Neural Network Analysis to Predict Mortality in End-Stage Renal Disease: Application to United States Renal Data System

Jacob, Adam N.; Khuder, Sadik A.; Malhotra, Nathan; Sodeman, Thomas; Gold, Jeffrey P.; Malhotra, Deepak; Shapiro, Joseph I.

doi:10.1159/000315884

Cited by 7 publications

(5 citation statements)

References 34 publications

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“…Diabetic nephropathy (DN) is the most common cause of chronic kidney disease and end stage renal disease, as about 30% to 35% of dialysis patients have diabetes (2). Diabetes is also the most common cause of renal replacement therapy requirement, in the United States (3). One of the common and serious complications of diabetes is nephropathy, defined by the development of proteinuria and classified based on the severity of proteinuria as microalbuminuria and macroalbuminuria.…”

Section: Introductionmentioning

confidence: 99%

Impact of vitamin D therapy on decreasing of proteinuria in type 2 diabetic patients

Momeni¹,

Mirhosseini²,

Kabiri³

et al. 2016

J Nephropathol

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BackgroundVitamin D (Vit D) deficiency is a common disorder in diabetic patients and may be a risk factor for ischemic heart disease and exacerbation of diabetic nephropathy(DN). ObjectivesThe aim of this study was to evaluate the effect of Vit D3 therapy on protein uriain type 2 diabetic patients with deficient or insufficient serum Vit D. Patients and MethodsIn a double blind clinical trial, 60 type 2 diabetic patients with proteinuria greater than 150 mg/day who had Vit D deficiency or insufficiency were randomly enrolled in two equal groups. Pearl of Vit D as 50 000 IU/week and placebo (1 tablet per week) were prescribed in patients of case and control groups respectively for 8 weeks. At the beginning and 2 months later, 24 hours urine protein was checked in all patients. ResultsThere is no difference between serums Vit D level in case and control group at the beginning of the study, however at the end of the study serum Vit D level was significantly higher in the case group. There is no difference in proteinuria between case and control group at the beginning and the end of the study, while a significant difference between the changes of proteinuria before and after the study was seen in two groups (P = 0.028). ConclusionsVit D deficiency may exacerbate protein uric and DN, hence correction of Vit D deficiency may decrease proteinuria in diabetic patients with nephropathy.

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Section: Introductionmentioning

confidence: 99%

Impact of vitamin D therapy on decreasing of proteinuria in type 2 diabetic patients

Momeni¹,

Mirhosseini²,

Kabiri³

et al. 2016

J Nephropathol

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show abstract

“…Diabetic nephropathy is the most common cause of chronic kidney disease and end stage renal disease, about 30% to 35% of dialysis patients have diabetes [11]. Diabetes is also the most common cause of renal replacement therapy requirement, in the United States [12]. Nephropathy is the serious complication of diabetes, defined by the development of proteinuria.…”

Section: Discussionmentioning

confidence: 99%

Effect of parenteral vitamin D (D3) on albuminuria in T2DM patients

et al. 2017

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Background: Vitamin D deficiency is a common disorder in diabetic patients and may be a risk factor for progression of diabetic nephropathy. The aim of our study was to assess the effects of large dose of parentral Vitamin D on 24 hours albuminuria in T2DM patients. This is a first study of its kind, where we used single large dose parental vitamin D. Methods: This prospective single center study included 50 vitamin D deficient [25(OH) D <50 nmol/l] T 2 DM patients with an adequate glycemic control (HbA 1c < 7.0%). Without any changes in anti-hyperglycemic or antihypertensive drugs, these patients were given a single high dose (600000 IU) of parenteral Vitamin D 3. Then the changes in Vitamin D levels and 24 hours albuminuria were seen on follow up at 3 months. Results: Vitamin D 3 supplementation improved 24 hrs albuminuria. In this study twenty-four hour urinary albumin excretion decreased from 200.4 ± 103.3 to 198.4 ± 105.0 mg/24 hrs (p value 0.015). In males it changed from 212.1 ± 95.4 to 209.6 ± 96.9 (p value 0.046) and in females it changed from 188.6 ± 111.3 to 186.8 ± 112.9. (P value 0.041) .There was a negative association of albuminuria with Vit D levels in our study with p value =0.001 at 3 months of follow up. Conclusion: Vitamin D 3 supplementation significantly reduces 24 hour urinary albumin excretion in T2DM patients with Vitamin D 3 deficiency.

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“…The authors described a feed-forward NN with two inputs, one output, and a hidden layer containing four neurons. A powerful tool was created to predict mortality with high accuracy [15].…”

Section: Biomed Research Internationalmentioning

confidence: 99%

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review

Burlacu

Iftene

Jugrin

et al. 2020

BioMed Research International

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Background. The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used? Methods. We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively. We identified 43 trials in the first group, 8 in the second, and 18 in the third. Then, studies were classified according to the type of algorithm. Results. AI and HD trials covered: (a) dialysis service management, (b) dialysis procedure, (c) anemia management, (d) hormonal/dietary issues, and (e) arteriovenous fistula assessment. PD studies were divided into (a) peritoneal technique issues, (b) infections, and (c) cardiovascular event prediction. AI in transplantation studies were allocated into (a) management systems (ML used as pretransplant organ-matching tools), (b) predicting graft rejection, (c) tacrolimus therapy modulation, and (d) dietary issues. Conclusions. Although guidelines are reluctant to recommend AI implementation in daily practice, there is plenty of evidence that AI/ML algorithms can predict better than nephrologists: volumes, Kt/V, and hypotension or cardiovascular events during dialysis. Altogether, these trials report a robust impact of AI/ML on quality of life and survival in G5D/T patients. In the coming years, one would probably witness the emergence of AI/ML devices that facilitate the management of dialysis patients, thus increasing the quality of life and survival.

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Neural Network Analysis to Predict Mortality in End-Stage Renal Disease: Application to United States Renal Data System

Cited by 7 publications

References 34 publications

Impact of vitamin D therapy on decreasing of proteinuria in type 2 diabetic patients

Impact of vitamin D therapy on decreasing of proteinuria in type 2 diabetic patients

Effect of parenteral vitamin D (D3) on albuminuria in T2DM patients

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review

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