The effects of lowering LDL cholesterol with simvastatin plus ezetimibe in patients with chronic kidney disease (Study of Heart and Renal Protection): a randomised placebo-controlled trial

BACKGROUND: Lowering LDL cholesterol with statin regimens reduces the risk of myocardial infarction, ischaemic stroke, and the need for coronary revascularisation in people without kidney disease, but its effects in people with moderate-to-severe kidney disease are uncertain. The SHARP trial aimed to assess the efficacy and safety of the combination of simvastatin plus ezetimibe in such patients. METHODS: This randomised double-blind trial included 9270 patients with chronic kidney disease (3023 on dialysis and 6247 not) with no known history of myocardial infarction or coronary revascularisation. Patients were randomly assigned to simvastatin 20 mg plus ezetimibe 10 mg daily versus matching placebo. The key prespecified outcome was first major atherosclerotic event (non-fatal myocardial infarction or coronary death, non-haemorrhagic stroke, or any arterial revascularisation procedure). All analyses were by intention to treat. This trial is registered at ClinicalTrials.gov, NCT00125593, and ISRCTN54137607. FINDINGS: 4650 patients were assigned to receive simvastatin plus ezetimibe and 4620 to placebo. Allocation to simvastatin plus ezetimibe yielded an average LDL cholesterol difference of 0·85 mmol/L (SE 0·02; with about two-thirds compliance) during a median follow-up of 4·9 years and produced a 17% proportional reduction in major atherosclerotic events (526 [11·3%] simvastatin plus ezetimibe vs 619 [13·4%] placebo; rate ratio [RR] 0·83, 95% CI 0·74-0·94; log-rank p=0·0021). Non-significantly fewer patients allocated to simvastatin plus ezetimibe had a non-fatal myocardial infarction or died from coronary heart disease (213 [4·6%] vs 230 [5·0%]; RR 0·92, 95% CI 0·76-1·11; p=0·37) and there were significant reductions in non-haemorrhagic stroke (131 [2·8%] vs 174 [3·8%]; RR 0·75, 95% CI 0·60-0·94; p=0·01) and arterial revascularisation procedures (284 [6·1%] vs 352 [7·6%]; RR 0·79, 95% CI 0·68-0·93; p=0·0036). After weighting for subgroup-specific reductions in LDL cholesterol, there was no good evidence that the proportional effects on major atherosclerotic events differed from the summary rate ratio in any subgroup examined, and, in particular, they were similar in patients on dialysis and those who were not. The excess risk of myopathy was only two per 10,000 patients per year of treatment with this combination (9 [0·2%] vs 5 [0·1%]). There was no evidence of excess risks of hepatitis (21 [0·5%] vs 18 [0·4%]), gallstones (106 [2·3%] vs 106 [2·3%]), or cancer (438 [9·4%] vs 439 [9·5%], p=0·89) and there was no significant excess of death from any non-vascular cause (668 [14·4%] vs 612 [13·2%], p=0·13). INTERPRETATION: Reduction of LDL cholesterol with simvastatin 20 mg plus ezetimibe 10 mg daily safely reduced the incidence of major atherosclerotic events in a wide range of patients with advanced chronic kidney disease. FUNDING: Merck/Schering-Plough Pharmaceuticals; Australian National Health and Medical Research Council; British Heart Foundation; UK Medical Research Council. Copyright © 2011 Elsevier Ltd. All rights reserved

Use of Aspirin Associates with Longer Primary Patency of Hemodialysis Grafts

Extended-release dipyridamole plus low-dose aspirin (ERDP/ASA) prolongs primary unassisted graft patency of newly created hemodialysis arteriovenous grafts, but the individual contributions of each component are unknown. Here, we analyzed whether use of aspirin at baseline associated with primary unassisted graft patency among participants in a randomized trial that compared ERDP/ASA and placebo in newly created grafts. We used Cox proportional hazards regression, adjusting for prespecified baseline comorbidities and covariates. Of all participants, 43% reported use of aspirin at baseline; of these, 82% remained on nonstudy aspirin (i.e., excluding ERDP/ASA) at 1 year. After 1 year of follow-up, the incidence of primary unassisted patency among participants using aspirin at baseline was 30% (95% CI: 24 to 35%) and among those not using aspirin was 23% (95% CI: 18 to 27%). Use of aspirin at baseline associated with a dose-dependent prolongation of primary unassisted graft patency that approached statistical significance (adjusted HR, 0.83; 95% CI: 0.68 to 1.01; P=0.06). Use of aspirin at baseline did not associate with prolongation of cumulative graft patency or participant survival. In conclusion, use of aspirin associates with a trend toward longer primary unassisted patency of newly placed hemodialysis grafts similar to that observed for ERDP/ASA. Copyright © 2011 by the American Society of Nephrolog

Sulodexide fails to demonstrate renoprotection in overt type 2 diabetic nephropathy

Sulodexide, a mixture of naturally occurring glycosaminoglycan polysaccharide components, has been reported to reduce albuminuria in patients with diabetes, but it is unknown whether it is renoprotective. This study reports the results from the randomized, double-blind, placebo-controlled, sulodexide macroalbuminuria (Sun-MACRO) trial, which evaluated the renoprotective effects of sulodexide in patients with type 2 diabetes, renal impairment, and significant proteinuria (\u3e900 mg/d) already receiving maximal therapy with angiotensin II receptor blockers. The primary end point was a composite of a doubling of baseline serum creatinine, development of ESRD, or serum creatinine ≥6.0 mg/dl. We planned to enroll 2240 patients over approximately 24 months but terminated the study after enrolling 1248 patients. After 1029 person-years of follow-up, we did not detect any significant differences between sulodexide and placebo; the primary composite end point occurred in 26 and 30 patients in the sulodexide and placebo groups, respectively. Side effect profiles were similar for both groups. In conclusion, these data do not suggest a renoprotective benefit of sulodexide in patients with type 2 diabetes, renal impairment, and macroalbuminuria

How to overcome barriers and establish a successful home HD program.

Home hemodialysis (HD) is an underused dialysis modality in the United States, even though it provides an efficient and probably cost-effective way to provide more frequent or longer dialysis. With the advent of newer home HD systems that are easier for patients to learn, use, and maintain, patient and provider interest in home HD is increasing. Although barriers for providers are similar to those for peritoneal dialysis, home HD requires more extensive patient training, nursing education, and infrastructure support in order to maintain a successful program. In addition, because many physicians and patients do not have experience with home HD, reluctance to start home HD programs is widespread. This in-depth review describes barriers to home HD, focusing on patients, individual physicians and practices, and dialysis facilities, and offers suggestions for how to overcome these barriers and establish a successful home HD program

Association of factor V gene polymorphism with arteriovenous graft failure

BACKGROUND: Dialysis grafts fail due to recurrent stenosis and thrombosis. Vasoactive and prothrombotic substances affecting intimal hyperplasia or thrombosis may modify graft outcomes. STUDY DESIGN: Genetic polymorphisms association study of patients enrolled in a multicenter randomized clinical trial. SETTING & PARTICIPANTS: 354 Dialysis Access Consortium (DAC) Study patients receiving a new graft with DNA samples obtained. Participants were randomly assigned to treatment with aspirin plus dipyridamole versus placebo. PREDICTOR: DNA sequence polymorphisms for the following candidate genes and their interaction with the study intervention: methylenetetrahydrofolate reductase (MTHFR), heme oxygenase 1 (HO-1), factor V (F5), transforming growth factor β1 (TGFβ1), klotho, nitric oxide synthase (NOS), and angiotensin-converting enzyme (ACE). OUTCOME: Graft failure (\u3e50% stenosis, angioplasty, thrombosis, surgical intervention, or permanent loss of function). RESULTS: During a median patient follow-up of 34.3 months, 304 grafts failed. After adjusting for clinical factors (patient age, sex, access location, diabetes, cardiovascular disease, baseline aspirin use, body mass index, timing of graft placement, and study treatment) and genetic ancestral background, single-nucleotide polymorphism rs6019 of the factor V gene was associated significantly with graft failure in a dominant model (HR of 1.70 [95% CI, 1.32-2.19; P \u3c 0.001] for G/C and G/G genotypes vs C/C genotypes). There was no significant association between graft failure and polymorphisms of MTHFR, HO-1, TGFβ1, klotho, NOS, or ACE. LIMITATIONS: Small sample size. CONCLUSION: The rs6019 genotype of Factor V is associated with increased risk of graft failure. Anticoagulation may reduce graft failure in patients with the G/C or G/G genotypes. Copyright © 2012 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved

Advancing Nephrology: Division Leaders Advise ASN

New treatments, new understanding, and new approaches to translational research are transforming the outlook for patients with kidney diseases. A number of new initiatives dedicated to advancing the field of nephrology-from value-based care to prize competitions-will further improve outcomes of patients with kidney disease. Because of individual nephrologists and kidney organizations in the United States, such as the American Society of Nephrology, the National Kidney Foundation, and the Renal Physicians Association, and international nephrologists and organizations, such as the International Society of Nephrology and the European Renal Association-European Dialysis and Transplant Association, we are beginning to gain traction to invigorate nephrology to meet the pandemic of global kidney diseases. Recognizing the timeliness of this opportunity, the American Society of Nephrology convened a Division Chief Retreat in Dallas, Texas, in June 2019 to address five key issues: (1) asserting the value of nephrology to the health system; (2) productivity and compensation; (3) financial support of faculty\u27s and divisions\u27 educational efforts; (4) faculty recruitment, retention, diversity, and inclusion; and (5) ensuring that fellowship programs prepare trainees to provide high-value nephrology care and enhance attraction of trainees to nephrology. Herein, we highlight the outcomes of these discussions and recommendations to the American Society of Nephrology. Keywords: Diversity; KidneyX; Medical Education; Nephrology Fellowship; Physician Productivity; Work Force

Convolutional Neural Network Model for Intensive Care Unit Acute Kidney Injury Prediction

Introduction: Acute kidney injury (AKI) is common among hospitalized patients and has a significant impact on morbidity and mortality. Although early prediction of AKI has the potential to reduce adverse patient outcomes, it remains a difficult condition to predict and diagnose. The purpose of this study was to evaluate the ability of a machine learning algorithm to predict for AKI as defined by Kidney Disease: Improving Global Outcomes (KDIGO) stage 2 or 3 up to 48 hours in advance of onset using convolutional neural networks (CNNs) and patient electronic health record (EHR) data. Methods: A CNN prediction system was developed to use EHR data gathered during patients\u27 stays to predict AKI up to 48 hours before onset. A total of 12,347 patient encounters were retrospectively analyzed from the Medical Information Mart for Intensive Care III (MIMIC-III) database. An XGBoost AKI prediction model and the sequential organ failure assessment (SOFA) scoring system were used as comparators. The outcome was AKI onset. The model was trained on routinely collected patient EHR data. Measurements included area under the receiver operating characteristic (AUROC) curve, positive predictive value (PPV), and a battery of additional performance metrics for advance prediction of AKI onset. Results: On a hold-out test set, the algorithm attained an AUROC of 0.86 and PPV of 0.24, relative to a cohort AKI prevalence of 7.62%, for long-horizon AKI prediction at a 48-hour window before onset. Conclusion: A CNN machine learning-based AKI prediction model outperforms XGBoost and the SOFA scoring system, revealing superior performance in predicting AKI 48 hours before onset, without reliance on serum creatinine (SCr) measurements. Keywords: acute kidney injury; convolutional neural net; electronic health record data; machine learning; prediction; serum creatinine

Effect of clopidogrel on early failure of arteriovenous fistulas for hemodialysis: a randomized controlled trial

CONTEXT: The arteriovenous fistula is the preferred type of vascular access for hemodialysis because of lower thrombosis and infection rates and lower health care expenditures compared with synthetic grafts or central venous catheters. Early failure of fistulas due to thrombosis or inadequate maturation is a barrier to increasing the prevalence of fistulas among patients treated with hemodialysis. Small, inconclusive trials have suggested that antiplatelet agents may reduce thrombosis of new fistulas. OBJECTIVE: To determine whether clopidogrel reduces early failure of hemodialysis fistulas. DESIGN, SETTING, AND PARTICIPANTS: Randomized, double-blind, placebo-controlled trial conducted at 9 US centers composed of academic and community nephrology practices in 2003-2007. Eight hundred seventy-seven participants with end-stage renal disease or advanced chronic kidney disease were followed up until 150 to 180 days after fistula creation or 30 days after initiation of dialysis, whichever occurred later. INTERVENTION: Participants were randomly assigned to receive clopidogrel (300-mg loading dose followed by daily dose of 75 mg; n = 441) or placebo (n = 436) for 6 weeks starting within 1 day after fistula creation. MAIN OUTCOME MEASURES: The primary outcome was fistula thrombosis, determined by physical examination at 6 weeks. The secondary outcome was failure of the fistula to become suitable for dialysis. Suitability was defined as use of the fistula at a dialysis machine blood pump rate of 300 mL/min or more during 8 of 12 dialysis sessions. RESULTS: Enrollment was stopped after 877 participants were randomized based on a stopping rule for intervention efficacy. Fistula thrombosis occurred in 53 (12.2%) participants assigned to clopidogrel compared with 84 (19.5%) participants assigned to placebo (relative risk, 0.63; 95% confidence interval, 0.46-0.97; P = .018). Failure to attain suitability for dialysis did not differ between the clopidogrel and placebo groups (61.8% vs 59.5%, respectively; relative risk, 1.05; 95% confidence interval, 0.94-1.17; P = .40). CONCLUSION: Clopidogrel reduces the frequency of early thrombosis of new arteriovenous fistulas but does not increase the proportion of fistulas that become suitable for dialysis. Trial Registration clinicaltrials.gov Identifier: NCT00067119

Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial

Background: Currently, physicians are limited in their ability to provide an accurate prognosis for COVID-19 positive patients. Existing scoring systems have been ineffective for identifying patient decompensation. Machine learning (ML) may offer an alternative strategy. A prospectively validated method to predict the need for ventilation in COVID-19 patients is essential to help triage patients, allocate resources, and prevent emergency intubations and their associated risks. Methods: In a multicenter clinical trial, we evaluated the performance of a machine learning algorithm for prediction of invasive mechanical ventilation of COVID-19 patients within 24 h of an initial encounter. We enrolled patients with a COVID-19 diagnosis who were admitted to five United States health systems between March 24 and May 4, 2020. Results: 197 patients were enrolled in the REspirAtory Decompensation and model for the triage of covid-19 patients: a prospective studY (READY) clinical trial. The algorithm had a higher diagnostic odds ratio (DOR, 12.58) for predicting ventilation than a comparator early warning system, the Modified Early Warning Score (MEWS). The algorithm also achieved significantly higher sensitivity (0.90) than MEWS, which achieved a sensitivity of 0.78, while maintaining a higher specificity (p \u3c 0.05). Conclusions: In the first clinical trial of a machine learning algorithm for ventilation needs among COVID-19 patients, the algorithm demonstrated accurate prediction of the need for mechanical ventilation within 24 h. This algorithm may help care teams effectively triage patients and allocate resources. Further, the algorithm is capable of accurately identifying 16% more patients than a widely used scoring system while minimizing false positive results. Keywords: COVID-19; Machine learning; Mechanical ventilation; Prediction