BMC anesthesiology
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Multicenter Study
Development and validation of an EHR-based risk prediction model for geriatric patients undergoing urgent and emergency surgery.
Clinical determination of patients at high risk of poor surgical outcomes is complex and may be supported by clinical tools to summarize the patient's own personalized electronic health record (EHR) history and vitals data through predictive risk models. Since prior models were not readily available for EHR-integration, our objective was to develop and validate a risk stratification tool, named the Assessment of Geriatric Emergency Surgery (AGES) score, predicting risk of 30-day major postoperative complications in geriatric patients under consideration for urgent and emergency surgery using pre-surgical existing electronic health record (EHR) data. ⋯ We developed a model to accurately predict major postoperative complications in geriatric patients undergoing urgent or emergency surgery using the patient's own existing EHR data. EHR implementation of this model could efficiently support clinicians' surgical risk assessment and perioperative decision-making discussions in this vulnerable patient population.
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Multicenter Study
Reticulocyte hemoglobin content: a new frontier in iron deficiency diagnostics for major surgical patients.
Iron deficiency (ID) is the most common nutritional deficiency among patients undergoing major surgery. Treatment of ID is straightforward, however implementing a comprehensive anemia management strategy within clinical routines is complex. Recently, reticulocyte hemoglobin content (Ret-He) has been evaluated as an early marker for ID diagnosis. ⋯ This study highlights the potential of Ret-He as a promising alternative marker for diagnosing ID in patients undergoing major surgery, particularly in cases of elevated ferritin levels or non-anemic patients. Ret-He may serve as a valuable tool to prioritize patients for further iron status testing, especially when preoperative time is limited.
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Multicenter Study Observational Study
Predicting early diagnosis of intensive care unit-acquired weakness in septic patients using critical ultrasound and biological markers.
Early diagnosis of intensive care unit-acquired weakness (ICUAW) is crucial for improving the outcomes of critically ill patients. Hence, this study was designed to identify predisposing factors for ICUAW and establish a predictive model for the early diagnosis of ICUAW. ⋯ Conclusively, a nomogram model is constructed for diagnosing ICUAW in septic patients, which is simple and rapid and allows for visual representation, with excellent diagnostic capability.