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Ketonemia and ketonuria in gestational diabetes mellitus

Loukia Spanou, Kalliopi Dalakleidi, Konstantia Zarkogianni, Anastasia Papadimitriou, Konstantina Nikita, Vasiliki Vasileiou, Maria Alevizaki, Eleni Anastasiou
2015 HORMONES  
BACKGROUND: The use of capillary blood 3-β-hydroxybutyrate (3HB) is a more precise method than urine ketones measurement for the diagnosis of diabetic ketoacidosis. Fasting ketonuria is common during normal pregnancy, while there is evidence that it is increased among pregnant women with Gestational Diabetes Mellitus (GDM) who are on a diet. 3HB levels have been related to impaired offspring psychomotor development. Reports with concomitant measurement of blood and urine ketones in women with
more » ... M who followed a balanced diet are lacking. OBJECTIVE: To compare the prevalence of fasting ketonemia and ketonuria in women with GDM following the Institute of Medicine diet instructions and assess their possible relation with metabolic parameters and therapeutic interventions. RESEARCH DESIGN AND METHODS: 180 women with GDM were studied. In each patient, in successive visits, capillary blood and urine ketones were simultaneously measured. The total measurements were 378, while the average number of measurements per patient was 2.1. RESULTS: The prevalence of ketonuria was significantly higher than that of ketonemia (x 2 =21.33, p <0.001). Significantly higher mean 3HB levels were observed with respect to ketonuria severity (p=0.001). Bedtime carbohydrate intake was associated with significantly lower 3HB levels (p=0.035). Insulin treatment was associated with significant 3HB levels reduction (p=0.032). Body weight reduction per week between two serial visits was associated with increased 3HB levels (p=0.005). Multiple linear regression analysis showed that weight loss remained the only independent predictor of 3HB levels. CONCLUSIONS: The presence of ketonemia was significantly lower than the presence of ketonuria. Weight loss per week was the only independent factor found to be associated with increased levels of 3HB. The clinical significance of this small increase requires further investigation.
doi:10.14310/horm.2002.1610 pmid:26732157 fatcat:57u5obzrajak3fao4iqlfxbj4y

Special issue on emerging technologies for the management of diabetes mellitus

Konstantia Zarkogianni, Konstantina S. Nikita
2015 Medical and Biological Engineering and Computing  
Zarkogianni et al.  ... 
doi:10.1007/s11517-015-1422-4 pmid:26612137 fatcat:w4ezqisdlng5jabjedc6dywvmu

A Multimodal Approach for Real Time Recognition of Engagement towards Adaptive Serious Games for Health

Konstantinos Mitsis, Konstantia Zarkogianni, Eleftherios Kalafatis, Kalliopi Dalakleidi, Amyn Jaafar, Georgios Mourkousis, Konstantina S. Nikita
2022 Sensors  
In this article, an unobtrusive and affordable sensor-based multimodal approach for real time recognition of engagement in serious games (SGs) for health is presented. This approach aims to achieve individualization in SGs that promote self-health management. The feasibility of the proposed approach was investigated by designing and implementing an experimental process focusing on real time recognition of engagement. Twenty-six participants were recruited and engaged in sessions with a SG that
more » ... romotes food and nutrition literacy. Data were collected during play from a heart rate sensor, a smart chair, and in-game metrics. Perceived engagement, as an approximation to the ground truth, was annotated continuously by participants. An additional group of six participants were recruited for smart chair calibration purposes. The analysis was conducted in two directions, firstly investigating associations between identified sitting postures and perceived engagement, and secondly evaluating the predictive capacity of features extracted from the multitude of sources towards the ground truth. The results demonstrate significant associations and predictive capacity from all investigated sources, with a multimodal feature combination displaying superiority over unimodal features. These results advocate for the feasibility of real time recognition of engagement in adaptive serious games for health by using the presented approach.
doi:10.3390/s22072472 pmid:35408088 pmcid:PMC9002748 fatcat:dybzbk46x5anxl5qlbabh4wnha

A Review of Emerging Technologies for the Management of Diabetes Mellitus

Konstantia Zarkogianni, Eleni Litsa, Konstantinos Mitsis, Po-Yen Wu, Chanchala D. Kaddi, Chih-Wen Cheng, May D. Wang, Konstantina S. Nikita
2015 IEEE Transactions on Biomedical Engineering  
Zarkogianni Fig. 1 . 1 Fig. 1. 2, Jawbone Up 24, Fitbit Flex, Basis Peak, BodyMedia LINK Armband, and Withings Pulse O2 incorporate multiple sensors [30] [31] [32] [33] [34] 101] [102] [103  ...  SkinPrep System - - 1 min EGA (A+B): 96.9% YSI 2300 STAT Plus glucose analyzer and commercial glucose meters Author Manuscript Author Manuscript Author Manuscript Author Manuscript Zarkogianni  ... 
doi:10.1109/tbme.2015.2470521 pmid:26292334 pmcid:PMC5859570 fatcat:wxl6rjdnwraqlooxzwsob2hmzm

An explainable XGBoost-based approach towards assessing the risk of cardiovascular disease in patients with Type 2 Diabetes Mellitus [article]

Maria Athanasiou, Konstantina Sfrintzeri, Konstantia Zarkogianni, Anastasia C. Thanopoulou, Konstantina S. Nikita
2020 arXiv   pre-print
Cardiovascular Disease (CVD) is an important cause of disability and death among individuals with Diabetes Mellitus (DM). International clinical guidelines for the management of Type 2 DM (T2DM) are founded on primary and secondary prevention and favor the evaluation of CVD related risk factors towards appropriate treatment initiation. CVD risk prediction models can provide valuable tools for optimizing the frequency of medical visits and performing timely preventive and therapeutic
more » ... s against CVD events. The integration of explainability modalities in these models can enhance human understanding on the reasoning process, maximize transparency and embellish trust towards the models' adoption in clinical practice. The aim of the present study is to develop and evaluate an explainable personalized risk prediction model for the fatal or non-fatal CVD incidence in T2DM individuals. An explainable approach based on the eXtreme Gradient Boosting (XGBoost) and the Tree SHAP (SHapley Additive exPlanations) method is deployed for the calculation of the 5-year CVD risk and the generation of individual explanations on the model's decisions. Data from the 5-year follow up of 560 patients with T2DM are used for development and evaluation purposes. The obtained results (AUC = 71.13%) indicate the potential of the proposed approach to handle the unbalanced nature of the used dataset, while providing clinically meaningful insights about the ensemble model's decision process.
arXiv:2009.06629v2 fatcat:b47p6iohezds7akfiqzed2ntlu

A hybrid genetic algorithm for the selection of the critical features for risk prediction of cardiovascular complications in Type 2 Diabetes patients

Kalliopi V. Dalakleidi, Konstantia Zarkogianni, Vassilios G. Karamanos, Anastasia C. Thanopoulou, Konstantina S. Nikita
2013 13th IEEE International Conference on BioInformatics and BioEngineering  
Dalakleidi, Konstantia Zarkogianni, Vassilios G. Karamanos, Anastasia C. Thanopoulou and Konstantina S. Nikita P 978-1-4799-3163-7/13/$31.00 ©2013 IEEE management.  ... 
doi:10.1109/bibe.2013.6701620 dblp:conf/bibe/DalakleidiZKTN13 fatcat:iowezj6q6bhqvk6wpcp6acazxq

SMARTDIAB: A Communication and Information Technology Approach for the Intelligent Monitoring, Management and Follow-up of Type 1 Diabetes Patients

Stavroula G. Mougiakakou, Christos S. Bartsocas, Evangelos Bozas, Nikos Chaniotakis, Dimitra Iliopoulou, Ioannis Kouris, Sotiris Pavlopoulos, Aikaterini Prountzou, Marios Skevofilakas, Alexandre Tsoukalis, Kostas Varotsis, Andrianni Vazeou (+2 others)
2010 IEEE Transactions on Information Technology in Biomedicine  
SMARTDIAB is a platform designed to support the monitoring, management, and treatment of patients with type 1 diabetes mellitus (T1DM), by combining state-of-the-art approaches in the fields of database (DB) technologies, communications, simulation algorithms, and data mining. SMARTDIAB consists mainly of two units: 1) the patient unit (PU); and 2) the patient management unit (PMU), which communicate with each other for data exchange. The PMU can be accessed by the PU through the internet using
more » ... devices, such as PCs/laptops with direct internet access or mobile phones via a Wi-Fi/General Packet Radio Service access network. The PU consists of an insulin pump for subcutaneous insulin infusion to the patient and a continuous glucose measurement system. The aforementioned devices running a user-friendly application gather patient's related information and transmit it to the PMU. The PMU consists of a diabetes data management system (DDMS), a decision support system (DSS) that provides risk assessment for long-term diabetes complications, and an insulin infusion advisory system (IIAS), which reside on a Web server. The DDMS can be accessed from both medical personnel and patients, with appropriate security access rights and front-end interfaces. The DDMS, apart from being used for data storage/retrieval, provides also advanced tools for the intelligent processing of the patient's data, supporting the physician in decision making, regarding the patient's treatment. The IIAS is used to close the loop between the insulin pump and the continuous glucose monitoring system, by providing the pump with the appropriate insulin infusion rate in order to keep the patient's glucose levels within predefined limits. The pilot version of the SMARTDIAB has already been implemented, while the platform's evaluation in clinical environment is being in progress.
doi:10.1109/titb.2009.2039711 pmid:20123578 fatcat:lo5jc5qc6jdq5pt2ilbbwa6qdi

What do healthcare professionals need to turn risk models for type 2 diabetes into usable computerized clinical decision support systems? Lessons learned from the MOSAIC project

Giuseppe Fico, Liss Hernanzez, Jorge Cancela, Arianna Dagliati, Lucia Sacchi, Antonio Martinez-Millana, Jorge Posada, Lidia Manero, Jose Verdú, Andrea Facchinetti, Manuel Ottaviano, Konstantia Zarkogianni (+9 others)
2019 BMC Medical Informatics and Decision Making  
To understand user needs, system requirements and organizational conditions towards successful design and adoption of Clinical Decision Support Systems for Type 2 Diabetes (T2D) care built on top of computerized risk models.
doi:10.1186/s12911-019-0887-8 pmid:31419982 pmcid:PMC6697904 fatcat:sdwxacw6nrfenhqs4dydragqf4

Intelligent Personalized Medical Decision Support Systems for the Management of Diabetes Mellitus [article]

Konstantia Ch. Zarkogianni, National Technological University Of Athens, National Technological University Of Athens, Κωνσταντίνα Νικήτα
2011
Στην παρούσα διατριβή σχεδιάζονται, αναπτύσσονται και αξιολογούνται ευφυή συστήματα υποστήριξης εξατομικευμένων ιατρικών αποφάσεων που στοχεύουν στη βελτιστοποίηση της θεραπείας των ατόμων με Σακχαρώδη Διαβήτη (ΣΔ). Συγκεκριμένα, οι μέθοδοι που αναπτύσσονται χρησιμοποιούνται για την ανάλυση και την επεξεργασία δεδομένων Ηλεκτρονικού Ιατρικού Φακέλου, Εργαστηριακών Μετρήσεων καθώς και συνεχών καταγραφών γλυκόζης και ινσουλίνης, με σκοπό i) τη σχεδίαση και ανάπτυξη Συμβουλευτικού Συστήματος
more » ... ς Ινσουλίνης (ΣΣΕΙ), το οποίο εκτιμά σε πραγματικό χρόνο τον απαιτούμενο ρυθμό έγχυσης ινσουλίνης σε άτομα με ΣΔ Τύπου Ι, που χρησιμοποιούν Διάταξη Συνεχούς Μέτρησης Γλυκόζης (ΔΣΜΓ) και αντλία έγχυσης ινσουλίνης («Τεχνητό Πάγκρεας»), ώστε τα επίπεδα γλυκόζης αίματος, να διατηρούνται εντός φυσιολογικών ορίων και ii) την ανάπτυξη μοντέλων αποτίμησης της πιθανότητας εμφάνισης μακροπρόθεσμων επιπλοκών του ΣΔ Τύπου Ι και Τύπου ΙΙ, εστιάζοντας στη διαβητική αμφιβληστροειδοπάθεια. Στο πρώτο μέρος της διατριβής εφαρμόζονται προηγμένες μέθοδοι μοντελοποίησης, που βασίζονται στη συνδυασμένη χρήση Διαμερισματικών Μοντέλων (ΔΜ) και Νευρωνικών Δικτύων (ΝΔ) για την προσομοίωση του μεταβολικού συστήματος γλυκόζης-ινσουλίνης σε άτομα με ΣΔ Τύπου Ι. Το τελικό μοντέλο ενσωματώνεται σε έναν ελεγκτή που βασίζεται σε μοντέλο πρόβλεψης (Model Predictive Control-MPC), για τον μετέπειτα υπολογισμό των συνιστώμενων ρυθμών έγχυσης ινσουλίνης. Για τον λεπτομερή έλεγχο ορθής λειτουργίας του ΣΣΕΙ, πραγματοποιήθηκε σειρά υπολογιστικών πειραμάτων. Επιπλέον, διεξήχθη κλινική δοκιμή σε νοσοκομείο υπό ελεγχόμενες συνθήκες, τα αποτελέσματα της οποίας ανέδειξαν αδυναμίες του ΣΣΕΙ και οδήγησαν στη βελτίωσή του. Συγκεκριμένα, αναπτύχθηκε προσαρμοστικός αλγόριθμος αυτόματης και σε πραγματικό χρόνο, ενημέρωσης των παραμέτρων του ελεγκτή χρησιμοποιώντας τεχνικές ασαφούς λογικής. Το βελτιωμένο ΣΣΕΙ εξετάστηκε ως προς την ικανότητά του να διαχειρίζεται διαταραχές γευμάτων, καταστάσεις νηστείας, καθυστερήσεις, ανακρίβειες στις μετρήσεις γλυκόζης, διαφορές στο μεταβο [...]
doi:10.26240/heal.ntua.305 fatcat:zyiu77qxenhtrdvfbm7izilchm

Table of Contents

2020 2020 IEEE Conference on Games (CoG)  
Zarkogianni, George Mourkousis and Konstantina Nikita  ...  obstructive sleep apnea . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 694 Kostantinos Mitsis, Eleftherios Kalafatis, Konstantia  ... 
doi:10.1109/cog47356.2020.9231623 fatcat:gxvdthpvsbandb7wcwv7e7h56q

Machine Learning Approaches to Predict Risks of Diabetic Complications and Poor Glycemic Control in Nonadherent Type 2 Diabetes

Yuting Fan, Enwu Long, Lulu Cai, Qiyuan Cao, Xingwei Wu, Rongsheng Tong
2021 Frontiers in Pharmacology  
Konstantia Zarkogianni et al. developed a risk prediction model for T2D cardiovascular complication (Zarkogianni et al., 2018) .  ...  Consistent with prior research studies (Murphree et al., 2018; Tsao et al., 2018; Zarkogianni et al., 2018; Aminian et al., 2020) , the findings of this study showed high AUCs.  ... 
doi:10.3389/fphar.2021.665951 fatcat:gdvdsf4vi5gqxag6fammfteyie

On the use of ECG and EMG Signals for Question Difficulty Level Prediction in the Context of Intelligent Tutoring Systems

Fehaid Alqahtani, Stamos Katsigiannis, Naeem Ramzan
2019 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE)  
Zarkogianni, Kalliopi Dalakleidi, George Mourkousis and Konstantina Nikita Inter Disease Relations Based on Human Biomarkers by Network AnalysisShaikh Farhad Hossain,Altaf-Ul Amin, Shigehiko Kanaya,  ...  Chatzimina, Lefteris Koumakis, Kostas Marias and Manolis Tsiknakis Evaluation of a Serious Game promoting Nutrition and Food Literacy: Experiment Design and Preliminary Results Konstantinos Mitsis, Konstantia  ... 
doi:10.1109/bibe.2019.00077 dblp:conf/bibe/AlqahtaniKR19 fatcat:h3o7hgpttzgfldy5ewkxzysejm

EPMA-World Congress 2015

Jella-Andrea Abraham, Olga Golubnitschaja, Ildar Akhmetov, Russell J. Andrews, Leonidas Quintana, Russell J. Andrews, Babak Baban, Jun Yao Liu, Xu Qin, Tailing Wang, Mahmood S. Mozaffari, Viktoriia V. Bati (+405 others)
2016 The EPMA Journal  
Predictive preventive personalized medicine Liver cancer is the fifth most common form of cancer worldwide [1], with an incidence rate almost equals the mortality rate and ranks 3 rd among causes of cancer related death [2]. The coexistence of two life threatening conditions, cancer and liver cirrhosis makes the staging challenging. However, there are some staging systems, e.g. the Barcelona staging system for Hepatocellular carcinoma (HCC) [3], that suggest treatment options and management.
more » ... reas diagnosis in early stages gives hope for a curative outcome, the treatment regime for around 80 % [2] of the patients classified as severe stages only gears towards palliation [4]. An intra-arterial radiation approach, radioembolisation (RE) is ubiquitously applied as one of palliative approaches. Although, in general RE shows promising results in intermediate and advanced stage HCC [5], individual treatment outcomes are currently unpredictable. Corresponding stratification criteria are still unclear. We hypothesised that individual radioresistance/radiosensitivity may play a crucial role in treatment response towards RE strongly influencing individual outcomes. Further, HCC represents a highly heterogeneous group of patients which requires patient stratification according to clear criteria for treatment algorithms to be applied individually. Multilevel diagnostic approach (MLDA) is considered helpful to set-up optimal predictive and prognostic biomarker panel for individualised application of radioembolisation. Besides comprehensive medical imaging, our MLDA includes non-invasive multi-omics and sub-cellular imaging. Individual patient profiles are expected to give a clue to targeting shifted molecular pathways, individual RE susceptibility, treatment response. Hence, a dysregulation of the detoxification pathway (SOD2/Catalase) might indicate possible adverse effects of RE, and highly increased systemic activities of matrix metalloproteinases indicate an enhanced tumour aggressiveness and provide insights into molecular mechanisms/targets. Consequently, an optimal set-up of predictive and prognostic biomarker panels may lead to the changed treatment paradigm from untargeted "treat and wait" to the cost-effective predictive, preventive and personalised approach, improving the life quality and life expectancy of HCC patients. A2 Integrated market access approach amplifying value of "Rx-CDx" Ildar Akhmetov (ildar.export@gmail.com ) Market Access at Unicorn, P.O.B. 91, Zhytomyr 10020, Ukraine The EPMA Journal 2016, 7(Suppl 1):A2 Predictive preventive personalized medicine Achieving and sustaining seamless "drugcompanion diagnostic" market access requires a sound strategy throughout a product life cycle, which enables timely creation, substantiation and communication of value to key stakeholders [1, 2]. The study aims at understanding the root-cause of market access inefficiencies of companies by gazing at the "Rx-CDx" co-development process through the prism of "value", and developing a perfect co-development scenario based on the literature review and discussions with the subject matter experts. The presenter suggests that an integrated market access approach is the need of the hour, and it should cover the entire "Rx-CDx" value chainfrom early-stage pre-clinical (Rx) and feasibility (CDx) studies to post-launch considerations of a co-labeled product [3]. Such approach can leverage patient selection strategies to reduce clinical study size, increase chances to achieve earlier regulatory submission and launches, contribute to better upside for drug developers, simplify value justification, fit with the emerging "value-based" healthcare delivery practices, enable risk sharing, and facilitate funding of the biomarker research [1, 3, 4]. References 1. Akhmetov I, Bubnov RV. Assessing value of innovative molecular diagnostic tests in the concept of predictive, preventive, and personalized medicine. EPMA 3. Akhmetov IR, Ramaswamy R, Akhmetov IR, Thimmaraju, P. Market access advancements and challenges in "drug-companion diagnostic test" co-development in Europe.
doi:10.1186/s13167-016-0054-6 fatcat:kavq6icxxbfm3fdyww6d42rob4