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The timely integration of palliative medicine is an important component in the treatment of various advanced diseases. While a German S‑3-guideline on palliative medicine exists for patients with incurable cancer, a recommendation for non-oncological patients and especially for palliative patients presenting in the emergency department or intensive care unit is missing to date. Based on the present consensus paper, the palliative care aspects of the respective medical disciplines are addressed. The timely integration of palliative care aims to improve quality of life and symptom control in clinical acute and emergency medicine as well as intensive care. [ABSTRACT FROM AUTHOR]

Purpose: This study identifies the most impactful papers on scapholunate reconstruction and provides a quantitative assessment of the impact of these papers in order to inform future clinical practice, education, and research of this condition. Methods: The Scopus database was used in May 2020 to identify the 50 most cited clinical articles pertaining solely to chronic scapholunate reconstruction. Citation number and density, publication variables, and Altmetric Attention Scores (AASs) were collected and analyzed. Results: The top 50 articles on chronic scapholunate reconstruction produced 1,868 total citations, with an average of 37.36 ± 39.90 citations per article (range 7–196) and an average citation density of 2.44 ± 2.27. US-based publications (n = 20) and articles published in Journal of Hand Surgery (n = 24) were associated with significantly higher citation number and density (p < 0.01 – p = 0.018). In addition, sample size was positively correlated with citation density (rho = 0.312, p = 0.029). Fourteen articles were associated with an AAS (mean score = 4.07 ± 4.70). There was no significant association between AAS and citation number or density, but AAS did significantly predict citation density (coefficient = 0.378, 95% CI: [0.013–0.741], p = 0.043). Conclusion: Numerous factors, such as journal of publication, location, and sample size, were significantly associated with citation number and/or citation density. Interestingly, AAS was predictive of, but not directly correlated with citation density, suggesting that the impact of scapholunate literature may not be adequately captured with a citation analysis. [ABSTRACT FROM AUTHOR]

Nonadherence to medication regimens is a worldwide challenge; adherence rates range from 38 to 57 % in older populations with an average rate of less than 45 % and nonadherence contributes to adverse drug events, increased emergency visits and hospitalisations. Accurate measurement of medication adherence is important in terms of both research and clinical practice. However, the identification of an objective approach to measure nonadherence is still an ongoing challenge. The aim of this Position Paper is to describe the advantages and disadvantages of the known medication adherence tools (self-report, pill count, medication event monitoring system (MEMS) and electronic monitoring devices, therapeutic drug monitoring, pharmacy records based on pharmacy refill and pharmacy claims databases) to provide the appropriate criteria to assess medication adherence in older persons. To the best of our knowledge, no gold standard has been identified in adherence measurement and no single method is sufficiently reliable and accurate. A combination of methods appears to be the most suitable. Secondly, adherence assessment should always consider tools enabling polypharmacy adherence assessment. Moreover, it is increasingly evident that adherence, as a process, has to be assessed over time and not just at one evaluation time point (drug discontinuation). When cognitive deficits or functional impairments may impair reliability of adherence assessment, a comprehensive geriatric assessment should be performed and the caregiver involved. Finally, studies considering the possible implementation in clinical practice of adherence assessment tools validated in research are needed. [ABSTRACT FROM AUTHOR]

In this study we evaluated indicators of the feasibility, reliability, and validity of the Child Health Questionnaire-Child Form (CHQ-CF). We compared the results in a subgroup of adolescents who completed the standard paper version of the CHQ-CF with the results in another subgroup of adolescents who completed an internet version, i.e., an online, web-based CHQ-CF questionnaire. Under supervision at school, 1,071 adolescents were randomized to complete the CHQ-CF and items on chronic conditions by a paper questionnaire or by an internet administered questionnaire. The participation rate was 87%; age range 13–17 years. The internet administration resulted in fewer missing answers. All but one multi-item scale showed internal consistency reliability (Cronbach’s α > 0.70). All scales clearly discriminated between adolescents with no, a few, or many self-reported chronic conditions. The paper administration resulted in statistically significant, higher scores on 4 of 10 CHQ-CF scales compared with the internet administration ( P < 0.05), but Cohen’s effect sizes d were ≤ 0.21. Mode of administration interacted significantly with age ( P < 0.05) on four CHQ-CF scales, but Cohen’s effect sizes for these differences were also ≤ 0.21. This study supports the feasibility, internal consistency reliability of the scales, and construct validity of the CHQ-CF administered by either a paper questionnaire or online questionnaire. Given Cohen’s suggested guidelines for the interpretation of effect sizes, i.e., 0.20–0.50 indicates a small effect, differences in CHQ-CF scale scores between paper and internet administration can be considered as negligible or small. [ABSTRACT FROM AUTHOR]

The global HIV epidemic has undergone significant shifts over the last decade, transforming HIV into a chronic illness. A shift in focus is now sorely needed on how to provide treatment and care to individuals living with HIV that can improve their quality of life by addressing the psychosocial milieu of the disease. In the area of HIV prevention and testing, the benefits of working with couples, rather than individuals, have been delineated and empirically supported. This paper extends the work by proposing a model of a couple-based intervention that can help couples, regardless of HIV concordance status, move through the HIV care cascade, from testing, linkage to care, treatment, and retention using a cognitive-behavioral couples framework. This paper draws primarily on research with heterosexual couples in sub-Saharan Africa, though adapting this framework to meet the needs of diverse couples in other geographical regions is recommended. [ABSTRACT FROM AUTHOR]

Objective:To detect immunoglobulin M (IgM) anti-Toxoplasma gondii antibodies and determine immunoglobulin G (IgG) titer and avidity in filter paper-embedded blood (FPEB) samples of pregnant women.Study Design:A total of 100 FPEB samples of pregnant women (30 positive and 70 negative) were analyzed for anti-T. gondii-specific IgM antibodies. Eleven and nine pairs of serum and FPEB samples were used to standardize IgG titration and avidity, respectively. Then, the correlation of avidity results was determined with 23 serum/FPEB pairs from IgG-positive cases.Result:IgM detection in FPEB was 92% sensitive and 100% specific. The titration of IgG antibodies in FPEB correlated with that of serum (r 0.9). Significant difference in avidity between the acute and the undetermined/chronic cases was observed in both samples. As expected, no correlation was found between IgM levels and avidity.Conclusion:The FPEB is useful to infer infection phase, and thus to speed clinical decisions in congenital toxoplasmosis management. [ABSTRACT FROM AUTHOR]

Wearable sensor technologies are becoming increasingly relevant in health research, particularly in the context of chronic disease management. They generate real-time health data that can be translated into digital biomarkers, which can provide insights into our health and well-being. Scientific methods to collect, interpret, analyze, and translate health data from wearables to digital biomarkers vary, and systematic approaches to guide these processes are currently lacking. This paper is based on an observational, longitudinal cohort study, BarKA-MS, which collected wearable sensor data on the physical rehabilitation of people living with multiple sclerosis (MS). Based on our experience with BarKA-MS, we provide and discuss ten lessons we learned in relation to digital biomarker development across key study phases. We then summarize these lessons into a guiding framework (DACIA) that aims to informs the use of wearable sensor data for digital biomarker development and chronic disease management for future research and teaching. [ABSTRACT FROM AUTHOR]

One of the essential non-pharmacological treatments for patients with chronic diseases are psychosocial supports and counselling services such as spiritual psychotherapy. Although several preliminary studies represent the effects of counselling and spiritual psychotherapy on anxiety in patients with chronic diseases, there are various contradictions among the findings. The present meta-analysis aimed to determine the effects of counselling and spiritual care programs on anxiety in patients with chronic diseases. For data collection, various databases were searched regarding no time limitation until May 2021, including SID, MagIran, Embase, ProQuest, Scopus, PubMed, and Web of Science (WoS) using Google Scholar search engine. Inclusion criteria were original research articles, interventional studies, and exclusion criteria were irrelevant assessments, systematic review and meta-analysis studies, case reports, letters to the editor, and duplicate papers. I2 test was used to calculate heterogeneity of studies, and the Egger's test was applied to examine the publication bias. According to the inclusion criteria, 26 articles were selected among 612 initial papers with a sample size of 1040 individuals. The mean anxiety scores before and after the interventions were 33.02 ± 3.77 and 25.27 ± 3.66, respectively. The significant (P < 0.05) mean difference before and after the interventions was 1.74 ± 0.23. Counselling and psychotherapy can reduce anxiety in patients with chronic diseases. [ABSTRACT FROM AUTHOR]

Purpose: More than 20 years ago we reported an analysis of a case series of elderly critically ill patients with acute kidney injury (AKI)--then termed acute renal failure. At that time, AKI was regarded as a "simple" complication, but has since undergone a fundamental change and actually has become one of the central syndromes in the critically ill patient.Methods: We have analyzed elderly patients above 65 years of age with an AKI defined as serum creatinine above 3 mg/dl corresponding to modern KDIGO stage 3, most of them requiring renal replacement therapy (RRT). Using an extremely complete data set the diagnosis differentiated the underlying disease entity, the dominant cause of AKI, acute and chronic risk factors (comorbidities). Special aspects such as severity of disease, early AKI at admission versus late AKI, early versus later start of RRT, AKI not treated by RRT in spite of indication for RRT, various measures of short-term and long-term prognosis, renal outcome, patients dying with resolved AKI, and causes of death were evaluated.Results: Crude mortality was 61% which corresponds to modern studies with gross variation among the different subgroups. Age per se was not a determinant of survival either within the group of elderly patients or as compared to younger age groups. Despite an increase in mean age and disease severity during the observation period prognosis improved. A total of 17% of patients developed a chronic kidney disease. Long-term survival as compared to the general population was low.Conclusions: A look back at the last two decades illustrates a remarkable evolution or rather metamorphosis of a syndrome. AKI has evolved as a central syndrome in intensive care patients, a systemic disease process associated with multiple systemic sequels and extra-renal organ injury and exerting a pronounced effect on the course of disease and short- and long-term prognosis not only of the patient but also of the kidney. Moreover, the "non-renal-naïve" elderly patient with multiple comorbidities has become the most frequent ICU patient in industrialized nations. [ABSTRACT FROM AUTHOR]

Obesity is a complex, chronic disease requiring a multidisciplinary approach to its management. In clinical practice, body mass index and waist-related measurements can be used for obesity screening. The estimated prevalence of obesity among adults worldwide is 12%. With the expected further increase in overall obesity prevalence, clinicians will increasingly be managing patients with obesity. Energy balance is regulated by a complex neurohumoral system that involves the central nervous system and circulating mediators, among which leptin is the most studied. The functioning of these systems is influenced by both genetic and environmental factors. Obesity generally occurs when a genetically predisposed individual lives in an obesogenic environment for a long period. Cardiologists are deeply involved in evaluating patients with obesity. Cardiovascular risk profile is one of the most important items to be quantified to understand the health risk due to obesity and the clinical benefit that a single patient can obtain with weight loss. At the individual level, appropriate patient involvement, the detection of potential obesity causes, and a multidisciplinary approach are tools that can improve clinical outcomes. In the near future, we will probably have new pharmacological tools at our disposal that will facilitate achieving and maintaining weight loss. However, pharmacological treatment alone cannot cure such a complex disease. The aim of this paper is to summarize some key points of this field, such as obesity definition and measurement tools, its epidemiology, the main mechanisms underlying energy homeostasis, health consequences of obesity with a focus on cardiovascular diseases and the obesity paradox. Level of evidence V: report of expert committees. [ABSTRACT FROM AUTHOR]

Purpose: The main objective of this study is to assess the test–retest and inter-administration mode reliability of the Impact of Vision Impairment profile (IVI), a common patient-reported outcome measure (PROM) for people with chronic eye diseases. Methods: The IVI was administered to adult patients with stable, chronic eye diseases two to four times per participant (average intervals between administrations 12 to 20 days; maximum two phone interviews, paper administration, electronic administration) by two trained interviewers. Rasch models were fit to the data. Intra-class correlation coefficients (ICCs), mean differences and Cronbach's alpha between test–retest administrations (two phone interviews) and inter-mode comparisons were calculated. Results: Two hundred-sixteen patients (mean age 67 ± 12 years, 40% male) were included in the study. The IVI met all psychometric requirements of the Rasch model, and the division into the domains of functional items (IVI_F) and emotional items (IVI_E) corresponded to the German validation study. ICCs (all for IVI_F and IVI_E, respectively) for the retest administrations were 0.938 and 0.912, and 0.853 and 0.893 for inter-mode comparisons phone/paper, 0.939 and 0.930 for phone/electronic, and 0.937 and 0.920 for paper/electronic (all p < 0.01). Mean differences (all for IVI_F and IVI_E, respectively) for the retest administrations were 2.8% and 0.7% and ranged from 2.0% to 6.2% and from 0.4 % to 4.9% between administration modes. Cronbach's alpha ranged from 0.886 to 0.944 for retest and inter-mode comparisons. Conclusion: Due to the high test–retest reliability and the almost equally high comparability of different modes of administration of the IVI, the study endorses its use as a robust PROM to capture vision-related quality of life. Our results further support the use of the IVI as an endpoint in clinical trials and may simplify implementing it in both clinical trials or real-world evidence generation by offering multiple administration modes with high reliability. [ABSTRACT FROM AUTHOR]

This paper used two waves (2016 and 2018) of longitudinal data from the China Families Panel Survey (CFPS) to analyze the economic impact of Non-communicable chronic diseases (NCDs) on individual earned income using propensity score matching and difference in difference (PSM-DID) methods to control for potential confounding. The occurrence of a NCDs was associated with a significant decrease in earned income by 19.2% (P = 0.002, t = 3.75). The reasons for this decrease include: a lower labour force participation rate; lower weekly hours worked; and a lower average hourly wage. After holding labour market behaviours constant, different types of NCDs have different impacts on earned income. Musculoskeletal diseases have the greatest negative impact, accounting for a 21.5% decrease in individual earned income (p < 0.0001, t = −7.84), while digestive system diseases have the smallest impact accounting for a 6.9% decrease in earned income (p = 0.012, t = −2.52). [ABSTRACT FROM AUTHOR]

Chronic granulomatous disease (CGD), a primary immunodeficiency caused by impaired phagocyte killing of intracellular pathogens, is characterized by recurrent, life-threatening, bacterial and fungal infections. As a result of improvements in microbiologic culture and identification techniques, a number of unique filamentous fungi have been reported as significant pathogens in patients with CGD. We report a case of subcutaneous basidiomycete Phellinus mori infection in a patient with CGD. To the best of our knowledge, this is the first reported case of human infection by this fungus. The causative fungus was identified on the basis of its morphological characteristics and nucleotide sequence on the internal transcribed spacer region of the ribosomal RNA gene. This is the fifth case report of filamentous basidiomycetes infecting a patient with CGD; all of these cases have been caused by Phellinus species. We highlight the importance of recognizing filamentous basidiomycetes Phellinus species as possible agents of non- Aspergillus fungal infections in patients with CGD. [ABSTRACT FROM AUTHOR]

Gentiopicroside (GPS), a single compound isolated from Gentiana lutea L. and the crucial representative of secoiridoid constituent, has been permitted for centuries in traditional Chinese medicine. GPS and its metabolites have been increasingly used in the search for clinical management with therapeutic properties and fewer side effects. The objective of this review was to provide a comprehensive overview of the involvement of molecular pathways in the therapeutic effects of GPS on human diseases and chronic conditions. This study presents a meticulously conducted comprehensive search of the PubMed and Google Scholar databases (from 1983 to 2023), aimed at identifying articles relating to regulatory mechanisms of GPS on human diseases and the pharmacokinetics of GPS. The inclusion criteria were meticulously and precisely defined to encompass original research papers that explicitly focused on elucidating the regulatory mechanisms of GPS in various human diseases through in vitro and animal studies. Notably, these studies were mandated to integrate specific genetic markers or pathways as essential components of their research inquiries. The evaluated pharmacokinetic parameters included maximum plasma concentration (Cmax), time to reach maximum plasma concentration (Tmax), area under the curve (AUC), clearance, and plasma half-life (t1/2). Subsequently, through a rigorous screening process of titles and abstracts, studies conducted in vitro or on animals, as well as those reporting pharmacokinetic data related to drugs other than GPS or language barriers, were systematically excluded. Drawing from the data and studies pertaining to this review, we conducted a thorough and informative analysis of the pharmacological characteristics and biological functions of GPS. These encompassed a wide range of effects, including hepatoprotective, anti-inflammatory, antifibrotic, antioxidant, analgesic, antitumor, and immunomodulatory properties. The analysis provided a comprehensive and insightful understanding of GPS's pharmacological profile and its diverse activities. Enhancing theoretical and experimental methodologies could prove advantageous in expanding the clinical applications of GPS. This could involve optimizing the bioavailability and pharmacokinetics of GPS, uncovering additional biomarkers and potential biotransformation pathways, and investigating its combined effects with standard-of-care medications. [ABSTRACT FROM AUTHOR]

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Aim: The aim of this study is to provide a synthesis of prior research of estimates of the willingness to pay (WTP) for chronic disease treatment and examines the impact of economic and political institutions, cultures, and other important factors on WTP. Subject and method: The paper applies meta-regression analysis to 1053 estimates of WTP from 188 medical treatment studies from 40 countries. Results: The results suggest that patients assign higher values for medical treatment in more capitalistic and more democratic countries. Cultural traits also appear to matter, with higher WTP in societies characterized by individualism and indulgence. Further, disease types matter. Compared to cancer, WTP is lower for diabetes, obesity, asthma, and heart disease treatment, but higher for amyotrophic lateral sclerosis therapy. GDP per capita is positively associated with WTP. The higher public health expenditure is in a country, the higher citizens value health benefits. If individuals expect to live longer, then they will spend less on their health. The published studies estimate a lower value than unpublished studies. Conclusion: This paper presents a comprehensive synthesis of estimates of chronically ill patients' WTP for medical treatment and identifies the key factors determining WTP through a meta-regression analysis. The main finding is that economic and political institutions, cultural traits, the types of disease, socio-economic characteristics, and valuation methods all influence WTP estimates. [ABSTRACT FROM AUTHOR]

In managing patients with chronic diseases, such as open angle glaucoma (OAG), the case treated in this paper, medical tests capture the disease phase (e.g. regression, stability, progression, etc.) the patient is currently in. When medical tests have low residual variability (e.g. empirical difference between the patient's true and recorded value is small) they can effectively, without the use of sophisticated methods, identify the patient's current disease phase; however, when medical tests have moderate to high residual variability this may not be the case. This paper presents a framework for handling the latter case. The framework presented integrates the outputs of interacting multiple model Kalman filtering with supervised learning classification. The purpose of this integration is to estimate the true values of patients' disease metrics by allowing for rapid and non-rapid phases; and dynamically adapting to changes in these values over time. We apply our framework to classifying whether a patient with OAG will experience rapid progression over the next two or three years from the time of classification. The performance (AUC) of our model increased by approximately 7% (increased from 0.752 to 0.819) when the Kalman filtering results were incorporated as additional features in the supervised learning model. These results suggest the combination of filters and statistical learning methods in clinical health has significant benefits. Although this paper applies our methodology to OAG, the methodology developed is applicable to other chronic conditions. [ABSTRACT FROM AUTHOR]

Epidemiologic investigations have previously been published in more than 200 papers, and several studies have examined the impacts of particle air pollution on health. The main conclusions now being made about the epidemiological evidence of particle pollution-induced health impacts are discussed in this article. Although there is no universal agreement, most reviewers conclude that particulate air pollution, particularly excellent combustion-cause contamination prevalent in many municipal and manufacturing environments, is a significant risk for cardiopulmonary sickness and mortality. Most epidemiological research has concentrated on the impacts of acute exposure, although the total public health implications of chronic acquaintance's outcome may be more extraordinarily significant. According to some reviewers, prolonged, repeated exposure raises the risk of cardiorespiratory death and chronic respiratory illness. A more general (but still universal) agreement is that short-term particle pollution exposure has been shown to aggravate pre-existing pulmonary and cardiovascular diseases and increase the number of community members who become sick, require medical treatment, or die. Several in-depth studies conducted in the global and Indian regions are addressed. [ABSTRACT FROM AUTHOR]

Whereas exercise training, as part of multidisciplinary rehabilitation, is a key component in the management of patients with chronic coronary syndrome (CCS) and/or congestive heart failure (CHF), physicians and exercise professionals disagree among themselves on the type and characteristics of the exercise to be prescribed to these patients, and the exercise prescriptions are not consistent with the international guidelines. This impacts the efficacy and quality of the intervention of rehabilitation. To overcome these barriers, a digital training and decision support system [i.e. EXercise Prescription in Everyday practice & Rehabilitative Training (EXPERT) tool], i.e. a stepwise aid to exercise prescription in patients with CCS and/or CHF, affected by concomitant risk factors and comorbidities, in the setting of multidisciplinary rehabilitation, was developed. The EXPERT working group members reviewed the literature and formulated exercise recommendations (exercise training intensity, frequency, volume, type, session and programme duration) and safety precautions for CCS and/or CHF (including heart transplantation). Also, highly prevalent comorbidities (e.g. peripheral arterial disease) or cardiac devices (e.g. pacemaker, implanted cardioverter defibrillator, left-ventricular assist device) were considered, as well as indications for the in-hospital phase (e.g. after coronary revascularisation or hospitalisation for CHF). The contributions of physical fitness, medications and adverse events during exercise testing were also considered. The EXPERT tool was developed on the basis of this evidence. In this paper, the exercise prescriptions for patients with CCS and/or CHF formulated for the EXPERT tool are presented. Finally, to demonstrate how the EXPERT tool proposes exercise prescriptions in patients with CCS and/or CHF with different combinations of CVD risk factors, three patient cases with solutions are presented. [ABSTRACT FROM AUTHOR]

Psoriatic arthritis (PsA) is a complex and chronic inflammatory condition in which the achievement of the best possible disease control has been proposed as the treatment target, which includes the possibility of reaching remission in all disease domains. However, due to the complexity of this multidomain disease, some patients may still have high disease activity in one or more domain and a high burden of disease, potentially leading to various treatment changes and to difficulty with the overall management. In this paper, we overview the concept of patients with difficult-to-treat PsA and the concept of patients with refractory-to-treatment PsA by providing a distinction between these two concepts and the possible implication for the management of patients with PsA. [ABSTRACT FROM AUTHOR]

Seamless handoff is crucial for wireless body area network (WBAN) data's transmission, it may avoid the death resulted from sudden diseases, especially for the elder people who suffer from chronic diseases. Therefore, a vertical handoff algorithm that conforms to the characteristics of body area network is urgent. Different from the traditional service types in telecommunications, service types in wireless body area network have their own characteristics. How to reasonably divide these service types according to their requirement of the internet is very important. In addition, we need to study the rationality of different weighting and network selection algorithms for body area network users. In view of the lack of vertical handoff algorithms to meet the characteristics of wireless body area networks, this paper first analyzes the service types in body area network, and reasonably divides the service types in body area network into four types. For these four services types, we comprehensively and systematically analyze the weight determination and network selection algorithms suitable for them. In addition, in wireless body area network environment, there may be situations when multiple users need to transmit information at the same time. For these situations, we propose a broadcast mechanism to prevent network congestion caused by group switching. The simulation results show that the combination of using Analytic hierarchy process to determine the weight and using Technique for Order Preference by Similarity to Ideal Solution as the network selection method is most suitable for vertical handoff in WBAN. The proposed broadcast mechanism can solve the network congestion problem caused by group handoff. [ABSTRACT FROM AUTHOR]

Background: Case-finding tools, such as the Identify Chronic Migraine (ID-CM) questionnaire, can improve detection of CM and alleviate its significant societal burden. We aimed to develop and validate the Italian version of the ID-CM (ID-EC) in paper and as a smart app version in a headache clinic-based setting.Methods: The study investigators translated and adapted to the Italian language the original ID-CM questionnaire (ID-EC) and further implemented it as a smart app. The ID-EC was tested in its paper and electronic version in consecutive patients referring to 9 Italian tertiary headache centers for their first in-person visit. The scoring algorithm of the ID-EC paper version was applied by the study investigators (case-finding) and by patients (self-diagnosis), while the smart app provided to patients automatically the diagnosis. Diagnostic accuracy of the ID-EC was assessed by matching the questionnaire results with the interview-based diagnoses performed by the headache specialists during the visit according to the criteria of International Classification of Headache Disorders, III edition, beta version.Results: We enrolled 531 patients in the test of the paper version of ID-EC and 427 in the validation study of the smart app. According to the clinical diagnosis 209 patients had CM in the paper version study and 202 had CM in the smart app study. 79.5% of patients returned valid paper questionnaires, while 100% of patients returned valid and complete smart app questionnaires. The paper questionnaire had a 81.5% sensitivity and a 81.1% specificity for case-finding and a 30.7% sensitivity and 90.7% specificity for self-diagnosis, while the smart app had a 64.9% sensitivity and 90.2% specificity.Conclusions: Our data suggest that the ID-EC, developed and validated in tertiary headache centers, is a valid case-finding tool for CM, with sensitivity and specificity values above 80% in paper form, while the ID-EC smart app is more useful to exclude CM diagnosis in case of a negative result. Further studies are warranted to assess the diagnostic accuracy of the ID-EC in general practice and population-based settings. [ABSTRACT FROM AUTHOR]

This paper promotes better life quality and lifestyle for patients. We attain this goal by creating a mobile application that analyses patient's medical records, such as diabetes, hypertension, and chronic kidney diseases. Then, we implement the system to diagnose patients with chronic conditions using machine learning techniques. Machine learning classifiers are used in this paper to decide whether a person has any chronic diseases. The investigated diseases are hypertension, diabetes, and chronic kidney disease. Four datasets were used to build the classifying models. Orange3 from Anaconda-Navigator, a data mining tool, was used to test machine learning algorithms. The study findings revealed the superiority of the tree algorithm with 100% accuracy for hypertension; it was the highest outcome for both males and females using Orange3. The highest precision, which is 100%, is observed by SVM, k-NN, decision trees, logistic regression, and CART for hypertension males' data collection. In comparison, the highest precision is 100% in SVM, MLP, decision tree, random forest, logistic regression, and CART for the female dataset. We conclude that the two datasets for the same diseases share mostly the same algorithm accuracy. For kidneys, the Random Forest algorithm produced 100% accuracy, which is the highest value among other algorithms. For diabetes, neural networks have attested the best accuracy. It was 76.3%, yet the accuracy increased slightly as the kNN algorithm showed 83% accuracy. [ABSTRACT FROM AUTHOR]

This paper uses the survival strategies of food shelf clients to explore how food access, chronic disease, and spatial isolation shape the lives of low- and no- income urban citizens. The abundant availability of unhealthy food intersects with the presence of long-term health conditions to create a marginalized urban space where low quality commodity food is available, but exacerbates existing health conditions, is difficult to access, and does little to create food security. To survive, clients have normalized a sustenance strategy of going to multiple food serving sites, carrying food long-distances and using SNAP benefits to make ends meet. However, this nourishment strategy is time-consuming and unsafe, demanding that people put themselves in precarious positions and push their bodies farther physically than is healthy. These food procurement strategies exacerbate their marginalization. Qualitative data from food shelf users is used to develop a theory of ambient struggling wherein the struggle for food access is unhealthy and time-consuming, making it difficult to improve their standard of living. [ABSTRACT FROM AUTHOR]

Medical image analysis plays a pivotal role in the evaluation of diseases, including screening, surveillance, diagnosis, and prognosis. Liver is one of the major organs responsible for key functions of metabolism, protein and hormone synthesis, detoxification, and waste excretion. Patients with advanced liver disease and Hepatocellular Carcinoma (HCC) are often asymptomatic in the early stages; however delays in diagnosis and treatment can lead to increased rates of decompensated liver diseases, late-stage HCC, morbidity and mortality. Ultrasound (US) is commonly used imaging modality for diagnosis of chronic liver diseases that includes fibrosis, cirrhosis and portal hypertension. In this paper, we first provide an overview of various diagnostic methods for stages of liver diseases and discuss the role of Computer-Aided Diagnosis (CAD) systems in diagnosing liver diseases. Second, we review the utility of machine learning and deep learning approaches as diagnostic tools. Finally, we present the limitations of existing studies and outline future directions to further improve diagnostic accuracy, as well as reduce cost and subjectivity, while also improving workflow for the clinicians. [ABSTRACT FROM AUTHOR]

Background and Objective: Rare diseases place a significant burden on patients, families, the healthcare system, and society. Evidence on the socioeconomic burden of rare disease is limited and mostly reflects diseases where treatments are available. We developed a framework encompassing recommended cost elements for studies of the socioeconomic burden of rare diseases. Methods: A scoping review, conducted in five databases (Cochrane Library, EconLit, Embase, MEDLINE, and APA PsycINFO), identified English language publications from 2000 to 2021 presenting frameworks developed for determining, measuring or valuing costs for rare or chronic diseases. Cost elements were extracted and used to develop a literature-informed framework. Structured feedback was gathered from experts in rare diseases, health economics/health services, and policy research to revise the framework. Results: Of 2990 records identified, eight papers were included and informed our preliminary framework; three focused on rare disease and five on chronic disease. Following expert input, we developed a framework consisting of nine cost categories (inpatient, outpatient, community, healthcare products/goods, productivity/education, travel/accommodation, government benefits, family impacts, and other), with several cost elements within each category. Our framework includes unique costs, added from the expert feedback, including genetic testing to inform treatment, use of private laboratories or out-of-country testing, family involvement in foundations and organizations, and advocacy costs for special access programs. Conclusions: Our work is the first to identify a comprehensive list of cost elements for rare disease for use by researchers and policy makers to fully capture socioeconomic burden. Use of the framework will increase the quality and comparability of future studies. Future work should focus on measuring and valuing these costs through onset, diagnosis, and post-diagnosis. [ABSTRACT FROM AUTHOR]

Despite decades of action to reduce global malnutrition, rates of undernutrition remain stubbornly high and rates of overweight, obesity and chronic disease are simultaneously on the rise. Moreover, while volumes of robust research on causes and solutions to malnutrition have been published, and calls for interdisciplinarity are on the rise, researchers taking different epistemological and methodological choices have largely remained disciplinarily siloed. This paper works to open a scholarly conversation between "mainstream" public health nutrition and "critical" nutrition studies. While critical nutrition scholars collectively question aspects of mainstream nutrition approaches, they also chart a different way to approach malnutrition research by focusing on politics, structural conditions, and the diverse ways people make sense of food and malnutrition. In this paper, we highlight the key research agendas and insights within both mainstream and critical nutrition in order to suggest spaces for their potential conversation. We ultimately argue that global public health nutrition interventions might achieve greater success in more equitable ways if they are informed by critical nutrition research. We aim for this intervention to facilitate more substantial crossing of disciplinary boundaries, critical to forging more socially and environmentally just dietary futures in the global South and beyond. [ABSTRACT FROM AUTHOR]

Many studies across disciplines assert that chronic illness and emotional wellbeing are closely related. Yet, studies in the literature rarely examined the mediators of the relationship from a socioeconomic perspective. In particular, despite its significance in the welfare of people in developing countries, studies have rarely investigated the effects of chronic illness on, among others, aspirations, the failure of which may be linked to a self-sustaining trap of poverty in developing countries. Using two waves of Indonesian Family Life Survey (IFLS 2007, 2014), this paper examines the effect of chronic illness on aspirations and the channel through which the duration of chronic illness affects aspirations and emotional wellbeing. To this end, this paper uses a variable measuring an aspirations gap, constructed by a difference between an individual's current level of life evaluation and his/her future aspired level of wealth. Overall, results of this study suggest that chronic illness brings about a vicious cycle in which a deterioration in an individual's current life evaluation, compared to the person's cognitive neighborhood, leads to a greater aspirations gap, which, in turn, reinforces feelings of unhappiness and dissatisfaction with life. Furthermore, the effects of chronic illness are found to be greater on the poor in the bottom 25% of household income. [ABSTRACT FROM AUTHOR]

Thanks to advances in care, most children with congenital heart disease nowadays survive into adulthood. The majority of patients remain at high risk for future complications. Hence, life-long follow-up is mandatory. Care needs of patients evolve, especially when reaching adulthood. A structured transition period to adult care is advocated. Currently, a fully detailed and structured transition program is not available for patients with congenital heart disease. The aim is to describe the development and design of a multicomponent transition program for adolescents with congenital heart disease, called "Transition with a heart." Transition with a heart was developed based on the Dutch program "On your own feet," starting at the age of 12 years and continuing after transfer. The most vital core components include a general and individualized flowchart, adolescent-centered communication, a joined transfer consultation, and an appointed transition coordinator. Adolescents are gradually informed about their condition and potential late consequences in adult life and stimulated to take medical care in their own hands.Conclusion: Transition with a heart is a practical, multicomponent, comprehensive transition program developed to cover the essential aspects of transitional care for adolescents with congenital heart disease (i.e., continuity of care, disease knowledge, and self-management skills). Interventions were selected from the highest sources of scientific evidence currently available.Clinical trial registration: Not applicableWhat is Known:• Transition towards adult life and health care is a complex process, requiring careful patients' guidance. Various task forces have described the need and potential benefits of transition programs in young people with chronic conditions. Details about the practical development and content of such programs in congenital heart disease are, however, currently lacking.What is New:• This method paper presents the development and design of a person-centered multicomponent transition program for adolescents with congenital heart disease comprising interventional components covering the most important aspects of transitional care: promoting autonomy, disease knowledge, and continuity of care. [ABSTRACT FROM AUTHOR]

This narrative review paper aims to build a common understanding of the vulnerabilities of children with chronic medical conditions who face exceptional challenges due to nature of the illness, deformity, injury, and traumatic healthcare encounters which could potentially lead to long-term psychological effects. The presence of chronic medical diagnoses in children and the subsequent impacts including social stigma, as well as their age and developmental level, may amplify adjustment challenges in parenting considerations, school, peer relations, career, and future relationships. Children may be traumatized by unfamiliar and painful healthcare experiences. Hospitalization can lead to increased feelings of isolation, fear, and self-doubt when children do not receive emotionally safe psychological support necessary to minimize the accompanying stress and anxiety. School experiences and parenting children with chronic illnesses have additional intersecting socialization characteristics. This paper highlights a vision for furthering the groundwork within Indian pediatric settings to promote emotional safety and psychosocial care. Principles from the United Nations Convention on the Rights of the Child and the World Health Organization's definition of health create an impetus for giving a voice to children with chronic medical conditions. While there are sporadic psychosocial services for children with chronic needs, they lack consistency, and this indicates a need and an opportunity for developing a unique career for human development and psychology professionals to address these concerns. As exemplars, two psychosocial care programs in India that help foster resilience in these children are highlighted. Although limited, extant research regarding the experiences of children with chronic medical conditions in India is discussed, and implications for future research and academic initiatives are interwoven within this paper. [ABSTRACT FROM AUTHOR]

This systematic review summarises the parenting intervention literature for parents of children who have a sibling with a chronic health condition, and evaluates intervention efficacy for improving parent (parenting skills, parenting efficacy) and child (emotional and behavioural adjustment, condition knowledge, quality of life) outcomes. Electronic databases were searched to identify relevant papers published in English from inception until May 2020. Reference lists of eligible papers were further searched for relevant articles. Six papers (two controlled trials, four uncontrolled trials) evaluating four separate intervention programs met inclusion criteria. All included parent- and child-focused intervention components. Results showed an overall trend for pre- to post-intervention improvement in children's behavioural and emotional adjustment and health condition knowledge. Few studies examined effects on parent outcomes, and there was no evidence of change on these measures. Overall, results suggest that parenting interventions may help to improve siblings' emotional and behavioural adjustment and condition knowledge; however, all of the interventions combined parent- and child-directed intervention components, making it difficult to determine which intervention elements drive change. Further research is needed to test mechanisms by which parenting interventions may improve outcomes for siblings of children with chronic health conditions, and to establish the efficacy of this approach. [ABSTRACT FROM AUTHOR]

Purpose: Self-efficacy is important for managing chronic conditions; however, its measurement in pediatric healthcare settings remains rare. The goal of this project was to adapt an existing disease-agnostic adult self-efficacy patient reported outcome (PRO) measure to enhance suitability of items for measuring the self-efficacy of parents that manage their children's health conditions. Methods: We adapted the existing Patient-Reported Outcomes Measurement Information System® (PROMIS®) adult self-efficacy healthcare measure to parental voice. First, a targeted literature review informed rephrasing of the adult items and identification of new pediatric-specific content. The initial item pool was revised based on input from 12 multidisciplinary experts. Next cognitive interviews of adapted items were simultaneously conducted with English and Spanish-speaking parents of pediatric patients with a range of chronic and/or disabling conditions recruited from a Midwestern children's hospital to finalize the measure. Results: Findings resulted in an initial item pool of 33 pediatric-specific items which were narrowed to 31 draft items based on expert input. Parent cognitive interview findings (N = 26) informed further item reduction resulting in a final measure consisting of 30 items representing nine domains. Fourteen items are relevant to children regardless of condition severity (e.g., health care information/decision making; symptom identification/management) and 16 items are relevant to children with specific health care needs (e.g., medication usage, equipment). Conclusion: We conducted a first step in developing a condition-agnostic, PRO measure of parental self-efficacy managing their children's chronic and/or disabling conditions that is acceptable and understandable to English and Spanish-speaking parents. Plain English Summary: Self-efficacy, which is someone's confidence in completing a task, is important for managing a chronic health condition. Knowing parents' self-efficacy managing their children's health conditions may be an important step in supporting their children's health but no single measure is available for diverse sets of conditions. In this paper, we present the development of a new patient reported outcomes measure designed to assess self-efficacy of parents managing their child's chronic and/or disabling conditions. We found that the measure is both acceptable and understandable to English and Spanish speakers and may be useful to proactively identify parents in need of additional supports at hospital discharge or at the time of a new diagnosis. [ABSTRACT FROM AUTHOR]

Background: Patients with a chronic disease are more vulnerable in the labor market, and work-related support in clinical care would enhance the timely support greatly needed in each phase of their working life. This paper describes the development of a generic stay-at-work intervention to provide work-related support in clinical care to patients with a chronic disease. Methods: Steps 1–4 of Intervention Mapping (IM) were combined with action research principles. A needs assessment (Step 1) involved the project group formation, a literature review, qualitative studies with healthcare professionals (HCPs; n = 9) and patients (n = 10), consultation with financial staff and testing, and resulted in objectives (Step 2). Guided by methods and applications (Step 3), the intervention was developed, tested and finalized (Step 4). Results: The needs assessment revealed the importance of behavioral change in HCPs, including changing attitude, self-efficacy, and social influence. For that purpose, a pathway and training sessions were developed. Testing these unveiled the need for practical tools and intervision. The final intervention comprises a care pathway as part of working routines, including screening, risk stratification, and tailored support. Practical tools, training sessions, and intervision for HCPs were developed. Conclusions: Combining IM with action research principles resulted in a generic stay-at-work intervention in clinical care via behavioral change in HCPs. A generic care pathway, practical tools, training sessions, and intervision were developed. More specific alignment to specific patient groups is possible. To implement the intervention in another hospital, the local context, (financial) resources, and the national legislation should be considered. [ABSTRACT FROM AUTHOR]

Purpose: Patient engagement has traditionally been limited to involving patients in decision-making regarding their healthcare choices. The goal of this paper was to assess patients' perspectives on how they might be involved as a research partner in the design and implementation of pharmacoepidemiology research studies. Methods: Qualitative research methods were used to elicit patient perspectives on their involvement in pharmacoepidemiologic research. A total of 20 patients participated in five focus groups held from April to August 2016. Each focus group represented one of five chronic conditions, namely: human immunodeficiency virus/acquired immunodeficiency syndrome (HIV)/(AIDS), diabetes, mental health conditions, mild cognitive impairment/Alzheimer's disease (AD), and cardiovascular disease (CVD)/hypertension. A semi-structured field guide was used to elicit views on drug safety and effectiveness and to identify which aspects of the design and implementation of a research study individuals felt most comfortable contributing to. The discussions were audio-recorded, transcribed verbatim, and analyzed following a grounded theory approach to identify the key themes that consequently emerged. Results: For the most part, individuals equated safety with side-effects. There were several dimensions of effectiveness that corresponded with biological, clinical, and psychological aspects of well-being. Most individuals (84%) were comfortable deciding what information should be collected, and 74% felt they could help researchers select target outcomes to study. Fewer (58%) were confident they could advise on selecting comparator drugs. Conclusion: There is a need for training the patient community and for adapting existing patient engagement standards to expand patient involvement in pharmacoepidemiologic research. [ABSTRACT FROM AUTHOR]

Chronic diseases (such as diabetes, hypertension, etc) are generally of long duration and slow progression. These diseases may be implied in electronic medical records (EMR), and one chronic disease may be accompanied by another. Recently, many methods have been proposed for chronic disease prediction and early detection. However, previous methods mainly focused on predicting one individual disease, thus possibly neglecting potential correlations among multiple diseases. In this paper, we propose a new framework for chronic disease prediction which can take into account possible correlations among multiple chronic diseases, called ChroNet. We propose a Multi-task Learning (MTL) based framework, for multiple chronic disease prediction. First, based on the characteristics of EMR, we introduce a novel approach for data embedding, including Content Embedding and Spatial Embedding. Then, an MTL convolutional neural network (CNN) is designed to perform multiple chronic disease prediction simultaneously. We collect a dataset from 5 local hospitals, involving 48953 patients' records. Then we conduct abundant experiments for hypertension and type 2 diabetes prediction, based on our dataset. For both hypertension and type 2 diabetes prediction, our proposed framework outperforms known single-task models (with the same CNN layers yet a single branch). Further, our MTL-based framework outperforms several most commonly used traditional machine learning models and convolutional neural networks. Theoretically, our framework can capture general features of different diseases and focus its attention on those features that actually matter for each disease. The performance superiority in experiments indicates that our framework may be able to capture more detailed characteristics of medical structural data after specific embedding, comparing with known single-task models. [ABSTRACT FROM AUTHOR]

Over the past decades, nanomedicine, the medical application of nanotechnology, has been extensively investigated as a promising approach in treating different inflammatory disorders and conditions. Nanomedicine provides a wide range of engineered nanomaterials, such as polymeric nanoparticles (NPs), lipid-based NPs, liposomes, silica NPs, metallic NPs, etc. Nanomaterial-based drug delivery systems exhibit multiple advantages such as the ability to pass through different physiological barriers within the body and specifically deliver drugs to the required sites without affecting healthy cells and tissues. Enormous amounts of in-vitro and in-vivo researches were previously conducted by many research groups to validate the positive contribution that nanomedicine has regarding the treatment of inflammation and its associated illnesses. The scope of this review paper is to overview the current status of using nanomaterials in the treatment of inflammatory diseases, with an emphasis on asthma, rheumatoid arthritis, inflammatory bowel disease, gout and atherosclerosis. The future prospects of using nanomaterials for inflammatory diseases were also briefly discussed. [ABSTRACT FROM AUTHOR]

Background: Interventions that use the Health Action Process Approach (HAPA) model show promise for increasing PA frequency, duration, and intensity. However, there is limited understanding of how HAPA model variables have been operationalized for PA interventions in chronic disease to promote behavior change and sustained PA or whether the phase or continuous form of the HAPA model was used. The aim of this scoping review is to describe how the HAPA model variables for PA interventions were operationalized and provide details of implementation.We searched five databases to identify studies published between January 1992 and March 2024. We aimed to describe (1) the characteristics of interventions including setting, delivery mode, duration, and content; (2) which HAPA variables were operationalized and the strategies used; and (3) the physical activity measures and outcome effects.The search identified 23 interventions in 30 papers (12 protocols, 3 quasi-experimental studies, and 15 randomized controlled trials (RCTs)). Seven of the 15 RCTs reported significant positive effects of the HAPA model on PA behavior outcomes. Interventions operationalized between three and nine HAPA constructs showed significant variability in how the HAPA model is used in intervention research. PA measures varied from self-report to validated objective instruments.We found a lack of clarity in decisions about which HAPA constructs were included in interventions. The wide variability in operationalized HAPA constructs made it challenging to compare interventions. Researchers should provide more detail about intervention design and implementation procedures to enhance transparency.Method: Interventions that use the Health Action Process Approach (HAPA) model show promise for increasing PA frequency, duration, and intensity. However, there is limited understanding of how HAPA model variables have been operationalized for PA interventions in chronic disease to promote behavior change and sustained PA or whether the phase or continuous form of the HAPA model was used. The aim of this scoping review is to describe how the HAPA model variables for PA interventions were operationalized and provide details of implementation.We searched five databases to identify studies published between January 1992 and March 2024. We aimed to describe (1) the characteristics of interventions including setting, delivery mode, duration, and content; (2) which HAPA variables were operationalized and the strategies used; and (3) the physical activity measures and outcome effects.The search identified 23 interventions in 30 papers (12 protocols, 3 quasi-experimental studies, and 15 randomized controlled trials (RCTs)). Seven of the 15 RCTs reported significant positive effects of the HAPA model on PA behavior outcomes. Interventions operationalized between three and nine HAPA constructs showed significant variability in how the HAPA model is used in intervention research. PA measures varied from self-report to validated objective instruments.We found a lack of clarity in decisions about which HAPA constructs were included in interventions. The wide variability in operationalized HAPA constructs made it challenging to compare interventions. Researchers should provide more detail about intervention design and implementation procedures to enhance transparency.Results: Interventions that use the Health Action Process Approach (HAPA) model show promise for increasing PA frequency, duration, and intensity. However, there is limited understanding of how HAPA model variables have been operationalized for PA interventions in chronic disease to promote behavior change and sustained PA or whether the phase or continuous form of the HAPA model was used. The aim of this scoping review is to describe how the HAPA model variables for PA interventions were operationalized and provide details of implementation.We searched five databases to identify studies published between January 1992 and March 2024. We aimed to describe (1) the characteristics of interventions including setting, delivery mode, duration, and content; (2) which HAPA variables were operationalized and the strategies used; and (3) the physical activity measures and outcome effects.The search identified 23 interventions in 30 papers (12 protocols, 3 quasi-experimental studies, and 15 randomized controlled trials (RCTs)). Seven of the 15 RCTs reported significant positive effects of the HAPA model on PA behavior outcomes. Interventions operationalized between three and nine HAPA constructs showed significant variability in how the HAPA model is used in intervention research. PA measures varied from self-report to validated objective instruments.We found a lack of clarity in decisions about which HAPA constructs were included in interventions. The wide variability in operationalized HAPA constructs made it challenging to compare interventions. Researchers should provide more detail about intervention design and implementation procedures to enhance transparency.Conclusion: Interventions that use the Health Action Process Approach (HAPA) model show promise for increasing PA frequency, duration, and intensity. However, there is limited understanding of how HAPA model variables have been operationalized for PA interventions in chronic disease to promote behavior change and sustained PA or whether the phase or continuous form of the HAPA model was used. The aim of this scoping review is to describe how the HAPA model variables for PA interventions were operationalized and provide details of implementation.We searched five databases to identify studies published between January 1992 and March 2024. We aimed to describe (1) the characteristics of interventions including setting, delivery mode, duration, and content; (2) which HAPA variables were operationalized and the strategies used; and (3) the physical activity measures and outcome effects.The search identified 23 interventions in 30 papers (12 protocols, 3 quasi-experimental studies, and 15 randomized controlled trials (RCTs)). Seven of the 15 RCTs reported significant positive effects of the HAPA model on PA behavior outcomes. Interventions operationalized between three and nine HAPA constructs showed significant variability in how the HAPA model is used in intervention research. PA measures varied from self-report to validated objective instruments.We found a lack of clarity in decisions about which HAPA constructs were included in interventions. The wide variability in operationalized HAPA constructs made it challenging to compare interventions. Researchers should provide more detail about intervention design and implementation procedures to enhance transparency. [ABSTRACT FROM AUTHOR]

During and beyond the twentieth century, urbanization has represented a major demographic shift particularly in the developed world. The rapid urbanization experienced in the developing world brings increased mortality from lifestyle diseases such as cancer and cardiovascular disease. We set out to understand how urbanization has been measured in studies which examined chronic disease as an outcome. Following a pilot search of PUBMED, a full search strategy was developed to identify papers reporting the effect of urbanization in relation to chronic disease in the developing world. Full searches were conducted in MEDLINE, EMBASE, CINAHL, and GLOBAL HEALTH. Of the 868 titles identified in the initial search, nine studies met the final inclusion criteria. Five of these studies used demographic measures (such as population density) at an area level to measure urbanization. Four studies used more complicated summary measures of individual and area level data (such as distance from a city, occupation, home and land ownership) to define urbanization. The papers reviewed were limited by using simple area level summary measures (e.g., urban rural dichotomy) or having to rely on preexisting data at the individual level. Further work is needed to develop a measure of urbanization that treats urbanization as a process and which is sensitive enough to track changes in “urbanicity” and subsequent emergence of chronic disease risk factors and mortality. [ABSTRACT FROM AUTHOR]

The three papers included in this special issue represent a set of presentations in an invited session on disease ecology at the 2005 Spring Meeting of the Eastern North American Region of the International Biometric Society. The papers each address statistical estimation and inference for particular components of different disease processes and, taken together, illustrate the breadth of statistical issues arising in the study of the ecology and public health impact of disease. As an introduction, we provide a very brief overview of the area of “disease ecology”, a variety of synonyms addressing different aspects of disease ecology, and present a schematic structure illustrating general components of the underlying disease process, data collection issues, and different disciplinary perspectives ranging from microbiology to public health surveillance. [ABSTRACT FROM AUTHOR]

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to present a review of existing researches in the literature, referring to Big Data sources and techniques in health sector and to identify which of these techniques are the most used in the prediction of chronic diseases. Academic databases and systems such as IEEE Xplore, Scopus, PubMed and Science Direct were searched, considering the date of publication from 2006 until the present time. Several search criteria were established as 'techniques' OR 'sources' AND 'Big Data' AND 'medicine' OR 'health', 'techniques' AND 'Big Data' AND 'chronic diseases', etc. Selecting the paper considered of interest regarding the description of the techniques and sources of Big Data in healthcare. It found a total of 110 articles on techniques and sources of Big Data on health from which only 32 have been identified as relevant work. Many of the articles show the platforms of Big Data, sources, databases used and identify the techniques most used in the prediction of chronic diseases. From the review of the analyzed research articles, it can be noticed that the sources and techniques of Big Data used in the health sector represent a relevant factor in terms of effectiveness, since it allows the application of predictive analysis techniques in tasks such as: identification of patients at risk of reentry or prevention of hospital or chronic diseases infections, obtaining predictive models of quality. [ABSTRACT FROM AUTHOR]

The huge health expenditure for chronic diseases in the elderly is one of the uncertain factors that may cause the Borderline poor families to return to poverty after China fully lifts itself out of poverty in 2020, especially in rural low-income areas. Based on the latest data released by China Health and Retirement Longitudinal Study, this paper used the two-part model to analyze the impact of elderly chronic diseases on health expenditure and catastrophic health expenditure of Borderline poor families in rural China. Some interesting results were found. For example, elderly chronic diseases such as stroke and hepatic disease have a large impact on the catastrophic health expenditures of families on the edge of poverty in rural China. Therefore, the government should drive middle-aged and elderly people to actively participate in physical exercise and prevent the high incidence of chronic diseases in the elderly. Furthermore, the government should improve the medical insurance system to provide solid support for low-income families and other vulnerable groups to avoid returning to poverty. [ABSTRACT FROM AUTHOR]

Purpose: For decades, it has been customary to relate human health to the nutritional composition of foods, and from there was born food composition databases, composition labelling scores and the recommendation to eat varied foods. However, individuals can fully address their nutritional needs and become chronically ill. The nutrient balance of a food is only a small part of its overall health potential. In this paper, we discussed the proof of concept that the increased risk of chronic diseases worldwide is primarily associated with the degradation and artificialization of food matrices, rather than only their nutrient contents, based on the assumption that "food matrices govern the metabolic fate of nutrients". Methods: An empirico-inductive proof of concept research design has been used, based on scientific data linking the degree of food processing, food matrices and human health, notably on the glycaemic index, nutrient bioavailability, satiety potential, and synergistic effects. Results: We postulate that if the nutrient content is insufficient to fully characterize the diet-global health relationship, one other dimensions is necessary, i.e., the food matrix through the degree of processing. Both matrix and nutrient composition dimensions have been included under the new concept of the 3V index for Real (Vrai), Vegetal (Végétal), and Varied (Varié) foods. The Real metric, reflecting the integrity of the initial food matrix, is the most important, followed by the Vegetal (nutrient origin) and the Varied ("composition" effect) metrics. Conclusion: Concerning their effects on health, food matrix comes first, and then nutrient composition, and calorie quality matters more than calorie quantity. [ABSTRACT FROM AUTHOR]

Long-term care (LTC) represents a significant and substantial proportion of healthcare spends across the globe. Its main aim is to assist individuals suffering with more or more chronic illnesses, disabilities or cognitive impairments, to carry out activities associated with daily living. Shifts in several economic, demographic and social factors have raised concerns surrounding the sustainability of current systems of LTC. Substantial effort has been put into modelling the LTC demand process itself so as to increase understanding of the factors driving demand for LTC and its related services. Furthermore, such modeling efforts have also been used to plan the operation and future composition of the LTC system itself. The main aim of this paper is to provide a structured review of the literature surrounding LTC demand modeling and any such industrial application, whilst highlighting any potential direction for future researchers. [ABSTRACT FROM AUTHOR]

This paper examines the development of and some logistical and methodological issues surrounding the use of animal models of chronic pain. The first section addresses the emergent move towards mechanism-based and disease-related animal models of chronic pain that has accelerated since the late 1980s following publication of Bennett and Xie's (Pain 33:87–107, 1998) paper on chronic constriction injury of the sciatic nerve and Stein et al.'s (Pharmacol Biochem Behav 31:445–451, 1988) paper on unilateral hind paw inflammation with complete Freund's adjuvant. The discussion covers vast areas of chronic pain models developed over the past 50 years, starting with the numerous neuropathic, inflammatory and central pain models, as well as the growing number of models developed to study various forms of chronic pain from chronic back pain to visceral pain. It also examines the advantages and disadvantages of tonic pain models, mechanism-based and disease-related models of chronic pain, including issues related to the novel discovery of injury- or disease-related pathophysiological processes, the expansion of testing repertoires, and the successes and failures in the translation of analgesic development from animal preclinical models to human chronic pain conditions. The second section addresses experimental design considerations in the implementation of one of the 3Rs for the use of animal models of chronic pain; that is methods employed to reduce the number of animals used. The discussion covers various issues including the advantages and disadvantages of repeated dose designs and within-group drug testing, including incremental dosing schedules, and crossover designs. It also examines concerns surrounding the stability of symptoms and measures, including varying durations of multiple symptoms and the potential development of nociceptive sensitization, as well as possible use-dependent alterations in drug sensitivity and time-dependent changes in pain processes in specific animal models. [ABSTRACT FROM AUTHOR]

In this paper we present MANTRA (Mobile ANticoagulant TheRApy), a project aimed at studying feasibility and acceptability of the introduction of mobile technology in the management of anticoagulant therapy involving both patients and health practitioners in their design. By the evaluation of the MANTRA Project, we developed a general approach to mHealth in the remote management of chronic diseases by supporting the communication among patients and healthcare practitioners. Patients usually have to make frequent visits to surgeries to meet nurses for the tests, and General Practitioners (GPs) for receiving drug prescriptions. We report on the implementation of the project as a proof of concept in London. A group of patients, General Practitioners, nurses, and healthcare assistants from the National Health Service (NHS) participated in design and evaluation phases. The distinct characteristics of the NHS as one of the world's largest publicly funded health services posed a number of sociotechnical challenges to the design team. We present how we approached and addressed these challenges through MANTRA. Patients and Healthcare practitioners recognized the validity of our proposed design approach not only for supporting the remote therapy practice preserving an efficient and effective communication with the patients, but also as a way for better managing resources in anticoagulant clinics in the context of the NHS. With our research we explored the process that needs to be followed to develop a mobile system that would fit the sociotechnical ecosystem of anticoagulant therapy. Furthermore, we are now able to identify the changes that will be necessary in the ecosystem itself to make an effective use of the mobile system. [ABSTRACT FROM AUTHOR]

The author reflects on the integration of state-of-the-art (SOTA) conference titled "Managing Complexity in Chronic Care" regarding the growth of chronic diseases. He points out that such conference aims to provide participants with common knowledge for the cited remediation of such disease through stimulated discussion. Further, he stresses his appreciation for Dr. Kevin Weiss members of the SOTA planning committee, and the participants for the realization of the program.

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This paper exposes the New Zealand (NZ) government's longstanding campaign to silence evidence of health impacts from dioxin-containing emissions during the production of the herbicide 2,4,5-trichlorophenoxyacetic acid (2,4,5-T) in New Plymouth in the 1960s. Our analysis of official documentation and related literature between 1960–2005 reveals a series of investigations engaging various silencing mechanisms that have culminated in a case of historical pollution. By doing so, they have intensified the acute injuries, chronic disease and multigenerational impacts stemming from the emissions, while discounting the lived experiences of suffering. We argue that silencing be seen as an epistemic violence that is intertwined with, but stands in evidence of, actions to ignore and deny harms that could be utilized in securing the long overdue acknowledgement and appropriate assistance for the Paritutu community. [ABSTRACT FROM AUTHOR]

Chronic diseases are one of the most severe health issues in the world, due to their terrible clinical presentations such as long onset cycle, insidious symptoms, and various complications. Recently, machine learning has become a promising technique to assist the early diagnosis of chronic diseases. However, existing works ignore the problems of feature hiding and imbalanced class distribution in chronic disease datasets. In this paper, we present a universal and efficient diagnostic framework to alleviate the above two problems for diagnosing chronic diseases timely and accurately. Specifically, we first propose a network-limited polynomial neural network (NLPNN) algorithm to efficiently capture high-level features hidden in chronic disease datasets, which is data augmentation in terms of its feature space and can also avoid over-fitting. Then, to alleviate the class imbalance problem, we further propose an attention-empowered NLPNN algorithm to improve the diagnostic accuracy for sick cases, which is also data augmentation in terms of its sample space. We evaluate the proposed framework on nine public and two real chronic disease datasets (partly with class imbalance). Extensive experiment results demonstrate that the proposed diagnostic algorithms outperform state-of-the-art machine learning algorithms, and can achieve superior performances in terms of accuracy, recall, F1, and G_mean. The proposed framework can help to diagnose chronic diseases timely and accurately at an early stage. [ABSTRACT FROM AUTHOR]