Erythropoiesis-stimulating agent (ESA) responsiveness has been reported to be associated with increased mortality in hemodialysis (HD) patients. ESA requirement to obtain the same hemoglobin (Hb) ...level is different between HD and peritoneal dialysis (PD) patients. In this study, we investigated the impact of ESA responsiveness on mortality between both HD and PD patients. Prevalent HD and PD patients were selected from the Clinical Research Center registry for end-stage renal disease, a prospective cohort study in Korea. ESA responsiveness was estimated using an erythropoietin resistant index (ERI) (U/kg/week/g/dL). Patients were divided into three groups by tertiles of ERI. ESA responsiveness was also assessed based on a combination of ESA dosage and hemoglobin (Hb) levels. The primary outcome was all-cause mortality. A total of 1,594 HD and 876 PD patients were included. The median ESA dose and ERI were lower in PD patients compared with HD patients (ESA dose: 4000 U/week vs 6000 U/week, respectively. P<0.001, ERI: 7.0 vs 10.4 U/kg/week/g/dl, respectively. P<0.001). The median follow-up period was 40 months. In HD patients, the highest ERI tertile was significantly associated with higher risk for all-cause mortality (HR 1.96, 95% CI, 1.07 to 3.59, P = 0.029). HD patients with high-dose ESA and low Hb levels (ESA hypo-responsiveness) had a significantly higher risk of all-cause mortality (HR 2.24, 95% CI, 1.16 to 4.31, P = 0.016). In PD patients, there was no significant difference in all-cause mortality among the ERI groups (P = 0.247, log-rank test). ESA hypo-responsiveness was not associated with all-cause mortality (HR = 1.75, 95% CI, 0.58 to 5.28, P = 0.319). Our data showed that ESA hypo-responsiveness was associated with an increased risk of all-cause mortality in HD patients. However, in PD patients, ESA hypo-responsiveness was not related to all-cause mortality. These finding suggest the different prognostic value of ESA responsiveness between HD and PD patients.
Serum alkaline phosphatase (ALP) levels have been reported to be associated with all-cause and cardiovascular mortality in peritoneal dialysis (PD) patients. However, it is unclear whether serum ALP ...levels predict infection-related clinical outcomes in PD patients. The aim of this study was to determine the relationships between serum ALP levels, infection-related mortality and hospitalization in PD patients.
PD patients from the Clinical Research Center registry for end-stage renal disease, a multicenter prospective observational cohort study in Korea, were included in the present study. Patients were categorized into three groups by serum ALP tertiles as follows: Tertile 1, ALP <78 U/L; Tertile 2, ALP = 78-155 U/L; Tertile 3, ALP >155 U/L. Tertile 1 was used as the reference category. The primary outcomes were infection-related mortality and hospitalization.
A total of 1,455 PD patients were included. The median follow-up period was 32 months. The most common cause of infection-related mortality and hospitalization was PD-related peritonitis. Multivariate Cox regression analyses showed that patients in the highest tertiles of serum ALP levels were at higher risk of infection-related mortality (HR 2.29, 95% CI, 1.42-5.21, P = 0.008) after adjustment for clinical variables. Higher tertiles of serum ALP levels were associated with higher risk of infection-related hospitalization (Tertile 2: HR 1.56, 95% CI, 1.18-2.19, P = 0.009, tertile 3: HR 1.34, 95% CI, 1.03-2.62, P = 0.031).
Our data showed that elevated serum ALP levels were independently associated with a higher risk of infection-related mortality and hospitalization in PD patients.
Background Renal infarction is a rare condition resulting from an acute disruption of renal blood flow, and the cause and outcome of renal infarction are not well established. Study Design Case ...series. Setting & Participants 438 patients with renal infarction in January 1993 to December 2013 at 9 hospitals in Korea were included. Renal infarction was defined by radiologic findings that included single or multiple wedge-shaped parenchymal perfusion defects in the kidney. Predictor Causes of renal infarction included cardiogenic (n = 244 55.7%), renal artery injury (n = 33 7.5%), hypercoagulable (n = 29 6.6%), and idiopathic (n = 132 30.1%) factors. Outcomes We used recurrence, acute kidney injury (AKI; defined as creatinine level increase ≥ 0.3 mg/dL within 48 hours or an increase to 150% of baseline level within 7 days during the sentinel hospitalization), new-onset estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 (for >3 months after renal infarction in the absence of a history of decreased eGFR), end-stage renal disease (ESRD; receiving hemodialysis or peritoneal dialysis because of irreversible kidney damage), and mortality as outcome metrics. Results Treatment included urokinase (n = 19), heparin (n = 342), warfarin (n = 330), and antiplatelet agents (n = 157). 5% of patients died during the initial hospitalization. During the median 20.0 (range, 1-223) months of follow-up, 2.8% of patients had recurrent infarction, 20.1% of patients developed AKI, 10.9% of patients developed new-onset eGFR < 60 mL/min/1.73 m2 , and 2.1% of patients progressed to ESRD. Limitations This was a retrospective study; it cannot clearly determine the specific causal mechanism for certain patients or provide information about the causes of mortality. 16 patients were excluded from the prognostic analysis. Conclusions Cardiogenic origins were the most important causes of renal infarction. Despite aggressive treatment, renal infarction can lead to AKI, new-onset eGFR < 60 mL/min/1.73 m2 , ESRD, and death.
Studies have found sleeping behaviors, such as sleep duration, to be associated with kidney function and cardiovascular disease risk. However, whether short or long sleep duration is a causative ...factor for kidney function impairment has been rarely studied.
We studied data from participants aged 40-69 years in the UK Biobank prospective cohort, including 25,605 self-reporting short-duration sleep (<6 hours per 24 hours), 404,550 reporting intermediate-duration sleep (6-8 hours), and 35,659 reporting long-duration sleep (≥9 hours) in the clinical analysis. Using logistic regression analysis, we investigated the observational association between the sleep duration group and prevalent CKD stages 3-5, analyzed by logistic regression analysis. We performed Mendelian randomization (MR) analysis involving 321,260 White British individuals using genetic instruments (genetic variants linked with short- or long-duration sleep behavior as instrumental variables). We performed genetic risk score analysis as a one-sample MR and extended the finding with a two-sample MR analysis with CKD outcome information from the independent CKDGen Consortium genome-wide association study meta-analysis.
Short or long sleep duration clinically associated with higher prevalence of CKD compared with intermediate duration. The genetic risk score for short (but not long) sleep was significantly related to CKD (per unit reflecting a two-fold increase in the odds of the phenotype; adjusted odds ratio, 1.80; 95% confidence interval, 1.25 to 2.60). Two-sample MR analysis demonstrated causal effects of short sleep duration on CKD by the inverse variance weighted method, supported by causal estimates from MR-Egger regression.
These findings support an adverse effect of a short sleep duration on kidney function. Clinicians may encourage patients to avoid short-duration sleeping behavior to reduce CKD risk.
Glaucoma shares common risk factors with chronic kidney disease (CKD) but previous cross-sectional studies have demonstrated discrepancies in the risk of glaucoma in CKD patients. This study enrolled ...kidney transplantation recipients (KTRs) (n = 10,955), end stage renal disease (ESRD) patients (n = 10,955) and healthy controls (n = 10,955) from National Health Insurance Service database of the Republic of Korea. A Cox proportional hazard regression model was used to calculate the hazard ratios (HR) for primary open-angle glaucoma (POAG) and primary angle-closure glaucoma (PACG) incidences. The incidence of POAG was higher in ESRD patients (3.36/1,000 person-years, P < 0.0001) and KTRs (3.22 /1,000 person-years, P < 0.0001), than in healthy controls (1.20/1,000 person-years). However, POAG risk showed no significant increase in either ESRD patients (P = 0.07) or KTRs (P = 0.08) when adjusted for the confounding factors. The incidence of PACG was significantly higher in ESRD patients (0.41/1,000 person-years) than in healthy controls (0.14/1,000 person-years, P = 0.008). The PACG incidence was significantly lower in KTRs than in ESRD patients (HR = 0.35, P = 0.015). In conclusion, this nationwide cohort study demonstrated that kidney transplantation can reduce the risk of PACG but not POAG in ESRD patients.
The causal effects of chondroitin, glucosamine, and vitamin/mineral supplement intake on kidney function remain unknown, despite being commonly used. We conducted a two-sample summary-level Mendelian ...randomization (MR) analysis to test for causal associations between regular dietary supplement intake and kidney function. Genetic instruments for chondroitin, glucosamine, and vitamin/mineral supplement intake were obtained from a genome-wide association study of European ancestry. Summary statistics for the log-transformed estimated glomerular filtration rate (log-eGFR) were provided by the CKDGen consortium. The multiplicative random-effects inverse-variance weighted method showed that genetically predicted chondroitin and glucosamine intake was causally associated with a lower eGFR (chondroitin, eGFR change beta = -0.113%, standard error (SE) = 0.03%,
-value = 2 × 10
; glucosamine, eGFR change beta = -0.240%, SE = 0.035%,
-value = 6 × 10
). However, a genetically predicted vitamin/mineral supplement intake was associated with a higher eGFR (eGFR change beta = 1.426%, SE = 0.136%,
-value = 1 × 10
). Validation analyses and pleiotropy-robust MR results for chondroitin and vitamin/mineral supplement intake supported the main results. Our MR study suggests a potential causal effect of chondroitin and glucosamine intake on kidney function. Therefore, clinicians should carefully monitor their long-term effects.
The roles of neutrophils in renal inflammation are currently unclear. On examining these cells in the unilateral ureteral obstruction murine model of chronic kidney disease, we found that the injured ...kidney bore a large and rapidly expanding population of neutrophils that expressed the eosinophil marker Siglec-F. We first verified that these cells were neutrophils. Siglec-F+ neutrophils were recently detected in several studies in other disease contexts. We then showed that a) these cells were derived from conventional neutrophils in the renal vasculature by TGF-β1 and GM-CSF; b) they differed from their parent cells by more frequent hypersegmentation, higher expression of profibrotic inflammatory cytokines, and notably, expression of collagen 1; and c) their depletion reduced collagen deposition and disease progression, but adoptive transfer increased renal fibrosis. These findings have thus unveiled a subtype of neutrophils that participate in renal fibrosis and a potentially new therapeutic target in chronic kidney disease.
Previous scoring models such as the Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) and the Sequential Organ Failure Assessment (SOFA) scoring systems do not adequately ...predict mortality of patients undergoing continuous renal replacement therapy (CRRT) for severe acute kidney injury. Accordingly, the present study applies machine learning algorithms to improve prediction accuracy for this patient subset.
We randomly divided a total of 1571 adult patients who started CRRT for acute kidney injury into training (70%, n = 1094) and test (30%, n = 477) sets. The primary output consisted of the probability of mortality during admission to the intensive care unit (ICU) or hospital. We compared the area under the receiver operating characteristic curves (AUCs) of several machine learning algorithms with that of the APACHE II, SOFA, and the new abbreviated mortality scoring system for acute kidney injury with CRRT (MOSAIC model) results.
For the ICU mortality, the random forest model showed the highest AUC (0.784 0.744-0.825), and the artificial neural network and extreme gradient boost models demonstrated the next best results (0.776 0.735-0.818). The AUC of the random forest model was higher than 0.611 (0.583-0.640), 0.677 (0.651-0.703), and 0.722 (0.677-0.767), as achieved by APACHE II, SOFA, and MOSAIC, respectively. The machine learning models also predicted in-hospital mortality better than APACHE II, SOFA, and MOSAIC.
Machine learning algorithms increase the accuracy of mortality prediction for patients undergoing CRRT for acute kidney injury compared with previous scoring models.
Abstract
Hypotension after starting continuous renal replacement therapy (CRRT) is associated with worse outcomes compared with normotension, but it is difficult to predict because several factors ...have interactive and complex effects on the risk. The present study applied machine learning algorithms to develop models to predict hypotension after initiating CRRT. Among 2349 adult patients who started CRRT due to acute kidney injury, 70% and 30% were randomly assigned into the training and testing sets, respectively. Hypotension was defined as a reduction in mean arterial pressure (MAP) ≥ 20 mmHg from the initial value within 6 h. The area under the receiver operating characteristic curves (AUROCs) in machine learning models, such as support vector machine (SVM), deep neural network (DNN), light gradient boosting machine (LGBM), and extreme gradient boosting machine (XGB) were compared with those in disease-severity scores such as the Sequential Organ Failure Assessment and Acute Physiology and Chronic Health Evaluation II. The XGB model showed the highest AUROC (0.828 0.796–0.861), and the DNN and LGBM models followed with AUROCs of 0.822 (0.789–0.856) and 0.813 (0.780–0.847), respectively; all machine learning AUROC values were higher than those obtained from disease-severity scores (AUROCs < 0.6). Although other definitions of hypotension were used such as a reduction of MAP ≥ 30 mmHg or a reduction occurring within 1 h, the AUROCs of machine learning models were higher than those of disease-severity scores. Machine learning models successfully predict hypotension after starting CRRT and can serve as the basis of systems to predict hypotension before starting CRRT.
Most persons with confirmed coronavirus disease (COVID-19) have no or mild symptoms. During the COVID-19 pandemic, communities need efficient methods to monitor asymptomatic patients to reduce ...transmission. We describe the structure and operating protocols of a community treatment center (CTC) run by Seoul National University Hospital (SNUH) in South Korea. SNUH converted an existing facility into a CTC to isolate patients who had confirmed COVID-19 but mild or no symptoms. Patients reported self-measured vital signs and symptoms twice a day by using a smartphone application. Medical staff in a remote monitoring center at SNUH reviewed patient vital signs and provided video consultation to patients twice daily. The CTC required few medical staff to perform medical tests, monitor patients, and respond to emergencies. During March 5-26, 2020, we admitted and treated 113 patients at this center. CTCs could be an alternative to hospital admission for isolating patients and preventing community transmission.
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