RESUMO
Introduction: Bioelectrical impedance analysis (BIA) serves as a method to estimate body composition. Parameters such as phase angle (PA), standardized phase angle (SPA), body mass cell (BCM), BCM index (BCMI), and fat-free mass (FFM) might significantly impact the prognosis of head and neck cancer (HNC) patients. The present study aimed to investigate whether bioelectrical parameters can be used to predict survival in the HNC population and establish the optimal cutoff points for predictive accuracy. Methods: A multicenter observational study was performed across 12 tertiary hospitals in Andalusia (a region from the south of Spain). A total of 494 patients diagnosed with HNC between 2020 and 2022 at different stages were included in this study, with a minimum follow-up period of 12 months. The BIA assessment was carried out during the first 2 weeks of radical radiotherapy treatment with chemotherapy or other systemic treatments. A multivariate logistic regression analysis of overall survival, complications, hospital admission, and palliative care and its relationship with BIA nutritional assessment was performed. Results: Significant prognostic factors identified in the multivariable analysis encompassed phase angle (PA), standardized phase angle (SPA), body cell mass (BCM), and BCM index (BCMI). Lower PA and BCM values were significantly associated with adverse clinical outcomes. A BCM threshold above 17 kg/m2 was the most significant predictor for predicting survival within the overall HNC population. The PA values of <5.1° in male and <4.8° in female patients showed the best predictive potential for mortality. Increased PA (as a continuous variable) demonstrated a significantly reduced risk for mortality (OR, 0.64; 95% CI, 0.43-0.94; p < 0.05) and a decreased likelihood of hospital admission (OR, 0.75; 95% CI, 0.52-1.07; p < 0.05). Higher BCM correlated with a lower risk of mortality (OR, 0.88; 95% CI, 0.80-0.96; p < 0.01) and a diminished probability of hospital admission (OR, 0.91; 95% CI, 0.83-0.99; p < 0.05). Conclusion: BIA is a crucial tool in the nutritional assessment of HNC patients. BCM and PA are the main bioelectrical parameters used to predict clinical outcomes in this population. Future studies are needed to validate BIA variables in a large cohort to ensure whether early intensification of nutritional treatment would improve survival.
RESUMO
BACKGROUND: Sarcopenia has recently been recognized as a complication of diabetes. However, there are few results about the prevalence of sarcopenia and dynapenia and the related clinical outcomes in type 1 diabetes mellitus (T1DM). Our objectives were to evaluate the prevalence of sarcopenia and dynapenia and to determine whether there are any associations with disease-related factors in people with T1DM. METHODS: A cross-sectional study was conducted in people with T1DM. We assessed appendicular skeletal mass index (ASMI) using bioimpedance 50 Hz (Nutrilab Akern). Muscle function was assessed through handgrip strength (HGS) using a Jamar dynamometer. Sarcopenia was defined as a low HGS with low ASMI, whereas dynapenia was defined as low HGS with a normal ASMI. We used HGS data from the Spanish population percentile table and a cut-off point at p5 as dynapenia. The association of clinical, metabolic, and lifestyle variables with sarcopenia and dynapenia was studied. RESULTS: This study included 62 T1DM patients (66% females, mean age of 38 ± 14 years, body mass index (BMI) of 24.9 ± 4.7 kg/m2). The prevalence of sarcopenia and dynapenia was 8% and 23%, respectively. In our sample, there were more men in the sarcopenic and dynapenic groups. The sarcopenic group showed a significantly higher mean HbA1c value. Lower diabetes duration, PREDIMED score, BMI, and muscle mass measures (fat-free mass index (FFMI), ASMI, and body cell mass index (BCMI)) were significantly associated with sarcopenia. Decreased diabetes duration, PREDIMED score, phase angle (PhA), and HGS values showed a significant association with dynapenia. CONCLUSIONS: The prevalence of sarcopenia and dynapenia was high in people with T1DM in our study. Specifically, the proportion of dynapenia was quite high. HGS and ASMI are practical tools for the assessment of muscle health status in T1DM, and low values are associated with poor glycemic control, underweight, and low adherence to the Mediterranean diet. Thus, dynapenia may predict accelerated muscle aging in T1DM.