CT and 18FDG-PET/CT findings in progressive mediastinal idiopathic fibrosis as a benign mimicker of esophageal carcinoma: a case report.

Idiopathic mediastinal fibrosis, also called sclerosing or fibrosing mediastinitis, is a very rare and aggressive fibroinflammatory process characterized by fibrous tissue proliferation in the mediastinal region. Herein, we present a rare case of idiopathic mediastinal fibrosis presenting with esophageal obstruction, most likely associated with immunoglobulin G (IgG4)-related disease, affecting the posterior mediastinum with intrapulmonary infiltration. Computed tomography revealed a narrowed lumen and thickened wall of the distal esophagus surrounded by a necrotic mass with infiltration into the nearby structures, suggesting a locally advanced malignant process. Positron emission tomography revealed intense accumulation of 18F-fluorodeoxyglucose, indicating an active inflammatory component, which complicates further differential diagnosis of mediastinal masses. Thoracoscopic biopsy and immunohistochemical analysis confirmed a fibroinflammatory process with perivascular lymphoid cell infiltration that was cluster of differentiation (CD)3 (++) and CD20 (++), with massive numbers of IgG4-immunoreactive plasma cells. Although a benign condition, sclerosing mediastinitis is a close mimicker of esophageal carcinoma, which cannot be differentiated by computed tomography or positron emission tomography and must be considered in a differential diagnosis.

Possibility of Using Conventional Computed Tomography Features and Histogram Texture Analysis Parameters as Imaging Biomarkers for Preoperative Prediction of High-Risk Gastrointestinal Stromal Tumors of the Stomach.

BACKGROUND: The objective of this study is to determine the morphological computed tomography features of the tumor and texture analysis parameters, which may be a useful diagnostic tool for the preoperative prediction of high-risk gastrointestinal stromal tumors (HR GISTs). METHODS: This is a prospective cohort study that was carried out in the period from 2019 to 2022. The study included 79 patients who underwent CT examination, texture analysis, surgical resection of a lesion that was suspicious for GIST as well as pathohistological and immunohistochemical analysis. RESULTS: Textural analysis pointed out min norm (p = 0.032) as a histogram parameter that significantly differed between HR and LR GISTs, while min norm (p = 0.007), skewness (p = 0.035) and kurtosis (p = 0.003) showed significant differences between high-grade and low-grade tumors. Univariate regression analysis identified tumor diameter, margin appearance, growth pattern, lesion shape, structure, mucosal continuity, enlarged peri- and intra-tumoral feeding or draining vessel (EFDV) and max norm as significant predictive factors for HR GISTs. Interrupted mucosa (p < 0.001) and presence of EFDV (p < 0.001) were obtained by multivariate regression analysis as independent predictive factors of high-risk GISTs with an AUC of 0.878 (CI: 0.797-0.959), sensitivity of 94%, specificity of 77% and accuracy of 88%. CONCLUSION: This result shows that morphological CT features of GIST are of great importance in the prediction of non-invasive preoperative metastatic risk. The incorporation of texture analysis into basic imaging protocols may further improve the preoperative assessment of risk stratification.

Sociodemographic predictors of pain in old people : Serbian population-based study.

BACKGROUND: With the growing increase in the older proportion of the world population, there is also an increase in specific age-related chronic diseases and conditions, including pain. We aimed to evaluate the association of sociodemographic factors with the presence and different degrees of pain intensity in people aged 65 years and older. METHODS: The population-based study, conducted in 2013, included 3540 individuals from Serbia. As pain predictors, we analyzed further sociodemographic characteristics: gender, age, body mass index, level of education, marital status, and wealth index. For pain assessment, we used the pain domain of the SF-36 version 2.0 questionnaire. RESULTS: People over the age of 85 years are 27% more likely to have moderate pain than younger respondents; however, pain is less likely reported by men (by 42%), persons with overweight (by 23%) or obesity (by 21%), respondents with secondary (by 50%) or university education (29%), as well as those belonging to the upper household wealth index (by 22%), than by their counterparts. CONCLUSION: Pain is less likely in people of age below 85 years, male gender, those with higher educational level and higher wealth index, as well as overweight or obese individuals. Also, we have demonstrated that sociodemographic predictors differently correlate with the onset of the pain and its severity degree in persons of 65 years and older.

Predicting the Assisted Living Care Needs Using Machine Learning and Health State Survey Data.

Effective pain management can significantly improve quality of life and outcomes for various types of patients (e.g. elderly, adult, young) and often requires assisted living for a significant number of people worldwide. In order to improve our understanding of patients' response to pain and needs for assisted living we need to develop adequate data processing techniques that would enable us to understand underlying interdependencies. To this purpose in this paper we develop several different algorithms that can predict the need for medically assisted living outcomes using a large database obtained as a part of the national health survey. As a part of the survey the respondents provided detailed information about general health care state, acute and chronic problems as well as personal perception of pain associated with performing two simple talks: walking on the flat surface and walking upstairs. We model the correspondent responses using multinomial random variables and propose structured deep learning models based on maximum likelihood estimation and machine learning for information fusion. For comparison purposes we also implement fully connected deep learning network and use its results as benchmark measurements. We evaluate the performance of the proposed techniques using the national survey data and split them into two parts used for training and testing. Our preliminary results indicate that the proposed models can potentially be useful in forecasting the need for medically assisted living.

Health Predictors of Pain in Elderly-A Serbian Population-Based Study.

OBJECTIVES: The aim of our study was to evaluate the association of health factors with the presence and different degrees of pain in elderly above 65 years of life. METHODS: The population-based study included 3540 individuals above 65 years of age of life from twofold stratified household sample representative for Serbia, during 2013 (the average age 73.9 ± 6.3 years; average Body Mass Index was 26.7 ± 4.4, females 56.8%, living with partner 55.5%, with primary education 55.3%, with poor wealth index 55.8% and from rural settings 46.2%). As health predictors of pain, we analyzed further health parameters: self-perceived general health, long-lasting health problems, diagnosed pulmonary disease, cardiovascular disease, musculoskeletal disease, diabetes, hyperlipidemia, hypertension and other chronic diseases. Pain domain of SF-36 version 2.0 was used for pain assessment. RESULTS: Significant health predictors of pain were: self-perceived general health (OR 2.28), where bad perception of self-perceived general health in our study had greater risk of pain with higher degree of severity; long-lasting health problems (OR 1.60), where elderly with long-lasting health problems had almost twice the risk of moderate degree of pain, and above twice the risk for severe degree of pain; pulmonary disease (OR 1.38); musculoskeletal disease (OR 2.98) and other chronic diseases (OR 1.71). The presence of musculoskeletal disease increases the risk for pain, even more than double in severe versus mild degrees of pain. CONCLUSION: Bad self-perceived general health, long-lasting health problems, pulmonary, musculoskeletal diseases, cardiovascular disease and other chronic disease were significant health-related predictors of various degrees of pain in elderly.

Alignment of Perceived Competencies and Perceived Job Tasks among Primary Care Managers.

In this study we aimed to explore how managers in primary health care (PHC) organizations assess their managerial knowledge and skills, as well as the importance of these competencies for their job, and to identify whether there is an alignment between these two perceptions; therefore, whether there is a need for management competency improvement. With this study, we tried to address a high demand for information about health managers, especially in health systems in low- and middle-income countries. In a sample of 58 primary health care centers (n = 106 managers) in Serbia, we used a basic managerial competency matrix consisting of the following six competencies-communication, team-building, planning and priority-setting, performance assessment, problem-solving, and leading. Managerial perception of the importance of their job tasks differs by educational level and managerial position. The best alignment between the importance of knowledge and skills was for communication and leading. The study pointed out that managers were aware of the necessity to improve their level of managerial competencies, particularly in the domains of planning and priority-setting, performance assessment, and problem solving. The study highlights the need for formal managerial education for managers in PHC settings and commitment to continuously evaluate and improve management competencies in order to better manage PHC.

Sociodemographic Predictors of Physical Functioning in the Elderly: A National Health Survey.

We aimed to evaluate the prevalence of sociodemographic factors with the presence and different degrees of walking difficulties in elderly above 65 years, and to analyze association between evaluated variables and the presence and degree of waking difficulties. In the population based study, 3540 individuals age above 65 years from Serbia were recruited. Further predictors were analyzed: gender, age, level of education, marital status, body mass index (BMI), index of well-being and place of residence. We assessed difficulty in walking half a km on level ground without the use of any aid (Group-1); and difficulty in walking up or down 12 steps (Group-2). Walking difficulties were categorized as no difficulty, some difficulty, a lot of difficulty and cannot do at all. For present difficulty significant predictors were: age (Group-1 (OR-3.022)/Group-2 (OR-3.825)), gender (Group-1 (OR-0.337)/Group-2 (OR-0.311)), educational level (Group-1 (OR-0.689)/Group-2 (OR-0.556)) and place of residence (Group-2 (OR-1.523)) while for non-performing the task, significant predictors were: age (Group-1 (OR-1.998)/Group-2 (OR-2.096)), gender (Group-1 (OR-0.629)/Group-2 (OR-0.495)), BMI (Group-1 (OR-1.219)/Group-2 (OR-1.305)), marital status (Group-1 (OR 0.764)/Group-2 (OR-0.769)), educational level (Group-1 (OR-0.679)/Group-2 (OR-0.719)) and index of well-being (Group-2 (OR-0.764)). Understanding of predictors, and their role on functional decline in elderly is of great importance for the development of specific population-based health programs to prevent further functional loss and preserve achieved functional gains.