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Post-operative hypoparathyroidism is the most encountered complication of thyroid surgery and is classified as temporary or permanent. However, its incidence varies greatly in the literature ranging from 0.5% to 65%. This can be mainly attributed to the different definition of hypoparathyroidism used in each study and especially to the different time cutoff applied to distinguish temporary from permanent hypoparathyroidism. We conducted a systematic literature search in PubMed, Scopus, Cochrane and GoogleScholar databases, as well as grey literature. Ultimately, 45 articles with 23,164 patients in total were included in this review. These articles used either the cutoff of six or twelve post-operative months to distinguish temporary from permanent hypoparathyroidism. The overall incidence of permanent hypoparathyroidism diagnosed at 6 months post-operatively was 4.11% and 4.08% at 12 months post-operatively. There was no statistically significant difference between the two groups (p = 0.92). We suggest that adhering to the current guidelines that recommend diagnosing temporary hypoparathyroidism when recovery is made within 6 months after surgery is important when conducting future research in order to narrow the gap that exists currently in the literature, as well as when deciding to put patients on long-term calcium supplements.

Background Coronary artery disease (CAD) remains one of the leading causes of mortality and morbidity worldwide. As oxygen and nutrient supply to the myocardium significantly decrease during ischemic periods, important changes occur regarding myocardial intermediary energy metabolism. Metabolomics is an emerging field in systems biology, which quantifies metabolic changes in response to disease progression. This study aims to evaluate the diagnostic utility of plasma metabolomics-based biomarkers for determining the complexity and severity of CAD, as it is assessed via the SYNTAX score. Methods Corlipid is a prospective, non-interventional cohort trial empowered to enroll 1065 patients with no previous coronary intervention history, who undergo coronary angiography in University Hospital AHEPA, Thessaloniki. Venous blood samples are collected before coronary angiography. State-of the-art analytical methods are performed to calculate the serum levels of novel biomarkers: ceramides, acyl-carnitines, fatty acids, and proteins such as galectin-3, adiponectin, and the ratio of apolipoprotein B/apolipoprotein A1. Furthermore, all patients will be categorized based on the indication for coronary angiography (acute coronary syndrome, chronic coronary syndrome, preoperative coronary angiography) and on the severity of CAD using the SYNTAX score. Follow-up of 12 months after enrollment will be performed to record the occurrence of major adverse cardiovascular events. A risk prediction algorithm will be developed by combining clinical characteristics with established and novel biomarkers to identify patients at high risk for complex CAD based on their metabolite signatures. The first patient was enrolled in July 2019 and completion of enrollment is expected until May 2021. Discussion CorLipid is an ongoing trial aiming to investigate the correlation between metabolic profile and complexity of coronary artery disease in a cohort of patients undergoing coronary angiography with the potential to suggest a decision-making tool with high discriminative power for patients with CAD. To our knowledge, Corlipid is the first study aspiring to create an integrative metabolomic biomarkers-based algorithm by combining metabolites from multiple classes, involved in a wide range of pathways with well-established biochemical markers. Trial registration CorLipid trial registration: ClinicalTrials.gov number: NCT04580173. Registered 8 October 2020—Retrospectively registered, https://clinicaltrials.gov/ct2/show/NCT04580173.

Gallbladder cancer is the most common malignancy of the biliary tract. When diagnosed in an advanced stage it has a very poor prognosis. Therefore, early diagnosis and thorough assessment of a suspicious gallbladder polyp is essential to improve survival rate. The aim of this systematic review is to assess the role of fine needle aspiration cytology (FNAC) in the management of gallbladder cancer. For that purpose, a systematic review was carried out in the MEDLINE, EMBASE, Cochrane, Scopus and Google Scholar databases between 1 July 2004 and 22 April 2021. Six studies with 283 patients in total were included. Pooled sensitivity and specificity of FNAC were 0.85 and 0.94, respectively, while the area under the calculated summary receiver operating characteristic (SROC curve (AUC) was 0.98. No complications were reported. Based on the high diagnostic performance of FNAC in the assessment of gallbladder masses, we suggest that every suspicious mass should be evaluated further with FNAC to facilitate the most appropriate management.

The GRACE score constitutes a useful tool for risk stratification in patients with acute coronary syndrome (ACS), while the SYNTAX score determines the complexity of coronary artery disease (CAD). This study sought to correlate these scores and assess the accuracy of the GRACE score in predicting the extent of CAD. A total of 539 patients with ACS undergoing coronary angiography were included in this analysis. The patients were classified into those with a SYNTAX score &lt, 33 and a SYNTAX score ≥ 33. Spearman’s correlation and receiver operator characteristic analysis were conducted to investigate the role of the GRACE score as a predictor of the SYNTAX score. There was a significantly positive correlation between the SYNTAX and the GRACE scores (r = 0.32, p &lt, 0.001). The GRACE score predicted severe CAD (SYNTAX ≥ 33) moderately well (the area under the curve was 0.595 (0.522–0.667)). A GRACE score of 126 was documented as the optimal cut-off for the prediction of a SYNTAX score ≥ 33 (sensitivity = 53.5% and specificity = 66%). Therefore, our study reports a significantly positive correlation between the GRACE and the SYNTAX score in patients with ACS. Notably, NSTEMI patients with a high-risk coronary anatomy have higher calculated GRACE scores. A multidisciplinary approach by a heart team could possibly alter the therapeutic approach and management in patients presenting with ACS and a high calculated GRACE score.

Background: Angiographic detection of thrombus in STEMI is associated with adverse outcomes. However, routine thrombus aspiration failed to demonstrate the anticipated benefit. Hence, management of high coronary thrombus burden remains challenging. We sought to assess for the first time extracted thrombotic material characteristics utilizing micro-computed tomography (micro-CT).Methods: One hundred thirteen STEMI patients undergoing thrombus aspiration were enrolled. Micro-CT was undertaken to quantify retrieved thrombus volume, surface, and density. Correlation of these indices with angiographic and electrocardiographic outcomes was performed.Results: Mean aspirated thrombus volume, surface, and density (±standard deviation) were 15.71 ± 20.10 mm3, 302.89 ± 692.54 mm2, and 3139.04 ± 901.88 Hounsfield units, respectively. Aspirated volume and surface were significantly higher (p < 0.001) in patients with higher angiographic thrombus burden. After multivariable analysis, independent predictors for thrombus volume were reference vessel diameter (RVD) (p = 0.011), right coronary artery (RCA) (p = 0.039), and smoking (p = 0.027), whereas RVD (p = 0.018) and RCA (p = 0.019) were predictive for thrombus surface. Thrombus volume and surface were independently associated with distal embolization (p = 0.007 and p = 0.028, respectively), no-reflow phenomenon (p = 0.002 and p = 0.006, respectively), and angiographically evident residual thrombus (p = 0.007 and p = 0.002, respectively). Higher thrombus density was correlated with worse pre-procedural TIMI flow (p < 0.001). Patients with higher aspirated volume and surface developed less ST resolution (p = 0.042 and p = 0.023, respectively).Conclusions: Angiographic outcomes linked with worse prognosis were more frequent among patients with larger extracted thrombus. Despite retrieving larger thrombus load in these patients, current thrombectomy devices fail to deal with thrombotic material adequately. Further studies of novel thrombus aspiration technologies are warranted to improve patient outcomes.Clinical Trial Registration: QUEST-STEMI trial ClinicalTrials.gov number: NCT03429608 Date of registration: February 12, 2018. The study was prospectively registered.

Obesity in childhood and adolescence represents a major health problem. Novel e-Health technologies have been developed in order to provide a comprehensive and personalized plan of action for the prevention and management of overweight and obesity in childhood and adolescence. We used information and communication technologies to develop a “National Registry for the Prevention and Management of Overweight and Obesity” in order to register online children and adolescents nationwide, and to guide pediatricians and general practitioners regarding the management of overweight or obese subjects. Furthermore, intelligent multi-level information systems and specialized artificial intelligence algorithms are being developed with a view to offering precision and personalized medical management to obese or overweight subjects. Moreover, the Big Data against Childhood Obesity platform records behavioral data objectively by using inertial sensors and Global Positioning System (GPS) and combines them with data of the environment, in order to assess the full contextual framework that is associated with increased body mass index (BMI). Finally, a computerized decision-support tool was developed to assist pediatric health care professionals in delivering personalized nutrition and lifestyle optimization advice to overweight or obese children and their families. These e-Health applications are expected to play an important role in the management of overweight and obesity in childhood and adolescence.

Atrial fibrillation is a heart arrhythmia strongly associated with other heart-related complications that can increase the risk of strokes and heart failure. Manual electrocardiogram (ECG) interpretation for its diagnosis is tedious, time-consuming, requires high expertise, and suffers from inter- and intra-observer variability. Deep learning techniques could be exploited in order for robust arrhythmia detection models to be designed. In this paper, we propose a novel hybrid neural model utilizing focal loss, an improved version of cross-entropy loss, to deal with training data imbalance. ECG features initially extracted via a Convolutional Neural Network (CNN) are input to a Long Short-Term Memory (LSTM) model for temporal dynamics memorization and thus, more accurate classification into the four ECG rhythm types, namely normal (N), atrial fibrillation (AFIB), atrial flutter (AFL) and AV junctional rhythm (J). The model was trained on the MIT-BIH Atrial Fibrillation Database and achieved a sensitivity of 97.87%, and specificity of 99.29% using a ten-fold cross-validation strategy. The proposed model can aid clinicians to detect common atrial fibrillation in real-time on routine screening ECG.

Note keeping is an indispensable ingredient of successful research. Although traditionally performed on paper, recently the task is increasingly facilitated by Electronic Lab Notebooks, i.e., ICT programs that allow their users to make electronic observations in laboratory settings. When it comes to human subject studies (HSR), i.e., the scientific investigation of human beings for medical, behavioral or social purposes, it is sometimes the case that multiple study participants perform a certain task concurrently. In such concurrent multi-participant experiments, efficient note keeping is critical as it can help assure the quality of the collected data and filter out compromised cases. The current paper presents Memorandum, a novel configurable Android application that allows the assistants of medical, behavioral or social HSR experiments to quickly and easily keep notes about the study participants. The app, which has already been employed in a behavioral study involving 40 participants, is freely available via Google Play.

The paradigm of citizen-science, i.e., scientific research that is conducted in whole or in part by non-professional scientists, has gained popularity lately, e.g., for the purpose of crowdsourced data collection. Smartphones with their abundance and ubiquity are perfectly suited and have been widely used for crowdsourced data collection in real life settings. The ongoing, EC-funded research programme named BigO exploits the citizen-science paradigm to collect behavioral (eating, sleeping and physical activity) and affective (mood) data from children populations by means of a novel smartphone application with the intention of developing a decision support system to assist public health authorities in effective policy making against childhood obesity. This paper presents the development – in the context of BigO – of the myBigO app, one of the first citizen-scientist smartphone applications addressed to children for behavioral and affective data collection. This includes the design, implementation, and deployment of myBigO app in a number of data collection studies as well as its preliminary evaluation with respect to technical robustness and user experience in the context of these studies.

Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants., Accepted version to be published in 2020, 42nd Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Montreal, Canada