Serum uromodulin and progression of kidney disease in patients with chronic kidney disease

Abstract Background Uromodulin is specifically synthesized and secreted by kidney tubular epithelial cells. Studies on the association of serum uromodulin and outcomes of chronic kidney disease (CKD) are lacking. This study aimed to evaluate whether serum uromodulin was associated with outcomes of patients with CKD. Methods We measured serum uromodulin concentrations by ELISA in 2652 CKD patients from the Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE) and investigated the association of serum uromodulin with outcomes of CKD patients, including end-stage kidney disease (ESKD) receiving kidney replacement therapy, cardiovascular events and mortality by Cox proportional hazards regression model. Results A total of 2652 CKD patients were enrolled in this study, with an age of 48.7 ± 13.8 years and the baseline eGFR of 49.6 ± 29.4 mL/min/1.73 m2, of whom 58.4% were male. The median level of urinary albumin/creatinine ratio and serum uromodulin was 473.7 mg/g (IQR 134.1–1046.6 mg/g) and 77.2 ng/mL (IQR 48.3–125.9 ng/mL), respectively. Altogether, 404 ESKD, 189 cardiovascular events, and 69 deaths occurred during the median follow-up of 53.6 (IQR 44.0–64.0) months. Lower levels of serum uromodulin were independently associated with higher risk of incident ESKD after adjusting for traditional cardiovascular risk factors, with the hazard ratios (HRs) of 3.23 (95% confidence intervals [CIs] 2.15–4.85) for the middle tertile and 7.47 (95% CI 5.06–11.03) for the bottom tertile, compared with top tertile and 0.31 (95% CI 0.25–0.38) per every standard deviation increase. After further adjustment for the baseline eGFR, the association was greatly attenuated, but still significant, with HRs of 1.92 (95% CI 1.26–2.90) for the bottom tertile compared with top tertile and 0.69 (95% CI 0.55–0.86) per every standard deviation increase. Conclusions Serum uromodulin is independently associated with an increased risk of incident ESKD in CKD patients.https://deepblue.lib.umich.edu/bitstream/2027.42/146520/1/12967_2018_Article_1693.pd

Ocular fundus pathology and chronic kidney disease in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Previous study indicated a high prevalence of ocular fundus pathology among patients with chronic kidney disease (CKD), while the relationship between them has never been explored in a Chinese Population.</p> <p>Methods</p> <p>This cross-sectional study included 9 670 participants enrolled in a medical screening program. Ocular fundus examination was performed by ophthalmologists using ophthalmoscopes. The presence of eGFR less than 60 mL/min/1.73 m²and/or proteinuria was defined as CKD.</p> <p>Results</p> <p>Compared to participants without CKD, participants with CKD had higher prevalence of retinopathy (28.5% vs. 16.3%, P < 0.001), glaucoma suspect (3.1% vs. 1.8%, P = 0.004), age-related macular degeneration (1.7% vs. 0.9%, P = 0.01) and overall eye pathology (32.0% vs. 19.4%, P < 0.001). After adjusting for potential confounders, the odds ratio of proteinuria for overall eye pathology and retinopathy was 1.29 (95% confidence interval [CI] 1.07-1.55) and 1.37 (95% CI 1.12-1.67), respectively. The results were robust after excluding participants with hypertension or with diabetes.</p> <p>Conclusions</p> <p>Ocular fundus pathology is common among Chinese patients with CKD. Regular eye exam among persons with proteinuria is warranted.</p

Hemophagocytic lymphohistiocytosis followed by an episode of peritoneal dialysis associated peritonitis: a case report

Abstract Background Hemophagocytic lymphohistiocytosis (HLH) is characterized by excessive activation of the immune system due to infection, autoimmune diseases, or malignancy. As an aggressive and life-threatening clinical syndrome, HLH secondary to peritoneal dialysis associated peritonitis (PDAP) has never been reported. Case presentation A 34-year-old female peritoneal dialysis (PD) patient was hospitalized for fever, progressively multi-organ damage (including cytopenias, abnormalities of coagulation and liver enzyme) after an episode of organism-specific peritonitis. She was refractory to the broad-spectrum antimicrobial agent. Further tests found hemophagocytosis on the bone marrow examination, and extremely high level of sIL2-R and impaired activity of NK cell. The diagnosis of HLH was eventually established. After HLH-specific therapy, this patient recovered and discharged. Conclusions The present case suggests that clinicians should to be aware of HLH in those patients apparently suspected with refractory or relapsing peritonitis, especially those accompanied with persist fever, hyperferritinemia, and cytopenias. HLH-specific therapy and supportive care should be applied without delay

Minimal change disease associated with anti-PD1 immunotherapy: a case report

Abstract Background Oncologic immunotherapy is a form of therapy intended to reactivate the immune response to tumor cells using agents that modulate immune checkpoints, such as programmed cell death protein 1 and its ligand (PD-1/PD-L), and cytotoxic T-lymphocyte-associated antigen 4. Along with activation of the immune system to tumors, immune-mediated kidney side effects have been reported, most of which are cases of interstitial nephritis. Glomerular disease, however, appears rare. Case presentation Herein, we describe a patient with nephrotic syndrome related to treatment with an anti-PD1 antibody for Hodgkin lymphoma. Following the third dose of anti-PD1 antibody, the patient developed massive proteinuria and nephrotic syndrome. Kidney biopsy showed diffuse podocyte foot process effacement upon electron microscopy, which was consistent with minimal change disease. Corticosteroid treatment yielded full and rapid remission of nephrotic syndrome in 1 month. Conclusion The present case suggests an association between anti-PD1 therapeutic immune activation and the development of nephrotic syndrome. Given the increasing prevalence of oncologic immunotherapy, patients should be routinely monitored for kidney side effects associated with these agents

Clustering of four major CVD risk factors and lifestyle risk factors.^*

<p>CVD =  cardiovascular disease; OR = odds ratio; CI = confidence interval; NSAIDS = non-steroidal anti-inflammatory drugs; DASH = dietary approaches to stop hypertension.</p>*<p>The data are presented as odds ratios (95% confidence intervals); all p<0.001.</p>†<p>The variables in the fully adjusted models included age, sex, family history of premature diseases and all of the variables in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0066780#pone-0066780-t002" target="_blank">Table 2</a>.</p

Relationship between lifestyles and socioeconomic status.^*

*<p>The data are presented as weighted prevalence rates (95% confidence intervals).</p

Distribution of four major CVD risk factors in the total sample.

<p>Grey represents the population with no defined CVD risk factors, and the other four colors represent the population with four different CVD risk factors. The numbers represent the number of individuals in the population with defined CVD risk factors in the respective regions.</p

Prevalence of CVD risk factor clustering by age and gender.

<p>The prevalence (and 95% confidence intervals) of clustering of CVD risk factors was calculated for various age groups and for both sexes (male or female). All prevalence rates were adjusted for synthesized weights.</p

Association of left ventricular hypertrophy and functional impairment with cardiovascular outcomes and mortality among patients with chronic kidney disease, results from the C‐STRIDE study

AimLeft ventricular hypertrophy and impaired systolic and diastolic function are commonly seen in patients with chronic kidney disease (CKD), but relationships between the disorders and cardiovascular outcomes are not well established among the patients.MethodsTotally, 2020 patients with CKD Stages 1–4 were used in the analysis. Left ventricular hypertrophy was defined by left ventricular mass index >49.2 g/m2.7 in men and > 46.7 g/m2.7 in women. Incident heart failure, non‐heart failure cardiovascular events, and all‐cause mortality were recorded longitudinally. Cox proportional hazards regression model was used to evaluate the association between the echo parameters and the outcomes, with death treated as the competing risk event for the cardiovascular events.ResultsAfter a median follow‐up of 4.5 years, 53 heart failure, 76 non‐heart failure cardiovascular events and 82 deaths occurred. No overall association was found between left ventricular hypertrophy and subsequent heart failure, but the relationship was significant among patients with no diabetes with the multivariable adjusted hazard ratio of 3.66 (95% confidence interval: 1.42–9.46). Ejection fraction<55% was associated with both heart failure and non‐heart failure cardiovascular events with hazard ratios of 3.16 (1.28–7.77) and 2.76 (1.08–7.04), respectively. E/A ratio ≤ 0.75 was associated with non‐heart failure cardiovascular events [hazard ratio = 2.03 (1.09–3.80)], compared with E/A ratio of 0.76–1.49.ConclusionAssociations of reduced left ventricular ejection fraction with both heart failure and non‐heart failure cardiovascular events and of impaired left ventricular diastolic function with non‐heart failure cardiovascular events were validated in a Chinese cohort of CKD.SUMMARY AT A GLANCEThis is a multi‐centre cohort from China on the association of left ventricular hypertrophy and functional impairment with cardiovascular outcomes and mortality in CKD patients. Ejection fraction <55% was associated with both heart failure and non‐heart failure cardiovascular events.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/172045/1/nep14009.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/172045/2/nep14009_am.pd

ESKD Risk Prediction Model in a Multicenter Chronic Kidney Disease Cohort in China: A Derivation, Validation, and Comparison Study

Background and objectives: In light of the growing burden of chronic kidney disease (CKD), it is of particular importance to create disease prediction models that can assist healthcare providers in identifying cases of CKD individual risk and integrate risk-based care for disease progress management. The objective of this study was to develop and validate a new pragmatic end-stage kidney disease (ESKD) risk prediction utilizing the Cox proportional hazards model (Cox) and machine learning (ML). Design, setting, participants, and measurements: The Chinese Cohort Study of Chronic Kidney Disease (C-STRIDE), a multicenter CKD cohort in China, was employed as the model’s training and testing datasets, with a split ratio of 7:3. A cohort from Peking University First Hospital (PKUFH cohort) served as the external validation dataset. The participants’ laboratory tests in those cohorts were conducted at PKUFH. We included individuals with CKD stages 1~4 at baseline. The incidence of kidney replacement therapy (KRT) was defined as the outcome. We constructed the Peking University-CKD (PKU-CKD) risk prediction model employing the Cox and ML methods, which include extreme gradient boosting (XGBoost) and survival support vector machine (SSVM). These models discriminate metrics by applying Harrell’s concordance index (Harrell’s C-index) and Uno’s concordance (Uno’s C). The calibration performance was measured by the Brier score and plots. Results: Of the 3216 C-STRIDE and 342 PKUFH participants, 411 (12.8%) and 25 (7.3%) experienced KRT with mean follow-up periods of 4.45 and 3.37 years, respectively. The features included in the PKU-CKD model were age, gender, estimated glomerular filtration rate (eGFR), urinary albumin–creatinine ratio (UACR), albumin, hemoglobin, medical history of type 2 diabetes mellitus (T2DM), and hypertension. In the test dataset, the values of the Cox model for Harrell’s C-index, Uno’s C-index, and Brier score were 0.834, 0.833, and 0.065, respectively. The XGBoost algorithm values for these metrics were 0.826, 0.825, and 0.066, respectively. The SSVM model yielded values of 0.748, 0.747, and 0.070, respectively, for the above parameters. The comparative analysis revealed no significant difference between XGBoost and Cox, in terms of Harrell’s C, Uno’s C, and the Brier score (p = 0.186, 0.213, and 0.41, respectively) in the test dataset. The SSVM model was significantly inferior to the previous two models (p C, Uno’s C, and the Brier score (p = 0.003, 0.027, and 0.032, respectively), while Cox and SSVM were almost identical concerning these three parameters (p = 0.102, 0.092, and 0.048, respectively). Conclusions: We developed and validated a new ESKD risk prediction model for patients with CKD, employing commonly measured indicators in clinical practice, and its overall performance was satisfactory. The conventional Cox regression and certain ML models exhibited equal accuracy in predicting the course of CKD