Type 2 diabetes (T2D) constitutes a major health problem, reaching alarming rates over the last decades, especially due to contemporary lifestyle and associated obesogenic environments, as well as the aging population. Diabetes not only causes social consequences but also leads to increasing healthcare costs, posing a significant challenge for the health system. This paper applies a five-step approach for estimating T2D-related costs in Greece. The approach initially estimates the T2D-related ICD10 prevalence and the target population. Next it applies the appropriate therapeutic protocols to identify the most appropriate treatments. Subsequently, it calculates the total cost of medical treatments for each target population, based on the distribution of patients between the different treatments and treatment lines. Finally, based on the diagnostic and treatment protocols, it calculates the annual direct costs associated with the cost categories. Using the estimated future population of the country, the proposed methodology can also project the budget required, under certain conditions, to deal with T2D. The analysis estimated that T2D-related costs in 2021 under rational use of resources were EUR 1,397,871,172.55 billion and EUR 1,512,934,947.63 billion projected in the year 2030 considering the aging effect, per cost category, and in total, presenting an increase of approximately 115 million euros in 2030 compared to 2021. The term “rational use of resources” in this study refers to the use of internationally recognized, evidence-based diagnostic and therapeutic protocols, as adopted by the Greek Ministry of Health. This scenario represents an idealized standard of care rather than actual real-world adherence and is used to estimate the potential resource needs under optimal medical practice conditions. An inflation rate of 4.2% was applied to costs between 2021 and 2030. The analysis showed that the highest percentage (39%) of the total T2D-related healthcare expenditures is associated with complications that occur in T2D patients. Despite a comparatively modest prevalence of T2D in Greece relative to other European and Mediterranean countries, the economic burden associated with its management remains high. The aging of the population will lead to an increase in the total cost of T2D. The applied methodology of estimating budgets by aggregating categories of expenses under a specific disease (ICD10), instead of dividing budgets into categories of expenses, can successfully lead to the optimization and rationalization of expenses according to actual needs. The findings underline the significant economic burden of T2D in Greece, particularly due to complications and population aging. These results emphasize the urgent need for health policy strategies focusing on prevention, early intervention, and the efficient allocation of healthcare resources. The methodology applied can serve as a decision-making tool for forecasting healthcare budgets and optimizing expenditures under different population and treatment scenarios.

Monitoring the number of defects in constant-size units is a well-defined problem in the industrial domain and usually, the c$c$ control chart is used for monitoring the total number of defects in a product or a sample of products. The c-chart tracks the total number of defects in each case by assuming that the underlying number of defects (single or several different types of defects) follows approximately the Poisson distribution. An interesting class of problems where the c$c$-chart is used is when the number of defects in a surface is of interest. Although the number of defects on the surface of products characterizes the quality of the products, it is especially important how concentrated the defects are in specific parts of the product. In this paper, we introduce a scan-based monitoring procedure, which simultaneously combines control charts for monitoring the evolvement of the number of defects (in general, events) through time and scan statistics for exploring the spatial distribution of defects. The numerical illustration showed that the new procedure has excellent performance under different scenarios.

Background: Chronic media with effusion (COME) and recurrent acute otitis media (RAOM) are closely related clinical entities that affect childhood. The aims of the study were to investigate the microbiological profile of otitis-prone children in the post-PCV7 era and, to examine the biofilm-forming ability in association with clinical history and outcome during a two-year post-operative follow-up. Methods: In this prospective study, pathogens from patients with COME and RAOM were isolated and studied in vitro for their biofilm-forming ability. The minimum inhibitory concentrations (MIC) of both the planktonic and the sessile forms were compared. The outcome of the therapeutic method used in each case and patient history were correlated with the pathogens and their ability to form biofilms. Results: Haemophilus influenzae was the leading pathogen (35% in COME and 40% in RAOM), and Streptococcus pneumoniae ranked second (12% in COME and 24% in RAOM). Polymicrobial infections were identified in 5% of COME and 19% of RAOM cases. Of the isolated otopathogens, 94% were positive for biofilm formation. Conclusions: This is the first Greek research studying biofilm formation in complex otitis media-prone children population in the post-PCV7 era. High rates of polymicrobial infections, along with treatment failure in biofilms, may explain the lack of antimicrobial efficacy in otitis-prone children.

In 2020, the whole planet was plagued by the extremely deadly COVID-19 pandemic. More than 83 million people had been infected with COVID-19 while more than 1.9 million people around the planet had died from this virus in the first year of the pandemic. From the first moment, the medical community started working to deal with this pandemic. For this reason, many clinical trials have been and continue to be conducted to find a safe and efficient cure for the virus. In this paper, we review the 96 clinical trials, registered in the ClinicalTrials.gov database, that had been completed by the end of the first year of the pandemic. Although the clinical trials contained significant heterogeneity in the main methodological features (enrollment, duration, allocation, intervention model, and masking) they seemed to be conducted based on an appropriate methodological basis.

Since the anthrax attacks in the USA in 2001, there is increasing concern about biosurveillance. Moreover, the coronavirus pandemic showed up, even more, the significance of continual systematic collection, analysis, interpretation, and dissemination of health data for early detection of disease outbreaks. To timely and efficiently detect infectious or noninfectious disease outbreaks we should consider both spatial and temporal dimensions. Of interest are global changes in the number of new disease events on time in a specific broader area and/or hotspots of disease events in smaller areas which may evolve into outbreaks or even into pandemics, such as the coronavirus pandemic. In this paper, we propose a practitioner-friendly monitoring procedure for monitoring simultaneously the number of disease events and the spatial distribution of disease events. The proposed method exploits a flexible and efficient mathematical tool, the convex hull, in conjunction with control charting procedures. As the numerical illustration showed, the proposed method has excellent performance under different outbreak scenarios.

A challenge, in the era of economic crisis and uncertainty, is to provide health care services in an efficient and effective manner. The protection of public health, the provision of quality healthcare services to patients, the location of health centers, the geographical distribution of patients, and the provision of specialist services are some of the topics that the government and/or a health organization responsible for health care services provision has to arrange. Other topics are the assessment of quality, safety, and effectiveness of healthcare services provided by healthcare providers. Moreover, a central pylon in designing healthcare policy is expenditure monitoring and control. However, among all these topics the most significant is the protection of public health; especially now that viruses such as Coronavirus are spreading rapidly worldwide. This paper aims to review the use of Statistical Process Monitoring techniques in the public health domain in order to improve health care decision-making under uncertainty and further on to provide an innovative three-layer framework for the collection, processing, and real-time analysis of related data like Coronavirus or any other infectious disease that will emerge in the future for both proper and effective case management and effective health policy planning.

Purpose: To investigate the prevalence of anxiety in adolescents and its correlation with lifestyle habits. Design and Methods: Three hundred and seventy-two adolescents aged 15 to 18 years from Messenia were randomly enrolled to the research. A lifestyle questionnaire was answered additionally to the Hamilton anxiety scale. Anthropometric characteristics and blood pressure were measured. Adolescents were studied according to their gender. Results: Sixty three percent of adolescents were female; the mean age was 16.63 years old. The majority of adolescents eats breakfast every morning and was also used to sleeping before midnight and exercise systematically. According to the Hamilton scale, 11.6% of the adolescents had mild anxiety and 5.1% had severe to very severe anxiety. Girls exhibited more stress than boys. In the female population, Body mass index (p=0.001) and Waist circumference (p=0.006) were positively correlated with anxiety. In both male and female adolescents, coffee was positively correlated with anxiety (p=0.039) in contrary to milk (p=0.002). Positive was also the correlation between anxiety and snack (p=0.001), sweet product (p<0.001) and fast food (p=0.001) consumption. Fish consumption (p=0.014) and physical activity (p=0.001) were negatively correlated with anxiety. Regarding sleep habits, adolescents who sleep less than 7.37 hours per day have higher anxiety (p=0.002). Regarding the male population, the consumption of products rich in: Vitamin B12 (p=0.024), magnesium (p=0.019), chromium (p=0.030) and zinc (p=0.036) was negatively correlated with anxiety. Conclusions: A balanced diet combined with good sleep habits and regular physical activity, are essential for the regulation of anxiety.

Abstract Background Apoptosis antigen 1/FAS receptor (APO1/Fas) signaling in endothelial cells plays a significant role in angiogenesis while increased mean platelet volume (MPV) is an important marker for platelet activation. We investigated the possible correlation between APO1/Fas and both metabolic parameters and platelet activity (indicated by the MPV) in a healthy pediatric population. Methods One hundred and eighty-five children, aged 5–17 years old, were enrolled in the study. The participants were divided into subgroups according to their age and body mass index percentile (BMI%). APO1/Fas was measured by enzyme-linked immunosorbent assay (ELISA) and MPV by the MEK-6410K. Results Eighty-one children (43.8%) had excess weight, which was more prevalent in children ≤9 years of age. Sixty-five children (35.1%) exhibited a predisposition for metabolic syndrome. A negative correlation was found between APO1/Fas and predisposing factors for metabolic syndrome: Glucose, cholesterol, uric acid, low-density lipoprotein (LDL), and triglycerides. In contrast, a positive correlation was found between APO1/Fas and C-reactive protein (CRP). Receiver operating characteristic (ROC) analysis showed a predisposition to metabolic syndrome when APO1/Fas was <78.46 pg/mL. A negative correlation was also observed between APO1/Fas and MPV. MPV was also positively correlated with predisposing factors for metabolic syndrome: BMI%, glucose, cholesterol, uric acid, LDL, and negatively with high-density lipoprotein. Conclusions APO1/Fas expression is associated with a lower predisposition to metabolic syndrome may be through endothelial homeostasis, the induction of apoptosis of cells involved in atherosclerosis, and platelet activity. It may also enhance CRP-mediated noninflammatory clearance of apoptotic cells. Early monitoring of all the components of metabolic syndrome in overweight children is important in order to prevent metabolic and cardiovascular complications.

AIM:The aim of this study was to investigate the relationship between nutritional habits, lifestyle, anxiety, and coping strategies.BACKGROUND:Anxiety is an underestimated and often undiagnosed subclinical disorder that burdens the general public of modern societies and increases illness suscentibility.METHODS:The study group consisted of 693 individuals living in Peloponnese, Greece. A standardized questionnaire that consists of the dietary habits and lifestyle questionnaire, the trait Anxiety STAI-X-2 questionnaire and the brief-COPE questionnaire, was used. Principal components analysis identified the factors from the questionnaires, and stepwise multivariate regression analysis investigated their relationships.RESULTS:Weekly consumption of fruits, tomatoes, salads and lettuce, together with Εmotional/Ιnstrumental support, Denial/Behavioural disengagement, substance use and self-blame, was the most important predictors of anxiety scores. Positive reframing/Humour and Acceptance/Planning are also associated with the Positive STAI factor and decreased anxiety scores.CONCLUSION:Healthy nutritional habits, comprised of consumption of salads and fruits, together with adaptive coping strategies, such as Positive reframing/Humour and Active problem solving, may provide the most profound improvement in the anxiety levels of a healthy population in Peloponnese, Greece.

PURPOSE:To estimate the roles of triglyceride/high-density lipoprotein cholesterol (TG/HDL) ratio and uric acid in predisposition for metabolic syndrome (MetS) and its components in healthy children. METHODS:Anthropometric and biochemical analyses were performed on 110 children, aged 5 to 12 years, from the Greek county of Laconia. The children were studied as a whole population and in separate groups according to age and predisposition to MetS after taking into consideration International Diabetes Federation criteria, body mass index, and lipid profile. RESULTS:Seventeen percent of children exhibited predisposition to MetS, while 39.1% had TG/HDL ratio &gt;1, and 3.64% had high level of uric acid. According to a receiver operating characteristic curve analysis, the relative probability for MetS predisposition sextupled when TG/HDL ratio was ≥1 (odds ratio [OR], 5.986; 95% confidence interval [CI], 1.968-18.205). Children in the total population and those aged &lt; 9 years had a greater probability for increased low-density lipoprotein (LDL) cholesterol (OR, 3.614; 95% CI, 1.561-8.365) when TG/HDL ratio was ≥ 1. The TG/HDL ratio was positively correlated with body mass index (BMI) (P=0.035) in children without MetS, cholesterol in the total population (P=0.06) and children ≥9 years old (P=0.026), and with LDL in the total population and both age groups (P=0.001). The TG/HDL ratio was also positively correlated with alanine aminotransferase in the total population (P=0.033) and gamma-glutamyl transferase in most studied groups (P&lt;0.001). Uric acid was positively correlated with waist circumference in the total population (P=0.043) and in those without MetS (P=0.027). It was also positively correlated with BMI, TG, cholesterol, and TG/HDL ratio and negatively correlated with HDL in most studied groups (P&lt;0.005). CONCLUSION:The studied parameters correlated with MetS components and could be characterized as effective indexes for childhood MetS, regardless of age and predisposition to MetS.

Control charts, the most popular tool of statistical process control, appeared in the literature to ensure that an industrial process is operating only with natural variability, i.e., under statistical control. In the last decades, control charts have been also widely used to assess the quality of non-industrial processes, such as medicine and public health. Mainly in the last two decades, a modification of standard and advanced control charts appeared in the bibliography to improve the monitoring mainly of medical processes. This is the risk-adjusted control charts which take into consideration the varying health conditions of the patients. These charts are used to monitor certain medical processes such as surgeries, mortality, and doctors’ experience. In this paper, we have tried to present all the risk-adjusted control charts presented in the literature appropriately categorized. The risk-adjusted charts have been grouped into three categories: control charts for continuous variables, control charts for attributes (non-continuous variables), time-weighted control charts. The application of risk-adjusted control charts in practical medical processes is also discussed. This review paper highlights the value of the risk-adjusted control charts.

Nowadays the use of the multivariate statistical process control (MSPC) toolbox is efficiently generalized beyond assuring product quality through the monitoring of industrial processes in order to be used in many other non industrial fields (e.g., public health, environmental, financial monitoring, etc.). Data produced by non industrial processes usually require the development of problem-oriented monitoring procedures. In this article we develop a method for monitoring bivariate random variables defined on contingency tables and introduce an appropriate one-sided control procedure, motivated by a problem from double reading used in many medical processes. Specifically, we propose a procedure for monitoring simultaneously the measure of agreement between Cohen's kappa defined on a contingency table associated with the process stability and one percentage associated with the process quality level, defined on the same contingency table. The procedure is based on an appropriate approximation that is assessed numerically and shows an excellent performance. Then we explore the performance of several candidate one-sided techniques for monitoring the process and we propose a new one that is based on a penalization strategy that appears to have the best performance. The new technique is very easy to implement by a non statistician, as illustrated by its application to a real case from double reading.

Adverse events in Phase II comparative clinical trials have received limited attention in the literature. Bersimis et al. (Stat Med 34:197–214, 2014 ) in proposed a class of comparative sequential designs with bivariate endpoints, where as a special case, the termination of the clinical trial due to the occurrence of a severe adverse event is treated. In this paper, using the Markov chain embedding technique, we extend this class of designs proposing two new designs, which treat cases where the development of an adverse event does not immediately stop the clinical trial, but penalizes appropriately the treatment that caused it. In both designs the penalty can be chosen either by assessing the severity of the adverse event or by optimizing the power. The numerical results show an excellent performance, achieving small expected sample sizes in conjunction with large values for power, satisfying in this way the ethical requirement for small sample sizes and fast decisions in clinical practice. The formulation of the procedure as a stochastic process is elegantly accomplished while it offers the necessary mathematical framework for further generalizing the designs covering more cases such as group sequential designs, etc.

Purpose: To investigate the effect of lifestyle habits in childhood Metabolic Syndrome (MTS). Design and Methods: Descriptive correlation study with 480 participants (5-12 years old) using a specially designed questionnaire was conducted. Anthropometric and biochemical analyses were performed. Results: Fifteen percent of children exhibited predisposition for MTS. Regarding sleep habits, logistic regression analysis (LRA) showed that hour of sleep -before 22: 00- was associated with decreased waist circumference (WC%) (p = .026). Midday siesta was negatively correlated with systolic (SBP) (p = .001) and diastolic blood pressure (DBP) (p = .046). In children without MTS, lack of sleep and night time sleep was positively correlated with DBP (p = .044) and fasting blood glucose (FBG) (p = .005). Regarding nutrition habits, fast food consumption was positively correlated with SBP (p = .006) and meat consumption was positively correlated with both Body Mass Index% (BMI%) (p = .038) and WC% (p = .023). LRA showed that fruit (p = .001) and legume (p = .040) consumption was associated with decreased FBG; fish consumption with decreased Low Density Lipoprotein (LDL) cholesterol (p = .031), vegetable (p = .054) and cereal consumption (p = .012) with decreased DBP. In children with MTS, fruits were associated with increased FBG (p = .034). In children without MTS, meat consumption was associated with increased LDL (p = .024), cereal with increased WC% (p = .002) and olive products with increased High Density Lipoprotein (HDL) cholesterol and BMI% (p = .037). Conclusions: The adoption of both balanced diet and sleep habits seemed to be crucial for the prevention of MTS. Practice Implications: Clinical health nurses could develop and implement preventive intervention programs in order to avoid metabolic complications in adulthood. (C) 2018 Elsevier Inc. All rights reserved.

Summary Background Phototherapy is one of the main treatments for mycosis fungoides ( MF ). In this study, we analyzed the efficacy and safety of phototherapy as a first‐line treatment in patients with early‐stage disease. Methods We analyzed treatment outcomes in a group of 227 early‐stage patients. The chi‐squared test, the parametric t test, and ANOVA test and the non‐parametric tests of Mann‐Whitney and Kruskal‐Wallis were applied for data analysis. Results 55.9% of patients treated with UVB ‐ NB reached complete remission ( CR ), while analog rates after PUVA treatment were 74.5% ( P = .015). Patients with patch‐stage disease showed better response rates to PUVA compared to UVB ‐ NB therapy ( CR s 56.7% vs 91.3%, P < .001). Regarding the latter, long‐lasting disease was proven as an independent negative prognostic factor for treatment outcome. Phototypes I and II were found to be favorable prognostic factors for patients treated with PUVA . Maintenance treatment did not alter final relapse rates but led to prolonged time to relapse compared to no‐maintenance treated cases (19.5 months, vs 32.3, P < .002). Conclusion Our analysis indicates that PUVA leads to better responses and longer relapse‐free intervals both in patch‐ and plaque‐stage disease. UVB ‐ NB could be a valid therapeutic alternative for patients with recent disease presentation.

OBJECTIVE Construction and validation of an instrument for assessing the social attitudes and the level of awareness of citizens towards people experiencing homelessness. METHOD The instrument, the Citizens' Awareness on Homelessness Scale, was constructed in the form of a self-completed questionnaire consisting of 30 items scored on a five point Likert scale, plus one open question. Study of the instrument was conducted in a large Greek municipality from March to April 2016 with 120 participants (response rate: 85.7%). The reliability and the construct validity of the questionnaire were measured. RESULTS The questionnaire has a good internal consistency (Cronbach's alpha= 0.732). Exploratory factor analysis resulted in statistically significant factors. The average rate of awareness was found to be 59.06 +/- 10.47 points. CONCLUSIONS The study confirmed that the instrument designed to measure the awareness of citizens in relation to homelessness was valid and reliable. The instrument revealed that the awareness of the citizens in the study sample was not high and was not related to demographic characteristics.

Health and health service monitoring is among the most promising research area today and the world work towards efficient and cost effective health care. This paper deals with monitoring health service performance using more than one performance outcome variable (multi-attribute processes), which is common in most health services. Although monitoring whether a health service changes or improves over time is important this is well covered in the current literature. Therefore this paper focuses on comparing similar health services in terms of their performance. The proposed procedure is based on an appropriate control chart. The paper deals with firstly the case when no risk adjustment is required because the health services being compared treat the same patient case-mix which does not vary over time. Secondly it deals with comparing health services where risk adjustment is required because the patient case-mix they service do differ because they service either very different geographical locations or service very different demographics of the same population. The technology developed in this paper could be used for example to assess and compare health practitioners’ competence over time, i.e. to decide if two doctors are equivalent in terms of their outcome performances. The waiting time random variable associated with the run length distribution of the control charts (as well as to competence testing) is studied using a Markov Chain embedding technique. Numerical results are provided that exhibit the value of the proposed procedures.

Assessing the agreement between two or more raters is an important topic in medical practice. Existing techniques, which deal with categorical data, are based on contingency tables. This is often an obstacle in practice as we have to wait for a long time to collect the appropriate sample size of subjects to construct the contingency table. In this paper, we introduce a nonparametric sequential test for assessing agreement, which can be applied as data accrues, does not require a contingency table, facilitating a rapid assessment of the agreement. The proposed test is based on the cumulative sum of the number of disagreements between the two raters and a suitable statistic representing the waiting time until the cumulative sum exceeds a predefined threshold. We treat the cases of testing two raters' agreement with respect to one or more characteristics and using two or more classification categories, the case where the two raters extremely disagree, and finally the case of testing more than two raters' agreement. The numerical investigation shows that the proposed test has excellent performance. Compared to the existing methods, the proposed method appears to require significantly smaller sample size with equivalent power. Moreover, the proposed method is easily generalizable and brings the problem of assessing the agreement between two or more raters and one or more characteristics under a unified framework, thus providing an easy to use tool to medical practitioners.

Discriminating integral membrane proteins from water-soluble ones, has been over the past decades an important goal for computational molecular biology. A major drawback of methods appeared in the literature, is that most of the authors tried to solve the problem using machine learning techniques. Specifically, most of the proposed methods require an appropriate dataset for training, and consequently the results depend heavily on the suitability of the dataset, itself. Motivated by these facts, in this paper we develop a formal discrimination procedure that is based on appropriate theoretical observations on the sequence of hydrophobic and polar residues along the protein sequence and on the exact distribution of a two dimensional runs-related statistic defined on the same sequence. Specifically, for setting up our discrimination procedure, we study thoroughly the exact distribution of a bivariate random variable, which accumulates the exact lengths of both success and failure runs of at least a specific length in a sequence of Bernoulli trials. To investigate the properties of this bivariate random variable, we use the Markov chain embedding technique. Finally, we apply the new procedure to a well-defined dataset of proteins.