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In the last decade, artificial intelligence (AI) has been increasingly applied in health technology assessment (HTA) to accelerate evidence synthesis, optimize resources allocation, and guarantee timely delivery of trustworthy technologies in health. The aim of the present scoping review is to map AI models applied in HTA, and technical characteristics of AI-based automation and semi-automation applied in HTA.
Methods
A search strategy containing core expressions “AI” and “HTA” and correlated terms was conducted in nine specialized databases (health and informatics) in February 2022. Inclusion criteria were publications testing AI models applied in HTA. Study selection was performed by independent pairs, with consensus meetings. No filters were applied. Data on year and country of publication, HTA phase, subsets of AI (e.g., machine learning [ML], neural networks), type of algorithm (e.g., support vector machine [SVM], K-nearest neighbors), and performance scale were extracted. Data were analyzed as descriptive frequency statistics. Used metrics will be presented narratively.
Results
Sixty-one publications were included. The first study identified was published in 2006, and since then the number of publications has been consistently growing, with 11 publications in the year 2021. Canada, USA, and the UK concentrate 72 percent of publications (44 in 61) equally distributed. The most common HTA phase was the evidence synthesis, with 59 studies (96%). The main task performed was study screening/selection (66.6%). The majority of ML models (80.9%) contained two learning nodes or fewer, and applied SVM and decision-tree-based algorithms. Inter-rater agreement, accuracy, and 95 percent recall were the most common scales observed.
Conclusions
Although recent developments in AI applied to HTA show increasing potentiality, studies are concentrated in the study selection phase of evidence synthesis. Many areas need further development, such as horizon scanning and policymaking processes. Additionally, studies reporting time gain and economic gain outcomes are scarce and should be considered for the development of future studies in the field.
One of the pillars of health technology assessment (HTA) is transparency, which guarantees reproducibility and accountability. Due to the “black-boxness” of artificial intelligence (AI) models, the use of AI-based tools adds new layers of complexity for transparency issues. The aim of this scoping review is to map AI-based tools applied in HTA processes, regarding human supervision and “open-sourceness” aspects.
Methods
A search strategy using the terms “AI,” “HTA,” and correlated terms was performed in nine specialized databases (health and informatics) in February 2022. Inclusion criteria were publications testing AI models applied in HTA. Selection of studies was performed by two independent researchers. No filter was applied. Variables of interest included a subset of AI models (e.g., machine learning [ML], neural network), learning methods (e.g., supervised, unsupervised, or semi-supervised learning), and code availability (e.g., open source, closed source). Data were analyzed exploratorily as frequency statistics.
Results
ML with one layer of hidden nodes was applied in 48 (78.6 %) studies, while deep learning (DL) (two-plus layers) were applied in eight (13.1 %). ML models that used supervised learning accounted only for half of the reported models, while half used unsupervised learning. Considering supervision methods in DL models, seven used unsupervised learning, and one used supervision. Four studies did not report the AI model, and 14 studies did not report the supervision paradigm. It was not possible to assess “open-sourceness” in 31 studies. Among the identified software, seven models were not open source, and 13 were open source.
Conclusions
Transparency and accountability are of utmost importance to HTA. Complexity of AI models may introduce trustworthiness issues in HTA. Transparency provided by open-source code becomes essential in building trust in the automation of HTA processes, as does quality of report. Although progress has been observed in transparency and quality, the lack of a methodological framework still poses challenges in the field.
The decision-making process for health technology assessment (HTA) in ultra-rare diseases faces a significant challenge for agencies worldwide. This study sought to offer an analytical overview of the clinical evidence outlined in the recommendations of the Brazilian National Committee for Health Technology Incorporation (Conitec) in ultra-rare diseases.
Methods
Data were extracted from recommendation reports for the ultra-rare diseases evaluated between 2012 and 2022. To classify a disease as ultra-rare, the epidemiological criterion or a consultation with the Orphanet platform was used (prevalence of ≤1/50,000 inhabitants). The extracted variables included the type of evidence synthesis, type of studies, instrument, the result of the assessment of the methodological quality of the studies, the format of evidence synthesis presentation, whether the evidence was graded, and the result.
Results
Among 53 analyzed reports, 70 percent relied on randomized controlled trials, followed by systematic reviews (SR), and observational studies. Reports with positive recommendations based on SR comprised 63 percent. GRADE applied to 27 reports and indicated low or very low results for the first two outcomes (62% and 65%). No clear link between evidence quality and final recommendations was observed. Meta-analysis-based reports had 83 percent positive recommendation rate, compared to 55 percent without meta-analysis. Surrogate outcomes were predominant. Clinical characteristics significantly influenced final decisions, especially when new data emerged in public consultation or had the potential to alter disease progression, reduce severe events, or enhance survival.
Conclusions
Ultra-rare diseases pose challenges in evidence quantity and quality. Traditional HTA frameworks seem inadequate, lacking robust evidence for these conditions. The difficulties in ultra-rare disease HTA underscore the need for specialized frameworks. This analysis acknowledges limitations, notably the heterogeneity in older report structures compared to recent ones, reflecting evolving HTA methodologies in Brazil.
The decision-making process for incorporating technologies for ultrarare diseases (URD) has been a challenge for health technology assessment agencies worldwide. These challenges have been presented in debates about the budget impact of incorporating technologies for URD. This is an important issue because there are other dimensions of the economic and social impact of URD that require consideration.
Methods
Data were extracted from National Committee for Health Technology Incorporation (CONITEC) reports (2012 to 2022) on technologies for the treatment of URD in Brazil. Diseases were classified using an epidemiological criterion or Orphanet consultation (prevalence ≤1 per 50,000 inhabitants). Variables included eligible patient count, population estimation method, incremental impact values for one and five years, and diffusion rate in the first and fifth year. Univariate logistic regression was used to adjust the relationship between the budget impact analysis and the final recommendation, considering factors associated with incorporation in univariate regression and p-values less than 0.10 in a multivariate regression.
Results
Among 53 reports, 48 percent exclusively employed the epidemiological approach for incremental impact assessment population estimation, rising to 69.5 percent when combined with measured demand. Population data were nearly evenly sourced from national and international platforms, with the UK, the USA, and multicenter studies being the most cited internationally. Notable differences were found between favorable and unfavorable CONITEC recommendations, with lower values being associated with incorporation. Market share diffusion rates favored the option of 100 percent diffusion in both the first year and the cumulative five years. The analysis highlighted the influence of demand characteristics and technology type on the budget impact value over one and five years.
Conclusions
The study found that budget impact data significantly influenced the final recommendation for technology incorporation, indicating a criterion favoring technologies with a lower budget impact. However, requester characteristics and technology type also played a role in the decision-making process, suggesting that additional factors influence recommendations.
Hospital-based health technology assessment (HB-HTA) is evolving constantly. In 2023, a survey was conducted by the HB-HTA Interest Group of Health Technology Assessment International with the aim of collecting data on HB-HTA activities, including perceptions of the role of, potential for, and barriers to HB-HTA. Overall, 87 responses were collected: 41 from hospitals performing health technology assessment (HTA), 18 from hospitals not conducting HTA, and 28 from policymakers.
Methods
The survey collected data from 28 countries. Italy, Poland, Brazil provided the highest number of responses. We conducted a descriptive comparative analysis focusing on these three countries to investigate whether and how the policies for HB-HTA, the activities of HB-HTA, and the perceptions of HB-HTA differed among policymakers and hospitals not performing HTA.
Results
Overall, 19 responses were collected from Italy and 10 each were collected from Brazil and Poland. While Italy (n=10) and Brazil (n=8) had a high number of responses from hospitals performing HB-HTA, most of the responses from Poland (n=9) were from hospitals not performing HTA. There was a lack of policies for HB-HTA in all three countries. HTA was performed in big hospitals (≥500 beds) in Italy and Brazil. HB-HTA covered all kinds of technologies, including digital health. In Poland, hospitals not conducting HTA recognized the ability of HB-HTA to promote cost containment. Policymakers were open to including HB-HTA in their activities.
Conclusions
Interpreting the diffusion of HB-HTA, its integration with other HTA processes, and the perceptions of its pros and cons should be both country specific and be conducted from an international perspective. The analysis demonstrated the need for specific policies and for better dissemination and promotion of HB-HTA activities and collaborations with HTA agencies.
The decision-making process for health technology assessment (HTA) in ultra-rare diseases is a global challenge. Establishing a comprehensive analytical framework for these unique diseases poses difficulties. This study aims to descriptively analyze arguments reported by the Brazilian National Committee for Health Technology Incorporation (Conitec) in deciding whether to include technology for ultra-rare diseases.
Methods
Data from recommendation reports (2012 to 2022) were analyzed. Diseases with a prevalence of fewer than one per 50,000 inhabitants were classified as ultra-rare. Extracted variables included preliminary and final recommendation results and justifications by Conitec. Six argument categories were created (method-related issues; evidence; cost; technology effectiveness or safety; context; innovation). Word clouds were generated based on word frequency in each category to present the data.
Results
In the analysis of 45 reports, the word clouds highlight frequent terms in favorable arguments, emphasizing evidence quality, cost reduction, and applicability in the healthcare system. Conversely, unfavorable arguments also revolve around evidence quality and cost impact. The analysis of the arguments according to categories, 16 arguments were identified: seven concern evidence issues, five cite methodological problems in presented studies, four relate to costs, and three pertain to technology effectiveness or safety. Unfavorable arguments primarily stem from evidence-related concerns. In favorable arguments, cost (seven) and safety (six) are prominent, with innovation (one) and context (three) being additional categories not found in the unfavorable group.
Conclusions
While technology assessment processes for ultra-rare diseases have evolved, the justifications for recommending or not incorporating new technologies remain unchanged. Over time, reports have become more detailed, focusing on evidence and methodological specifics. This highlights the importance of scrutinizing evidence characteristics and determining relevant criteria and data types for this unique context.
Several countries established health technology assessment (HTA) processes to support decision-making. Considering the high volume of submissions processed by HTA agencies, approaches to determine factors associated with the approval would be beneficial. This study aimed to predict the final recommendation of the National Committee for Health Technology Incorporation (Conitec) using a natural language processing (NLP) algorithm for text extraction.
Methods
Conitec’s 2012 to 2022 reports (n=389) were split into 75 percent training and 25 percent testing data. Tokenization enabled NLP models: Least Absolute Shrinkage and Selection Operator (LASSO), logistic regression, support vector machine (SVM), random forest, neural network, and Extreme Gradient Boosting (XGBOOST). Evaluation criteria included accuracy, area under the receiver operating characteristic curve (ROC AUC) score, precision, and recall. Cluster analysis with k-modes identified two clusters (group 0 = approved, group 1 = rejected).
Results
The neural network model demonstrated the best accuracy metrics with a precision of 0.815, accuracy of 0.769, ROC AUC of 0.871, and a recall of 0.746. Some tokenization identified that linguistic markers could contribute to the prediction of incorporation decision by the Brazilian HTA Committee, such as international HTA agencies’ experience and the government as the main requester. Cluster and XGBOOST analysis identified similar results with approved technologies with a predominance of drugs assessment, mainly requested by the government, and not approved mostly assessing drugs, the industry as the main requester.
Conclusions
The NLP model could identify predictors for the final decision process on the incorporation of health technologies in Brazil’s Unified Health System, opening paths for future work using HTA reports coming from other agencies. This model could potentially improve the throughput of HTA systems by supporting experts with prediction/factors/criteria for approval or nonapproval as an earlier step.
Ultrarare diseases (URD) represent a challenge to health technology assessment (HTA). The traditional framework for assessing efficacy and cost effectiveness may be biased to include clinically relevant outcomes, leaving patient-centered outcomes doomed to neglect. Here we explore patient-centered outcomes in the context of patient and citizen involvement in the assessment of URD by the Brazilian National Committee for Health Technology Incorporation (CONITEC).
Methods
We assessed 53 HTA reports from CONITEC that evaluated URD-related technologies (and included highlights of patients’ and citizens’ perspectives during recommendation meetings) published from 2012 to 2022. Data extraction was performed by two independent researchers. Data on year of report, sex, ethnicity, category (patient or family), and previous experience with the assessed technology were extracted and analyzed using descriptive statistics. Patients’ and citizens’ narratives were collated from the reports. A thematic analysis was conducted according to patient-centered outcomes and technology-related outcomes and was then compared with the evidence synthesis protocol described in the HTA.
Results
Only seven URD-related HTA reports registered patient or citizen participation, all of which were published in 2022. The age of two participants was reported (both 17 years). Six participants were women. Ethnicity was not reported. All participants had previous experience with the technology. Four participants were family or caregivers and three were patients. Considering patient-centered outcomes, physical (muscular strength) and emotional (self-confidence) improvements that positively affected independence in basic daily functions were reported. These functions included activities such as dressing, self-care, cooking, and leisure. Advantages listed for the assessed technologies included the possibility of self-administration of medication (e.g., swallowing a pill, opening a medicine bottle, and using a syringe).
Conclusions
The results show that although, in some cases, primary outcomes reported in evidence synthesis protocols include patient-centered outcomes (e.g., activities of daily living), in other cases the evidence synthesis failed to identify relevant studies. In other cases, the reports failed to differentiate between primary and secondary outcomes or to fully account for patient-centered outcomes.
Incorporating technologies for ultrarare diseases (URD) poses challenges for global health technology assessment (HTA) agencies. Difficulties include defining an analytical framework and establishing differentiated cost-effectiveness thresholds. The rise of technological innovations intensifies demands from healthcare professionals, media, and the general population, placing pressure on healthcare systems in developing countries.
Methods
To analyze ultrarare medicine costs in submissions to the Brazilian National Committee for Health Technology Incorporation (CONITEC), data from HTA reports on URD (from 2012 to 2022) were extracted. Diseases were classified as URD based on an epidemiological criterion or Orphanet consultation (prevalence ≤1 per 50,000 inhabitants). Extracted variables included initial and final prices, annual patient cost, incremental cost-effectiveness ratio (ICER), and initial and final CONITEC recommendations. Price differences were calculated by the Brazilian Medicines Market Regulation Chamber.
Results
Among 53 reports, 30 featured economic evaluations, with only 13.3 percent initially receiving positive recommendations. However, eight gained favor, including post-consultation, price-conditioned, and risk sharing-based approvals. Annual medication costs ranged from USD17,439.20 to USD1,108,237.00 per patient, with discounts of between 25 and 64 percent. Despite some technologies having ICERs that were significantly higher than the national threshold, no statistical relationship was found between ICERs and recommendations. Monthly and annual costs varied, with higher costs for heterogeneous diseases and lower costs for metabolic conditions. Sensitivity analyses, using both deterministic and probabilistic analyses, were conducted in 58 percent of the reports.
Conclusions
Incorporation of technologies for URD does not correlate with lower annual costs or increased discounts because costs are not considered in isolation by CONITEC’s decision-making process. Recognizing URD as a subgroup with distinct criteria may enhance the implementation of HTA processes tailored to the unique challenges of these conditions.
Health technology assessment (HTA) agencies and researchers recognize the necessity of evidence-based methodologies beyond quantitative data to assess feasibility, appropriateness, meaningfulness, patient values, preferences, acceptability, and equity. Despite existing guidelines for synthesizing qualitative data, the HTA framework requires clarification. This review aims to describe the frameworks, tools, and processes used to synthesize qualitative evidence and assess the quality of HTA.
Methods
Using the JBI methodology, the authors accessed databases such as MEDLINE, LILACS, CINAHL, Embase, Web of Science, Scopus, PsycINFO, Cochrane Library, JBI Database, and ScienceDirect. Grey literature searches included ProQuest, OpenGrey, CADTH’s Grey Matters, Google Scholar, and HTA agencies’ websites. Inclusion criteria focused on synthesizing qualitative evidence frameworks, methods for evidence synthesis, and quality rating. The review had a global scope, without specific population and time restrictions. Data, encompassing fundamental concepts, frameworks, methods, subjects, and objectives, were presented in tables and figures.
Results
Out of 2,054 articles, 31 were included, mainly from Europe, with a predominant “guide” authored by an HTA agency and university. The majority of documents did not originate from agencies. Only three agencies developed specific documents. A surge in publications occurred in 2018/2019. Qualitative data in HTA were justified for opinions, acceptability, feasibility, and equity. SPICE was the most cited acronym; RETREAT was the preferred framework. Thematic synthesis was the most cited method, CASP for quality assessment. GRADE-CERQual graded evidence quality, and ENTREQ was cited for reporting qualitative research. The GRADE EtD framework was the sole tool mentioned for recommendations.
Conclusions
This review highlights a growing trend in including qualitative evidence in HTA. While various proposals suggest instruments and methods, few documents cover all necessary steps, resulting in diverse recommendations. Standardizing processes can improve decision-making by guiding the integration of qualitative evidence, potentially enhancing recommendation quality. This ensures evidence on feasibility, appropriateness, significance, patient values, preferences, acceptability, and equity are considered.
Diagnostic test accuracy (DTA) systematic reviews (SR) provide acknowledged challenges for health technology assessment (HTA) due to insufficiency of trials and a paucity of methodological frameworks (compared with interventional SRs). Additionally, research in neglected tropical diseases (NTDs) is scarce. Assessing the methodological compliance of a SR protocol in this context is of utmost importance for developing robust HTA in NTD.
Methods
A search strategy was conducted in PROSPERO in November 2023 to identify protocols of SRs on diagnostic test accuracy using the following terms: “diagnostic accuracy test”, “diagnostic test”, and “diagnostic accuracy”. Deduplication was performed using Excel’s “remove duplicates” functionality. Eligible studies were SRs with predicted meta-analyses on DTA in any NTD (as per the World Health Organization list). in vitro studies, those with non-human populations, and methodological studies were ineligible. The variables of interest included registry characteristics (author, year, country), protocol status, and methodological characteristics (pre-defined statistical analyses, sensitivity analyses, and heterogeneity analyses). The results were presented using descriptive statistics and narrative analysis of methodological issues.
Results
From 7,931 registries, 106 protocols were selected that anticipated conducting a meta-analysis of DTA in the context of NTDs. The number of registry entries has grown steadily from one protocol in 2012 to 17 in 2023. Twenty-three NTDs were identified, the three most common being dengue (n=23; 22%), leishmaniasis (n=18; 17%), and syphilis (n=12; 11%). Only 14 protocols were reported as published. Regarding quality of reporting and methods, half (n=54) of the reports explicitly stated a meta-analytical approach in their title. Only 16 mentioned a sensitivity analysis and 32 did not mention an analysis of heterogeneity.
Conclusions
The meager number of protocols reported as published could mean a lack of updates or publications, or both. The absence of essential methodological descriptions in protocol titles and body text is worrisome and may ultimately be reflected in the number of publications. Further analysis should assess the specifics of methodological quality based on well-established methodological frameworks for quality of reporting and methods.
Visceral leishmaniasis (VL) is a tropical disease that can be fatal if acute and untreated. Diagnosis is difficult, the treatment is toxic and prophylactic vaccines do not exist. Leishmania parasites express hundreds of proteins and several of them are relevant for the host's immune system. In this context, in the present study, 10 specific T-cell epitopes from 5 parasite proteins, which were identified by antibodies in VL patients’ sera, were selected and used to construct a gene codifying the new chimeric protein called rCHI. The rCHI vaccine was developed and thoroughly evaluated for its potential effectiveness against Leishmania infantum infection. We used monophosphoryl lipid A (MPLA) and polymeric micelles (Mic) as adjuvant and/or delivery system. The results demonstrated that both rCHI/MPLA and rCHI/Mic significantly stimulate an antileishmanial Th1-type cellular response, with higher production of IFN-γ, TNF-α, IL-12 and nitrite in vaccinated animals, and this response was sustained after challenge. In addition, these mice significantly reduced the parasitism in internal organs and increased the production of IgG2a isotype antibodies. In vivo and in vitro toxicity showed that rCHI is safe for the mammalians, and the recombinant protein also induced in vitro lymphoproliferative response and production of Th1-type cytokines by human cells, which were collected from healthy subjects and treated VL patients. These data suggest rCHI plus MPLA or micelles could be considered as a vaccine candidate against VL.
This article presents a systematic review on the use of eye-tracking technology to assess the mental workload of unmanned aircraft system (UAS) operators. With the increasing use of unmanned aircraft in military and civilian operations, understanding the mental workload of these operators has become essential for ensuring mission effectiveness and safety. The review covered 26 studies that explored the application of eye-tracking to capture nuances of visual attention and assess cognitive load in real-time. Traditional methods such as self-assessment questionnaires, although useful, showed limitations in terms of accuracy and objectivity, highlighting the need for advanced approaches like eye-tracking. By analysing gaze patterns in simulated environments that reproduce real challenges, it was possible to identify moments of higher mental workload, areas of concentration and sources of distraction. The review also discussed strategies for managing mental workload, including adaptive design of human-machine interfaces. The analysis of the studies revealed a growing relevance and acceptance of eye-tracking as a diagnostic and analytical tool, offering guidelines for the development of interfaces and training that dynamically respond to the cognitive needs of operators. It was concluded that eye-tracking technology can significantly contribute to the optimisation of UAS operations, enhancing both the safety and efficiency of military and civilian missions.
Health Technology Assessment (HTA) practitioners recognize the significance of qualitative methodologies that focus on how a technology is feasible, meaningfulness, acceptable, and equitable. This mapping aimed to delineate the frameworks employed to synthesize qualitative evidence and assess the quality of synthesis in HTA .
Methods
Mapping was conducted using Medline, LILACS, CINAHL, Embase, Web of Science, Scopus, PsycINFO, Cochrane Library, JBI, and ScienceDirect databases. Gray literature searches included PROQUEST, Open Grey, Canadian Agency for Drugs and Technologies in Health’s Grey Matters, Google Scholar, and HTA agency websites. The inclusion criteria were centered on global qualitative evidence synthesis frameworks. The data are presented in the tables.
Results
Of the 2054 articles, 31 were included, mostly from Europe. Guide was the type of document more cited, and most authors are from HTA agencies and universities. Incorporating both patient and family perspectives is the most cited reason for include qualitative evidence. Regardless of the framework or tool, SPICE was the main acronym, and RETREAT was preferred for approach selection. Thematic synthesis dominated analytic methods, and CASP was the primary quality appraisal tool. GRADE-CERQual graded evidence synthesis, with ENTREQ as the top reporting guidance. The GRADE evidence-to-decision framework was mentioned for recommendations.
Conclusion
This mapping highlights the movement incorporate qualitative evidence in HTA employing specific frameworks. Despite the similarities among documents, most of them describe part of the process to synthesize qualitative evidence. Standardizing procedures to incorporate qualitative evidence into HTA can enhance decision-making. These findings offer essential considerations for HTA practice.
Early phases of the design process require designers to select into view elements of the problem that they deem important. This exploration process is commonly referred to as problem framing and is essential to solution generation. There have recently been calls in the literature for more precise representations of framing activity and how individual designers come to negotiate shared frames in team settings. This paper presents a novel research approach to understand design framing activity using a system thinking lens. Systems thinking is the way that we understand a system’s components and the interrelations to create interventions, which can be used to move the system outcomes in a more favorable direction. The proposed approach is based on the observation that systems as mental representations of the problem bear some similarity to frames as collections of concepts implicit in the designer’s cognition. Systems mapping – a common visualization tool used to facilitate systems thinking – could then be used to model external representations of framing, made explicit through speech, and sketches. We thus adapt systems mapping to develop a coding scheme to analyze verbal protocols of design activity to retrospectively represent framing activity. The coding scheme is applied on two distinct datasets. The resulting system maps are analyzed to highlight team problem frames, individual contributions, and how the framing activity evolves over time. This approach is well suited to visualize the framing activity that occurs in open-ended problem contexts, where designers are more focused on problem finding and analysis rather than concept generation and detailed design. Several future research avenues for which this approach could be used or extended, including using new computational methods, are presented.
This study investigated the association between screen time and ultra-processed food (UPF) consumption across the lifespan, using data from the 2019 Brazilian National Health Survey, a cross-sectional and population-based study. A score was used to evaluate UPF consumption, calculated by summing the positive answers to questions about the consumption of ten UPF subgroups on the previous day. Scores ≥5 represented high UPF consumption. Daily time spent engaging with television or other screens was self-reported. Crude and adjusted models were obtained through Poisson regression and results were expressed in prevalence ratios by age group. The sample included 2315 adolescents, 65 803 adults and 22 728 older adults. The prevalence of UPF scores ≥5 was higher according to increased screen time, with dose–response across all age groups and types of screen time. Adolescents, adults and older adults watching television for ≥6 h/d presented prevalence of UPF scores ≥5 1·8 (95 % CI 1·2, 2·9), 1·9 (95 % CI 1·6, 2·3) and 2·2 (95 % CI 1·4, 3·6) times higher, respectively, compared with those who did not watch television. For other screens, the prevalence of UPF scores ≥5 was 2·4 (95 % CI 1·3, 4·1) and 1·6 (95 % CI 1·4, 1·9) times higher for adolescents and adults using screens for ≥ 6 h/d, respectively, while for older adults, only screen times of 2 to < 3 and 3 to < 6 h were significantly associated with UPF scores ≥5. Screen time was associated with high consumption of UPF in all age groups. Considering these associations when planning and implementing interventions would be beneficial for public health across the lifespan.
The Amazon basin has the largest number of fish in the world, and among the most common fishes of the Neotropical region, the threespot (Leporinus friderici) is cited, which in relation to its microparasitic fauna, has described only 1 species of the genus Henneguya, Henneguya friderici. The Myxozoa class is considered an obligate parasite, being morphologically characterized by spores formed by valves connected by a suture line. This study describes a new species of Henneguya sp. in the Amazon region for L. friderici. This parasite was found in the host's pyloric caeca and caudal kidney, with mature spores with a total spore length of 38.4 ± 2.5 (35.9–40.9) μm; the spore body 14.4 ± 1.1 (13.3–15.5) μm and 7.3 ± 0.6 (6.7–7.9) μm wide. Regarding its 2 polar capsules, they had a length of 5.1 ± 0.4 (4.7–5.5) μm and a width of 2.0 ± 0.1 (1.9–2.1) μm in the same pear-shaped, and each polar capsule contained 9–11 turns. Morphological and phylogenetic analyses denote that this is a new species of the genus Henneguya.
Temporal energy intake (EI) and physical activity (PA) patterns may be associated with obesity. We aimed to derive and characterise temporal EI and PA patterns, and assess their cross-sectional association with weight status, in 6-to-14-year-old Portuguese participants of the National Food, Nutrition and Physical Activity Survey 2015–2016. We extracted times and EI of all eating occasions from two 1-d food diaries/24-h recalls, while types and times of PA from 4-d PA diaries. We derived EI patterns (n 714) and PA patterns (n 595), using, respectively, a hierarchical and K-means cluster analysis, considering the average proportion of total daily EI (%TEI) and PA intensity (%TPA), within each 2-h interval across the 24-h day. Patterns were labelled based on the 2-h intervals of %TEI/TPA peaks. We assessed the association between patterns and overweight or obesity (BMI z-score ≥ +1 sd) using adjusted logistic regressions (OR (95 % CI)). Three EI patterns emerged: 1 – ‘Early afternoon and early evening’; 2 – ‘Early afternoon and late evening’; and 3 – ‘Late morning, early and mid-afternoon and late evening’. EI Pattern 3 v. Pattern 1 was negatively associated with overweight or obesity (0·49 (0·26, 0·92)). PA Pattern 1 – ‘Late morning, mid-afternoon and early evening’ v. Pattern 2 – ‘Late afternoon’, was not associated with weight status (0·95 (0·65, 1·38)). A daily EI pattern with more and even %TEI peaks at earlier daytime periods, rather than fewer and higher, may be negatively associated with overweight or obesity amongst this population whereas the identified PA patterns might have no relationship.
Around the world, people living in objectively difficult circumstances who experience symptoms of generalized anxiety disorder (GAD) do not qualify for a diagnosis because their worry is not ‘excessive’ relative to the context. We carried out the first large-scale, cross-national study to explore the implications of removing this excessiveness requirement.
Methods
Data come from the World Health Organization World Mental Health Survey Initiative. A total of 133 614 adults from 12 surveys in Low- or Middle-Income Countries (LMICs) and 16 surveys in High-Income Countries (HICs) were assessed with the Composite International Diagnostic Interview. Non-excessive worriers meeting all other DSM-5 criteria for GAD were compared to respondents meeting all criteria for GAD, and to respondents without GAD, on clinically-relevant correlates.
Results
Removing the excessiveness requirement increases the global lifetime prevalence of GAD from 2.6% to 4.0%, with larger increases in LMICs than HICs. Non-excessive and excessive GAD cases worry about many of the same things, although non-excessive cases worry more about health/welfare of loved ones, and less about personal or non-specific concerns, than excessive cases. Non-excessive cases closely resemble excessive cases in socio-demographic characteristics, family history of GAD, and risk of temporally secondary comorbidity and suicidality. Although non-excessive cases are less severe on average, they report impairment comparable to excessive cases and often seek treatment for GAD symptoms.
Conclusions
Individuals with non-excessive worry who meet all other DSM-5 criteria for GAD are clinically significant cases. Eliminating the excessiveness requirement would lead to a more defensible GAD diagnosis.
Selenium (Se) is a mineral with several biological functions, and studies have shown that its deficiency can be linked to many complications in patients with chronic kidney disease (CKD). This study aims to systematically review the effects of Se supplementation in patients with CKD undergoing haemodialysis (HD). This systematic review was carried out according to the PRISMA statement. Clinical trials were searched in PubMed, Lilacs, Embase, Scopus and Cochrane Library databases from inception to July 2021 and updated in July 2024. The protocol was registered on PROSPERO (CRD42021231444). Two independent reviewers performed the study screening and data extraction, and the risk of bias was evaluated using the Cochrane Collaboration tool. Thirteen studies were included in this review. Only nine studies showed results on Se levels; in all, reduced Se levels were observed before supplementation. A positive effect of supplementation on plasma Se level was demonstrated. Of the ten studies analysed, six demonstrated positive effects on antioxidant and inflammatory markers. Only one study analysed immunological parameters, showing a positive impact. From two studies that analysed thyroid hormones, only one showed positive results. All studies were classified as high risk of bias. The findings suggest that Se supplementation significantly increases plasma Se levels in these patients; however, there are still not enough studies to clarify the effects of Se supplementation on the antioxidant and inflammatory markers, immune system and thyroid hormones. Further studies are needed to elucidate the effects of Se supplementation and to provide a recommendation for patients with CKD undergoing HD.