Early markers of renal damage in obstructive sleep apnea syndrome (OSAS) patients with or without diabetes mellitus

Background: Although obstructive sleep apnea syndrome (OSAS) has been associated with chronic kidney disease CKD, there are little data about early screening of renal affection in OSAS patients. Aim of the work: To evaluate renal function in OSAS patients with or without diabetes mellitus (DM) using blood indices [mean platelet volume (MPV) and red cell distribution width (RDW)] and serum neutrophil gelatinase associated lipocalin (NGAL) as early markers of kidney injury. Patients and methods: This case control analytic study was designed to enroll 20 OSAS patients with DM, 20 OSAS patients without DM, and 20 non OSAS diabetic patients as control group. All patients underwent full over-night attended diagnostic polysomnography. Those with AHI ≥5 were considered to have OSAS. Laboratory parameters including complete blood count with MPV and RDW, serum glucose, urea, creatinine, Hemoglobin A1c, urine albumin creatinine ratio UACR and serum NGAL were done to all enrolled participants. Results: Urine albumin creatinine ratio UACR ≥ 3 mg/mmol was found in 11 (55%) of OSAS diabetic group, 6 (30%) of non diabetic OSAS group and in 11 (55%) of D.M group. Both diabetic and non diabetic OSAS patients had significantly higher RDW and NGAL compared to non OSAS diabetic. The diabetic OSAS group had also significantly higher serum urea and creatinine compared to DM group. In OSAS patients, RDW had significant positive correlation with UACR. Meanwhile both RDW and NGAL were determined to have significant positive correlation with desaturation index during sleep, but not correlated to AHI. Conclusion: Renal impairment is common in OSAS patients but more frequent if associated with diabetes mellitus. RDW% can be used as simple screening test for early detection of renal injury in OSAS patients with or without diabetes mellitus

Precision Face Milling of Maraging Steel 350: An Experimental Investigation and Optimization Using Different Machine Learning Techniques

Maraging steel, characterized by its superior strength-to-weight ratio, wear resistance, and pressure tolerance, is a material of choice in critical applications, including aerospace and automotive components. However, the machining of this material presents significant challenges due to its inherent properties. This study comprehensively examines the impacts of face milling variables on maraging steel’s surface quality, cutting temperature, energy consumption, and material removal rate (MRR). An experimental analysis was conducted, and the gathered data were utilized for training and testing five machine learning (ML) models: support vector machine (SVM), K-nearest neighbor (KNN), artificial neural network (ANN), random forest, and XGBoost. Each model aimed to predict the outcomes of different machining parameters efficiently. XGBoost emerged as the most effective, delivering an impressive 98% prediction accuracy across small datasets. The study extended into applying a genetic algorithm (GA) for optimizing XGBoost’s hyperparameters, further enhancing the model’s predictive accuracy. The GA was instrumental in multi-objective optimization, considering various responses, including surface roughness and energy consumption. The optimization process evaluated different weighting methods, including equal weights and weights derived from the analytic hierarchy process (AHP) based on expert insights. The findings indicate that the refined XGBoost model, augmented by GA-optimized hyperparameters, provides highly accurate predictions for machining parameters. This outcome holds significant implications for industries engaged in the machining of maraging steel, offering a pathway to optimized operational efficiency, reduced costs, and enhanced product quality amid the material’s machining challenges

Epidemiology of surgery associated acute kidney injury (EPIS-AKI): a prospective international observational multi-center clinical study

Purpose: The incidence, patient features, risk factors and outcomes of surgery-associated postoperative acute kidney injury (PO-AKI) across different countries and health care systems is unclear. Methods: We conducted an international prospective, observational, multi-center study in 30 countries in patients undergoing major surgery (> 2-h duration and postoperative intensive care unit (ICU) or high dependency unit admission). The primary endpoint was the occurrence of PO-AKI within 72 h of surgery defined by the Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Secondary endpoints included PO-AKI severity and duration, use of renal replacement therapy (RRT), mortality, and ICU and hospital length of stay. Results: We studied 10,568 patients and 1945 (18.4%) developed PO-AKI (1236 (63.5%) KDIGO stage 1500 (25.7%) KDIGO stage 2209 (10.7%) KDIGO stage 3). In 33.8% PO-AKI was persistent, and 170/1945 (8.7%) of patients with PO-AKI received RRT in the ICU. Patients with PO-AKI had greater ICU (6.3% vs. 0.7%) and hospital (8.6% vs. 1.4%) mortality, and longer ICU (median 2 (Q1-Q3, 1-3) days vs. 3 (Q1-Q3, 1-6) days) and hospital length of stay (median 14 (Q1-Q3, 9-24) days vs. 10 (Q1-Q3, 7-17) days). Risk factors for PO-AKI included older age, comorbidities (hypertension, diabetes, chronic kidney disease), type, duration and urgency of surgery as well as intraoperative vasopressors, and aminoglycosides administration. Conclusion: In a comprehensive multinational study, approximately one in five patients develop PO-AKI after major surgery. Increasing severity of PO-AKI is associated with a progressive increase in adverse outcomes. Our findings indicate that PO-AKI represents a significant burden for health care worldwide

Acute kidney disease beyond day 7 after major surgery: a secondary analysis of the EPIS-AKI trial

Purpose: Acute kidney disease (AKD) is a significant health care burden worldwide. However, little is known about this complication after major surgery. Methods: We conducted an international prospective, observational, multi-center study among patients undergoing major surgery. The primary study endpoint was the incidence of AKD (defined as new onset of estimated glomerular filtration rate (eCFR) < 60 ml/min/1.73 m2 present on day 7 or later) among survivors. Secondary endpoints included the relationship between early postoperative acute kidney injury (AKI) (within 72 h after major surgery) and subsequent AKD, the identification of risk factors for AKD, and the rate of chronic kidney disease (CKD) progression in patients with pre-existing CKD. Results: We studied 9510 patients without pre-existing CKD. Of these, 940 (9.9%) developed AKD after 7 days of whom 34.1% experiencing an episode of early postoperative-AKI. Rates of AKD after 7 days significantly increased with the severity (19.1% Kidney Disease Improving Global Outcomes [KDIGO] 1, 24.5% KDIGO2, 34.3% KDIGO3; P < 0.001) and duration (15.5% transient vs 38.3% persistent AKI; P < 0.001) of early postoperative-AKI. Independent risk factors for AKD included early postoperative-AKI, exposure to perioperative nephrotoxic agents, and postoperative pneumonia. Early postoperative-AKI carried an independent odds ratio for AKD of 2.64 (95% confidence interval [CI] 2.21-3.15). Of 663 patients with pre-existing CKD, 42 (6.3%) had worsening CKD at day 90. In patients with CKD and an episode of early AKI, CKD progression occurred in 11.6%. Conclusion: One in ten major surgery patients developed AKD beyond 7 days after surgery, in most cases without an episode of early postoperative-AKI. However, early postoperative-AKI severity and duration were associated with an increased rate of AKD and early postoperative-AKI was strongly associated with AKD independent of all other potential risk factors