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Objectives: To compare the assessment of decision-making capacity of ICU patients by attending clinicians (physicians, nurses, and residents) with a capacity score measured by the Mini-Mental Status Examination, completed by Aid to Capacity Evaluation if necessary. The primary outcome was agreement between physicians' assessments and the score. Secondary outcomes were agreement between nurses' or residents' assessments and the score and identification of factors associated with disagreement.
Design: A 1-day prevalence study.
Setting: Nineteen ICUs in France.
Subjects: All patients hospitalized in the ICU on the study day and the attending clinicians.
Interventions: The decision-making capacity of patients was assessed by the attending clinicians and independently by an observer using the score.
Measurements And Main Results: A total of 206 patients were assessed by 213 attending clinicians (57 physicians, 97 nurses, and 59 residents). Physicians designated more patients as having decision-making capacity (n = 92/206 [45%]) than score (n = 34/206 [17%]; absolute difference 28% [95% CI, 20-37%]; p = 0.001). There was a high disagreement between assessments of all clinicians and score (Kappa coefficient 0.39 [95% CI, 0.29-0.50] for physicians; 0.39 [95% CI, 0.27-0.52] for nurses; and 0.46 [95% CI, 0.35-0.58] for residents). The main factor associated with disagreement was a Glasgow Coma Scale score between 10 and 15 (odds ratio, 2.92 [1.18-7.19], p = 0.02 for physicians; 4.97 [1.50-16.45], p = 0.01 for nurses; and 3.39 [1.12-10.29], p = 0.03 for residents) without differentiating between the Glasgow Coma Scale scores from 10 to 15.
Conclusions: The decision-making capacity of ICU patients was largely overestimated by all attending clinicians as compared with a score. The main factor associated with disagreement was a Glasgow Coma Scale score between 10 and 15, suggesting that clinicians confused consciousness with decision-making capacity.
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http://dx.doi.org/10.1097/CCM.0000000000003550 | DOI Listing |
Int J Health Care Qual Assur
September 2025
Department of Electrical and Computer Engineering, Graduate University of Advanced Technology, Kerman, Iran.
Purpose: Neonatal mortality is a significant global health issue, particularly in low- and middle-income countries. This study aims to identify and understand the factors contributing to high neonatal mortality rates in the cities of Kerman and Bam, Iran, to develop effective strategies for improvement.
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September 2025
University of Wisconsin, 600 Highland Ave Madison, WI 53792.
Vascular surgeons are often responsible for navigating treatment decisions when caring for older adults. Care for these patients is informed by the surgeon's assessment of the patient's decision-making capacity, use of advance care planning, and understanding of futility. Having difficult conversations with patients and their families is supported by strategies that promote empathic communication and shared decision making with older adults with serious illness due to, and associated with, vascular disease.
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Department of Physical Therapy, Steinhardt School of Culture, Education, and Human Development, New York University, New York, NY.
ChatGPT has been increasingly used in clinical practice, education, and research. In orthopedic research, ChatGPT's accuracy in clinical decision-making has been a major concern, with results ranging from 33% to 80% accuracy. Inaccuracies from ChatGPT can be harmful to clinicians, trainees, or patients when responses appear plausible, are trusted, and acted upon.
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September 2025
Department of Business Administration, World University of Bangladesh, Dhaka, 1230, Bangladesh.
Supply chain risk management is crucial for the consumer products industry, given its susceptibility to uncertainties and risks. This research investigates the relationship between supply chain risks and performance within this sector, based on a sample of 385 entrepreneurs from Small Medium Sized enterprises (SMEs) in the consumer goods industry across ASEAN countries. Supply chain performance, defined as the ability to meet end-customer demands, involves ensuring commodity availability, on-time deliveries, and maintaining sufficient inventory and capacity across organizational boundaries, from raw materials to the final consumer.
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Department of Public Health, Faculty of Medicine, Padjadjaran University, Bandung, West Java, Indonesia.
Background: Currently, midwifery education is confronted with a variety of obstacles, such as inadequate resources and conventional learning methods that are less effective in enhancing the clinical skills of students. Technological advancements and the rapid evolution of maternal and neonatal health services necessitate the transformation of midwifery education to a competency-based curriculum and outcome-based assessment paradigm. Artificial intelligence (AI) and deep learning have the potential to provide adaptive, personalized, and precise learning in this context.
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