Aims: This retrospective audit was conducted to investigate the association between outcome and protein-energy malnutrition diagnosed using Subjective Global Assessment (SGA), to evaluate the predictive validity of Subjective Global Assessment in adults admitted to intensive care.
Methods: The audit analysed the medical records of 1034 consecutive adult patients who had nutrition assessment on admission to the intensive care unit between January 2017 and July 2018. Extracted data included patient demographics, nutritional status, outcomes, and Acute Physiology and Chronic Health Evaluation II score. Regression was used to explore the association between Subjective Global Assessment and outcomes.
Results: The prevalence of protein-energy malnutrition was 39.5% (342 patients SGA-B, and 75 patients SGA-C), and there was a significant independent association between Subjective Global Assessment and outcomes both in surgical and non-surgical patients. Compared with well-nourished patients, mortality was significantly higher in the malnourished, during the intensive care admission (p = 0.007), in hospital (p < 0.0001), at 90 days (p = 0.001) and at 180 days (p = 0.002). Pressure injuries were more common (p = 0.01). Length of stay was longer in intensive care (p = 0.001) and in hospital (p < 0.001), with increased readmission rate (p < 0.001).
Conclusion: Protein-energy malnutrition diagnosed by Subjective Global Assessment had a significant independent association with adverse clinical outcomes in critically ill patients. Subjective Global Assessment appears to have predictive validity in this patient population.
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http://dx.doi.org/10.1111/1747-0080.12767 | DOI Listing |
Biomedicines
December 2024
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December 2024
Department of Economics, Sejong University, Seoul 05006, Republic of Korea.
The advancement of autonomous driving technology, particularly Tesla's launch of its new Robotaxi, marks a transformation in transportation. Understanding the theoretical mechanisms that drive consumers' intention to use autonomous taxis is essential. This study develops a structural equation model (SEM), extending the applicability of the TAM and TPB model, and incorporates external factors like attitudes, subjective norms, traffic efficiency, and perceived cost-benefit into the model to analyze their impact on consumers' perceived characteristics (perceived usefulness and perceived ease of use).
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December 2024
School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, PA 19104, USA.
Background: Cognitive impairment poses a significant global health challenge, emphasizing the critical need for early detection and intervention. Traditional diagnostics like neuroimaging and clinical evaluations are often subjective, costly, and inaccessible, especially in resource-poor settings. Previous research has focused on speech analysis primarily conducted using English data, leaving multilingual settings unexplored.
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November 2024
Department of Computer, Control and Management Engineering, Sapienza University of Rome, Via Ariosto 25, 00185 Roma, Italy.
The COVID-19 pandemic has led to increased mental health issues, particularly among long-COVID patients, who experience persistent symptoms post-recovery, potentially leading to chronic conditions. The psychological impact of long-COVID is still largely unknown, but it may contribute to mental disorders like Post-Traumatic Stress Disorder (PTSD). Given the global rise in anxiety and depression, exploring therapies like Eye Movement Desensitization and Reprocessing (EMDR) for long-COVID traumatic disorders is crucial.
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