Appetite and Nutritional Status as Potential Management Targets in Patients with Heart Failure with Reduced Ejection Fraction—The Relationship between Echocardiographic and Biochemical Parameters and Appetite

This study aimed to investigate the role of appetite loss and malnutrition in patients with heart failure with reduced ejection fraction (HFrEF). In this prospective, observational, single-center study, we enrolled 120 consecutive adults with HFrEF. We analyzed the selected clinical, echocardiographic, and biochemical parameters. Appetite loss and malnutrition were assessed by CNAQ (Council on Nutrition Appetite Questionnaire) and MNA (Mini Nutritional Assessment)/GNRI (Geriatric Nutritional Risk Index) questionnaires, respectively.Most patients were men (81.7%), mean age was 55.1 ± 11.3 years, and mean left ventricular ejection fraction was 23.9 ± 8.0%. The mean CNAQ score was 28.8 ± 3.9, mean MNA—23.1 ± 2.6, and mean GNRI—113.0 ± 12.3. Based on ROC curves, we showed that a sodium concentration <138 mmol/L had the greatest discriminating power for diagnosing impaired nutritional status (MNA ≤ 23.5) with a sensitivity of 54.5% and specificity of 77.8%. The threshold of HDL <0.97 mmol/L characterized 40.7% sensitivity and 86% specificity, B-type natriuretic peptide >738.6 pg/dL had 48.5% sensitivity and 80.8% specificity, high-sensitivity C-reactive protein >1.8 mg/L had 94.9% sensitivity and 42.9% specificity, and bilirubin >15 µmol/L had 78.2% sensitivity and 56.9% specificity. Nutritional status and appetite assessed by MNA/GNRI and CNAQ questionnaires showed poor correlations with other findings in HFrEF patients

Relationship between Nutritional Status and Clinical and Biochemical Parameters in Hospitalized Patients with Heart Failure with Reduced Ejection Fraction, with 1-year Follow-Up

Heart Failure (HF) is a cardiovascular disease with continually increasing morbidity and high mortality. The purpose of this study was to analyze nutritional status in patients diagnosed with HF with reduced ejection fraction (HFrEF) and evaluate the impact of malnutrition on their prognosis. The Polish version of MNA form (Mini Nutritional Assessment) was used to assess the patients’ nutritional status. The New York Heart Association (NYHA) class, exacerbation of HF, chosen echocardiographic and biochemical parameters, e.g., natriuretic peptides or serum albumin, were also analyzed. Among the 120 consecutive patients, 47 (39%) had a normal nutritional status, 62 (52%) were at risk of malnutrition and 11 (9%) were malnourished. The patients with malnutrition more frequently presented with HF exacerbation in comparison to those with normal nutritional status (82% vs. 30% respectively, p = 0.004). There were no significant differences between the investigated groups as to natriuretic peptides; however, both the malnourished patients and those at risk of malnutrition tend to show higher B-type natriuretic peptide (BNP) and NT-proBNP concentrations. During the average 344 days of follow-up 19 patients died and 25 were hospitalized due to decompensated HF. Malnutrition or being at risk of malnutrition seems to be associated with both worse outcomes and clinical status in HFrEF patients

Application of Artificial Neural Networks for Yield Modeling of Winter Rapeseed Based on Combined Quantitative and Qualitative Data

Rapeseed is considered as one of the most important oilseed crops in the world. Vegetable oil obtained from rapeseed is a valuable raw material for the food and energy industry as well as for industrial applications. Compared to other vegetable oils, it has a lower concentration of saturated fatty acids (5%–10%), a higher content of monounsaturated fatty acids (44%–75%), and a moderate content of alpha-linolenic acid (9%–13%). Overall, rapeseed is grown in all continents on an industrial scale, so there is a growing need to predict yield before harvest. A combination of quantitative and qualitative data were used in this work in order to build three independent prediction models, on the basis of which yield simulations were carried out. Empirical data collected during field tests carried out in 2008–2015 were used to build three models, QQWR15_4, QQWR31_5, and QQWR30_6. Each model was composed of a different number of independent variables, ranging from 21 to 27. The lowest MAPE (mean absolute percentage error) yield prediction error corresponded to QQWR31_5, it was 6.88%, and the coefficient of determination R2 was 0.69. As a result of the sensitivity analysis of the neural network, the most important independent variable influencing the final rapeseed yield was indicated, and for all the analyzed models it was “The kind of sowing date in the previous year” (KSD_PY)

Parental Report via a Mobile App in the Context of Early Language Trajectories: StarWords Study Protocol

Social sciences researchers emphasize that new technologies can overcome the limitations of small and homogenous samples. In research on early language development, which often uses parental reports, taking the testing online might be particularly compelling. Due to logistical limitations, previous studies on bilingual children have explored the language development trajectories in general (e.g., by including few and largely set apart timepoints), or focused on small, homogeneous samples. The present study protocol presents a new, on-going study which uses new technologies to collect longitudinal data continuously from parents of multilingual, bilingual, and monolingual children. Our primary aim is to establish the developmental trajectories in Polish-British English and Polish-Norwegian bilingual children and Polish monolingual children aged 0–3 years with the use of mobile and web-based applications. These tools allow parents to report their children’s language development as it progresses, and allow us to characterize children’s performance in each language (the age of reaching particular language milestones). The project’s novelty rests on its use of mobile technologies to characterize the bilingual and monolingual developmental trajectory from the very first words to broader vocabulary and multiword combinations

Parental Report via a Mobile App in the Context of Early Language Trajectories: StarWords Study Protocol

Social sciences researchers emphasize that new technologies can overcome the limitations of small and homogenous samples. In research on early language development, which often uses parental reports, taking the testing online might be particularly compelling. Due to logistical limitations, previous studies on bilingual children have explored the language development trajectories in general (e.g., by including few and largely set apart timepoints), or focused on small, homogeneous samples. The present study protocol presents a new, on-going study which uses new technologies to collect longitudinal data continuously from parents of multilingual, bilingual, and monolingual children. Our primary aim is to establish the developmental trajectories in Polish-British English and Polish-Norwegian bilingual children and Polish monolingual children aged 0–3 years with the use of mobile and web-based applications. These tools allow parents to report their children’s language development as it progresses, and allow us to characterize children’s performance in each language (the age of reaching particular language milestones). The project’s novelty rests on its use of mobile technologies to characterize the bilingual and monolingual developmental trajectory from the very first words to broader vocabulary and multiword combinations

Parental Report via a Mobile App in the Context of Early Language Trajectories: StarWords Study Protocol.

Social sciences researchers emphasize that new technologies can overcome the limitations of small and homogenous samples. In research on early language development, which often uses parental reports, taking the testing online might be particularly compelling. Due to logistical limitations, previous studies on bilingual children have explored the language development trajectories in general (e.g., by including few and largely set apart timepoints), or focused on small, homogeneous samples. The present study protocol presents a new, on-going study which uses new technologies to collect longitudinal data continuously from parents of multilingual, bilingual, and monolingual children. Our primary aim is to establish the developmental trajectories in Polish-British English and Polish-Norwegian bilingual children and Polish monolingual children aged 0-3 years with the use of mobile and web-based applications. These tools allow parents to report their children's language development as it progresses, and allow us to characterize children's performance in each language (the age of reaching particular language milestones). The project's novelty rests on its use of mobile technologies to characterize the bilingual and monolingual developmental trajectory from the very first words to broader vocabulary and multiword combinations

Diet and Lifestyle Intervention-Induced Pattern of Weight Loss Related to Reduction in Low-Attenuation Coronary Plaque Burden

Background: Despite extensive research on body weight and cardiovascular risk, the mechanistic relationship between weight loss and coronary plaque modification has not been adequately addressed. This study aimed to determine the association between body composition dynamics and low-attenuation coronary plaque (LAP) burden. Methods: Eighty-nine participants (40% women, 60 ± 7.7 years) of the Dietary Intervention to Stop Coronary Atherosclerosis in Computed Tomography (DISCO-CT) study with non-obstructive atherosclerosis with nonobstructive atherosclerosis confirmed in computed tomography angiography (CCTA), a randomized (1:1), prospective, single-center study were included into the analysis. Patients were randomly assigned to either experimental arm (intensive diet and lifestyle intervention atop optimal medical therapy, n = 45) or control arm (optimal medical therapy alone, n = 44) over 66.8 ± 13.7 weeks. Changes (∆) in body mass (BM) and body composition parameters, including total body fat (TBF), skeletal muscle mass (SMM), and fat-to-muscle ratio (FMR), measured with bioimpedance analyzer were compared with CCTA-measured ∆LAP. Coronary plaque analysis was performed using the 2 × 192 dual-energy scanner (Somatom Force, Siemens, Germany), while quantitative coronary plaque measurements were performed using a semi-automated plaque analysis software system (QAngioCT v3.1.3.13, Medis Medical Imaging Systems, Leiden, The Netherlands). Results: Significant intergroup differences were found for ∆BM (−3.6 ± 4.9 kg in the experimental vs. −1.4 ± 2.9 kg in the control group, p = 0.015), ∆TBF (−3.4 ± 4.8% in the experimental vs. 1.1 ± 5.5% in the control arm, p p p p p = 0.004; r = 0.233, p = 0.028, respectively), and negatively with ∆SMM (r = −0.285, p = 0.007). Multivariate linear regression analysis revealed the association of ∆LAP with ∆BM, ∆TBF, and ∆FMR. Conclusions: The study intervention resulted in BM reduction characterized by fat loss, skeletal muscle gain, and increased FMR. This weight loss pattern may lead to a reduction in high-risk coronary plaque. Compared to a simple weight control, tracking body composition changes over time can provide valuable information on adverse coronary plaque modification