Body Composition Measurement Improved Performance of GLIM Criteria in Diagnosing Malnutrition Compared to PG-SGA in Ambulatory Cancer Patients: A Prospective Cross-Sectional Study

Background and aims: Muscle mass reduction (MMR) is one of the three etiologic criteria in the Global Leadership Initiative on Malnutrition (GLIM) framework. This study aimed to evaluate the value of MMR in GLIM criteria among ambulatory cancer patients. Methods: A single-center prospective cross-sectional study was conducted. All participants underwent calf circumference (CC) measurement and body composition measurement by bioelectrical impedance analysis (BIA). MMR was identified by CC, fat-free mass index (FFMI), appendicular skeletal muscle index (ASMI), or combinations of the above three indicators. Patients-generated Subjective Global Assessment (PG-SGA) was used as the comparator. Results: A total of 562 cancer patients receiving intravenous treatment were evaluated. Of the participants, 62.8% (355/562) were male. The median age of the patients was 59.0 years (range, 21–82 y). The median BMI was 22.8 kg/m2 (range, 14.6–34.5 kg/m2). A total of 41.8% of patients were evaluated as malnutrition (PG-SGA ≥ 4), and 11.9% were diagnosed with severe malnutrition (PG-SGA ≥ 9). For the GLIM criteria, the prevalence of malnutrition was 26.9%, and severe malnutrition was 12.3%. For all criteria combinations of GLIM together versus PG-SGA, sensitivity was 60.4% (53.8–66.7), specificity was 97.9% (95.4–99.1), while the accordance between GLIM and PG-SGA was moderate (κ = 0.614). The performance of the GLIM worsened when MMR was excluded (κ = 0.515), with reduced sensitivity (50.2% (43.7–56.8)) and the same specificity (97.9% (95.4–99.1)). Including FFMI and ASMI by BIA can further improve the performance of GLIM than using CC alone (κ = 0.614 vs. κ = 0.565). Conclusions: It is important to include MMR in the GLIM framework. Using body composition measurement further improves the performance of the GLIM criteria than using anthropometric measurement alone.

IGF-I, Growth, and Body Composition in Preterm Infants up to Term Equivalent Age

Context There are concerns that a higher fat mass in the early life of preterm infants is associated with adverse cardiometabolic outcomes in young adulthood. Objective To investigate the role of IGF-I and growth in determining body composition of preterm infants at term equivalent age. Methods An observational study was conducted from August 2015 to August 2018. From birth to term equivalent age, IGF-I levels were measured bi-weekly and growth was assessed weekly. At term equivalent age, body composition was assessed through air displacement plethysmography; 65 infants with a gestational age of 24 to 32 weeks were assessed at term equivalent age, of whom 58 completed body composition measurement. The main outcome measures were fat (free) mass (g) and fat (free) mass percentage at term equivalent age. Results In the first month of life, each 0.1 nmol/L per week increase in IGF-I was associated with a 465 g (SE 125 g) increase in fat free mass. A greater increase in weight SDS in the first month of life was associated with a higher fat free mass percentage (B 200.9; 95% CI, 12.1-389.6). A higher head circumference SDS was associated with more fat free mass (r = 0.46; 95% CI, 0.21-0.65). However, a greater increase in weight SDS up to term equivalent age was associated with a lower fat free mass percentage (B −55.7, SE 9.4). Conclusion These findings suggest that impaired growth in the first month of life is associated with a less favorable body composition at term equivalent age.

Application of a New Method for Simultaneous Phase and Baseline Correction of NMR Signals (SINC)

Recently, we presented a new approach for simultaneous phase and baseline correction of nuclear magnetic resonance (NMR) signals (SINC) that is based on multiobjective optimization. The algorithm can automatically correct large sets of NMR spectra, which are commonly acquired when reactions and processes are monitored with NMR spectroscopy. The aim of the algorithm is to provide spectra that can be evaluated quantitatively, for example, to calculate the composition of a mixture or the extent of reaction. In this work, the SINC algorithm is tested in three different studies. In an in‐house comparison study, spectra of different mixtures were corrected both with the SINC method and manually by different experienced users. The study shows that the results of the different users vary significantly and that their average uncertainty of the composition measurement is larger than the uncertainty obtained when the spectra are corrected with the SINC method. By means of a dilution study, we demonstrate that the SINC method is also applicable for the correction of spectra with low signal‐to‐noise ratio. Furthermore, a large set of NMR spectra that was acquired to follow a reaction was corrected with the SINC method. Even in this system, where the areas of the peaks and their chemical shifts changed during the course of reaction, the SINC method corrected the spectra robustly. The results show that this method is especially suited to correct large sets of NMR spectra and it is thus an important contribution for the automation of the evaluation of NMR spectra.