Continuous ambulatory peritoneal dialysis (CAPD) is a treatment used by patients in the end-stage of chronic kidney diseases. Those patients need to be monitored using blood tests and those tests can present some patterns or correlations. It could be meaningful to apply data mining (DM) to the data collected from those tests. To discover patterns from meaningless data, it becomes crucial to use DM techniques. DM is an emerging field that is currently being used in machine learning to train machines to later aid health professionals in their decision-making process. The classification process can found patterns useful to understand the patients' health development and to medically act according to such results. Thus, this study focuses on testing a set of DM algorithms that may help in classifying the values of serum creatinine in patients undergoing CAPD procedures. Therefore, it is intended to classify the values of serum creatinine according to assigned quartiles. The better results obtained were highly satisfactory, reaching accuracy rate values of approximately 95%, and low relative absolute error values.

OBJECTIVE Finerenone significantly improved cardiorenal outcomes in patients with chronic kidney disease (CKD) and type 2 diabetes (T2D) in the Finerenone in Reducing Kidney Failure and Disease Progression in Diabetic Kidney Disease trial. We explored whether baseline HbA1c level and insulin treatment influenced outcomes. RESEARCH DESIGN AND METHODS Patients with T2D, urine albumin-to-creatinine ratio (UACR) of 30–5,000 mg/g, estimated glomerular filtration rate (eGFR) of 25 to <75 mL/min/1.73 m2, and treated with optimized renin–angiotensin system blockade were randomly assigned to receive finerenone or placebo. Efficacy outcomes included kidney (kidney failure, sustained decrease ≥40% in eGFR from baseline, or renal death) and cardiovascular (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure) composite endpoints. Patients were analyzed by baseline insulin use and by baseline HbA1c <7.5% (58 mmol/mol) or ≥7.5%. RESULTS Of 5,674 patients, 3,637 (64.1%) received insulin at baseline. Overall, 5,663 patients were included in the analysis for HbA1c; 2,794 (49.3%) had baseline HbA1c <7.5% (58 mmol/mol). Finerenone significantly reduced risk of the kidney composite outcome independent of baseline HbA1c level and insulin use (Pinteraction = 0.41 and 0.56, respectively). Cardiovascular composite outcome incidence was reduced with finerenone irrespective of baseline HbA1c level and insulin use (Pinteraction = 0.70 and 0.33, respectively). Although baseline HbA1c level did not affect kidney event risk, cardiovascular risk increased with higher HbA1c level. UACR reduction was consistent across subgroups. Adverse events were similar between groups regardless of baseline HbA1c level and insulin use; few finerenone-treated patients discontinued treatment because of hyperkalemia. CONCLUSIONS Finerenone reduces kidney and cardiovascular outcome risk in patients with CKD and T2D, and risks appear consistent irrespective of HbA1c levels or insulin use.

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