American journal of critical care : an official publication, American Association of Critical-Care Nurses
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Evaluating energy expenditure is important for establishing optimal goals for nutrition treatment. However, indirect calorimetry, the reference standard for measuring energy expenditure, is difficult to apply widely in clinical practice. ⋯ Results of BIA were highly consistent with indirect calorimetry assessments of energy expenditure in critically ill patients. Few factors except comorbidity affect the accuracy of BIA when assessing energy expenditure. Therefore, as a low-cost, easy-to-use, and noninvasive method, BIA is a valuable clinical tool for assessing energy expenditure in critically ill patients.
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Sepsis is a complex condition with high morbidity and mortality. Prompt treatment can improve survival, but for survivors the risk of deterioration and readmission remains high. Little is known about the association between discharge setting and readmission among sepsis survivors. ⋯ Sepsis survivors discharged to skilled nursing facilities, home health care, and home are at high risk for 30-day readmission. The rates of readmission from home health care and home settings were alarming. Often patients are discharged to inappropriate settings, placing them at risk for residual sepsis and readmission. Future research should focus on appropriate timing of hospital discharge and transition to the most appropriate discharge setting.
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Communication and collaboration among health care professionals during bedside rounds improve patient outcomes and nurses' and physicians' satisfaction. ⋯ Initiating discussions of care between nurses and physicians and discussing nurses' concerns during bedside rounds have multiple benefits.
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Promoting bonding and neurodevelopmental care is an important element in the cardiovascular intensive care unit (CICU); however, holding of infants by family members is inconsistently practiced. ⋯ Expert group consensus with high-fidelity simulation training is a feasible, safe, and reliable method for teaching higher risk skills and guiding protocol development.
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Hospital-acquired pressure injuries (HAPIs) have a major impact on patient outcomes in intensive care units (ICUs). Effective prevention relies on early and accurate risk assessment. Traditional risk-assessment tools, such as the Braden Scale, often fail to capture ICU-specific factors, limiting their predictive accuracy. Although artificial intelligence models offer improved accuracy, their "black box" nature poses a barrier to clinical adoption. ⋯ The model and its dashboard provide clinicians with a transparent, interpretable artificial intelligence-based risk-assessment system for HAPIs that may enable more effective and timely preventive interventions.