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Background Digital technologies have evolved dramatically in recent years, finding applications in a variety of aspects of everyday life. Smartphones and mobile apps are being used for a steadily increasing number of tasks, including health monitoring. A large number of nutrition and diet apps are available, and some of them are very popular in terms of user downloads, highlighting a trend toward diet monitoring and assessment. Objective We sought to explore the perspectives of end users on the features, current use, and acceptance of nutrition and diet mHealth apps with a survey. We expect that this study can provide user insights to assist researchers and developers in achieving innovative dietary assessments. Methods A multidisciplinary team designed and compiled the survey. Before its release, it was pilot-tested by 18 end users. A 19-question survey was finally developed and was translated into six languages: English, German, French, Spanish, Italian, and Greek. The participants were mainly recruited via social media platforms and mailing lists of universities, university hospitals, and patient associations. Results A total of 2382 respondents (1891 female, 79.4%; 474 male, 19.9%; and 17 neither, 0.7%) with a mean age of 27.2 years (SD 8.5) completed the survey. Approximately half of the participants (1227/2382, 51.5%) had used a nutrition and diet app. The primary criteria for selecting such an app were ease of use (1570/2382, 65.9%), free cost (1413/2382, 59.3%), and ability to produce automatic readings of caloric content (1231/2382, 51.7%) and macronutrient content (1117/2382, 46.9%) (ie, food type and portion size are estimated by the system without any contribution from the user). An app was less likely to be selected if it incorrectly estimated portion size, calories, or nutrient content (798/2382, 33.5%). Other important limitations included the use of a database that does not include local foods (655/2382, 27.5%) or that may omit major foods (977/2382, 41%). Conclusions This comprehensive study in a mostly European population assessed the preferences and perspectives of potential nutrition and diet app users. Understanding user needs will benefit researchers who develop tools for innovative dietary assessment as well as those who assist research on behavioral changes related to nutrition.
Maria F Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study. JMIR mHealth and uHealth 2021, 9, e27885 .
AMA StyleMaria F Vasiloglou, Stergios Christodoulidis, Emilie Reber, Thomai Stathopoulou, Ya Lu, Zeno Stanga, Stavroula Mougiakakou. Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study. JMIR mHealth and uHealth. 2021; 9 (7):e27885.
Chicago/Turabian StyleMaria F Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. 2021. "Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study." JMIR mHealth and uHealth 9, no. 7: e27885.
Background Disease-related malnutrition is highly prevalent in hospitalized medical and geriatric inpatients. It is associated with negative outcomes such as muscle wasting, decline of functional status, and increased morbidity and mortality. Oral nutritional supplements (ONS) are frequently used in nutritional therapy to increase intake. However, compliance to ONS is often limited and maybe improved by prescribing ONS in small portions timed with the medication (MEDPass). However, it is unknown whether the MEDPass administration enhances patients’ total energy and protein intake. Methods The MEDPass Trial is a randomized, controlled, open-label superiority trial. Patients in the MEDPass group receive 50 ml of ONS four times per day, distributed with the medication rounds. Patients in the control group receive ONS between meals. The primary outcome is average daily energy intake (% of calculated daily requirement). For our power analysis, we assumed that administration of ONS in the MEDPass administration mode increases energy intake by at least 10% (i.e., by 200 kcal for an average energy requirement of 2200 kcal/day). Thus, with the inclusion of 200 patients, this trial has 80% power to demonstrate that intervention group patients have an average intake of 2200 kcal/day (SD 500 kcal) versus 2000 kcal/day (SD 500 kcal) in control group patients. Energy and protein intakes from ONS and all food consumed are monitored continuously throughout the hospital stay and are statistically compared to the patient’s requirements. Secondary outcomes include average daily protein intake (% of calculated daily requirement), average intake of ONS/day, the course of body weight, handgrip strength, appetite, and nausea. Furthermore, hospital length of stay and 30-day mortality are assessed. The primary statistical analysis will be performed as an intention-to-treat analysis adjusted for the stratification factors used in randomization. Discussion To our knowledge, this is the first randomized controlled trial assessing total energy and protein intake for the entire hospitalization period in patients receiving MEDPass versus conventional ONS administration. Thus, the MEDPass Trial will fill a gap and answer this relevant clinical question. Trial registration ClinicalTrials.gov NCT03761680. Registered on 3 December 2018. Kofam.ch SNCTP000003191. Registered on 15 October 2018
Silvia Kurmann; Emilie Reber; Maria F. Vasiloglou; Philipp Schuetz; Andreas W. Schoenenberger; Katja Uhlmann; Anna-Barbara Sterchi; Zeno Stanga. Energy and protein intake in medical and geriatric inpatients with MEDPass versus conventional administration of oral nutritional supplements: study protocol for the randomized controlled MEDPass Trial. Trials 2021, 22, 1 -11.
AMA StyleSilvia Kurmann, Emilie Reber, Maria F. Vasiloglou, Philipp Schuetz, Andreas W. Schoenenberger, Katja Uhlmann, Anna-Barbara Sterchi, Zeno Stanga. Energy and protein intake in medical and geriatric inpatients with MEDPass versus conventional administration of oral nutritional supplements: study protocol for the randomized controlled MEDPass Trial. Trials. 2021; 22 (1):1-11.
Chicago/Turabian StyleSilvia Kurmann; Emilie Reber; Maria F. Vasiloglou; Philipp Schuetz; Andreas W. Schoenenberger; Katja Uhlmann; Anna-Barbara Sterchi; Zeno Stanga. 2021. "Energy and protein intake in medical and geriatric inpatients with MEDPass versus conventional administration of oral nutritional supplements: study protocol for the randomized controlled MEDPass Trial." Trials 22, no. 1: 1-11.
BACKGROUND Digital technologies have evolved dramatically in recent years, finding applications in a variety of aspects of everyday life. Smartphones and mobile apps are being used for a steadily increasing number of tasks, including health monitoring. A large number of nutrition and diet apps are available, and some of them are very popular in terms of user downloads, highlighting a trend toward diet monitoring and assessment. OBJECTIVE We sought to explore the perspectives of end users on the features, current use, and acceptance of nutrition and diet mHealth apps with a survey. We expect that this study can provide user insights to assist researchers and developers in achieving innovative dietary assessments. METHODS A multidisciplinary team designed and compiled the survey. Before its release, it was pilot-tested by 18 end users. A 19-question survey was finally developed and was translated into six languages: English, German, French, Spanish, Italian, and Greek. The participants were mainly recruited via social media platforms and mailing lists of universities, university hospitals, and patient associations. RESULTS A total of 2382 respondents (1891 female, 79.4%; 474 male, 19.9%; and 17 neither, 0.7%) with a mean age of 27.2 years (SD 8.5) completed the survey. Approximately half of the participants (1227/2382, 51.5%) had used a nutrition and diet app. The primary criteria for selecting such an app were ease of use (1570/2382, 65.9%), free cost (1413/2382, 59.3%), and ability to produce automatic readings of caloric content (1231/2382, 51.7%) and macronutrient content (1117/2382, 46.9%) (ie, food type and portion size are estimated by the system without any contribution from the user). An app was less likely to be selected if it incorrectly estimated portion size, calories, or nutrient content (798/2382, 33.5%). Other important limitations included the use of a database that does not include local foods (655/2382, 27.5%) or that may omit major foods (977/2382, 41%). CONCLUSIONS This comprehensive study in a mostly European population assessed the preferences and perspectives of potential nutrition and diet app users. Understanding user needs will benefit researchers who develop tools for innovative dietary assessment as well as those who assist research on behavioral changes related to nutrition.
Maria F Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study (Preprint). 2021, 1 .
AMA StyleMaria F Vasiloglou, Stergios Christodoulidis, Emilie Reber, Thomai Stathopoulou, Ya Lu, Zeno Stanga, Stavroula Mougiakakou. Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study (Preprint). . 2021; ():1.
Chicago/Turabian StyleMaria F Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. 2021. "Perspectives and Preferences of Adult Smartphone Users Regarding Nutrition and Diet Apps: Web-Based Survey Study (Preprint)." , no. : 1.
Background Technological advancements have enabled nutrient estimation by smartphone apps such as goFOOD. This is an artificial intelligence–based smartphone system, which uses food images or video captured by the user as input and then translates these into estimates of nutrient content. The quality of the data is highly dependent on the images the user records. This can lead to a major loss of data and impaired quality. Instead of removing these data from the study, in-depth analysis is needed to explore common mistakes and to use them for further improvement of automated apps for nutrition assessment. Objective The aim of this study is to analyze common mistakes made by participants using the goFOOD Lite app, a version of goFOOD, which was designed for food-logging, but without providing results to the users, to improve both the instructions provided and the automated functionalities of the app. Methods The 48 study participants were given face-to-face instructions for goFOOD Lite and were asked to record 2 pictures (1 recording) before and 2 pictures (1 recording) after the daily consumption of each food or beverage, using a reference card as a fiducial marker. All pictures that were discarded for processing due to mistakes were analyzed to record the main mistakes made by users. Results Of the 468 recordings of nonpackaged food items captured by the app, 60 (12.8%) had to be discarded due to errors in the capturing procedure. The principal problems were as follows: wrong fiducial marker or improper marker use (19 recordings), plate issues such as a noncompatible or nonvisible plate (8 recordings), a combination of various issues (17 recordings), and other reasons such as obstacles (hand) in front of the camera or matching recording pairs (16 recordings). Conclusions No other study has focused on the principal problems in the use of automatic apps for assessing nutritional intake. This study shows that it is important to provide study participants with detailed instructions if high-quality data are to be obtained. Future developments could focus on making it easier to recognize food on various plates from its color or shape and on exploring alternatives to using fiducial markers. It is also essential for future studies to understand the training needed by the participants as well as to enhance the app’s user-friendliness and to develop automatic image checks based on participant feedback.
Maria F Vasiloglou; Klazine Van Der Horst; Thomai Stathopoulou; Michael P Jaeggi; Giulia S Tedde; Ya Lu; Stavroula Mougiakakou. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App. JMIR mHealth and uHealth 2021, 9, e24467 .
AMA StyleMaria F Vasiloglou, Klazine Van Der Horst, Thomai Stathopoulou, Michael P Jaeggi, Giulia S Tedde, Ya Lu, Stavroula Mougiakakou. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App. JMIR mHealth and uHealth. 2021; 9 (1):e24467.
Chicago/Turabian StyleMaria F Vasiloglou; Klazine Van Der Horst; Thomai Stathopoulou; Michael P Jaeggi; Giulia S Tedde; Ya Lu; Stavroula Mougiakakou. 2021. "The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App." JMIR mHealth and uHealth 9, no. 1: e24467.
The Mediterranean diet (MD) is regarded as a healthy eating pattern with beneficial effects both for the decrease of the risk for non-communicable diseases and also for body weight reduction. In the current manuscript, we propose an automated smartphone application which monitors and evaluates the user’s adherence to MD using images of the food and drinks that they consume. We define a set of rules for automatic adherence estimation, which focuses on the main MD food groups. We use a combination of a convolutional neural network (CNN) and a graph convolutional network to detect the types of foods and quantities from the users’ food images and the defined set of rules to evaluate the adherence to MD. Our experiments show that our system outperforms a basic CNN in terms of recognizing food items and estimating quantity and yields comparable results as experienced dietitians when it comes to overall MD adherence estimation. As the system is novel, these results are promising; however, there is room for improvement of the accuracy by gathering and training with more data and certain refinements can be performed such as re-defining the set of rules to also be able to be used for sub-groups of MD (e.g., vegetarian type of MD).
Maria F. Vasiloglou; Ya Lu; Thomai Stathopoulou; Ioannis Papathanail; David Faeh; Arindam Ghosh; Manuel Baumann; Stavroula Mougiakakou. Assessing Mediterranean Diet Adherence with the Smartphone: The Medipiatto Project. Nutrients 2020, 12, 3763 .
AMA StyleMaria F. Vasiloglou, Ya Lu, Thomai Stathopoulou, Ioannis Papathanail, David Faeh, Arindam Ghosh, Manuel Baumann, Stavroula Mougiakakou. Assessing Mediterranean Diet Adherence with the Smartphone: The Medipiatto Project. Nutrients. 2020; 12 (12):3763.
Chicago/Turabian StyleMaria F. Vasiloglou; Ya Lu; Thomai Stathopoulou; Ioannis Papathanail; David Faeh; Arindam Ghosh; Manuel Baumann; Stavroula Mougiakakou. 2020. "Assessing Mediterranean Diet Adherence with the Smartphone: The Medipiatto Project." Nutrients 12, no. 12: 3763.
BACKGROUND Technological advancements have enabled nutrient estimation by smartphone apps such as goFOOD. This is an artificial intelligence–based smartphone system, which uses food images or video captured by the user as input and then translates these into estimates of nutrient content. The quality of the data is highly dependent on the images the user records. This can lead to a major loss of data and impaired quality. Instead of removing these data from the study, in-depth analysis is needed to explore common mistakes and to use them for further improvement of automated apps for nutrition assessment. OBJECTIVE The aim of this study is to analyze common mistakes made by participants using the goFOOD Lite app, a version of goFOOD, which was designed for food-logging, but without providing results to the users, to improve both the instructions provided and the automated functionalities of the app. METHODS The 48 study participants were given face-to-face instructions for goFOOD Lite and were asked to record 2 pictures (1 recording) before and 2 pictures (1 recording) after the daily consumption of each food or beverage, using a reference card as a fiducial marker. All pictures that were discarded for processing due to mistakes were analyzed to record the main mistakes made by users. RESULTS Of the 468 recordings of nonpackaged food items captured by the app, 60 (12.8%) had to be discarded due to errors in the capturing procedure. The principal problems were as follows: wrong fiducial marker or improper marker use (19 recordings), plate issues such as a noncompatible or nonvisible plate (8 recordings), a combination of various issues (17 recordings), and other reasons such as obstacles (hand) in front of the camera or matching recording pairs (16 recordings). CONCLUSIONS No other study has focused on the principal problems in the use of automatic apps for assessing nutritional intake. This study shows that it is important to provide study participants with detailed instructions if high-quality data are to be obtained. Future developments could focus on making it easier to recognize food on various plates from its color or shape and on exploring alternatives to using fiducial markers. It is also essential for future studies to understand the training needed by the participants as well as to enhance the app’s user-friendliness and to develop automatic image checks based on participant feedback.
Maria F Vasiloglou; Klazine Van Der Horst; Thomai Stathopoulou; Michael P Jaeggi; Giulia S Tedde; Ya Lu; Stavroula Mougiakakou. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App (Preprint). 2020, 1 .
AMA StyleMaria F Vasiloglou, Klazine Van Der Horst, Thomai Stathopoulou, Michael P Jaeggi, Giulia S Tedde, Ya Lu, Stavroula Mougiakakou. The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App (Preprint). . 2020; ():1.
Chicago/Turabian StyleMaria F Vasiloglou; Klazine Van Der Horst; Thomai Stathopoulou; Michael P Jaeggi; Giulia S Tedde; Ya Lu; Stavroula Mougiakakou. 2020. "The Human Factor in Automated Image-Based Nutrition Apps: Analysis of Common Mistakes Using the goFOOD Lite App (Preprint)." , no. : 1.
Accurate estimation of nutritional information may lead to healthier diets and better clinical outcomes. We propose a dietary assessment system based on artificial intelligence (AI), named goFOODTM . The system can estimate the calorie and macronutrient content of a meal, on the sole basis of food images captured by a smartphone. goFOODTM requires an input of two meal images or a short video. For conventional single-camera smartphones, the images must be captured from two different viewing angles; smartphones equipped with two rear cameras require only a single press of the shutter button. The deep neural networks are used to process the two images and implements food detection, segmentation and recognition, while a 3D reconstruction algorithm estimates the food’s volume. Each meal’s calorie and macronutrient content is calculated from the food category, volume and the nutrient database. goFOODTM supports 319 fine-grained food categories, and has been validated on two multimedia databases that contain non-standardized and fast food meals. The experimental results demonstrate that goFOODTM performed better than experienced dietitians on the non-standardized meal database, and was comparable to them on the fast food database. goFOODTM provides a simple and efficient solution to the end-user for dietary assessment.
Ya Lu; Thomai Stathopoulou; Maria F. Vasiloglou; Lillian F. Pinault; Colleen Kiley; Elias K. Spanakis; Stavroula Mougiakakou. goFOODTM : An Artificial Intelligence System for Dietary Assessment. Sensors 2020, 20, 4283 .
AMA StyleYa Lu, Thomai Stathopoulou, Maria F. Vasiloglou, Lillian F. Pinault, Colleen Kiley, Elias K. Spanakis, Stavroula Mougiakakou. goFOODTM : An Artificial Intelligence System for Dietary Assessment. Sensors. 2020; 20 (15):4283.
Chicago/Turabian StyleYa Lu; Thomai Stathopoulou; Maria F. Vasiloglou; Lillian F. Pinault; Colleen Kiley; Elias K. Spanakis; Stavroula Mougiakakou. 2020. "goFOODTM : An Artificial Intelligence System for Dietary Assessment." Sensors 20, no. 15: 4283.
Accurate dietary assessment is crucial for both the prevention and treatment of nutrition-related diseases. Since mobile-based dietary assessment solutions are promising, we sought to examine the acceptability of ″Nutrition and Diet″ (ND) apps by Healthcare Professionals (HCP), explore their preferences on apps′ features and identify predictors of acceptance. A 23 question survey was developed by an interdisciplinary team and pilot-tested. The survey was completed by 1001 HCP from 73 countries and 6 continents. The HCP (dietitians: 833, doctors: 75, nurses: 62, other: 31/females: 847, males: 150, neither: 4) had a mean age (SD) of 34.4 (10.2) years and mean job experience in years (SD): 7.7 (8.2). There were 45.5% who have recommended ND apps to their clients/patients. Of those who have not yet recommended an app, 22.5% do not know of their existence. Important criteria for selecting an app were ease of use (87.1%), apps being free of charge (72.6%) and validated (69%). Significant barriers were the use of inaccurate food composition database (52%), lack of local food composition database support (48.2%) and tech-savviness (43.3%). Although the adoption of smartphones is growing and mobile health research is advancing, there is room for improvement in the recommendation of ND apps by HCP.
Maria F. Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. What Healthcare Professionals Think of ″Nutrition & Diet″ Apps: An International Survey. Nutrients 2020, 12, 2214 .
AMA StyleMaria F. Vasiloglou, Stergios Christodoulidis, Emilie Reber, Thomai Stathopoulou, Ya Lu, Zeno Stanga, Stavroula Mougiakakou. What Healthcare Professionals Think of ″Nutrition & Diet″ Apps: An International Survey. Nutrients. 2020; 12 (8):2214.
Chicago/Turabian StyleMaria F. Vasiloglou; Stergios Christodoulidis; Emilie Reber; Thomai Stathopoulou; Ya Lu; Zeno Stanga; Stavroula Mougiakakou. 2020. "What Healthcare Professionals Think of ″Nutrition & Diet″ Apps: An International Survey." Nutrients 12, no. 8: 2214.
Regular monitoring of nutrient intake in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition. Although several methods to estimate nutrient intake have been developed, there is still a clear demand for a more reliable and fully automated technique, as this could improve data accuracy and reduce both the burden on participants and health costs. In this paper, we propose a novel system based on artificial intelligence (AI) to accurately estimate nutrient intake, by simply processing RGB Depth (RGB-D) image pairs captured before and after meal consumption. The system includes a novel multi-task contextual network for food segmentation, a few-shot learning-based classifier built by limited training samples for food recognition, and an algorithm for 3D surface construction. This allows sequential food segmentation, recognition, and estimation of the consumed food volume, permitting fully automatic estimation of the nutrient intake for each meal. For the development and evaluation of the system, a dedicated new database containing images and nutrient recipes of 322 meals is assembled, coupled to data annotation using innovative strategies. Experimental results demonstrate that the estimated nutrient intake is highly correlated (> 0.91) to the ground truth and shows very small mean relative errors (< 20%), outperforming existing techniques proposed for nutrient intake assessment.
Ya Lu; Thomai Stathopoulou; Maria Vasiloglou; Stergios Christodoulidis; Zeno Stanga; Stavroula Mougiakakou. An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients. IEEE Transactions on Multimedia 2020, 23, 1136 -1147.
AMA StyleYa Lu, Thomai Stathopoulou, Maria Vasiloglou, Stergios Christodoulidis, Zeno Stanga, Stavroula Mougiakakou. An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients. IEEE Transactions on Multimedia. 2020; 23 (99):1136-1147.
Chicago/Turabian StyleYa Lu; Thomai Stathopoulou; Maria Vasiloglou; Stergios Christodoulidis; Zeno Stanga; Stavroula Mougiakakou. 2020. "An Artificial Intelligence-Based System to Assess Nutrient Intake for Hospitalised Patients." IEEE Transactions on Multimedia 23, no. 99: 1136-1147.
Refeeding syndrome (RFS) is the metabolic response to the switch from starvation to a fed state in the initial phase of nutritional therapy in patients who are severely malnourished or metabolically stressed due to severe illness. It is characterized by increased serum glucose, electrolyte disturbances (particularly hypophosphatemia, hypokalemia, and hypomagnesemia), vitamin depletion (especially vitamin B1 thiamine), fluid imbalance, and salt retention, with resulting impaired organ function and cardiac arrhythmias. The awareness of the medical and nursing staff is often too low in clinical practice, leading to under-diagnosis of this complication, which often has an unspecific clinical presentation. This review provides important insights into the RFS, practical recommendations for the management of RFS in the medical inpatient population (excluding eating disorders) based on consensus opinion and on current evidence from clinical studies, including risk stratification, prevention, diagnosis, and management and monitoring of nutritional and fluid therapy.
Emilie Reber; Natalie Friedli; Maria F. Vasiloglou; Philipp Schuetz; Zeno Stanga. Management of Refeeding Syndrome in Medical Inpatients. Journal of Clinical Medicine 2019, 8, 2202 .
AMA StyleEmilie Reber, Natalie Friedli, Maria F. Vasiloglou, Philipp Schuetz, Zeno Stanga. Management of Refeeding Syndrome in Medical Inpatients. Journal of Clinical Medicine. 2019; 8 (12):2202.
Chicago/Turabian StyleEmilie Reber; Natalie Friedli; Maria F. Vasiloglou; Philipp Schuetz; Zeno Stanga. 2019. "Management of Refeeding Syndrome in Medical Inpatients." Journal of Clinical Medicine 8, no. 12: 2202.
Swallowing difficulties, also called dysphagia, can have various causes and may occur at many points in the swallowing process. The treatment and rehabilitation of dysphagia represent a major interdisciplinary and multiprofessional challenge. In dysphagic patients, dehydration is frequent and often accelerated as a result of limited fluid intake. This condition results from loss of water from the intracellular space, disturbing the normal levels of electrolytes and fluid interfering with metabolic processes and body functions. Dehydration is associated with increased morbidity and mortality rates. Dysphagic patients at risk of dehydration thus require close monitoring of their hydration state, and existing imbalances should be addressed quickly. This review gives an overview on dehydration, as well as its pathophysiology, risk factors, and clinical signs/symptoms in general. Available management strategies of dehydration are presented for oral, enteral, and parenteral fluid replacement.
Emilie Reber; Filomena Gomes; Ilka A. Dähn; Maria F. Vasiloglou; Zeno Stanga. Management of Dehydration in Patients Suffering Swallowing Difficulties. Journal of Clinical Medicine 2019, 8, 1923 .
AMA StyleEmilie Reber, Filomena Gomes, Ilka A. Dähn, Maria F. Vasiloglou, Zeno Stanga. Management of Dehydration in Patients Suffering Swallowing Difficulties. Journal of Clinical Medicine. 2019; 8 (11):1923.
Chicago/Turabian StyleEmilie Reber; Filomena Gomes; Ilka A. Dähn; Maria F. Vasiloglou; Zeno Stanga. 2019. "Management of Dehydration in Patients Suffering Swallowing Difficulties." Journal of Clinical Medicine 8, no. 11: 1923.
Nutritional counselling has been recognised as the first line approach in the management of numerous chronic diseases. Though usually carried out by dietitians, nutritional counselling may be used by nurses, or other healthcare professionals to improve nutritional status and meet healthcare goals. Healthcare professionals require training and education to facilitate a patient centred approach to effective counselling. Advances in digital technology have the potential to improve access to nutritional counselling for some patients such as those in primary care. However, caution is required to ensure that valuable interpersonal relationships are not lost, as these form the cornerstone of effective nutritional counselling. The aim of this narrative review is to explore aspects of effective nutritional counselling, including advances in e-counselling and areas where nursing input in nutritional counselling might enhance overall nutritional care.
Maria F. Vasiloglou; Jane Fletcher; Kalliopi-Anna Poulia. Challenges and Perspectives in Nutritional Counselling and Nursing: A Narrative Review. Journal of Clinical Medicine 2019, 8, 1489 .
AMA StyleMaria F. Vasiloglou, Jane Fletcher, Kalliopi-Anna Poulia. Challenges and Perspectives in Nutritional Counselling and Nursing: A Narrative Review. Journal of Clinical Medicine. 2019; 8 (9):1489.
Chicago/Turabian StyleMaria F. Vasiloglou; Jane Fletcher; Kalliopi-Anna Poulia. 2019. "Challenges and Perspectives in Nutritional Counselling and Nursing: A Narrative Review." Journal of Clinical Medicine 8, no. 9: 1489.
Malnutrition is an independent risk factor that negatively influences patients’ clinical outcomes, quality of life, body function, and autonomy. Early identification of patients at risk of malnutrition or who are malnourished is crucial in order to start a timely and adequate nutritional support. Nutritional risk screening, a simple and rapid first-line tool to detect patients at risk of malnutrition, should be performed systematically in patients at hospital admission. Patients with nutritional risk should subsequently undergo a more detailed nutritional assessment to identify and quantify specific nutritional problems. Such an assessment includes subjective and objective parameters such as medical history, current and past dietary intake (including energy and protein balance), physical examination and anthropometric measurements, functional and mental assessment, quality of life, medications, and laboratory values. Nutritional care plans should be developed in a multidisciplinary approach, and implemented to maintain and improve patients’ nutritional condition. Standardized nutritional management including systematic risk screening and assessment may also contribute to reduced healthcare costs. Adequate and timely implementation of nutritional support has been linked with favorable outcomes such as a decrease in length of hospital stay, reduced mortality, and reductions in the rate of severe complications, as well as improvements in quality of life and functional status. The aim of this review article is to provide a comprehensive overview of nutritional screening and assessment methods that can contribute to an effective and well-structured nutritional management (process cascade) of hospitalized patients.
Emilie Reber; Filomena Gomes; Maria F. Vasiloglou; Philipp Schuetz; Zeno Stanga. Nutritional Risk Screening and Assessment. Journal of Clinical Medicine 2019, 8, 1065 .
AMA StyleEmilie Reber, Filomena Gomes, Maria F. Vasiloglou, Philipp Schuetz, Zeno Stanga. Nutritional Risk Screening and Assessment. Journal of Clinical Medicine. 2019; 8 (7):1065.
Chicago/Turabian StyleEmilie Reber; Filomena Gomes; Maria F. Vasiloglou; Philipp Schuetz; Zeno Stanga. 2019. "Nutritional Risk Screening and Assessment." Journal of Clinical Medicine 8, no. 7: 1065.
Anorexia Nervosa (AN) is a psychiatric disorder characterised by a physical and psychosocial deterioration due to an altered pattern on the intake and weight control. The severity of the disease is based on the degree of malnutrition. The objective of this article is to review the scientific evidence of the refeeding process of malnourished inpatients with AN; focusing on the clinical outcome. We conducted an extensive search in Medline and Cochrane; on April 22; 2019; using different search terms. After screening all abstracts; we identified 19 papers that corresponded to our inclusion criteria. The article focuses on evidence on the characteristics of malnutrition and changes in body composition; energy and protein requirements; nutritional treatment; physical activity programmes; models of organisation of the nutritional treatment and nutritional support related outcomes in AN patients. Evidence-based standards for clinical practice with clear outcomes are needed to improve the management of these patients and standardise the healthcare process.
Cristina Cuerda; Maria F. Vasiloglou; Loredana Arhip. Nutritional Management and Outcomes in Malnourished Medical Inpatients: Anorexia Nervosa. Journal of Clinical Medicine 2019, 8, 1042 .
AMA StyleCristina Cuerda, Maria F. Vasiloglou, Loredana Arhip. Nutritional Management and Outcomes in Malnourished Medical Inpatients: Anorexia Nervosa. Journal of Clinical Medicine. 2019; 8 (7):1042.
Chicago/Turabian StyleCristina Cuerda; Maria F. Vasiloglou; Loredana Arhip. 2019. "Nutritional Management and Outcomes in Malnourished Medical Inpatients: Anorexia Nervosa." Journal of Clinical Medicine 8, no. 7: 1042.
Regular nutrient intake monitoring in hospitalised patients plays a critical role in reducing the risk of disease-related malnutrition (DRM). Although several methods to estimate nutrient intake have been developed, there is still a clear demand for a more reliable and fully automated technique, as this could improve the data accuracy and reduce both the participant burden and the health costs. In this paper, we propose a novel system based on artificial intelligence to accurately estimate nutrient intake, by simply processing RGB depth image pairs captured before and after a meal consumption. For the development and evaluation of the system, a dedicated and new database of images and recipes of 322 meals was assembled, coupled to data annotation using innovative strategies. With this database, a system was developed that employed a novel multi-task neural network and an algorithm for 3D surface construction. This allowed sequential semantic food segmentation and estimation of the volume of the consumed food, and permitted fully automatic estimation of nutrient intake for each food type with a 15% estimation error.
Ya Lu; Thomai Stathopoulou; Maria Vasiloglou; Stergios Christodoulidis; Beat Blum; Thomas Walser; Vinzenz Meier; Zeno Stanga; Stavroula G. Mougiakakou. An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients*. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) 2019, 5696 -5699.
AMA StyleYa Lu, Thomai Stathopoulou, Maria Vasiloglou, Stergios Christodoulidis, Beat Blum, Thomas Walser, Vinzenz Meier, Zeno Stanga, Stavroula G. Mougiakakou. An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients*. 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). 2019; ():5696-5699.
Chicago/Turabian StyleYa Lu; Thomai Stathopoulou; Maria Vasiloglou; Stergios Christodoulidis; Beat Blum; Thomas Walser; Vinzenz Meier; Zeno Stanga; Stavroula G. Mougiakakou. 2019. "An Artificial Intelligence-Based System for Nutrient Intake Assessment of Hospitalised Patients*." 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) , no. : 5696-5699.
GoCARB is a computer vision-based smartphone system designed for individuals with Type 1 Diabetes to estimate plated meals’ carbohydrate (CHO) content. We aimed to compare the accuracy of GoCARB in estimating CHO with the estimations of six experienced dietitians. GoCARB was used to estimate the CHO content of 54 Central European plated meals, with each of them containing three different weighed food items. Ground truth was calculated using the USDA food composition database. Dietitians were asked to visually estimate the CHO content based on meal photographs. GoCARB and dietitians achieved comparable accuracies. The mean absolute error of the dietitians was 14.9 (SD 10.12) g of CHO versus 14.8 (SD 9.73) g of CHO for the GoCARB (p = 0.93). No differences were found between the estimations of dietitians and GoCARB, regardless the meal size. The larger the size of the meal, the greater were the estimation errors made by both. Moreover, the higher the CHO content of a food category was, the more challenging its accurate estimation. GoCARB had difficulty in estimating rice, pasta, potatoes, and mashed potatoes, while dietitians had problems with pasta, chips, rice, and polenta. GoCARB may offer diabetic patients the option of an easy, accurate, and almost real-time estimation of the CHO content of plated meals, and thus enhance diabetes self-management.
Maria F. Vasiloglou; Stavroula Mougiakakou; Emilie Aubry; Anika Bokelmann; Rita Fricker; Filomena Gomes; Cathrin Guntermann; Alexa Meyer; Diana Studerus; Zeno Stanga. A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians. Nutrients 2018, 10, 741 .
AMA StyleMaria F. Vasiloglou, Stavroula Mougiakakou, Emilie Aubry, Anika Bokelmann, Rita Fricker, Filomena Gomes, Cathrin Guntermann, Alexa Meyer, Diana Studerus, Zeno Stanga. A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians. Nutrients. 2018; 10 (6):741.
Chicago/Turabian StyleMaria F. Vasiloglou; Stavroula Mougiakakou; Emilie Aubry; Anika Bokelmann; Rita Fricker; Filomena Gomes; Cathrin Guntermann; Alexa Meyer; Diana Studerus; Zeno Stanga. 2018. "A Comparative Study on Carbohydrate Estimation: GoCARB vs. Dietitians." Nutrients 10, no. 6: 741.
Diabetes knowledge has been shown to improve glycemic control and associate with several demographic parameters. In Greece, a country with high obesity rates, disease knowledge has never been evaluated in diabetic patients. This cross sectional study aimed to assess diabetes knowledge and its associations between social and demographic parameters, among Greek type 2 diabetes mellitus (T2DM) patients. One hundred fifty nine patients with T2DM were recruited from an urban and a rural clinic in Greece. Diabetes knowledge was assessed with the Brief Diabetes Knowledge Test (DKT). Basic anthropometry was performed. Data regarding glycemic control and sociodemographic characteristics were collected from the patients' medical files. Greek T2DM patients demonstrated poor disease knowledge (mean DKT score 8.3±2.2/14.0 and mean DKT as a percent of correct answers 59.6±15.8%). No differences were observed between sex, place of residence, or glycemic control, among subjects. Patients with higher education demonstrated greater diabetes knowledge. Simple obesity with concurrent central obesity or suboptimal glycemic control decreased diabetes knowledge among participants. Additionally, waist circumference was inversely correlated to diabetes knowledge. Based on the DKT, Greek patients exhibit poor diabetes knowledge. This study provides evidence for the need for better diabetes education in order to ameliorate disease outcome.
Dimitrios Poulimeneas; Maria G. Grammatikopoulou; Vasiliki Bougioukli; Parthena Iosifidou; Maria Vasiloglou; Maria-Assimina Gerama; Dimitrios Mitsos; Ioanna Chrysanthakopoulou; Maria Tsigga; Kyriakos Kazakos. Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients. Endocrinología y Nutrición 2016, 63, 320 -326.
AMA StyleDimitrios Poulimeneas, Maria G. Grammatikopoulou, Vasiliki Bougioukli, Parthena Iosifidou, Maria Vasiloglou, Maria-Assimina Gerama, Dimitrios Mitsos, Ioanna Chrysanthakopoulou, Maria Tsigga, Kyriakos Kazakos. Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients. Endocrinología y Nutrición. 2016; 63 (7):320-326.
Chicago/Turabian StyleDimitrios Poulimeneas; Maria G. Grammatikopoulou; Vasiliki Bougioukli; Parthena Iosifidou; Maria Vasiloglou; Maria-Assimina Gerama; Dimitrios Mitsos; Ioanna Chrysanthakopoulou; Maria Tsigga; Kyriakos Kazakos. 2016. "Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients." Endocrinología y Nutrición 63, no. 7: 320-326.
Dimitrios Poulimeneas; Maria G. Grammatikopoulou; Vasiliki Bougioukli; Parthena Iosifidou; Maria Vasiloglou; Maria-Assimina Gerama; Dimitrios Mitsos; Ioanna Chrysanthakopoulou; Maria Tsigga; Kyriakos Kazakos. Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients. Endocrinología y Nutrición (English Edition) 2016, 63, 320 -326.
AMA StyleDimitrios Poulimeneas, Maria G. Grammatikopoulou, Vasiliki Bougioukli, Parthena Iosifidou, Maria Vasiloglou, Maria-Assimina Gerama, Dimitrios Mitsos, Ioanna Chrysanthakopoulou, Maria Tsigga, Kyriakos Kazakos. Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients. Endocrinología y Nutrición (English Edition). 2016; 63 (7):320-326.
Chicago/Turabian StyleDimitrios Poulimeneas; Maria G. Grammatikopoulou; Vasiliki Bougioukli; Parthena Iosifidou; Maria Vasiloglou; Maria-Assimina Gerama; Dimitrios Mitsos; Ioanna Chrysanthakopoulou; Maria Tsigga; Kyriakos Kazakos. 2016. "Diabetes knowledge among Greek Type 2 Diabetes Mellitus patients." Endocrinología y Nutrición (English Edition) 63, no. 7: 320-326.
Clinical data regarding circulating leptin levels in patients with non-alcoholic fatty liver disease (NAFLD) are conflicting. The purpose of this meta-analysis was to compare leptin levels between the following groups: patients with biopsy-proven NAFLD vs controls; simple steatosis (SS) patients vs controls; non-alcoholic steatohepatitis (NASH) patients vs controls and NASH patients vs SS patients. We performed a systematic search in PubMed, Scopus and the Cochrane Library. We analysed 33 studies, published between 1999 and 2014, including 2,612 individuals (775 controls and 1,837 NAFLD patients). Higher circulating leptin levels were observed in NAFLD patients vs controls (standardised mean difference [SMD] 0.640; 95% CI 0.422, 0.858), SS patients vs controls (SMD 0.358; 95% CI 0.043, 0.673), NASH patients vs controls (SMD 0.617; 95% CI 0.403, 0.832) and NASH patients vs SS patients (SMD 0.209; 95% CI 0.023, 0.395). These results remained essentially unchanged after excluding studies involving paediatric or adolescent populations and/or individuals undergoing bariatric surgery. There was moderate-to-severe heterogeneity among studies in all comparisons, but no significant publication bias was detected. Meta-regression analysis demonstrated that BMI was inversely associated with leptin SMD and accounted for 26.5% (p = 0.014) and 32.7% (p = 0.021) of the between-study variance in the comparison between NASH patients and controls and NAFLD patients and controls, respectively. However, when bariatric studies were excluded, BMI did not significantly explain the between-study variance. Circulating leptin levels were higher in patients with NAFLD than in controls. Higher levels of circulating leptin were associated with increased severity of NAFLD, and the association remained significant after the exclusion of studies involving paediatric or adolescent populations and morbidly obese individuals subjected to bariatric surgery.
Stergios A. Polyzos; Konstantinos Aronis; Jannis Kountouras; Dimitrios D. Raptis; Maria Vasiloglou; Christos S. Mantzoros. Circulating leptin in non-alcoholic fatty liver disease: a systematic review and meta-analysis. Diabetologia 2015, 59, 30 -43.
AMA StyleStergios A. Polyzos, Konstantinos Aronis, Jannis Kountouras, Dimitrios D. Raptis, Maria Vasiloglou, Christos S. Mantzoros. Circulating leptin in non-alcoholic fatty liver disease: a systematic review and meta-analysis. Diabetologia. 2015; 59 (1):30-43.
Chicago/Turabian StyleStergios A. Polyzos; Konstantinos Aronis; Jannis Kountouras; Dimitrios D. Raptis; Maria Vasiloglou; Christos S. Mantzoros. 2015. "Circulating leptin in non-alcoholic fatty liver disease: a systematic review and meta-analysis." Diabetologia 59, no. 1: 30-43.
The myokine irisin may increase energy expenditure and affect metabolism. The objective of the study was to elucidate predictors of irisin and study whether circulating irisin may have day-night rhythm in humans. This was an observational, cross-sectional study with an additional 24-hour prospective observational arm (day-night rhythm substudy) and two prospective interventional arms (mixed meal substudy and exercise substudy). The study was conducted at the Hellenic Military School of Medicine (Thessaloniki, Greece). One hundred twenty-two healthy, young individuals were subjected to anthropometric and body composition measurements, and their eating and exercise behavior profiles were assessed with validated questionnaires. Subgroups were subjected to day-night rhythm, standardized meal ingestion, and 30-minute aerobic exercise studies. Circulating irisin levels were measured. Ιrisin levels were lower in males than females (P = .02) after adjustment for lean body mass, which was its major determinant. Irisin levels followed a day-night rhythm (P < .001) with peak at 9:00 pm. Irisin levels were increased at the end of exercise (84.1 ± 10.0 vs 105.8 ± 14.3 ng/mL; P < .001). Irisin levels were not affected by intake of a standardized meal and were not associated with caloric intake or diet quality. In healthy, young individuals, circulating irisin displays a day-night rhythm, is correlated with lean body mass, and increases acutely after exercise.
Athanasios D. Anastasilakis; Stergios A. Polyzos; Zacharias G. Saridakis; Georgios Kynigopoulos; Elpida C. Skouvaklidou; Dimitrios Molyvas; Maria Vasiloglou; Aggeliki Apostolou; Thomai Karagiozoglou-Lampoudi; Aikaterina Siopi; Vassilis Mougios; Panagiotis Chatzistavridis; Grigorios Panagiotou; Andreas Filippaios; Sideris Delaroudis; Christos S. Mantzoros. Circulating Irisin in Healthy, Young Individuals: Day-Night Rhythm, Effects of Food Intake and Exercise, and Associations With Gender, Physical Activity, Diet, and Body Composition. The Journal of Clinical Endocrinology & Metabolism 2014, 99, 3247 -3255.
AMA StyleAthanasios D. Anastasilakis, Stergios A. Polyzos, Zacharias G. Saridakis, Georgios Kynigopoulos, Elpida C. Skouvaklidou, Dimitrios Molyvas, Maria Vasiloglou, Aggeliki Apostolou, Thomai Karagiozoglou-Lampoudi, Aikaterina Siopi, Vassilis Mougios, Panagiotis Chatzistavridis, Grigorios Panagiotou, Andreas Filippaios, Sideris Delaroudis, Christos S. Mantzoros. Circulating Irisin in Healthy, Young Individuals: Day-Night Rhythm, Effects of Food Intake and Exercise, and Associations With Gender, Physical Activity, Diet, and Body Composition. The Journal of Clinical Endocrinology & Metabolism. 2014; 99 (9):3247-3255.
Chicago/Turabian StyleAthanasios D. Anastasilakis; Stergios A. Polyzos; Zacharias G. Saridakis; Georgios Kynigopoulos; Elpida C. Skouvaklidou; Dimitrios Molyvas; Maria Vasiloglou; Aggeliki Apostolou; Thomai Karagiozoglou-Lampoudi; Aikaterina Siopi; Vassilis Mougios; Panagiotis Chatzistavridis; Grigorios Panagiotou; Andreas Filippaios; Sideris Delaroudis; Christos S. Mantzoros. 2014. "Circulating Irisin in Healthy, Young Individuals: Day-Night Rhythm, Effects of Food Intake and Exercise, and Associations With Gender, Physical Activity, Diet, and Body Composition." The Journal of Clinical Endocrinology & Metabolism 99, no. 9: 3247-3255.