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Introduction: In a low-income country, the impact of preoperative anemia on postoperative mortality among noncardiac surgery patients is little understood. As a result, we aim to investigate the association between preoperative anemia and postoperative mortality in noncardiac surgery patients in Northwest Ethiopia.

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Background: Postoperative delirium (POD) is characterized by fluctuating attention after surgery and is associated with increased risk of developing Alzheimer's Disease (AD). While the neurophysiological changes that underlie POD and increased risk of AD are unclear, recent data has raised the possibility that an exaggerated brain response to anesthetics may be a biomarker for POD risk and preclinical AD-like pathology. Thus, we examined whether anesthetic-dose-adjusted intraoperative brain activity is associated with POD or preoperative brain vulnerabilities (preclinical AD-like pathology, preoperative inattention) that may contribute to risk of POD (and later AD).

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Background: APOE4 leads to increased neuroinflammation, neurocognitive decline, increased risk of Alzheimer's disease, and may be associated with increased delirium risk. However, the safety and feasibility of pharmacologic modulation of APOE to prevent neuroinflammation and postoperative delirium is unclear.

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Background: The inadequate inclusion of sex and gender in medical research has resulted in biased clinical guidance and disparities in knowledge and patient outcomes. Despite efforts by regulatory and funding agencies, opportunities to generate sex-specific knowledge are frequently overlooked. While certain disciplines in cardiovascular medicine have made notable progress, these advances have yet to permeate the literature on perioperative cardiovascular complications in non-cardiac surgery.

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Introduction: Understanding 1-year mortality following major surgery offers valuable insights into patient outcomes and the quality of peri-operative care. Few models exist that predict 1-year mortality accurately. This study aimed to develop a predictive model for 1-year mortality in patients undergoing complex non-cardiac surgery using a novel machine-learning technique called multi-objective symbolic regression.

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