Search Results (102)

Background/Objectives: Unmet healthcare needs, driven by structural and patient-level barriers, are particularly critical in chronic obstructive pulmonary disease (COPD). However, limited research has examined how academic themes on this topic connect and evolve over time. This study analyzed the structure and temporal shifts in research trends on unmet healthcare needs in COPD to identify key concepts and topics and policy implications. Methods: We systematically searched PubMed, Embase, and CINAHL (12–15 March 2025) to identify English-language abstracts on unmet healthcare needs in COPD. Eligible studies were peer-reviewed articles with an English-language abstract that examined unmet healthcare needs from the patient perspective. In total, 451 abstracts were analyzed using text network analysis and Latent Dirichlet Allocation. Topic distributions before and after the coronavirus disease pandemic were assessed using chi-square tests, and findings were interpreted within Penchansky and Thomas’s 5A healthcare access framework. Results: Six topics emerged: socioeconomic disparities, early diagnosis and symptom management, guideline-based information and technology use, integrated care for advanced COPD, access to pulmonary rehabilitation, and equitable medication availability. These topics mapped onto all five access dimensions, underscoring the multidimensional nature of unmet healthcare needs. Network analysis identified management, diagnosis, symptoms, exacerbation, and other related terms as central hubs in the discourse. Post-pandemic, research shifted toward digital information delivery, technology adoption, and equitable pharmacotherapy. Conclusions: Findings suggest that reducing unmet healthcare needs in COPD requires integrated systems that address both disease complexity and access barriers. Targeted, multidisciplinary, and policy-driven interventions in highly central domains are needed to reduce disparities and improve outcomes. This study also confirmed a post-pandemic shift in research priorities, emphasizing the need for equitable and adaptive healthcare policies. Full article

This review aims to discuss the apparent reduction in pulmonary cancer incidence in the general population during and shortly after the COVID-19 pandemic from a biological and pathophysiological mechanistic point of view. While the epidemiological evidence points to a disruption in the early- and mid-stage diagnostic process, which causes a shift to late-stage lung cancer discovery with no impact on its actual prevalence, an alternative hypothesis based on the intersection of viral and cancer biology could have a real effect on lung carcinogenesis as an independent phenomenon. By weaving together population-level trends, mechanistic insights, and translational oncology, we discuss whether the pandemic-associated decline in lung cancer diagnoses reflects primarily a temporary diagnostic artifact or whether it also reveals biologically relevant intersections between SARS-CoV-2 and pulmonary oncogenesis. The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has exerted profound and multifaceted effects on global healthcare systems, altering patterns of disease detection, management, and outcomes across nearly all medical disciplines. These disruptions generated what has been termed a “diagnostic deficit”, producing a backlog of undetected cancers that have only partially been recovered in subsequent years. This phenomenon, sometimes described as a “COVID-19 debt” in oncology, is thought to contribute to excess late-stage diagnoses and potentially worse medium-term survival outcomes. Beyond the disruption of medical systems, the pandemic also raised a more speculative but biologically intriguing question: could SARS-CoV-2 infection itself, through direct or indirect mechanisms, influence lung cancer biology? Our review aims to critically synthesize the evidence across seven domains to address this dual hypothesis. (1) We examine the observed effects of the pandemic on cancer incidence, highlighting global registry and health-system data; (2) we review SARS-CoV-2 infection biology, including viral entry, replication, protein functions, and treatment implications; (3) we summarize the pathogenesis of lung cancer; (4) we explore the role of immune checkpoints in tumor immune evasion, followed by (5) analyses of immune dysregulation in acute infection and (6) in long COVID; and (7) finally, we evaluate proposed oncogenic mechanisms of SARS-CoV-2, integrating molecular virology with cancer immunology. We conclude that the “diagnostic deficit” phenomenon was a reality during and immediately post-pandemic. However, a definitive answer to the questions related to the impact of the infection as an independent phenomenon would require advanced research information covering the biology of the viral infection and lung cancer oncogenesis: processes that are not currently implemented in routine clinical laboratory investigations. Full article

Mental health disorders, particularly depression and anxiety, have become increasingly prevalent among elite athletes, exacerbated by factors such as competitive pressure and the Coronavirus Disease 19 (COVID-19) pandemic. This study analyzes trends in the use of antidepressants, anxiolytics, and cannabinoids (delta-9-tetrahydrocannabinol (THC)/cannabidiol (CBD)) among Italian athletes from 2011 to the first half of 2023 (FH2023), referring to anti-doping reports published by the Italian Ministry of Health. Data from 13,079 athletes were examined, with a focus on non-prohibited medications, banned substances, and regulatory impacts, including threshold adjustments for THC since 2013 and the legalization of CBD. The results show fluctuating use of antidepressants/anxiolytics, with peaks in 2021 and the FH2023, coinciding with post-pandemic awareness. Positive THC cases rose following regulatory changes, reflecting socio-cultural trends. Gender disparities emerged, with THC use predominantly among males (e.g., nine males vs. one female in 2013), though female athletes were underrepresented in testing. This study highlights the need for personalized, evidence-based strategies that balance therapeutic efficacy and anti-doping compliance. Clinicians should carefully consider prescribing selective serotonin reuptake inhibitors (SSRIs) and benzodiazepines to address depression and anxiety and should monitor the risks of CBD contamination. Future research should adopt longitudinal, gender-sensitive approaches to refining guidelines and combating stigma in professional sports. Full article

Background/Objectives: The coronavirus disease 2019 (COVID-19) pandemic has significantly affected global health, economies, and societies, necessitating a deeper understanding of the factors influencing its spread and severity. Methods: This study employed text network analysis to examine relationships among various risk factors associated with severe COVID-19. Analyzing a dataset of published studies from January 2020 to December 2021, this study identifies key determinants, including age, hypertension, and pre-existing health conditions, while uncovering their interconnections. Results: The analysis reveals five thematic clusters: biomedical, occupational, demographic, behavioral, and complication-related factors. Temporal trend analysis reveals distinct shifts in research focus over time. In early 2020, studies primarily addressed immediate clinical characteristics and acute complications of COVID-19. By mid-2021, research increasingly emphasized long COVID, highlighting its prolonged symptoms and impact on quality of life. Concurrently, vaccine efficacy became a dominant topic, with studies assessing protection rates against emerging viral variants, such as Alpha, Delta, and Omicron. This evolving landscape underscores the dynamic nature of COVID-19 research and the adaptation of public health strategies accordingly. Conclusions: These findings offer valuable insights for targeted public health interventions, emphasizing the need for tailored strategies to mitigate severe outcomes in high-risk groups. This study demonstrates the potential of text network analysis as a robust tool for synthesizing complex datasets and informing evidence-based decision-making in pandemic preparedness and response. Full article

The novel coronavirus (COVID-19) pandemic has become one of the most devastating epidemics recorded in world history. The adverse impact of the pandemic is significant within the architecture, engineering, and construction (AEC) industry and other sectors of the economy. A considerable number of COVID-19 research studies have been undertaken in response to this global challenge across disciplines, with minimal output in the built environment. Thus, this study aims to identify, analyse, and visualise COVID-19 research trends in the AEC industry to unfold the sector’s response and readiness for possible future global pandemics. The study employed the scientometric approach to explore COVID-19 research outputs in the AEC industry, an aspect of health and safety in construction that has not been considered in past studies owing to the novel nature of the coronavirus pandemic. The findings revealed that the USA, China, and the United Kingdom were the top published countries and most affected as well. Co-occurring keywords analysis further showed that the predominant focus of scholarly outputs on the subject is around four clusters focusing on sustainable resilience, pandemic pathways and insights, land use and energy strategies, and indoor air excellence. Notwithstanding its limitations, the findings establish the need for the AEC industry to adopt innovative and holistically sustainable construction practices in the event of future disasters and pandemics. The findings of the study provide a robust theoretical foundation for researchers and stakeholders in the built environment, improving the sector’s mitigative and adaptive capacity in the potential occurrence of future pandemics. Full article

Introduction: COVID-19 is a respiratory disease caused by the SARS-CoV-2 virus, which belongs to the coronavirus family. SARS-CoV-2 is related to other viruses that cause severe acute respiratory syndrome. The emergence of cases of pneumonia of unknown origin triggered the largest viral pandemic in modern times, presenting major challenges to global public health. Objective: To analyze the evolution of the COVID-19 pandemic in the state of São Paulo from 2020 to 2023, focusing on trends in incidence, mortality, and lethality. Methods: Ecological study of time series of incidence, mortality and lethality by COVID-19 in the state of São Paulo using Prais-Winsten regression considering the Weekly Percentage Change (WPC) and probability values (p), considering a significance level of 95% (95% CI). To ensure the reliability of the entered data, double-blind typing was performed by different researchers in the same database extracted from the 2024 Ministry of Health Coronavirus dashboard. Results: From February 2020 and the end of December 2023, 6,763,310 accumulated cases and 182,254 deaths were recorded. Stationary trends were observed for the year 2022, with a reduction in incidence and mortality in the year 2023. However, the epidemiological variable lethality showed a stationary trend. Conclusion: The analysis of the trends in incidence, mortality, and lethality revealed variable dynamics over time, with emphasis on the significant reduction of these indicators in 2023. Full article

The COVID-19 pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)virus, resulted in significant global health consequences. The interventions introduced to limit the spread of the virus had a significant impact on the course of the pandemic, but they might also involve other pathogens besides SARS-CoV-2. This study investigates the epidemiological variations for major bacterial and common fungal pathogens represented by Candida species infection in Qatar through retrospective hospital records. Retrospective data were collected on all bacterial and Candida infections from Hamad General Hospital between January 2019 and December 2021. Statistical analyses were performed using R (Version 4.1.0). Infection count comparisons were performed using chi-square goodness of fit tests. Differences in patient numbers were tested with one-way ANOVA followed by post hoc Tukey HSD. The number of infections and measures were correlated using Spearman rank correlation. The significance level was set at 0.05, and where applicable, the Holm–Bonferroni method was used to correct for multiple testing. The general trend for bacterial and Candida infections showed a significant decrease (p < 0.05) following the imposed restrictions and increases during restriction lifting periods. The number of bacterial infections correlated with the number of international visitors (ρ = 0.61, p < 0.01), while the number of Candida infections correlated with hospital admissions of COVID-19 patients (ρ = 0.59, p = 0.013). The results provide a general overview of the infection trends in Qatar during the COVID-19 pandemic and illustrate some of the pandemic interventions’ effects on bacterial and Candida infections. However, further research is needed to better understand the underlying trend dynamics. Full article

Background and Objective: Obtaining reliable and up-to-date information on mortality causes is essential for the planning and implementation of effective preventive interventions. We present here an analysis of the leading causes of death in the US in 2022. Material and Methods: We conducted an electronic search of the US Centers for Control and Prevention (CDC) Web-based Injury Statistics Query and Reporting System (WISQARS) and Wide-Ranging, Online Data for Epidemiologic Research (WONDER) to obtain information on the leading causes of death in the US for the most recent searchable year with definitive data (i.e., 2022), stratified by age and sex. Results: Overall, heart disease was the leading cause of death (26.2% of all deaths), followed by malignant neoplasms (22.7%), unintentional injuries (8.5%) and coronavirus disease 2019 (COVID-19; 6.9%). Although heart disease and malignant neoplasms remained the leading causes of death in both sexes, unintentional injuries were the third cause for men (10.5%), while strokes were the third cause in women (7.5%). COVID-19 remained the fourth most common cause of death in both sexes (7.1% in men and 6.8% in women). The ten most common causes of death showed an increasing mortality tendency in parallel with the aging of population, with similar trends for both sexes. The only exception was unintentional injury, which was the most common cause of death in both sexes between the ages of 15-44 years, then reached a plateau, before increasing again in people aged 65 years or older. Conclusions: Greater efforts should be put into prevention and education, as heart disease, cancer, and even unintentional injuries are preventable diseases. Full article

Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This research analyzes the mutation trend in various RBD samples from Indonesia published in the Global Initiative on Sharing All Influenza Data (GISAID) database using genomic profiling. Method: Patients in Indonesia infected with SARS-CoV-2, whose samples have been published in genomic databases, were selected for this research. The collected data were processed for analysis following several bioinformatics protocols: visualization into phylogenetic trees, 3D rendering, and the assessment of mutational impact. Results: In Indonesia, there are 25 unique SARS-CoV-2 clades and 318 unique SARS-CoV-2 RBD mutations from the earliest COVID-19 sample to samples collected in 2022, with T478K being the most prevalent RBD mutation and 22B being the most abundant clade. The Omicron variant has a lower docking score, higher protein destabilization, and higher K_D than the Delta variant and the original virus. Conclusions: The study findings reveal a decreasing trend in virus pathogenicity as a potential trade-off to increase transmissibility via mutations in RBD over the years. Full article

Background: The number of foreign-born patients with tuberculosis (TB) has been increasing in Japan, and the number of Vietnamese patients was the highest in 2019. Tuberculosis (TB) is the second leading cause of death from infectious diseases after coronavirus disease-2019 (COVID-19). As the prevalence of TB varies widely globally, measures must be tailored to local characteristics. The Directly Observed Treatment (DOTS) short-course was introduced by the World Health Organization as a global strategy to overcome these challenges. The purpose of this study is to develop an original risk assessment for treatment interruption for Vietnamese patients with TB to be used in Directly Observed Treatment (DOTS), a tuberculosis control measure. Methods: The researchers adopted the Delphi method. Public health nurses of mid-career or above (n = 15) who had conducted DOTS for several Vietnamese patients with TB were selected and surveyed about the content and surface validities of the draft risk assessment items for treatment interruption. The survey was conducted three times. The quantification of content validity and the review and modification of responses regarding each item were analyzed by the researchers. Results: The results identified the following risk categories: “physical characteristics”, “background of life during residence”, “treatment environment”, “understanding tuberculosis and disease acceptance”, and “cultural and value trends”. Conclusions: The results suggest the need to provide support for tuberculosis recovery from various perspectives, including the living environment of Vietnamese patients with TB, their social environment in Japan, and the culture and values of their country of birth and upbringing. Full article

The emergence of COVID-19 has evolved into a global pandemic, causing an unprecedented public health crisis marked by unprecedented levels of morbidity never seen in the recent past. Considerable research efforts have been made in the scientific community to establish an optimal method to identify severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections and to understand the induced immune response. This review examined the development of serological tests during the COVID-19 pandemic, considering the factors affecting sensitivity and specificity, which are key to promote an efficient vaccination strategy for public health. The market has witnessed the introduction of various serological tests for the detection of SARS-CoV-2, such as the chemiluminescence immunoassay (CLIA), which emerged as a powerful and rapid tool to monitor the antibody response before and after vaccination or infection. Therefore, developing serological tests by studying antibody trends and persistence is essential for creating long-term strategies. Our analysis underscores the multifaceted applications of serological tests in pandemic management with a focus on the critical insights they provide into antibody dynamics that help in managing the ongoing pandemic and shaping future public health initiatives, providing a basis for optimizing the future response to viral threats. Full article

Artificial Intelligence (AI) technologies have been widely applied to tackle Coronavirus Disease 2019 (COVID-19) challenges, from diagnosis to prevention. Patents are a valuable source for understanding the AI technologies used in the COVID-19 context, allowing the identification of the current technological scenario, fields of application, and research, development, and innovation trends. This study aimed to analyze the global patent landscape of AI applications related to COVID-19. To do so, we analyzed AI-related COVID-19 patent metadata collected in the Derwent Innovations Index using systematic review, bibliometrics, and network analysis., Our results show diagnosis as the most frequent application field, followed by prevention. Deep Learning algorithms, such as Convolutional Neural Network (CNN), were predominantly used for diagnosis, while Machine Learning algorithms, such as Support Vector Machine (SVM), were mainly used for prevention. The most frequent International Patent Classification Codes were related to computing arrangements based on specific computational models, information, and communication technology for detecting, monitoring, or modeling epidemics or pandemics, and methods or arrangements for pattern recognition using electronic means. The most central algorithms of the two-mode network were CNN, SVM, and Random Forest (RF), while the most central application fields were diagnosis, prevention, and forecast. The most significant connection between algorithms and application fields occurred between CNN and diagnosis. Our findings contribute to a better understanding of the technological landscape involving AI and COVID-19, and we hope they can inform future research and development’s decision making and planning. Full article

Background: In the wake of the coronavirus disease 19 (COVID-19) pandemic, affecting healthcare systems globally, urgent research is needed to understand its potential repercussions on the diagnosis and management of cardiovascular disorders. This emphasises the importance of detecting coronary artery anomalies (CAAs), rare conditions that can range from benign to potentially life-threatening manifestations. We aimed to retrospectively assess the impact of the COVID-19 pandemic on the detection of various coronary anomalies using Coronary Computed Tomography Angiography (CCTA) within a regional tertiary cardiology unit in north-eastern Romania, focusing on perceived occurrence in the population under study, types, and related demographic and clinical factors. Methods: We analysed CCTA scans and investigated the trends in CAA detection among cardiology patients over a decade. We compared pre-COVID-19 and pandemic-era data to assess the impact of healthcare utilisation, patient behaviour, and diagnostic approaches on anomaly detection. Results: Our analysis revealed a higher detection rate of CAAs during the pandemic (3.9% versus 2.2%), possibly highlighting differences in patient clinical profile and addressability changes presentation compared to the previous period. Origination and course anomalies, often linked to severe symptoms, were significantly higher pre-COVID-19 (64.1% versus 51.3%). Conversely, intrinsic CAAs, typically asymptomatic or manifesting later in life, notably increased during the pandemic (49.0% versus 61.4%; p = 0.020). Conclusions: Our study underscores a significant rise in CAA detection during the COVID-19 era, potentially linked to changes in cardiovascular and respiratory clinical patterns, with advanced imaging modalities like CCTA offering accuracy in identification. Full article

Research into digital interventions for mental well-being promotion has grown in recent years, fuelled by the need to improve mental health prevention strategies and respond to challenges arising from the coronavirus (COVID-19) pandemic. This bibliometric analysis provides a structured overview of publication trends and themes in primary research studies reporting an array of digital interventions indexed at WoS from 2004 to 2023. Bibliometric data were collected on a sample of 1117 documents and analysed using the Biblioshiny package. Supplemental network visualisation analysis was conducted using VosViewer. The study, based on Web of Science and Scopus databases, indicates a marked increase in publications post-2020. There were seven groups of research themes clustered around “Mindfulness”, “Anxiety”, “COVID-19”, “Acceptance and Commitment Therapy”, “Depression”, “Web-based”, and “Positive Psychology”. Further, results demonstrated the growth of specific themes (e.g., mindfulness, mhealth), the defining impact of COVID-19 studies, and the importance of both randomised controlled trials and formative research. Overall, research in the field is still early in its development and is expected to continue to grow. Findings highlight the field’s dynamic response to societal and technological changes, suggesting a future trajectory that leans increasingly on digital platforms for mental health promotion and intervention. Finally, study limitations and implications for future studies are discussed. Full article

Background: The COVID-19 pandemic not only adversely impacted physical health but also affected older adults’ mental health. The first news on COVID-19 vaccination made a major breakthrough to the effect of improving older adults’ mood, notwithstanding the fact that vaccinated individuals in this age group accounted only for 40.6% of the overall vaccination rollout in Poland. This study was aimed at assessing the level of anxiety regarding COVID-19 amongst older adults in Poland and assessing the attitude of older adults toward COVID-19 vaccination. Methods: The study sample encompassed a population of 800 individuals aged 60 years and older randomly picked up from a representative sample of all the residents in 16 voivodeship cities (50 individuals from each of the cities). The research method used in this study was a diagnostic survey, and its technique was based on an author-designed questionnaire and four standardised psychometric scales: the Fear of COVID-19 Scale (FCV-19S), Coronavirus Anxiety Scale (CAS), the Drivers of COVID-19 Vaccination Acceptance Scale (DrVac-COVID-19S), and the Scale to Measure the Perception of SARS-CoV-2 Vaccines Acceptance (the VAC-COVID-19 Scale). Results: The degree of fear of SARS-CoV-2 among seniors equalled 1.03 ± 1.95 in terms of the CAS and 15.61 ± 5.75 in terms of the FCV-19S. Attitudes towards COVID-19 vaccination have proven positive (DrVac-COVID-19S—61.23 ± 12.35; VAC-COVID-19—44.31 ± 7.20). Females scored higher than males to the extent of the scales under consideration. The older the respondents were, the higher the scale score. A group of individuals with higher educational status was characterized by substantially higher scores covering the Knowledge subscale (p < 0.001) and the Autonomy subscale (p = 0.038), as well as a higher total score in terms of the DrVac-COVID-19S (p < 0.001). A group of positive factors including the reasons for COVID-19 vaccination in terms of the VAC-COVID-19 Scale was the only case to prove statistically insignificant relationships between the population size of the city the respondents came from and the scale values under consideration (p = 0.790). Statistically significant relationships were proven between SARS-CoV-2 contraction and fear of COVID-19 as measured by means of the CAS (p < 0.001) as well as between SARS-CoV-2 contraction and the Values subscale (p = 0.017) and the Knowledge subscale (p < 0.001) within the framework of the DrVac-COVID-19S scale and the total score in terms of the DrVac-COVID-19S scale (p = 0.023). No relationship was detected between the Autonomy subscale scores in terms of the DrVac-COVID-19S and the Knowledge subscale scores in terms of the DrVac-COVID-19S. The remaining scales were correlated to the extent of statistical significance. Conclusions: A subjective fear of COVID-19 was measured to be low or moderate within the group under study depending on the scale under consideration, proving declining trends as compared to the results arising from previously conducted studies. Seniors have more often had positive attitudes toward COVID-19 vaccination. The relationship between all of the sociodemographic features under consideration and the feeling of COVID-19 anxiety and between educational status, place of residence, SARS-CoV-2 contraction, COVID-19 vaccination, and the overall attitude toward COVID-19 vaccination indicator was proven to be statistically significant (depending on the scale under consideration). Furthermore, the correlation between the overall results arising from the standardised psychometric scales applied to this study was indicated to be statistically significant. Full article