Physical activity modifies cognitive impairment-associated mortality risks among chronic kidney disease.

BACKGROUND: Older chronic kidney disease (CKD) patients frequently face unrecognized cognitive impairment and excess mortality. Physical activity (PA) reduces cognitive decline but whether PA modifies cognitive impairment-associated mortality remains unknown. METHODS: From 2005 to 2011, 30,561 older Taiwanese CKD patients were enrolled. Patients were divided into intact cognition (≥8 scores), mild (6-7 scores), and severe (≤5 scores) cognitive impairment groups by the Short Portable Mental Status Questionnaire (SPMSQ), and were also categorized into high-PA (≥60 min/week of moderate-intensity PA), low-PA (20-60 min/week) or inactive (<20 min/week) groups. Cox regression was conducted to evaluate the individual and joint associations of cognitive impairment and PA on all-cause and cardiovascular mortality. RESULTS: After a median follow-up of 4.52 years, the all-cause mortality were higher in CKD patients with severe (multivariable-adjusted hazard ratio [aHR] 2.31; 95 % confidence interval [CI] 2.05-2.60) and mild (aHR 1.74; CI 1.51-1.99) cognitive impairment than cognitively intact ones. Remarkably, decreased PA amount interacted and amplified the cognitive impairment-associated mortality risks. Notably, the high-PA status linked to lower overall mortality risks both in mild (aHR 0.65; CI 0.45-0.93) and severe (aHR 0.73; CI 0.54-0.99) cognitively-impaired patients as compared to inactivity. Survival tree analysis indicated the least mortality in those with high PA and >8 SPMSQ scores. Similar associations were found in the cardiovascular mortality. LIMITATIONS: Residual confounding and single ethnicity. CONCLUSIONS: Cognitive impairment defined by SPMSQ was progressively associated with higher mortality among elderly CKD. Higher PA linked to lower cognitive impairment-associated death risks, and could be promoted for longevity benefits.

Plasma SCUBE2 as a novel biomarker associates with survival outcomes in patients with sepsis-associated acute kidney injury.

BACKGROUND: The adverse effects of sepsis-associated acute kidney injury (SA-AKI) highlight the need for new biomarkers. Signal Peptide-Complement C1r/C1s, Uegf, Bmp1-Epidermal Growth Factor-like Domain-Containing Protein 2 (SCUBE2), important for angiogenesis and endothelial integrity, has been linked to increased mortality in models of lipopolysaccharide-induced lung injury. This research aimed to assess the utility of plasma SCUBE2 levels as a prognostic indicator for SA-AKI in intensive care unit (ICU) patients. METHODS: Between September 2020 and December 2022, our study enrolled ICU patients diagnosed with stage 3 SA-AKI. We collected demographic information, illness severity indices, and laboratory data, including plasma SCUBE2 and sepsis-triggered cytokine levels. We employed receiver operating characteristic curves and DeLong tests to assess the predictive accuracy for survival, Kaplan-Meier curves to evaluate the relative risk of death, and multivariate logistic regression to identify independent mortality predictors. RESULTS: Among the total of 200 participants, the survivors had significantly higher plasma SCUBE2 levels (115.9 ng/mL) compared to those who died (35.6 ng/mL). SCUBE2 levels showed a positive correlation with the anti-inflammatory cytokine IL-10 and a negative correlation with the APACHE II score, SOFA score, C-reactive protein, and monocyte chemoattractant protein-1. Multivariate analysis revealed that elevated SCUBE2 and IL-10 levels were independently protective against mortality, and associated with the most favorable 30-day survival outcomes. CONCLUSIONS: In ICU patients with stage 3 SA-AKI, lower plasma levels of SCUBE2 were correlated with elevated pro-inflammatory factors, which impacted survival outcomes. This suggests that SCUBE2 could be a potential biomarker for predicting prognosis in patients with SA-AKI.

Associations of urinary fetuin-A with histopathology and kidney events in biopsy-proven kidney disease.

Background: Fetuin-A is implicated in the pathogenesis of vascular calcification in chronic kidney disease (CKD); however, the relationship between fetuin-A, histopathologic lesions and long-term kidney outcomes in patients with various types of kidney disease remains unclear. Methods: We measured urinary fetuin-A levels in 335 individuals undergoing clinically indicated native kidney biopsy. The expressions of fetuin-A mRNA and protein in the kidney were assessed using RNA sequencing and immunohistochemistry. The association of urinary fetuin-A with histopathologic lesions and major adverse kidney events (MAKE), defined as a decline in estimated glomerular filtration rate (eGFR) of at least 40%, kidney failure or death, was analyzed. Results: Urinary fetuin-A levels showed a positive correlation with albuminuria (rs = 0.67, P < .001) and a negative correlation with eGFR (rs = -0.46, P < .001). After multivariate adjustment, higher urinary fetuin-A levels were associated with glomerular inflammation, mesangial expansion, interstitial fibrosis and tubular atrophy, and arteriolar sclerosis. Using a 1 transcript per million gene expression cutoff, we found kidney fetuin-A mRNA levels below the threshold in both individuals with normal kidney function and those with CKD. Additionally, immunohistochemistry revealed reduced fetuin-A staining in tubular cells of CKD patients compared with normal controls. During a median 21-month follow-up, 115 patients experienced MAKE, and Cox regression analysis confirmed a significant association between elevated urinary fetuin-A and MAKE. This association remained significant after adjusting for potential confounding factors. Conclusion: Urinary fetuin-A is associated with chronic histological damage and adverse clinical outcomes across a spectrum of biopsy-proven kidney diseases.

The Risk Factors and Clinical Outcomes in Hepatitis B Seropositive and Seronegative Renal Transplant Patients.

INTRODUCTION: Hepatitis B virus (HBV) infection is prevalent in Asia including Taiwan. We retrospectively evaluated the risk of HBV reactivation and clinical outcomes in HBV+ and HBV- kidney transplant recipients. METHODS: Patients who underwent kidney transplantation between January 2004 and December 2021 were reviewed. The outcomes of interest included risks of HBV reactivation and patient/graft survival. RESULTS: We identified 337 patients (47.5 ± 12 years) in our final cohort. Fifty-two (15.4%) had hepatitis B surface antigen (HBsAg) positive at the time of transplantation. Seventeen developed viral reactivations, with 41.2% of them accompanied by active hepatitis. The graft survival, acute rejection rate, and cancer development after kidney transplantation did not differ in terms of HBsAg status. The Cox multivariate analysis indicated the HBV reactivation risk was increased by a lack of pretransplant anti-HBV medication (hazard ratio [HR], 5.95; 95% confidence interval [CI], 1.31-27.02; p = 0.021) or an absence of lifelong antiviral therapy (HR: 3.14; 95% CI: 1.01-9.74; p = 0.047). CONCLUSION: Individuals, independent of HBsAg status, had similar prognosis in terms of patient and graft survival, acute rejection rate, and cancer development. The absence of either pretransplant anti-HBV medication or lifelong antiviral therapy was significantly associated with an increased risk of HBV reactivation.

Machine-learning models are superior to severity scoring systems for the prediction of the mortality of critically ill patients in a tertiary medical center.

BACKGROUND: Intensive care unit (ICU) mortality prediction helps to guide therapeutic decision making for critically ill patients. Several scoring systems based on statistical techniques have been developed for this purpose. In this study, we developed a machine-learning model to predict patient mortality in the very early stage of ICU admission. METHODS: This study was performed with data from all patients admitted to the intensive care units of a tertiary medical center in Taiwan from 2009 to 2018. The patients' comorbidities, co-medications, vital signs, and laboratory data on the day of ICU admission were obtained from electronic medical records. We constructed random forest and extreme gradient boosting (XGBoost) models to predict ICU mortality, and compared their performance with that of traditional scoring systems. RESULTS: Data from 12,377 patients was allocated to training (n = 9901) and testing (n = 2476) datasets. The median patient age was 70.0 years; 9210 (74.41%) patients were under mechanical ventilation in the ICU. The areas under receiver operating characteristic curves for the random forest and XGBoost models (0.876 and 0.880, respectively) were larger than those for the Acute Physiology and Chronic Health Evaluation II score (0.738), Sequential Organ Failure Assessment score (0.747), and Simplified Acute Physiology Score II (0.743). The fraction of inspired oxygen on ICU admission was the most important predictive feature across all models. CONCLUSION: The XGBoost model most accurately predicted ICU mortality and was superior to traditional scoring systems. Our results highlight the utility of machine learning for ICU mortality prediction in the Asian population.

Circulating Activin A, Kidney Fibrosis, and Adverse Events.

BACKGROUND: Identification of reliable biomarkers to assess kidney fibrosis severity is necessary for patients with CKD. Activin A, a member of the TGF- ß superfamily, has been suggested as a biomarker for kidney fibrosis. However, its precise utility in this regard remains to be established. METHODS: We investigated the correlation between plasma activin A levels, kidney fibrosis severity, and the incidence of major adverse kidney events in patients who underwent native kidney biopsies at a tertiary medical center. We performed RNA sequencing and histological analyses on kidney biopsy specimens to assess activin A expression. In vitro experiments were also conducted to explore the potential attenuation of TGF- ß -induced fibroblast activation through activin A inhibition. RESULTS: A total of 339 patients with biopsy-confirmed kidney diseases were enrolled. Baseline eGFR was 36 ml/min per 1.73 m 2 , and the urine protein/creatinine ratio was 2.9 mg/mg. Multivariable logistic regression analysis revealed a significant association between plasma activin A levels and the extent of tubulointerstitial fibrosis. Our RNA sequencing data demonstrated a positive correlation between kidney INHBA expression and plasma activin A levels. Furthermore, the histological analysis showed that myofibroblasts were the primary activin A-positive interstitial cells in diseased kidneys. During a median follow-up of 22 months, 113 participants experienced major adverse kidney events. Cox proportional hazards analysis initially found a positive association between plasma activin A levels and kidney event risk, but it became insignificant after adjusting for confounders. In cultured fibroblasts, knockdown of activin A significantly attenuated TGF- ß -induced fibroblast-myofibroblast conversion. CONCLUSIONS: Plasma activin A levels correlate with kidney fibrosis severity and adverse outcomes in various kidney disorders.

Survival benefit of a third dose of the COVID-19 vaccine among hemodialysis patients: A prospective cohort study.

BACKGROUND: Hemodialysis (HD) patients are particularly vulnerable to severe coronavirus disease 2019 (COVID-19) due to their immunocompromised state and comorbid conditions. Timely vaccination could be the most effective strategy to reduce morbidity and mortality. However, data on the survival benefit of the COVID-19 vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and death among HD patients are limited, especially during the Omicron-dominant period. METHODS: In this prospective hospital-based cohort study, we identified HD patients from July 1, 2021, to April 29, 2022. The patients were divided into fully vaccinated and partially vaccinated groups. We compared the humoral response, risk of developing SARS-CoV-2 infection, and all-cause mortality between the two groups. RESULTS: Among the 440 HD patients included, 152 patients were fully vaccinated, and 288 patients were partially vaccinated. Patients in the fully vaccinated group exhibited higher anti-spike protein receptor-binding domain (S protein RBD) antibody levels and lower risks of all-cause mortality (adjusted hazard ratio, 0.35; 95% confidence interval, 0.17-0.73; p = 0.005) than the partially vaccinated group. However, the risk for SARS-CoV-2 infection did not significantly differ between the two groups. Irrespective of the number of vaccinations, the risk of all-cause mortality was lower in patients with anti-S protein RBD antibody levels in the higher tertile. CONCLUSION: A third dose of the COVID-19 vaccine was associated with a decreased risk of all-cause mortality among HD patients during the Omicron-dominant period. A higher post-vaccination anti-S protein RBD antibody level was also associated with a lower risk of mortality.

Prediction of the risk of developing end-stage renal diseases in newly diagnosed type 2 diabetes mellitus using artificial intelligence algorithms.

OBJECTIVES: Type 2 diabetes mellitus (T2DM) imposes a great burden on healthcare systems, and these patients experience higher long-term risks for developing end-stage renal disease (ESRD). Managing diabetic nephropathy becomes more challenging when kidney function starts declining. Therefore, developing predictive models for the risk of developing ESRD in newly diagnosed T2DM patients may be helpful in clinical settings. METHODS: We established machine learning models constructed from a subset of clinical features collected from 53,477 newly diagnosed T2DM patients from January 2008 to December 2018 and then selected the best model. The cohort was divided, with 70% and 30% of patients randomly assigned to the training and testing sets, respectively. RESULTS: The discriminative ability of our machine learning models, including logistic regression, extra tree classifier, random forest, gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), and light gradient boosting machine were evaluated across the cohort. XGBoost yielded the highest area under the receiver operating characteristic curve (AUC) of 0.953, followed by extra tree and GBDT, with AUC values of 0.952 and 0.938 on the testing dataset. The SHapley Additive explanation summary plot in the XGBoost model illustrated that the top five important features included baseline serum creatinine, mean serum creatine within 1 year before the diagnosis of T2DM, high-sensitivity C-reactive protein, spot urine protein-to-creatinine ratio and female gender. CONCLUSIONS: Because our machine learning prediction models were based on routinely collected clinical features, they can be used as risk assessment tools for developing ESRD. By identifying high-risk patients, intervention strategies may be provided at an early stage.

Associations of the Serum Total Carbon Dioxide Level with Long-Term Clinical Outcomes in Sepsis Survivors.

INTRODUCTION: Sepsis is characterized by a dysregulated host response to infection that leads to multiple organ dysfunction and often complicated with metabolic acidosis. However, the associations between serum total carbon dioxide level (TCO2) and long-term clinical outcomes in sepsis survivors remains unknown. METHODS: A total of 7212 sepsis survivors aged ≥ 20 years who were discharged from January  1, 2008 to December 31, 2018 were included in our analyses. The sepsis survivors were further divided into high TCO2 (≥ 18 mmol/L) and low TCO2 (< 18 mmol/L) groups, comprising 5023 and 2189 patients, respectively. The following outcomes of interest were included: all-cause mortality, myocardial infarction, ischemic stroke, hospitalization for heart failure, ventricular arrhythmia, and end-stage renal disease (ESRD). RESULTS: After propensity score matching, the low TCO2 group was at higher risks of all-cause mortality (hazard ratio [HR] 1.28, 95% confidence interval [95% CI] 1.18-1.39), myocardial infarction (HR 1.83, 95% CI 1.39-2.43), and ESRD (HR 1.38, 95% CI 1.16-1.64) than the high TCO2 group. The results remained similar after considering death as a competing risk. CONCLUSION: Patients discharged from hospitalization for sepsis have higher risks of worse long-term clinical outcomes. Physicians may need to pay more attention to sepsis survivors whose TCO2 was low.

Plasma Galectin-9 Is a Useful Biomarker for Predicting Renal Function in Patients Undergoing Native Kidney Biopsy.

CONTEXT.­: Galectin-9 reduces tissue damage in certain immune-mediated glomerular diseases. However, its role in structural and functional renal changes in patients with varying types of chronic kidney disease (CKD) is less clear. OBJECTIVE.­: To investigate the association between plasma galectin-9 levels, proteinuria, tubulointerstitial lesions, and renal function in different CKD stages. DESIGN.­: We measured plasma galectin-9 levels in 243 patients undergoing renal biopsy for determining the CKD etiology. mRNA and protein expression levels of intrarenal galectin-9 were assessed by quantitative real-time polymerase chain reaction and immunostaining. Relationships between plasma galectin-9, clinical characteristics, and tubulointerstitial damage were analyzed with logistic regression. We investigated galectin-9 expression patterns in vitro in murine J774 macrophages treated with differing stimuli. RESULTS.­: To analyze the relationship between galectin-9 and clinical features, we divided the patients into 2 groups according to median plasma galectin-9 levels. The high galectin-9 group tended to be older and to have decreased renal function, higher proteinuria, and greater interstitial fibrosis. After multivariable adjustment, elevated plasma galectin-9 levels were independently associated with stage 3b or higher CKD. An analysis of gene expression in the tubulointerstitial compartment in the biopsy samples showed a significant positive correlation between intrarenal galectin-9 mRNA expression and plasma galectin-9 levels. Immunohistochemistry confirmed increased galectin-9 expression in the renal interstitium of patients with advanced CKD, and most galectin-9-positive cells were macrophages, as determined by double-immunofluorescence staining. In vitro experiments showed that galectin-9 expression in macrophages was significantly increased after interferon-γ stimulation. CONCLUSIONS.­: Our findings suggest that plasma galectin-9 is a good biomarker for diagnosing advanced CKD.

The strategy of diminishing age gap effect on different donor-recipient combinations in living donor kidney transplantation.

BACKGROUND: The disparity between kidney donation and the number of uremic patients on the waiting list has increased the demand for older live-donor kidneys (OLK). However, the donor-recipient age gap may have an impact on the recipient's outcome. METHODS: Patients who underwent living donor kidney transplantation at our institute between 2005 and 2019 were enrolled and categorized into four donor-recipient groups according to age (≥50 years and <50 years). The Estimated Post-Transplant Survival (EPTS) score was used to quantify the recipient's condition. Adjusted models analyzed recipient outcomes and related risks among the four groups. RESULTS: Of the 154 pairs of live donors and recipients, OLK did not influence overall or death-censored graft survival. The four donor-recipient combinations had similar recipient outcomes, except it slightly worsened in the "old donor to young recipient" group. The EPTS score (adjusted HR, 1.02; 95% CI, 1.01-1.04; p = 0.014) and rejection (adjusted HR, 4.26; 95% CI, 1.36-13.37; p = 0.013) were significant risk factors for overall and death-censored graft survival, respectively. Recipients with pretransplant diabetes or prior solid organ transplantation could have amplified risk effects. The main causes of graft loss were death in older recipients and chronic rejection in younger recipients. CONCLUSION: OLK is safe for young recipients. Nevertheless, adequate immunosuppression should be maintained to prevent rejection and subsequent graft loss, especially for those receiving second kidney transplantation. In contrast, older recipients should avoid overt immunosuppression and control their comorbidities, such as diabetes-related complications to improve their long-term outcomes.

Echocardiographic features of left ventricular dysfunction and outcomes in chronic kidney disease.

OBJECTIVE: Heart failure (HF) imposes a substantial burden and the prevalence of HF is high in patients with chronic kidney disease (CKD). HF results in multiple hospital admissions, but whether HF subtypes worsen long-term outcomes and renal function in patients with CKD remains inconclusive. METHODS: The study comprised 10 904 patients with CKD aged ≥20 years who underwent echocardiography between 1 January 2011 and 31 December 2018. The patients were stratified into four groups: non-HF, HF with reduced ejection fraction (HFrEF), HF with mildly reduced ejection fraction (HFmrEF) and HF with preserved ejection fraction (HFpEF). The primary end points were all-cause mortality, major adverse cardiovascular events (MACEs) and adverse renal outcomes. RESULTS: In inverse probability of treatment weighting-adjusted method, the risk of all-cause mortality and MACEs relative to the non-HF group was greatest in the HFrEF group (HR 3.18 (95% CI 2.57 to 3.93) and HR 3.83 (95% CI 3.20 to 4.59)), followed by the HFmrEF (HR 2.75 (95% CI 2.22 to 3.42) and HR 3.08 (95% CI 2.57 to 3.69)) and HFpEF (HR 1.85 (95% CI 1.59 to 2.15) and HR 2.43 (95% CI 2.16 to 2.73) groups. In addition, the HFrEF group had the greatest risks of end-stage renal disease (HR 2.58 (95% CI 1.94 to 3.44)) compared with other groups. CONCLUSIONS: HF is associated with subsequent worse clinical outcomes, which may be more pronounced in patients with HFrEF, followed by those with HFmrEF and those with HFpEF relative to non-HF group.

Sacubitril/Valsartan in Patients With Heart Failure and Concomitant End-Stage Kidney Disease.

Background Heart failure with reduced ejection fraction (HFrEF) is a chronic disease with substantial mortality. Management of HFrEF has seen significant breakthrough after the launch of neprilysin inhibitor. The PARADIGM-HF (Prospective Comparison of ARNI with ACEI to Determine Impacton Global Mortality and Morbidity in Heart Failure) trial showed that sacubitril/valsartan significantly reduces HFrEF mortality and the heart failure hospitalization rate. However, in patients with advanced kidney disease, who have the highest prevalence of heart failure, the efficacy and safety of sacubitril/valsartan remains uncertain. We aim to study the efficiency of sacubitril/valsartan in patients with end-stage kidney disease. Methods and Results Heart function was screened by echocardiogram among all patients with end-stage kidney disease in 2 hospitals. Patients with HFrEF received either sacubitril/valsartan or conventional treatment. Fifteen echocardiographic parameters were compared before and after treatment. After 1-year sacubitril/valsartan treatment, parameters of systolic (left ventricular ejection fraction 31.3% to 45.1%, P<0.0001; left ventricular end-systolic volume 95.7 to 70.1 mL, P=0.006; left ventricular internal diameter at end-systole phase 47.2 to 40.1 mm, P=0.005), and diastolic (E/A ratio 1.3 to 0.8, P=0.009; E/Med e' ratio 25.3 to 18.8, P=0.010) function improved in patients with HFrEF and end-stage kidney disease. These parameters were unchanged in the conventional treatment group. Serum potassium did not increase in the sacubitril/valsartan group. Conclusions Sacubitril/valsartan improves left ventricular systolic and diastolic function in patients with HFrEF and end-stage kidney disease.

Far-Infrared Therapy Improves Arteriovenous Fistula Patency and Decreases Plasma Asymmetric Dimethylarginine in Patients with Advanced Diabetic Kidney Disease: A Prospective Randomized Controlled Trial.

Asymmetric dimethylarginine (ADMA) is an endogenous inhibitor of nitric oxide synthase and plays a significant role in the pathogenesis of arteriovenous fistula (AVF) dysfunction. The aim of this study is to evaluate the effect of far-infrared (FIR) therapy on the maturation and patency of newly-created AVFs in patients with advanced diabetic kidney disease (DKD) as well as the concurrent change in plasma ADMA. The study enrolled 144 participants with advanced DKD where 101 patients were randomly allocated to the FIR therapy group (N = 50) and control group (N = 51). Patients receiving FIR therapy had a decreased AVF failure rate within 12 months (16% versus 35.3%; p = 0.027); decreased incremental change of ADMA concentration at the 3rd and 12th month; increased AVF blood flow at the 1st, 3rd, and 12th month; increased 3-month physiologic maturation rate (88% versus 68.6%; p = 0.034); increased 1-year unassisted AVF patency rate (84% versus 64.7%; p = 0.017); and increased clinical AVF maturation rate within 12 months (84% versus 62.7%; p = 0.029) compared to the control group. The study demonstrates that FIR therapy can reduce the incremental changes in plasma ADMA concentration, which may be associated with the improvement of AVF prognosis in patients with advanced DKD.

Artificial Intelligence for Risk Prediction of End-Stage Renal Disease in Sepsis Survivors with Chronic Kidney Disease.

Sepsis may lead to kidney function decline in patients with chronic kidney disease (CKD), and the deleterious effect may persist in patients who survive sepsis. We used a machine learning approach to predict the risk of end-stage renal disease (ESRD) in sepsis survivors. A total of 11,661 sepsis survivors were identified from a single-center database of 112,628 CKD patients between 2010 and 2018. During a median follow-up of 3.5 years, a total of 1366 (11.7%) sepsis survivors developed ESRD after hospital discharge. We adopted the random forest, extra trees, extreme gradient boosting, light gradient boosting machine (LGBM), and gradient boosting decision tree (GBDT) algorithms to predict the risk of ESRD development among these patients. GBDT yielded the highest area under the receiver operating characteristic curve of 0.879, followed by LGBM (0.868), and extra trees (0.865). The GBDT model revealed the strong effect of estimated glomerular filtration rates <25 mL/min/1.73 m2 at discharge in predicting ESRD development. In addition, hemoglobin and proteinuria were also essential predictors. Based on a large-scale dataset, we established a machine learning model computing the risk for ESRD occurrence among sepsis survivors with CKD. External validation is required to evaluate the generalizability of this model.

Urinary Galectin-3 as a Novel Biomarker for the Prediction of Renal Fibrosis and Kidney Disease Progression.

Plasma galectin-3 (Gal-3) is associated with organ fibrosis, but whether urinary Gal-3 is a potential biomarker of kidney disease progression has never been explored. Between 2018 and 2021, we prospectively enrolled 280 patients who underwent renal biopsy and were divided into three groups based on their urinary Gal-3 levels (<354.6, 354.6−510.7, and ≥510.8 pg/mL) to assess kidney disease progression (defined as ≥40% decline in the estimated glomerular filtration rate or end-stage renal disease) and renal histology findings. Patients in the highest urinary Gal-3 tertile had the lowest eGFRs and highest proteinuria levels. In multivariate Cox regression models, patients in the highest tertile had the highest risk of kidney disease progression (adjusted hazard ratio, 4.60; 95% confidence interval, 2.85−7.71) compared to those in the lowest tertile. Higher urinary Gal-3 levels were associated with more severe renal fibrosis. Intrarenal mRNA expression of LGALS3 (Gal-3-encoded gene) was most correlated with the renal stress biomarkers (IGFBP7 and TIMB2), renal function biomarkers (PTGDS) and fibrosis-associated genes (TGFB1). The urinary Gal-3 level may be useful for the identification of patients at high risk of kidney disease progression and renal fibrosis, and for the early initiation of treatments for these patients.

Sepsis and the Risks of Long-Term Renal Adverse Outcomes in Patients With Chronic Kidney Disease.

Background: Sepsis is known to cause renal function fluctuations during hospitalization, but whether these patients discharged from sepsis were still at greater risks of long-term renal adverse outcomes remains unknown. Methods: From 2011 to 2018, we included 1,12,628 patients with chronic kidney disease (CKD) aged ≥ 20 years. The patients with CKD were further divided into 11,661 sepsis group and 1,00,967 non-sepsis group. The following outcome of interest was included: all-cause mortality, readmission for acute kidney injury, estimated glomerular filtration rate decline ≥50% or doubling of serum creatinine, and end-stage renal disease. Results: After propensity score matching, the sepsis group was at higher risks of all-cause mortality [hazard ratio (HR) 1.39, 95% CI, 1.31-1.47], readmission for acute kidney injury (HR 1.67, 95% CI 1.58-1.76), eGFR decline ≥ 50% or doubling of serum creatinine (HR 3.34, 95% CI 2.78-4.01), and end-stage renal disease (HR 1.43, 95% CI 1.34-1.53) than non-sepsis group. Conclusions: Our study found that patients with CKD discharged from hospitalization for sepsis have higher risks of subsequent renal adverse events.

Pentraxin 3 Predicts Arteriovenous Fistula Functional Patency Loss and Mortality in Chronic Hemodialysis Patients.

INTRODUCTION: Viable vascular access is the lifeline for hemodialysis patients. In the nondialysis population, emerging evidence suggests that circulating pentraxin 3 (PTX3), neutrophil gelatinase-associated lipocalin (NGAL), and chitinase-3-like protein 1 (CHI3L1) are associated with cardiovascular inflammation and endothelial injury. However, predictive values of these three biomarkers on arteriovenous fistula (AVF) outcomes are unknown. METHODS: This prospective observational cohort study enrolled 135 hemodialysis patients using AVF and then followed them for 3 years. Plasma levels of PTX3, NGAL, and CHI3L1 were measured. Patients were followed up prospectively for two clinical outcomes, including AVF functional patency loss and death. Cox proportional hazards regression models were used to analyze hazard ratios for the commencement of AVF functional patency loss and mortality. RESULTS: Among 135 patients, the mean age was 66.0 ± 15.7 years old and 48.1% were male. The plasma level of PTX3, NGAL, and CHI3L1 was 2.8 ± 2.3 ng/mL, 349.2 ± 111.4 ng/mL, and 185.5 ± 66.8 ng/mL, respectively. During a 3-year follow-up period, the plasma level of PTX3 was an independent predictor for AVF functional patency loss (per 1 ng/mL increase, HR 1.112 [95% CI: 1.001-1.235], p = 0.048). Besides, patients with higher plasma levels of PTX3 were more likely to suffer from cardiovascular mortality (per 1 ng/mL increase, HR 1.320 [95% CI: 1.023-1.703], p = 0.033), infectious mortality (per 1 ng/mL increase, HR 1.394 [95% CI: 1.099-1.769], p = 0.006), and all-cause mortality (per 1 ng/mL increase, HR 1.233 [95% CI: 1.031-1.476], p = 0.022). CONCLUSIONS: The plasma level of PTX3, not NGAL or CHI3L1, was associated with higher risks of AVF functional patency loss in chronic hemodialysis patients, showing its value in reflecting AVF endothelial dysfunction. Furthermore, PTX3 also predicts mortality in chronic hemodialysis patients.

Influence of Dialysis Membranes on Clinical Outcomes: From History to Innovation.

Dialysis membranes were traditionally classified according to their material compositions (i.e., as cellulosic or synthetic) and on the basis of the new concept of the sieving coefficient (determined by the molecular weight retention onset and molecular weight cut-off). The advantages of synthetic polymer membranes over cellulose membranes are also described on the basis of their physical, chemical, and structural properties. Innovations of dialysis membrane in recent years include the development of medium cutoff membranes; graphene oxide membranes; mixed-matrix membranes; bioartificial kidneys; and membranes modified with vitamin E, lipoic acid, and neutrophil elastase inhibitors. The current state of research on these membranes, their effects on clinical outcomes, the advantages and disadvantages of their use, and their potential for clinical use are outlined and described.

Artificial Intelligence for Risk Prediction of Rehospitalization with Acute Kidney Injury in Sepsis Survivors.

Sepsis survivors have a higher risk of long-term complications. Acute kidney injury (AKI) may still be common among sepsis survivors after discharge from sepsis. Therefore, our study utilized an artificial-intelligence-based machine learning approach to predict future risks of rehospitalization with AKI between 1 January 2008 and 31 December 2018. We included a total of 23,761 patients aged ≥ 20 years who were admitted due to sepsis and survived to discharge. We adopted a machine learning method by using models based on logistic regression, random forest, extra tree classifier, gradient boosting decision tree (GBDT), extreme gradient boosting, and light gradient boosting machine (LGBM). The LGBM model exhibited the highest area under the receiver operating characteristic curves (AUCs) of 0.816 to predict rehospitalization with AKI in sepsis survivors and followed by the GBDT model with AUCs of 0.813. The top five most important features in the LGBM model were C-reactive protein, white blood cell counts, use of inotropes, blood urea nitrogen and use of diuretics. We established machine learning models for the prediction of the risk of rehospitalization with AKI in sepsis survivors, and the machine learning model may set the stage for the broader use of clinical features in healthcare.