Editorial

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Prediction of cardiovascular outcomes with machine learning techniques: application to the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) study.

Background: Data derived from the Cardiovascular Outcomes in Renal Atherosclerotic Lesions (CORAL) study were analyzed in an effort to employ machine learning methods to predict the composite endpoint described in the original study. Methods: We identified 573 CORAL subjects with complete baseline data and the presence or absence of a composite endpoint for the study. These data were subjected to several models including a generalized linear (logistic-linear) model, support vector machine, decision tree, feed-forward neural network, and random forest, in an effort to attempt to predict the composite endpoint. The subjects were arbitrarily divided into training and testing subsets according to an 80%:20% distribution with various seeds. Prediction models were optimized within the CARET package of R. Results: The best performance of the different machine learning techniques was that of the random forest method which yielded a receiver operator curve (ROC) area of 68.1%±4.2% (mean ± SD) on the testing subset with ten different seed values used to separate training and testing subsets. The four most important variables in the random forest method were SBP, serum creatinine, glycosylated hemoglobin, and DBP. Each of these variables was also important in at least some of the other methods. The treatment assignment group was not consistently an important determinant in any of the models. Conclusion: Prediction of a composite cardiovascular outcome was difficult in the CORAL population, even when employing machine learning methods. Assignment to either the stenting or best medical therapy group did not serve as an important predictor of composite outcome. Clinical Trial Registration: ClinicalTrials.gov, NCT00081731

Interleukin 10-Mediated Response and Correlated Anemia in a Patient with Advanced Non-Small Cell Lung Carcinoma

Anemia in cancer patients is associated with poor quality of life, reduced response to therapy, and decreased overall survival. We describe a case of a 56-year old woman with advanced metastatic non-small cell lung carcinoma who demonstrated marked response to a novel combinational immunotherapy approach involving a long-acting PEGylated construct of recombinant human Interleukin-10 with Nivolumab, an anti-PD-L1 checkpoint inhibitor. While on treatment, the patient developed severe anemia and hyper-ferritinemia requiring RBC transfusion support. Here we discuss a possible novel immune mechanism of IL10-mediated anemia in correlation with tumor response

Current Strategies for Management of Hypertensive Renal Disease

The incidence of hypertensive end-stage renal disease continues to increase annually. To reduce this incidence, it is necessary to control systolic and diastolic hypertension. Reversible causes should always be sought in any hypertensive patient who develops renal insufficiency. Blood pressure should be reduced to 130/85 mm Hg, and in African Americans with hypertensive renal failure, reducing the blood pressure to 120/75 mm Hg may be beneficial. Any antihypertensive treatment regimen that effectively lowers blood pressure will help slow progressive renal failure. Whenever possible, an angiotensin-converting enzyme inhibitor should be part of the treatment, since these drugs have been shown to be renoprotective beyond their antihypertensive effect in certain renal disease categories.Arch Intern Med. 1999;159:23-28--

Microdose Lithium Protects against Pancreatic Islet Destruction and Renal Impairment in Streptozotocin-Elicited Diabetes

Psychiatric use of lithium has been associated with hypoglycemic effects, but its effect on type 1 diabetes mellitus (T1D) is unknown. In streptozotocin (STZ) induced murine models of T1D, microdose lithium therapy improved hyperglycemia, attenuated body weight loss and prevented early signs of diabetic kidney injury. This beneficial effect was associated with preservation of pancreatic islet histology and β-cell production of insulin as well as mitigated oxidative damage of islets. Mechanistically, lithium in islets cells induced inhibitory phosphorylation of glycogen synthase kinase 3β (GSK3β), the major molecular target of lithium that has been recently implicated in non-canonical regulation of Nrf2 activity. In turn, Nrf2 antioxidant response was potentiated in islets, marked by nuclear translocation of Nrf2 and augmented expression of its target antioxidant enzyme heme oxygenase 1 (HO-1). Conversely, cotreatment with trigonelline, a selective blockade of Nrf2, offset the lithium enhanced Nrf2 antioxidant response in islets, blunted the protective effect of lithium on pancreatic islets and β-cells, and abolished the hypoglycemic activity of lithium in STZ-injured mice. Collectively, our findings suggest that microdose lithium confers a protective effect on islet β-cells via targeting the GSK3β-regulated Nrf2 antioxidant response and thereby ameliorates T1D and its related kidney impairment