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End-stage kidney disease (ESKD) presents a significant public health challenge, with hemodialysis (HD) remaining one of the most prevalent kidney replacement therapies. Ensuring the longevity and functionality of arteriovenous accesses is challenging for HD patients. Blood flow sound, which contains valuable information, has often been neglected in the past. However, machine learning offers a new approach, leveraging data non-invasively and learning autonomously to match the experience of healthcare professionas. This study aimed to devise a model for detecting arteriovenous grafts (AVGs) stenosis. A smartphone stethoscope was used to record the sound of AVG blood flow at the arterial and venous sides, with each recording lasting one minute. The sound recordings were transformed into mel spectrograms, and a 14-layer convolutional neural network (CNN) was employed to detect stenosis. The CNN comprised six convolution blocks with 3x3 kernel mapping, batch normalization, and rectified linear unit activation function. We applied contrastive learning to train the pre-training audio neural networks model with unlabeled data through self-supervised learning, followed by fine-tuning. In total, 27,406 dialysis session blood flow sounds were documented, including 180 stenosis blood flow sounds. Our proposed framework demonstrated a significant improvement (p<0.05) over training from scratch and a popular pre-trained audio neural networks (PANNs) model, achieving an accuracy of 0.9279, precision of 0.8462, and recall of 0.8077, compared to previous values of 0.8649, 0.7391, and 0.6538. This study illustrates how contrastive learning with unlabeled blood flow sound data can enhance convolutional neural networks for detecting AVG stenosis in HD patients.

Background Kidney function is associated with clinical outcomes in patients with cancer. Objectives This study aimed to assess the association between kidney function decline and cancer‐related mortality among community‐dwelling elderly individuals. Design This was a retrospective longitudinal cohort study. Participants The 61,988 participants were from an elderly health examination database in Taipei City from 2005 to 2012. Measurements Multivariable logistic regression was used to assess the association between baseline covariates and rapidly deteriorating estimated glomerular filtration rate (eGFR). In addition, Cox proportional hazards model and the Fine–Gray model were used to quantify the effects of covariates on total cancer mortality and six specific cancer mortalities. Results During the follow‐up period, 1482 participants died of cancer. Their baseline average eGFR was 73.8 ± 19.9 mL/min/1.73 m2, and 18.3% had rapid renal function decline (≥5 mL/min/1.73 m2 per year). Rapid renal function decline was positively related to age, baseline eGFR, proteinuria, hypertension, waist circumferences, high log triglyceride levels, and diabetes mellitus (DM) history. In Cox proportional hazard models, participants with rapid eGFR decline had an increased risk of cancer mortality [hazard ratio (95% CI): 1.97 (1.73, 2.24); p < 0.001] compared to those without rapid eGFR decline. In the analysis of site‐specific cancer mortality risk, rapid eGFR decline was associated with six site‐specific cancer mortality, namely gastrointestinal tract, hepatobiliary, lung, prostate, urinary tract, and hematological malignancies. Conclusions Elderly individuals with rapid kidney function decline had higher cancer mortality risks. Serial assessments of dynamic changes in eGFR might provide information relevant for cancer prognosis. This study aimed to assess the association between kidney function decline and cancer‐related mortality among community‐dwelling elderly individuals. In Cox proportional hazard models, participants with rapid eGFR decline had an increased risk of cancer mortality compared to those without rapid eGFR decline. In the analysis of site‐specific cancer mortality risk, rapid eGFR decline was associated with six site‐specific cancer mortality, namely gastrointestinal tract, hepatobiliary, lung, prostate, urinary tract, and hematological malignancies.

Adiponectin is the most abundant circulating adipokine, and it has insulin-sensitizing and anti-inflammatory properties. Although it has been speculated that kidney function decline associated with elevated adiponectin is attributable to decreased renal clearance and compensatory responses to adiponectin resistance, it is unclear how elevated adiponectin affects clinical outcomes in chronic kidney disease (CKD) patients and whether the effects are the same as those in the general population. Therefore, the aim of this study is to examine whether the association between serum adiponectin levels and clinical outcomes in non-diabetic CKD patients is independent of adiposity and metabolic syndrome. We enrolled 196 non-diabetic CKD patients with eGFR ranging between 10 and 60 mL/min/1.73 m2, these patients were divided into two groups based on the presence of metabolic syndrome. The primary endpoint was all-cause mortality or renal events (renal failure requiring renal replacement therapy [RRT] or 50% reduction in eGFR). During the mean follow-up period of 5 years, 48 (24.5%) incident cases of end-stage renal disease (ESRD) were observed, and 33 (16.8%) deaths occurred. The mean eGFR was 29.8 ± 12.8 mL/min/1.73m2. The baseline median adiponectin concentration in the cohort was 29.4(interquartile range, 13.3-108.7) μg/ml. Adiponectin levels were inversely related to body mass index (BMI) (r = -0.29; P < 0.001) and waist circumference (r = -0.35; P < 0.001). In the fully adjusted Cox regression model, the hazard ratios (HRs) were 2.08 (95% confidence interval [CI], 1.08-4.02; P = 0.03) for RRT and 1.66 (95% CI, 1.03-2.65; P = 0.04) for composite renal outcome. The risks remained consistent within different subgroups. However, no association was observed with mortality risk. In conclusion, higher adiponectin levels are associated with a higher risk of ESRD independent of conventional risk factors, BMI, and metabolic syndrome components.

Pyuria is common in chronic kidney disease (CKD), which could be due to either urinary tract infection (UTI) or renal parenchymal inflammation. Only little is known regarding the association of pyuria or UTI with renal outcomes. We investigated 3226 patients with stage 3–5 CKD. Pyuria was defined as ≥ 50 WBC per high-power field (hpf) and was correlated to old age, female, diabetes, hypoalbuminemia, lower eGFR, and higher inflammation status. In Cox regression, patients with more than one episode of pyuria in the first year (11.8%) had increased risks for end-stage renal disease (ESRD) [hazard ratio (95% CI): 1.90 (1.58–2.28); p  <  0.001 ], rapid renal function progression [odds ratio (95% CI): 1.49 (1.13–1.95); p  =  0.001 ], and all-cause mortality [hazard ratio: 1.63 (1.29–2.05); p  <  0.001 ], compared to those without pyuria. In a subgroup analysis, the risk of pyuria for ESRD was modified by CKD stages. We investigated the effects of UTI (urinary symptoms and treated by antibiotics) and pyuria without UTI (urine WBC < 50 to ≥ 10/hpf without any episodes of ≥ 50 WBC/hpf or UTI), while both groups were associated with clinical outcomes. In conclusion, CKD stage 3–5 patients with frequent pyuria or UTI episodes have increased risks of renal outcomes.

Kt/V and URR (urea reduction ratio) measurements represent dialysis adequacy. Single-pool Kt/V is theoretically a superior method and is recommended by the Kidney Disease Outcomes Quality Initiative guidelines. However, the prognostic value of URR compared with Kt/V for all-cause mortality is unknown. The effect modifiers and cut-off values of the two parameters have not been compared. We investigated 2615 incident hemodialysis patients with URR of 72% and Kt/V (Daugirdas) of 1.6. The average patient age was 59 years, 50.7% were female, and 1113 (40.2%) died within 10 years. URR and Kt/V were both positively associated with nutrition factors and female sex and negatively associated with body weight and heart failure. In Cox regression mod-els for all-cause mortality, the hazard ratios (HRs) of high URR groups (65–70%, 70–75%, and > 75%) and the URR < 65% group were 0.748 (0.623–0.898), 0.693 (0.578–0.829), and 0.640 (0.519–0.788), respectively. The HRs of high Kt/V groups (Kt/V 1.2–1.4, 1.4–1.7, and > 1.7) and the Kt/V < 1.2 group were 0.711 (0.580–0.873), 0.656 (0.540–0.799), and 0.623 (0.498–0.779), respec-tively. In subgroup analysis, Kt/V was not associated with all-cause mortality in women. The prognostic value of URR for all-cause mortality is as great as that of Kt/V. URR > 70% and Kt/V > 1.4 were associated with a higher survival rate. Kt/V may have weaker prognostic value for women.

A common complication of chronic kidney disease (CKD), anemia can influence glycated hemoglobin (HbA1c) levels. In diabetic patients, anemia occurs earlier and with higher severity over the course of CKD stages. To elucidate the effect of hemoglobin (Hb) on the predictive value of HbA1c, we enrolled 1558 diabetic patients with stages 3-4 CKD, categorized according to baseline Hb and HbA1c quartiles. Linear regression revealed that higher HbA1c correlated significantly with higher Hb in the Hb < 10 g/dL group (β = 0.146, P = 0.004). A fully-adjusted Cox regression model revealed worse clinical outcomes in patients with higher HbA1c quartiles in the Hb ≥ 10 g/dL group. Hazard ratios for end-stage renal disease (ESRD), all-cause mortality, and composite endpoint (cardiovascular events and all-cause mortality) in patients with Hb ≥ 10 g/dL and the highest HbA1c quartile were 1.92 (95% confidence interval [CI], 1.17-3.15), 1.76 (95% CI, 1.02-3.03), and 1.54 (95% CI, 1.03-2.31), respectively. By contrast, HbA1c was not associated with clinical outcomes in the Hb < 10 g/dL group. In conclusion, in stages 3-4 diabetic CKD, higher HbA1c is associated with a higher risk of poor clinical outcomes in patients with Hb ≥ 10 g/dL.

Background/Objectives: Autosomal dominant polycystic kidney disease (ADPKD) is a progressive genetic disorder marked by bilateral renal cysts and extrarenal manifestations, ultimately resulting in renal failure. Emerging research indicates that metformin might influence the intracellular mechanisms of ADPKD, though its clinical significance remains uncertain. Methods: We applied the Taiwan National Health Insurance Database (NHIRD) to investigate the clinical impact of metformin utilization in ADPKD patients in real-world practice. The metformin user group was defined by more than 90 days of usage. To mitigate selection bias, we established a non-user group with a 1:2 ratio, matching for age, sex, and comorbidities by a propensity score matching method. Results: A total of 10,222 ADPKD cases were identified in the NHIRD between 2009 and 2018. After matching, the metformin user group was composed of 778 cases with a mean age of 59.5 ± 13.9 years, and the non-user group of 1546 cases with a mean age of 59.3 ± 14.4 years. The time from the index date to the outcome of ESKD in ADPKD was 5.3 ± 2.2 years in the metformin user group and 5.3 ± 2.3 years in the metformin non-user group, respectively. The metformin user group exhibited a significant reduction in the risk of end-stage kidney disease (ESKD), as indicated in the fully adjusted model (0.75, 95% CI 0.58–0.97, p = 0.03). A decreased risk of major adverse cardiovascular events (MACEs) was noted in metformin users, with an adjusted hazard ratio (HR) of 0.78 (95% CI 0.65–0.95, p = 0.01). Sensitivity analysis showed similar results by excluding late-stage CKD (CKD stage 5 or erythropoietin-stimulating agents use). Conclusions: Metformin usage in real-world practice showed lower hazards of ESKD and MACEs in patients with ADPKD, except for those with advanced CKD.

Evaluating nutritional status is crucial to detecting malnutrition in patients with chronic kidney disease (CKD). The Geriatric Nutritional Risk Index (GNRI) has been associated with overall and cardiovascular mortality in the dialysis population. The aim of this study was to evaluate whether the GNRI is associated with progression to dialysis in patients with moderate to advanced CKD. We enrolled 496 patients with stage 3–5 CKD who had received echocardiographic examinations, and categorized them according to baseline GNRI values calculated using the serum albumin level and body weight. The renal end-point was defined as the commencement of dialysis. During follow-up (mean, 25.2 ± 12.5 months; range, 3.3–50.1 months), 106 (21.4%) of the patients progressed to dialysis. The GNRI was positively correlated with the left ventricular ejection fraction (LVEF) (r = 0.111, p = 0.014), and negatively correlated with the left ventricular mass index (r = −0.116, p = 0.001), left ventricular hypertrophy (r = −0.095, p = 0.035), and LVEF < 50% (r = −0.138, p = 0.002). In multivariable Cox analysis, a low GNRI, female sex, high systolic blood pressure, high fasting glucose, and low estimated glomerular filtration rate were independently associated with progression to dialysis. A low GNRI was independently associated with progression to dialysis in our study cohort. The GNRI may be useful in predicting the risk of adverse renal outcomes in patients with CKD stages 3–5. Additional studies are needed to explore whether an improvement in GNRI delays CKD progression.

Diabetes duration, diabetic retinopathy (DR), and a diagnostic model have been proposed as clinical parameters favoring the presence of diabetic nephropathy (DN) in biopsied patients with diabetic kidney disease. DN, compared with non-diabetic renal disease, had poorer renal outcomes. We tested whether these clinical parameters favoring DN are associated with poorer renal outcomes in non-biopsied patients. In this study, 1330 patients with type 2 diabetes and chronic kidney disease stages 1–4 were included and divided according to diabetes mellitus (DM) duration >8 years, DR, or a diagnostic model for DN. These clinical parameters favoring DN were found in 62–77% of patients and associated with higher levels of proteinuria. In a Cox survival analysis, DR and the diagnostic model favoring DN were associated with an increased risk for end-stage renal disease with adjusted hazard ratios of 1.69 (95% CI: 1.16–2.45, P  = 0.006) and 1.66 (95% CI: 1.05–2.61, P  = 0.029), respectively. DR was associated with an increased risk for rapid renal disease progression. DM >8 years was not associated with renal outcome. Propensity score-matched analyses also showed similar results. In conclusion, DR and the diagnostic model favoring DN were associated with poorer renal outcomes.

Obesity-related nephropathy is associated with renal function progression. However, some studies have associated a high body mass index (BMI) with improved renal outcomes—this is referred to as the obesity paradox for renal outcomes, especially in relation to advanced chronic kidney disease (CKD). Central obesity can explain the obesity paradox in all-cause mortality. However, whether obesity or central obesity is associated with renal outcomes (renal replacement therapy or a 50% decline in the estimated glomerular filtration rate) in patients with advanced CKD remains unclear. Our study included 3605 Asian patients with CKD stages 1–5 divided into six groups according to their BMI (between 15 and 35 kg/m2). Through linear regression, BMI was positively associated with hemoglobin and albumin at CKD stages 4 and 5. In the competing risk Cox regression model, a high BMI (27.5–35 kg/m2) was associated with renal outcomes at CKD stages 1–3, but not stages 4 and 5. A high BMI was associated with renal outcomes in patients with hemoglobin ≥11 g/dL, but not <11 g/dL. A high waist-to-hip ratio was not associated with renal outcomes. We conclude that the CKD stage and anemia may explain the obesity paradox in renal outcomes in patients with CKD.