Background & Aims: The severity of pain is routinely assessed in hospitalised patients but the impact of pain and pain control on energy coverage has been poorly studied. This One-day cross-sectional observational study assessed the association between severity of pain and coverage of energy needs in hospitalised patients.
Methods: Foods provided and consumed were assessed on one day by dedicated dieticians for unselected hospitalised patients receiving three meals per day. Severity of pain was evaluated by a visual analogue scale at the mealtimes, averaged over the study day, and categorized as no pain, slight, moderate or severe pain. The coverage of energy needs was expressed in percentage of predicted needs.
Results: Among the 755 included patients, 63% reported having pain. Severe pain was associated with a lower energy coverage than no pain (p = 0.001) or slight pain (p = 0.001). Insufficient energy coverage, defined as ≤70% of predicted needs, occurred in 13% of the patients. In univariate logistic regressions, predictors of insufficient energy coverage were severe pain as compared to no pain (OR 2.38; 95% CI 1.21, 4.64) and treatment with opioid drugs as compared to no pain killer (OR 1.73; 95% CI 1.07, 2.79). When including sex, age, body mass index, treatment with analgesics and severity of pain in a multivariate logistic regression, severe pain more than doubled the risk of insufficient energy coverage (OR 2.32; CI 1.15, 4.66).
Conclusions: Patients experiencing severe pain have a high risk of insufficient energy coverage. Optimal pain control is probably critical to prevent underfeeding in the hospital.
Trial Registration: Identifier no NCT02463565 on www.ClinicalTrials.gov.
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http://dx.doi.org/10.1016/j.clnu.2018.03.005 | DOI Listing |
ACS Nano
January 2025
College of Chemistry Chemical Engineering and Materials Science, Shandong Normal University, Jinan, Shandong 250014, China.
Coastal/offshore renewable energy sources combined with seawater splitting offer an attractive means for large-scale H electrosynthesis in the future. However, designing anodes proves rather challenging, as surface chlorine chemistry must be blocked, particularly at high current densities (). Additionally, waste seawater with increased salinity produced after long-term electrolysis would impair the whole process sustainability.
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January 2025
Department of Civil & Environmental Engineering, University of California Los Angeles (UCLA), Los Angeles, CA, USA.
Am J Epidemiol
December 2024
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Identifying the determinants of pregnancy loss is a critical public health concern. However, pregnancy loss is often not noticed, and even when it is, it is inconsistently recorded. Thus, past studies have been limited to medically-identified losses or small, highly selected cohorts, which can lead to biased or non-generalizable results.
View Article and Find Full Text PDFMater Horiz
January 2025
Department of Chemical Engineering, National Tsing Hua University, 101, Section 2, Kuang-Fu Road, Hsin-Chu 300044, Taiwan.
The formation of a high-density nanotwinned structure in copper deposits is presently acknowledged as a paramount goal for enhancing the material characteristics of copper. However, the conventional manufacturing processes often involve the incorporation of organic additives, resulting in consequential impurity effects and aging concerns. In this work, we introduce a high-rate approach to fabricate (220)-orientation nanotwinned copper foils in a concentrated methanesulfonate copper solution with mere amount of chloride ions as additives.
View Article and Find Full Text PDFJ Chem Theory Comput
January 2025
Department of Electrical & Computer Engineering, Stony Brook University, Stony Brook, New York 11794, United States.
In this work, we develop a novel Bayesian approach to study the adsorption and desorption of CO onto a Pd(111) surface, a process of great importance in natural sciences. The motivation for this work comes from the recent availability of time-resolved infrared spectroscopy data and the need for model interpretability and uncertainty quantification in chemical processes. The objective is to learn the relevant parameters that characterize the process: coverage with time, rate constants, activation energies, and pre-exponential factors.
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