Purpose: To prospectively determine the quality of life and functional outcome at 3, 6 and 12 months following acute necrotising pancreatitis.
Methods: Thirty-one consecutive patients with acute necrotising pancreatitis requiring intensive care in our hospital were identified. Survivors were assessed at 3, 6 and 12 months following hospital discharge by an investigator blinded to their previous treatment. Health-related quality of life was assessed by the Short Form 36 (SF-36) questionnaire and functional outcome by the six minute walk test.
Results: Twenty-one patients (68%) survived to leave hospital. The median score for the physical function domain increased from 32 at 3 months to 38 and 12 months (P = 0.013), but remained lower than the score in the normal population of 88 (P < 0.001). The median physical component summary score increased from 33 at 3 months to 40 at 12 months (P = 0.030), but remained lower than the score in the normal population of 50 (P = 0.009). Between 3 and 12 months the median distance walked in 6-min increased from 358 to 424 m (P = 0.021), but remained lower than the predicted distance of 503 m (P = 0.014).
Conclusions: In the first year after acute necrotising pancreatitis patients showed improvement in their physical components of quality of life and in their physical function, but their outcome at 12 months was still poor compared to the general population. This patient group in particular may benefit from a structured rehabilitation programme continuing after hospital discharge.
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Sci Rep
December 2024
Department of Neurobiology and Behavior, University of California Irvine, Irvine, CA, 92697, USA.
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December 2024
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December 2024
State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau, China.
Lipid nanoparticles (LNPs) have proven effective in mRNA delivery, as evidenced by COVID-19 vaccines. Its key ingredient, ionizable lipids, is traditionally optimized by inefficient and costly experimental screening. This study leverages artificial intelligence (AI) and virtual screening to facilitate the rational design of ionizable lipids by predicting two key properties of LNPs, apparent pKa and mRNA delivery efficiency.
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