Reported cases of end-stage kidney disease—United States, 2000–2019

Burrows, Nilka Ríos; Koyama, Alain; Pavkov, Meda E.

doi:10.1111/ajt.16657

Cited by 10 publications

(4 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Diabetes and hypertension are the most common causes of chronic kidney disease (CKD) and ESRD worldwide. Although the majority of patients undergoing KT do not have primary urologic pathologies, poor bladder capacity (< 100 mL) and compliance (< 10 mL/cmH 2 O) can be found in 14-34% and up to 32% of ERSD patients, respectively, and are directly associated with length of anuria [12][13][14][15][16][17]. Historically, urologists have explored the concept of bladder rehabilitation through bladder cycling, in which continuous bladder irrigation is up-titrated over several days [18].…”

Section: Defunctionalized Bladders and Bladder Cyclingmentioning

confidence: 99%

Urodynamics in the Transplant Population

Lee,

Van Kuiken

2024

Curr Bladder Dysfunct Rep

View full text Add to dashboard Cite

Purpose of Review Urodynamic testing (UDS) is a valuable tool for understanding the safety of the lower urinary tract (LUT). The goal of this review is to provide evidence-based indications for use of UDS in both the pre-and post-kidney transplant (KT) settings. Recent Findings Pre-transplant bladder cycling with UDS for anuric or oliguric patients is no longer recommended. Instead, UDS aids in identifying LUT anomalies that may require optimization prior to transplant, especially in patients with known urologic etiologies of end-stage renal disease (ERSD). In pre-KT patients with recurrent urinary tract infections (UTIs) or prior urologic/pelvic interventions, UDS should be used judiciously when the etiology of LUT dysfunction is unclear. In the post-transplant setting, urologists are often consulted for LUT symptoms (LUTS), hydronephrosis, urinary retention, declining renal function, and most commonly, recurrent UTI. Again, UDS should not be routinely performed first line, but as an adjunct to distinguish similarly presenting LUT etiologies such as bladder outlet obstruction (BOO) and bladder dysfunction. Summary UDS remains the gold standard for characterizing the LUT, and when utilized appropriately, can identify factors promoting graft and patient survival after KT.

show abstract

Section: Defunctionalized Bladders and Bladder Cyclingmentioning

confidence: 99%

Urodynamics in the Transplant Population

Lee,

Van Kuiken

2024

Curr Bladder Dysfunct Rep

View full text Add to dashboard Cite

show abstract

“…Chronic kidney disease (CKD) is a worldwide public health problem. The prevalence of CKD and its most advanced stage, end-stage renal disease (ESRD), continues to increase [1]. Irrespective of the initial cause, CKD is a progressive disease.…”

Section: Introductionmentioning

confidence: 99%

SDS Electrophoresis on Gradient Polyacrylamide Gels as a Semiquantitative Tool for the Evaluation of Proteinuria

et al. 2023

View full text Add to dashboard Cite

Proteinuria is an important sign of kidney diseases. Different protein patterns in urine associated with glomerular, tubular and overload proteinuria may be differentiated using the immunochemical detection of indicator proteins or via urinary proteins electrophoresis. Our aim was to characterize sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS-PAGE) using commercially available 4–20% gradient gels as a method to detect and differentiate proteinuria. Our laboratory-based study used excess urine samples collected for routine diagnostic purposes from adult patients of a tertiary-care hospital, including patients with albumin/creatinine < 30 mg/g and patients with dipstick proteinuria. The limit of albumin detection was estimated to be 3 mg/L. In 93 samples with albumin/creatinine < 30 mg/g, an albumin fraction was detected in 87% of samples with a minimum albumin concentration of 2.11 mg/L. The separation of 300 urine samples of patients with proteinuria revealed distinct protein patterns differentiated using the molecular weights of the detected proteins: glomerular (albumin and higher molecular weights) and two types of tubular proteinuria (“upper” ≥20 kDa and “lower” with lower molecular weights). These patterns were associated with different values of the glomerular filtration rate (median 66, 71 and 31 mL/min/1.72 m2, respectively, p = 0.004) and different proportions of multiple myeloma and nephrological diagnoses. As confirmed using tandem mass spectrometry and western blot, the SDS-PAGE protein fractions contained indicator proteins including immunoglobulin G, transferrin (glomerular proteinuria), α1-microglobulin, retinol-binding protein, neutrophil gelatinase-associated lipocalin, cystatin C, and β2-microglobulin (tubular), immunoglobulin light chain, myoglobin, and lysozyme (overflow). SDS-PAGE separation of urine proteins on commercially available 4–20% gradient gels is a reliable technique to diagnose proteinuria and differentiate between its main clinically relevant types.

show abstract

“…According to a 2020 US Renal Data System report, Taiwan ranks among the top five countries globally in terms of the incidence rate of ESRD per million population. ESRD is a condition in which a person’s renal function declines to < 15% of normal renal function [ 1 ]. Patients with ESRD experience the symptoms of uremia, including loss of appetite, nausea, vomiting, itchy skin, facial and limb edema, and foul breath [ 2 , 3 ].…”

Section: Introductionmentioning

confidence: 99%

Application of deep learning to predict the low serum albumin in new hemodialysis patients

Yang

Chen

et al. 2023

Nutr Metab (Lond)

View full text Add to dashboard Cite

Background Serum albumin level is a crucial nutritional indicator for patients on dialysis. Approximately one-third of patients on hemodialysis (HD) have protein malnutrition. Therefore, the serum albumin level of patients on HD is strongly correlated with mortality. Methods In study, the data sets were obtained from the longitudinal electronic health records of the largest HD center in Taiwan from July 2011 to December 2015, included 1,567 new patients on HD who met the inclusion criteria. Multivariate logistic regression was performed to evaluate the association of clinical factors with low serum albumin, and the grasshopper optimization algorithm (GOA) was used for feature selection. The quantile g-computation method was used to calculate the weight ratio of each factor. Machine learning and deep learning (DL) methods were used to predict the low serum albumin. The area under the curve (AUC) and accuracy were calculated to determine the model performance. Results Age, gender, hypertension, hemoglobin, iron, ferritin, sodium, potassium, calcium, creatinine, alkaline phosphatase, and triglyceride levels were significantly associated with low serum albumin. The AUC and accuracy of the GOA quantile g-computation weight model combined with the Bi-LSTM method were 98% and 95%, respectively. Conclusion The GOA method was able to rapidly identify the optimal combination of factors associated with serum albumin in patients on HD, and the quantile g-computation with DL methods could determine the most effective GOA quantile g-computation weight prediction model. The serum albumin status of patients on HD can be predicted by the proposed model and accordingly provide patients with better a prognostic care and treatment.

show abstract

Reported cases of end-stage kidney disease—United States, 2000–2019

Cited by 10 publications

References 5 publications

Urodynamics in the Transplant Population

Urodynamics in the Transplant Population

SDS Electrophoresis on Gradient Polyacrylamide Gels as a Semiquantitative Tool for the Evaluation of Proteinuria

Application of deep learning to predict the low serum albumin in new hemodialysis patients

Contact Info

Product

Resources

About