Validity of Dietary Assessment Methods When Compared to the Method of Doubly Labeled Water: A Systematic Review in Adults.

Accuracy in quantifying energy intake (EI) using common dietary assessment methods is crucial for interpreting the relationship between diet and chronic disease. The aim of this systematic review was to evaluate the validity of dietary assessment methods used to estimate the EI of adults in comparison to total energy expenditure (TEE) measured by doubly labeled water (DLW). Articles in English across nine electronic databases, published between 1973 and February 2019 were retrieved. Studies were included if participants were adults (≥18 years) and used the DLW technique to measure TEE compared to self-reported EI. A total of 59 studies were included, with a total of 6,298 free living adults and a mean of 107 participants per study. The majority of studies including 16 studies that included a technology based method reported significant (P < 0.05) under-reporting of EI when compared to TEE, with few over-reporting EI. Misreporting was more frequent among females compared to males within recall based dietary assessment methods. The degree of under-reporting was highly variable within studies using the same method, with 24 h recalls having less variation and degree of under-reporting compared to other methods.

Comparison of the verification performance and radiation dose between ExacTrac x-ray system and On-Board Imager-A phantom study.

Recently, On-Board Imager (OBI) and ExacTrac x-ray 6 degree-of-freedom system (ExacTrac) are increasingly used verification systems in local radiotherapy centers. This study aimed to compare the differences between these two systems in terms of verification accuracy, organ doses, and verification time for head-and-neck (H&N) and pelvic cases. Rando anthropomorphic phantoms of H&N and pelvic regions were positioned with known set-up deviations from the reference position in the linear accelerator. x-Ray verification images were then acquired using both systems. Verification accuracy was evaluated based on the residual positioning error (δD) after image registration. Thermoluminescence dose meters (TLD-100s) were placed in specific locations of the phantoms for the measurement of imaging doses at the organs of interest. Besides, the verification time was also recorded for comparison. Most average detection errors for both systems were within 1 mm. The detection error of ExacTrac was significantly larger than OBI in the H&N region in all directions (p < 0.05), but was significantly lower in the pelvis (p < 0.05). The mean imaging doses to all organs of interest from ExacTrac were significantly lower than OBI (p < 0.05). The mean verification time for ExacTrac was about 10 seconds, which was significantly shorter than the 100 seconds in OBI (p < 0.001). Both verification systems achieved satisfactory performance in the H&N and pelvic regions despite ExacTrac being better in terms of verification time and organ dose. The verification accuracy of Exactrac was better in pelvic region than the H&N region when compared with OBI.

Identification of Chinese medicine syndromes in persistent insomnia associated with major depressive disorder: a latent tree analysis.

BACKGROUND: Chinese medicine (CM) syndrome (zheng) differentiation is based on the co-occurrence of CM manifestation profiles, such as signs and symptoms, and pulse and tongue features. Insomnia is a symptom that frequently occurs in major depressive disorder despite adequate antidepressant treatment. This study aims to identify co-occurrence patterns in participants with persistent insomnia and major depressive disorder from clinical feature data using latent tree analysis, and to compare the latent variables with relevant CM syndromes. METHODS: One hundred and forty-two participants with persistent insomnia and a history of major depressive disorder completed a standardized checklist (the Chinese Medicine Insomnia Symptom Checklist) specially developed for CM syndrome classification of insomnia. The checklist covers symptoms and signs, including tongue and pulse features. The clinical features assessed by the checklist were analyzed using Lantern software. CM practitioners with relevant experience compared the clinical feature variables under each latent variable with reference to relevant CM syndromes, based on a previous review of CM syndromes. RESULTS: The symptom data were analyzed to build the latent tree model and the model with the highest Bayes information criterion score was regarded as the best model. This model contained 18 latent variables, each of which divided participants into two clusters. Six clusters represented more than 50 % of the sample. The clinical feature co-occurrence patterns of these six clusters were interpreted as the CM syndromes Liver qi stagnation transforming into fire, Liver fire flaming upward, Stomach disharmony, Hyperactivity of fire due to yin deficiency, Heart-kidney noninteraction, and Qi deficiency of the heart and gallbladder. The clinical feature variables that contributed significant cumulative information coverage (at least 95 %) were identified. CONCLUSION: Latent tree model analysis on a sample of depressed participants with insomnia revealed 13 clinical feature co-occurrence patterns, four mutual-exclusion patterns, and one pattern with a single clinical feature variable.