephritis, 18.4% (n = 9); diabetic nephropathy, 16.3% (n = 8); hypertensive nephropathy, 16.3% (n = 8); undetermined, 24.5% (n = 12); and other causes, 24.5% (n = 12). Clinical and nutritional characteristics of PD patients are shown in Forty-nine PD patients were enrolled, with mean age 55.5 ± 16.3 years, 53.1% . In the comparison between the patients with diabetes or not, there were differences regarding age (p = 0.003), SPPB (p = 0.025) and sit-to-stand test (p = 0.009). OH (p = 0.184), PhA (p = 0.193), CRP (p = 0.572), TNF-α (p = 0.937), and gait test (p = 0.150) did not differ between diabetic and non-diabetic patients.Results of physical function assessments of both genders were compared. There were no differences between male and female (SPPB: Forty-seven patients (96.0%) reached the maximum score in the balance test. The results of physical function assessments and inflammatory markers are shown in r = −0.400, p = 0.004). Creatinine was correlated with all the physical function test .In the correlation analysis, there was a positive correlation between PhA and SPPB and negative correlations of PhA with time of a 4-m gait and sit-to-stand tests. OH was negatively correlated with the total SPPB score, and positively correlated with a 4-m gait and sit-to-stand tests. Inflammatory markers were not significantly correlated with physical function parameters . DialysiMultiple linear regression models were performed with the SPPB, gait test, and sit-to-stand test as dependent variables . Age andIn the multiple linear regression final models, OH was associated with all physical function tests only in the models with no adjustments. PhA was independently associated with all physical function tests after adjustments, except with the gait test when diabetes was included as an adjustment.Although BIA has been used in the last decades for body composition assessment, it is not a direct method for this evaluation . BIA is More recently, the use of raw and associated impedance parameters has gained attention. Kidney failure patients are characterized by fluid imbalance, which turn BIA even more valuable. Huang et al. showed that age, diabetes, and fluid overload were independently associated with lower PhA in PD patients. Moreover, in the same study, lower PhA was associated with higher cardiovascular and all-cause mortality . IncreasThe present study aimed to evaluate the association of BIA parameters (PhA and OH), and inflammation with physical function in PD patients. PhA was positively correlated with the SPPB total score and negatively correlated with the time to complete a 4-m gait and sit-to-stand tests. As expected, these results show the association of increased PhA with better physical function.In addition to the association of PhA with better physical function, OH was negatively correlated with the SPPB total score and positively correlated with the time to complete the 4-m gait and sit-to-stand tests. The patients in the third tertile had worse physical function compared with the first tertile. However, OH was not independently associated with physical function after adjustments in multiple analyses.Inflammation is considered one of the aspects that lead to decrease of physical function , 20. SinIn the hemodialysis patients, the presence of fluid overload can slow the gait speed. The fluid overload significantly impacts on the physical performance of the patients over time, as observed in a longitudinal study by Carlos et al. . On the In PD, data about the impact of increased fluid on the physical function assessed by walking are scarce. A walking variable may be reduced in these patients due to conditions such as physical inactivity, peripheral neuropathy, and muscle strength . HoweverIn the multiple linear regression analyses, the association of PhA with the sit-to-stand test and SPPB was maintained even after adjusting for age, diabetes, and sex. All the physical function tests used in the present study reflect common daily living activities, i.e., getting up from a chair or walking small distances. Moreover, these tests are easy, fast, portable, and inexpensive procedures to measure physical performance.PhA has been associated with physical function in many conditions. Recently, Vincenzo et al.  have shoAlthough the relationship between PhA and physical function in PD is still not well-established, there are studies associating PhA with muscle function in other CKD populations. Muscle function, assessed by handgrip strength, was associated with PhA in maintenance hemodialysis , 29 and A possible explanation for the relationship between PhA and physical function is based on cellular structures and its interaction with the electrical current. The structure and the function of cells are dependent on cell membranes, which are composed of electrically non-conducting lipid bilayers with associated proteins . The proThe main limitation of this study is the single-center small sample size, which does not allow the inclusion of many variables in the multiple analyses. However, due to the scarcity of studies assessing the association of PhA and OH with physical function in PD, the results may be significant for PD patients. Thus, studies with a larger number of patients are still necessary.In conclusion, bioimpedance parameters (PhA and OH) were correlated with physical function tests, but only PhA was independently associated with physical function tests in the PD patients. Inflammatory markers were not associated with physical function in this sample. In this sense, easy-to-apply tools with good accuracy are important to identify the risk of reduced physical function, allowing interventions to avoid worse outcomes.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Research Ethics Committee of the Faculty of Medicine of Botucatu-Universidade Estadual Paulista (UNESP). The patients/participants provided their written informed consent to participate in this study.VMS, MZCS, BPV, and JCTC were responsible for the research idea and the study design. VMS, MZCS, NSCR, MSD, and FLC performed the data acquisition. VMS, MZCS, and BPV performed the data analysis and the interpretation, were involved in the statistical analysis, and drafted the manuscript. BPV, JCTC, and MFM were responsible for supervision and mentorship. All the authors provided intellectual content to the work and gave final approval of the version to be published.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.


IL4RA gene polymorphism, which is related to type 2 inflammation, in these exacerbation-prone phenotypes.Chronic inflammatory airway diseases, including asthma and chronic obstructive pulmonary disease (COPD), are complex syndromes with diverse clinical symptoms due to multiple pathophysiological conditions. In this study, using common and shared risk factors for the exacerbation of asthma and COPD, we sought to clarify the exacerbation-prone phenotypes beyond disease labels, and to specifically investigate the role of the IL4RA gene polymorphism rs8832 with each exacerbation-prone phenotype was evaluated by multinomial logistic analyses using non-asthma non-COPD healthy adults as controls . In addition, the genetic influence of rs8832 was also examined in asthma patients with allergic rhinitis and no history of exacerbation (n = 130).The study population comprised patients with asthma (n = 117), asthma-COPD overlap  or COPD (n = 48) and a history of exacerbation within the previous year. Cluster analyses were performed using factors associated with both asthma and COPD exacerbation. The association of the p = 0.013) and also for the type 2 exacerbation-prone phenotypes , p = 1.9 × 10−3).Two-step cluster analyses identified five clusters that did not necessarily correspond to the diagnostic disease labels. Cluster 1 was characterized by high eosinophil counts, cluster 2 was characterized by smokers with impaired lung function, cluster 3 was characterized by the presence of gastroesophageal reflux, cluster 4 was characterized by non-allergic females, and cluster 5 was characterized by allergic rhinitis and elevated total immunoglobulin E levels. A significant association with rs8832 was observed for cluster 5 , Our results indicated that the clinical heterogeneity of disease exacerbation may reflect the presence of common exacerbation-prone endotypes across asthma and COPD, and may support the use of the treatable traits approach for the prevention of exacerbations in patients with chronic inflammatory airway diseases. Chronic inflammatory airway diseases, including asthma and chronic obstructive pulmonary disease (COPD), are complex syndromes with diverse clinical symptoms due to multiple pathophysiological conditions. Despite the fact that asthma and COPD share common mechanisms, the mainstream approach to treating chronic inflammatory airway diseases has been to name a diagnosis first, then to follow the clinical guidelines that correspond to that diagnosis. This approach, also known as one-size-fits-all medicine, has been reported to have limitations in providing appropriate treatment for a variety of conditions that vary from patient to patient . A newlyAcute exacerbations of asthma and COPD are common occurrences that are associated with an increased decline in lung function, poor quality of life and increased mortality. Asthma and COPD are chronic diseases with high morbidity worldwide, and their acute exacerbations, in particular, are a major socioeconomic burden , 4. PatiIL4RA gene expression in whole blood cells [The G allele at rs8832 is associated with upregulated od cells . Moreoveod cells , 11.IL4RA gene polymorphism, which is related to type 2 inflammation, in these exacerbation-prone phenotypes.In this study, using these common and shared risk factors for the exacerbation of asthma and COPD, we sought to clarify the exacerbation-prone phenotypes beyond disease labels, and also to investigate the role of the IL4RA on the exacerbation of chronic inflammatory pulmonary diseases in relation to the exacerbation phenotypes was evaluated.In this study, we focused on the exacerbation-prone phenotypes of chronic inflammatory pulmonary diseases  and conducted cluster analyses using patients with at least one exacerbation within the previous year despite being treated by pulmonologists. Multiple clinical features related to exacerbation were used to clarify the phenotypes of exacerbation that were independent of conventional diagnoses. Furthermore, the genetic effect of the functional single nucleotide polymorphism (SNP) of This study consecutively enrolled patients who had experienced at least one exacerbation within the past year, without matching of the number of patients per disease, within the study period of January 2017 to December 2017. The target population comprised patients with asthma (n = 117), ACO (N = 37) or COPD (n = 48) and a history of at least one exacerbation within the previous year who visited the University of Tsukuba Hospital and/or its affiliated hospitals. In all patients, the diagnosis of the disease was made by a pulmonologist. Patients with smoking COPD with features of asthma were defined as having ACO . PatientIn addition, asthma patients with allergic rhinitis who had not experienced an asthma exacerbation within the past year n = 130) were also recruited to investigate the genetic influence of rs8832 on the development, but not exacerbation, of allergic asthma with rhinitis. Healthy volunteers with the rs8832 genotype (n = 1529) were recruited from among the individuals who visited the Tsukuba Medical Center and the Health Center of Kamisu City for annual health checkups [0 were alSpirometry was performed at each participating site using an automated electronic spirometer with the patient in a sitting position. These tests were performed and evaluated by well-trained technicians as described in the ATS/ERS guidelines .9/L) were obtained from the automated laboratory test results from each participating site.The total serum immunoglobulin E (IgE) level was measured using a commercial fluorescence enzyme immunoassay . The specific serum IgE antibody was measured in both the healthy and asthmatic groups with the multiple allergen simultaneous test (MAST)-26 chemiluminescent assay systems  . We defiPatients’ health-related quality of life was assessed using the COPD assessment test (CAT), a self-administered questionnaire consisting of eight items that assess various manifestations of chronic airway disease . GastroeIL4RA, was performed using the Infinium Asian Screening Array  or the Illumina HumanHap 550v3/610-Quad BeadChip (Illumina) [Genomic DNA was extracted from peripheral blood samples using an automated DNA extraction system . The typing of rs8832, which is an expression quantitative trait locus and splicing quantitative trait locus of llumina) .One-way analyses of variance, Kruskal-Wallis tests and the chi-square test were used for comparisons among the exacerbation-prone phenotypes for parametric continuous, non-parametric continuous and categorical variables, respectively.For SNP data analysis, the genotype frequency in each exacerbation-prone phenotype was summarized and the odds ratios for risk genotypes were calculated by multinomial multiple logistic regression analyses using non-asthmatic non-COPD healthy volunteers as the control group with adjustments made for age, sex and smoking index .1)/forced vital capacity (FVC), body mass index (BMI), CAT score, FSSG score, peripheral blood eosinophil count and the number of exacerbations that required steroid administration within the previous year. The distribution of serum IgE was not normal, and the values were thus log-transformed (log IgE).For cluster analyses, two-step cluster analyses were performed using SPSS® Statistics V26 . The analysis used the following 12 variables, including factors associated with both asthma and COPD exacerbation: age, sex, smoking index, age at onset, total IgE, presence/absence of allergic rhinitis, forced expiratory volume in 1 s  and duration (years smoked), and was categorized into three groups: 0, >0 to <200, and >200 cigarette-years . A cutofWe validated the results of the two-step cluster analyses using the silhouette coefficient, which is a measure for the cohesion and separation of clusters . ObtaineThis study was approved by the institutional review board of the University of Tsukuba (IRB No. 136–4) and the University of Tsukuba Hospital (IRB No. H29-294). After verbally explaining the research to all target participants, the survey and analyses were conducted in accordance with the joint Ethical Guidelines for Human Genome/Gene Analysis Research and the principles of the Declaration of Helsinki after obtaining written consent from the patients.1/FVC, BMI, CAT score, FSSG score, peripheral blood eosinophil count and number of exacerbations in the previous year. Consequently, a total of 202 patients  who had information for all 12 items were included in the subsequent cluster analysis. The presence/absence of allergic rhinitis was judged mainly based on the typical symptoms, including sneezing or a runny/blocked nose, especially when the patients did not experience a cold or the flu within the past 12 months.A total of 225 patients were initially enrolled, including 127 with asthma, 41 with ACO and 57 with COPD. Patients with missing data for at least one of the following 12 items were excluded: age, sex, smoking index, age at onset, total IgE, presence/absence of allergic rhinitis, FEV2 for those with asthma, ACO and COPD, respectively. The mean FEV1/FVC was 74.1%, 54.4% and 44.4% among those with asthma, ACO and COPD, respectively. Furthermore, the percentage of patients with a peripheral blood eosinophil count ≥450 cells/μL was 18.8%, 21.6% and 10.4%  among those with asthma, ACO and COPD, respectively. The number of patients who experienced at least two exacerbations within the previous year was 66, 22 and 24  among those with asthma, ACO and COPD, respectively. The prevalence of allergic rhinitis, as determined by interviews, was 36.8%, 18.9% and 4.2% among those with asthma, ACO and COPD, respectively. The mean fractional exhaled nitric oxide  was 1.41, 1.51 and 1.29 ppb among those with asthma, ACO and COPD, respectively .Cluster 1  was a smoking male dominant group with a mean age of 72.8 years. The mean peripheral blood eosinophil count was 362.1 cells/μL, which was the highest among all clusters. The mean serum IgE level  was 2.23 IU/mL, which was the second highest after cluster 5. Together with an elevated level of exhaled NO  of 1.56 ppb, cluster 1 was considered to be an eosinophilic phenotype. The rate of complications of allergic rhinitis was 19.6%.1/FVC was 48.9%, which was the lowest among all clusters. The mean BMI was 22.2 kg/m2, which was also the lowest among all clusters. The mean peripheral blood eosinophil count was 160.2 cells/μL, and the rate of complications of allergic rhinitis was 2.8%.Cluster 2  was a group of symptomatic smokers with a mean age of 76.1 years. The mean FEV1/FVC was 57.3%.Cluster 3  was a group with a higher mean age of 75.5 years and a relatively high number of smokers. The FSSG score was 8 or more in all patients, indicating that this cluster was an exacerbation-prone phenotype characterized by the presence of GERD. The mean FEVCluster 4  was a group of non-smoking females with a mean age of 64.8 years. The mean serum IgE level  was 1.71 IU/mL, and the rate of complications of allergic rhinitis was 2.1%; these were the lowest among all clusters, indicating that this cluster was non-smoking females without a predisposition for allergies. The mean level of exhaled NO  was 1.31 ppb.In cluster 5 , all patients had allergic rhinitis. The proportion of females was as high as 82.4%. The mean age and age at onset were 58.4 and 36.0 years, respectively, both of which were the lowest among all clusters. This group also had the highest mean serum IgE level  at 2.35 IU/mL. The peripheral blood eosinophil count and exhaled NO level  were 272.4 cells/μL and 1.44 ppb, respectively.Exacerbations treated by steroids were most frequent in cluster 5, while exacerbations treated by antibiotics only were most frequent in clusters 2 and 3.p = 1.9 × 10−3). In contrast, non-type 2 exacerbation-prone phenotypes  were not associated with the SNP. We further examined the role of the IL4RA SNP in participants with increased eosinophil counts in the studied population .Genotyping for rs8832 was unsuccessful in some of the patients included in the cluster analysis . In addition, the same proinflammatory mediators are present in both the nasal and bronchial mucosa, including IL-4 and IL-13 . Thus, tIL4RA gene expression, was significantly associated with the high IgE allergic rhinitis group (cluster 5). When the effects of the G allele on the type 2 exacerbation-prone phenotypes (clusters 1 and 5 combined) were examined, the association became stronger, while the non-type 2 exacerbation-prone phenotypes  were not associated with the SNP. In addition, a significant association was found between the SNP and patients characterized by an increased number of blood eosinophils. Taken together, the functional SNP at IL4RA may have some role in the susceptibility to exacerbation, especially in patients with a type 2 phenotype. Among patients with asthma who had concomitant allergic rhinitis, but no history of exacerbation within the previous year, the frequency of the G allele did not differ significantly from that in the healthy volunteers; therefore, it seems that the functional allele might be primarily involved in the susceptibility to exacerbation itself rather than to the development of the type 2 phenotypes of asthma and/or COPD. A previous study revealed that SNPs in IL4RA were also associated with severe asthma exacerbations, lower lung function and increased mast cell-related tissue inflammation; the study suggested that the SNPs may modify the activation status of mast cells through a FceRI-dependent manner [The G allele at rs8832, which is associated with upregulated t manner . Given tt manner , rs8832 There are some limitations of this study. First, in the studied population, the causes of the exacerbations, which may include viral infection, environmental exposures, air pollution and/or psychological stress, were not confirmed. Second, the clinical variables used to search for exacerbation-prone phenotypes included variables that are subject to fluctuations . These clinical indicators may vary depending on the control status of the patients and the details of treatment, which may have affected the results of the cluster analyses. However, to minimize these changes as much as possible, data for clinical variables that were obtained during periods of stable disease were used. Third, no clear information on non-eosinophilic airway inflammation was available, which is considered to play a central role in airway inflammation in COPD and the neutrophilic phenotype is also present in asthma. However, to detect exacerbation phenotypes associated with non-type 2 inflammation, the indicators of a smoking history, GERD and BMI were used in our cluster analyses. Furthermore, the peripheral blood eosinophil count, total IgE, and presence or absence of allergic rhinitis were used as indicators for inferring non-eosinophil exacerbation phenotypes. Last, the number of patients evaluated in the present study was small; therefore, these findings are preliminary in nature and it is important to confirm the findings of the current study by performing a replication study in a larger population in the future.IL4RA was found to be particularly associated with the type 2 exacerbation-prone phenotypes. Therefore, our results indicated that the clinical heterogeneity of disease exacerbation may reflect the presence of common exacerbation-prone endotypes across asthma and COPD, and may support the use of the treatable traits approach for the treatment of exacerbations of chronic inflammatory airway diseases.In summary, five phenotypes associated with the exacerbation of chronic inflammatory airway diseases were identified across traditional diagnostic labels, including asthma, COPD and ACO. Furthermore, the functional SNP at S1 Data(XLSX)Click here for additional data file.S2 Data(XLSX)Click here for additional data file.S3 Data(XLSX)Click here for additional data file.


Frailty plays a crucial role in the management of hypertension in the very elderly and has a strong association with cardiovascular diseases. Nevertheless, its influence on the 24‐hour blood pressure pattern, including elevated asleep systolic blood pressure (BP) and the lack of BP fall during sleep (non‐dipping) has not been explored in a population above 80 years.Patients older than 80 years were classified into frail or robust subtypes by the five item frailty phenotype criteria. All participants were submitted to office blood pressure measurements and ambulatory BP monitoring over a 24‐hour period. Nocturnal dipping was defined as nighttime BP fall ≥10%.p = .04) and reduced systolic BP fall [1 (‐4.5 – 5)% vs. 6.8 (2.1 – 12.8)% p < .01]. Frailty was independently associated with higher risk of non‐dipping  and reduced nighttime systolic BP fall . In conclusions, frailty has a substantial influence on nighttime BP values and pattern in patients older than 80 years.Thirty‐eight frail and 36 non‐frail individuals  were analyzed. Awake systolic and diastolic BP were similar for frail and robust individuals. Frail patients had higher systolic BP during sleep (128 ± 15 mm Hg vs. 122 ±13 mm Hg  While the frail population tends to have higher cardiovascular risk, greater disease burden and increased disability and mortality; the non‐frail of the same age behave in an opposite manner.Elevated asleep systolic blood pressure (BP) and the lack of BP fall (dipping) have been associated with poorer cardiovascular outcome and are, amongst ABPM findings, the best prognostic markers of future cardiovascular events.No studies have been designed so far to analyze the role of frailty on these important cardiovascular risk markers in individuals above 80 years old. Therefore, the objective of the present study was to examine the effect of frailty on the 24‐hour blood pressure profile, in a population above 80 years, with specific focus on nighttime BP values and pattern.22.1All participants were enrolled from March 2019 to April 2021 at a geriatric clinic of the University Hospital, University of São Paulo, located in the city of Ribeirão Preto, São Paulo, Brazil. Participants included in the study were any patient older than 80 years classified into frail or robust subtype. Exclusion criteria were based on circumstances that could interfere with the 24‐hour blood pressure measurement or with the natural sleep pattern such as atrial fibrillation, being bedridden, inability to walk, advanced cognitive disorders, presence of obstructive sleep apnea or use of breathing devices for sleep.Data collection was suspended during local restrictions due to COVID‐19 pandemic outbreak. When the study was resumed, proper safety measures were taken, with special care that all included individuals were asymptomatic at the time of the analysis.The study was approved by an independent Ethics Committee (protocol no. 3.500.611) and all patients gave written informed consent to participate in the study. A total of 120 individuals were first assessed for frailty and 77 of them met the inclusion criteria and were invited to participate in the study. Three had to be excluded due to insufficient ABPM measurements, with the final sample thus consisting of 74 patients.All participants were submitted to comprehensive evaluation including comorbidities, medications in use, weight, height, abdominal circumference, as well as office blood pressure measurements in the sitting, lying, and standing position according to current guidelines.2.2Frailty was assessed by the phenotype model proposed by Fried and coworkers which consists of a five‐item questionnaire whereby the patients are classified as robust, pre‐frail or frail if they fulfill none, one or two, and more than two criteria, respectively.The five criteria considered were: presence of fatigue evaluated by self‐report questions of the Center for Epidemiological Studies Depression; unintentional loss of weight ; low physical activity defined by the International Physical Activity Questionnaire (IPAQ) as less than ten consecutive minutes of any activity in the last week; slow gait, measured by walking time in seconds (a distance of 4.6 m adjusted for sex and height); and reduced grip strength measured with a dynamometer (Jamar Hydraulic Hand Dynamometer) in the dominant hand. Reference values were extracted from a local population study and adjusted for sex, height, and body mass index (BMI).2.3Ambulatory blood pressure monitoring was conducted using an automated and validated device  which was adapted to record BP every 15 minutes during the day and every 30 minutes during the night. A cuff of appropriate size was installed on the non‐dominant arm according to current guidelines.The examination was considered appropriate if at least 75% of the systolic and diastolic readings were successful with at least 16 valid readings while awake and eight valid readings while asleep according to local guidelines.Patients were considered hypertensive when they used any antihypertensive medication or in the presence of systolic BP ≥140 mm Hg or diastolic ≥90 mm Hg on two different occasions.2.4Continuous data were tested for normality by the Shapiro Wilk test and reported as mean ± standard deviation or as median (interquartile range) accordingly. Qualitative values are reported as absolute frequency and percentages. Continuous variables were compared between groups with Student t test or Mann‐Whitney according to normality. Pearson Chi‐Square test was applied for categorical variables comparison between groups.Multiple unadjusted logistic regression tests were performed by logistic regression and linear models considering non‐dipping and systolic BP fall as dependent variables. A first model was created for adjustment with all the clinically relevant variables. In accordance with the number of individuals evaluated, which limits the number of covariates that can be added to logistic regression models, a second model was created with lesser covariates of adjustment with only the clinically relevant variables or with the variables that showed positive correlation in an unadjusted analysis. Coefficient was used to estimate the effect of each variable over the dependent variable. The covariables considered for adjusted analysis were: presence of frailty, age, body mass index (BMI), number of antihypertensive medications, presence of hypertension, 24‐hour systolic BP and orthostatic hypotension.p < .05.The analyses were performed using the SAS 9.4  and SPSS 25  software, with the level of significance set at 3p < .01) for the robust group, with 89% and 67% of hypertensive patients (p = .02), respectively. The demographic characteristics and distribution between groups are summarized in Table Mean age was 85.3 ± 3,7 years; 38 patients 51.4%) were found to be frail and 36 (48.6%) were robust. The female sex was predominant, accounting for 50 (67.5%) individuals. Fifty‐four  were of white ethnicity, 58  were hypertensive, and 21  had type 2 diabetes. There was homogeneity for most of the demographic characteristics such as age, BMI, abdominal circumference, diabetes, and number of antihypertensives taken among frail and robust patients. However, the median number of comorbidities was seven (5–9) for the frail group compared to four (3–6)  and standing  positions (Table p = .04), whereas no difference was detected for asleep diastolic BP. Frailty was associated with a greater prevalence of non‐dipping status [36 (61%) vs. 23 (39%) p < .01] and reduced systolic BP fall when compared to the robust population [1 (‐4.5 – 5)% vs. 6.8 (2.1 – 12.8)% p = < .01]. The ABPM findings are summarized in Table Twenty‐four‐hour readings of systolic and diastolic BP, mean arterial pressure, pulse pressure and heart rate were similar between the two groups. Awake systolic and diastolic BP were similar for frail and robust individuals. In contrast, mean systolic BP during sleep was higher among frail patients (128 ± 15 mm Hg vs. 122 ±13 mm Hg p < .01) and BMI  were associated with a higher risk in an unadjusted analysis. In a multivariate model, frailty  and BMI  were independently associated with a higher risk of non‐dipping even after adjustment for age, presence of hypertension, number of antihypertensives taken, 24‐hour systolic BP and presence of orthostatic hypotension. In accordance with the number of individuals analyzed, a second model was created with only the presence of frailty and BMI to avoid overfeeding. The second model showed persistent association of the risk for either frailty  and BMI  with stronger association of the former. All these analyzes are shown in Table Clinically relevant variables were analyzed by logistic regression to find association with the risk of non‐dipping. Frailty  whereas the presence of hypertension by ‐5.7% (CI ‐10 – ‐1.2% p = .01). In a multivariate model, frailty was independently associated with a reduce in BP fall by ‐6.1% (CI ‐9.6 – ‐2.6 % p = .01) even after adjustment for age, BMI, presence of hypertension, number of antihypertensives, 24h systolic BP and orthostatic hypotension. The effect was maintained and strengthen in a second model with lesser variables: ‐6.4% (CI ‐10 – ‐2.8% p < .01).The effect of each variable over systolic BP fall was individually estimated by coefficient in logistic regression as shown in Table Separate sensitivity analyses were performed with linear regressions considering the effect of awake systolic BP in non‐dipping status and systolic BP fall but no association was found.4This was a cross‐sectional study, designed to determine the role of frailty on the 24‐hour blood pressure pattern in a population above 80 years old, with specific focus on circadian variations. The results showed no difference in office measures for systolic BP but substantial influence of frailty on elevated asleep systolic BP and its lack of decrease in the very elderly. These data support the evidence of frailty as an important instrument for assessing cardiovascular risk in this heterogenous population and can be used in clinical practice, and further clinical trials, to guide treatment decisions. It also emphasizes the importance of sleep on future investigations and treatment of frailty and hypertension.p = .02), previous studies show that frailty is associated with hypertension.p < .01] which might be explained by the strong association between comorbidities and frailty as proposed by Rockwood and coworkersThe groups were homogenous in terms of demographic characteristics such as frailty, age, sex, BMI, and abdominal circumference, which allowed reducing biases. Despite a predominance of hypertension in the frail population , might represent a 20% higher risk of cardiovascular mortality in 9 years according to previous prospective study.The strong and independent effect of frailty on BP fall supports that even with these possible mechanisms involved, frailty plays an independent role over cardiovascular disease and must be considered as a crucial aspect when evaluating older adults, especially the very elderly. The American Heart Association raises the issue by pointing to the heterogeneity of this population and by suggesting emphasis in studies that include the role of frailty in cardiovascular diseases.To our knowledge, this was the first study to analyze the role of frailty on the 24‐hour blood pressure pattern in the very elderly population. The relatively small number of patients evaluated could be cited as one of the major limitations of the present study. However, there was great difficulty of finding very elderly individuals with the profile of this research and who agreed to participate in it. The exclusion of pre‐frail patients hinders extrapolation to a general population of the same age, in contrast, it emphasizes the effect of frailty on the dependent variables. The cross‐sectional design did not permit establishing a causal relationship, neither it allowed control of medications, a fact that could hinder interpretation of the data, although statistical analysis was used to adjust for possible confounding factors. The higher prevalence of hypertension in the frail could be cited as possible bias; however, this was compatible with previous studies in a similar population and after statistical adjustments with frailty and other variables, the effect of hypertension over the dependent variables did not prevail. Since comorbidities are implied in some definitions of frailty, it was not possible to equalize nor adjust this variable between groups.Further studies objectively measuring daily mobility and sleep quality in this specific population are suggested for a better understanding of this patient. Based in the present study, a focus in frailty and sleep treatment could be cited as promising adjuvant therapies for cardiovascular disease in the very elderly, although intervention trials designed to include frailty are warranted to clarify treatment.5In conclusions, frailty has a substantial influence on nighttime BP values and pattern in patients older than 80 years.The authors declare no conflict of interest.


By multivariate linear regression analyses, we found that salivary conductivity was positively related to age and fasting glucose but negatively associated with eGFR. We further divided subjects into low, medium, and high groups according to the tertials of salivary conductivity levels. There was a significant trend for an increment of CKD patients from low to high salivary conductivity groups . The receiver operating characteristic (ROC) curves disclosed an excellent performance by using salivary conductivity combined with age, gender, and body weight to diagnose CKD . The adjusted odds ratio of CKD is 2.66  in subjects with high salivary conductivity levels. Overall, salivary conductivity can serve as a good surrogate marker of kidney function; this real-time, non-invasive, and easy-to-use portable biosensing device may be a reliable tool for screening CKD.The prevalence of chronic kidney disease (CKD) is increasing, and it brings an enormous healthcare burden. The traditional measurement of kidney function needs invasive blood tests, which hinders the early detection and causes low awareness of CKD. We recently designed a device with miniaturized coplanar biosensing probes for measuring salivary conductivity at an extremely low volume (50 μL). Our preliminary data discovered that the salivary conductivity was significantly higher in the CKD patients. This cross-sectional study aims to validate the relationship between salivary conductivity and kidney function, represented by the estimated glomerular filtration rate (eGFR). We enrolled 214 adult participants with a mean age of 63.96 ± 13.53 years, of whom 33.2% were male. The prevalence rate of CKD, defined as eGFR < 60 mL/min/1.73 m Chronic kidney disease (CKD) is one of the most important public health issues and it brings an enormous socioeconomic burden . The preSaliva is a kind of body fluid that can be obtained easily in a non-invasive manner and serves as a potential specimen for monitoring our health situation ,16,17,18The composition of saliva changes with progressive CKD . SalivarThe portable biodevice was implemented to measure salivary conductivity. In brief, the construction steps were composed of three main steps, including biodevice design, the collection and analysis of saliva, and the test of reusability and selectivity of the electrodes.2 which can be covered with testing samples with only 50 μL required. The 10 × 5.5 × 2.2 cm3 conductivity meter was fabricated as the previous study, which composes of an analog-to-digital converter (ADC) , a micro control unit (MCU system) , a temperature sensor , and an organic light-emitting diode (OLED) . The electrode was bonded to the PCB by using nickel immersion gold wired. The conductivity meter can be implemented with 1 Vpp and 1 kHz sine waves via ADC to accomplish the measurement. The electrical conductivity parameters can be acquired through a discrete Fourier transform. The conductivity signal at 25 °C can be calculated through temperature compensation by the MCU system and be displayed on the OLED within 10 s.The proposed system is composed of two main parts, including a PCB with coating-free gold electrodes and a conductivity meter . The sizSalivary samples of all eligible subjects were collected and processed as previously described ,29. BrieFor testing the reusability of the electrode, salivary samples were tested 20 times with the same electrode. We used ultrapure water to clean the well until confirming the conductivity drops to the same level as the baseline before every measurement. In the clinical study, each PCB electrode was used with no more than five salivary samples to ensure the quality of the clinical data.Saliva is composed of 99% water, 1% protein and salts, etc. . Our senThis is a cross-sectional pilot study including adults aged ≥18 years who attended the annual health examination at Yunlin Branch of the Chang Gung Memorial Hospital, a regional teaching hospital in southern Taiwan, in August 2021. Before the investigation, we conducted a sample size calculation using PASS V.15 . Assuming a CKD prevalence rate of 12% , with 802). The blood pressure was measured with a validated electronic automated sphygmomanometer on the right arm of seated participants after 15 min’ rest in a quiet and comfortable environment. Two blood pressure readings were obtained at an interval of 5 min; if the readings differed by more than 20 mmHg, a third measurement was made, and the two closest blood pressure values were averaged. After an 8 to 12 h overnight fasting, venous blood and salivary samples were collected. Blood specimens were left undisturbed at room temperature for 30 min to allow the blood to clot. The clot was then removed by centrifuging at 3000 rpm for 10 min. The resulting supernatant was the serum which was analyzed for biochemical data using an automatic chemistry analyzer  following standardized laboratory procedures.Before health examination, all subjects received a comprehensive questionnaire survey conducted by trained nurses to provide information about previous head and neck surgery or radiotherapy and comorbid diseases, including diabetes, hypertension, chronic kidney disease, ischemic heart disease, stroke, dyslipidemia, gout, and chronic liver disease. Anthropometric data of their body weight (kg) and height (cm) were obtained, and the corresponding body mass index (BMI) was calculated as weight in kilograms divided by height in meters squared  [2.We used the revised Modification of Diet in Renal Disease (IDMS-MDRD) equation to calculate the eGFR: 175 × Cr female) . The deft-test was used to compare the means of the continuous variables of normal distribution, while the Mann–Whitney U test was applied for continuous but not normally distributed data. For comparison between multiple groups, the Analysis of Variance (ANOVA) with post hoc analysis were used for quantitative variables. The Pearson’s chi-square test was conducted for the comparison of categorical variables. The association between salivary conductivity and other quantitative variables was analyzed by univariate linear regression models. Furthermore, the multivariate linear regression analysis with backward selection was utilized to form a predictive model for salivary conductivity. Statistically significant factors identified in the univariate analysis were incorporated into the multivariate regression analysis. ROC curve analysis was used to evaluate the diagnostic accuracy of salivary conductivity on CKD. To improve the diagnostic ability, we performed the multivariable logistic regression analysis with backward selection using combined variables. The diagnostic power of different models was determined by calculating the area under the ROC curve (AUROC). Multivariate logistic regression with stepwise backward selection was utilized to estimate the odds ratios (ORs) of CKD, with salivary conductivity and other risk factors as independent variables. Subgroup analyses for heterogeneity in saliva conductivity effect were further performed, with subgroups defined according to age (<75 years or ≥75 years), gender, BMI (<25 kg/m2 or ≥25 kg/m2), history of diabetes (yes or no), underlying hypertension (yes or no), and coexisting dyslipidemia (yes or no). All statistical analyses were two-sided and were performed using the Statistical Program for Social Sciences (SPSS) version 22 . Values of p < 0.05 were considered statistically significant.Continuous variables are expressed as means ± standard deviations and categorical variables are displayed as numbers with their percentages. For examining the normality of numerical variables, the Kolmogorov–Smirnov method was performed. The independent two-tailed Student’s After serial measurements of the salivary conductivity of the same saliva sample 20 times, the mean absolute percentage error (MAPE) is 0.88%, with a maximum error of 2.39% .For determining the selectivity of the sensor, we measured the conductivity of ultrapure water, BSA, PBS solution, different BSA concentrations mixed with PBS solution, and healthy participants’ saliva. The results revealed that our co-planar microelectrodes have almost no interference from BSA and the majority of the conductivity was originated from the electrolytes in the solution A. By det2. Other biochemical parameters, anthropometric data, and blood pressure were shown in This cross-sectional study included 214 subjects with a mean age of 63.96 ± 13.53 years, of whom 33.2% were male. The mean salivary conductivity value was 5.91 ± 1.79 ms/cm. Diabetes mellitus, hypertension, chronic kidney disease, ischemic heart disease/stroke, dyslipidemia, gout, and chronic liver disease were recognized in 26 (12.1%), 62 (29.0%), 3 (1.4%), 16 (7.5%), 30 (14.0%), 9 (4.2%) and 24 (11.2%) participants, respectively. Their mean eGFR was equal to 86.33 ± 22.81 mL/min/1.73 mThe relationship between salivary conductivity and continuous variables was analyzed by Pearson’s correlation coefficient. Salivary conductivity was positively associated with age, systolic blood pressure, blood urea nitrogen (BUN), creatinine, and fasting glucose, but was inversely related to the eGFR .p < 0.001), higher fasting glucose , and lower eGFR  were significantly associated with higher salivary conductivity  < 5, thus no co-linearity exists among independent variables . Adjustep for trend = 0.016).To investigate the association of salivary conductivity and CKD, we divided study subjects into low, medium, and high salivary conductivity groups based on the tertial of conductivity levels . There wTo examine the diagnostic ability of salivary conductivity on CKD, the ROC curve analysis was conducted. The AUROC was equal to 0.648 (95% CI: 0.542–0.755) when salivary conductivity is the only predicting factor. To improve the diagnostic performance, age, gender, and body weight were further combined into the prediction model. This combination model demonstrated a significant increase in AUROC to 0.798 (95% CI: 0.726–0.871) A. Strikip < 0.01). They also had higher systolic blood pressure , higher BUN , higher creatinine , lower eGFR , higher serum osmolality , higher fasting glucose level , higher hemoglobin A1c , and a higher percentage of underlying diabetes mellitus . There were no significant differences in gender, body weight and height, body mass index, diastolic blood pressure, the prevalence of hypertension, chronic kidney disease, ischemic heart disease/stroke, dyslipidemia, gout, and chronic liver disease, ALT, triglyceride, total cholesterol, LDL-C, and HDL-C between groups.To further evaluate the risk of CKD concerning salivary conductivity, the subjects were stratified into low and high salivary conductivity level groups based on the cutoff value of the ROC curve calculated by using only salivary conductivity as the predictor (6.59 ms/cm). The characteristics of low versus high salivary conductivity groups were summarized in The subgroup analysis of the risk of CKD, comparing high versus low salivary conductivity was shown in The results reported here reveal that salivary conductivity is negatively correlated with eGFR and can serve as a potential biomarker for detecting CKD. Traditionally, the golden standard of measuring kidney function requires the collection of 24 h urine creatinine amount and the blood test of serum creatinine, which is cumbersome for patients ,35. Simp2 by the revised MDRD equation, is 11.2% in our study. A large-scale cohort study based on 462,293 adults in Taiwan showed that the national prevalence of CKD was 11.93% [The prevalence rate of CKD, defined as eGFR < 60 mL/min/1.73 ms 11.93% ,36. SincFurthermore, multivariate linear regression analyses also showed a significantly positive correlation between salivary conductivity with age or fasting glucose . SubjectThe ROC curve of our study implied that using salivary conductivity combined with age, gender, and body weight can yield an excellent prediction model with AUC equal to 0.8 . The tra2, thus individuals of higher eGFR but with kidney damage were not diagnosed. This would underestimate the occurrence or risk of CKD. In addition, current criteria for diagnosing CKD need eGFR and albuminuria or proteinuria data. A lack of urinalysis, proteinuria, or albuminuria data in study participants may underestimate the prevalence of CKD. However, the percentage of CKD is 11.2% in our study, which was comparable with the reported 12% national prevalence of CKD in Taiwan, reported by Wen et al. [There are several limitations needed to be mentioned in this research. First, this is a cross-sectional study; therefore, the true relationship between salivary conductivity and eGFR or CKD could not be confirmed by a single test. Second, CKD in our study was defined by a single eGFR measurement, which may erroneously include subjects with acute kidney injury. Third, CKD was defined as an eGFR < 60 mL/min/1.73 mTimely screening and detection for undiagnosed CKD are decisive for delaying the disease progression and reducing its complications or mortality. The results of this study demonstrate a significant correlation between salivary conductivity and eGFR. Higher salivary conductivity is associated with an increased risk of CKD. We have also shown an acceptable diagnostic accuracy and sensitivity of salivary conductivity in distinguishing CKD, especially for the elderly. Taken together, salivary conductivity can serve as a good surrogate marker of renal function; this real-time, non-invasive, and easy-to-use portable biosensing device may be a reliable tool for screening early-stage CKD.