Search Results (1,836)

This paper aims to leverage artificial intelligence (AI) to assist physicians in utilizing advanced deep learning techniques integrated into developed models within electronic health records (EHRs) in medical information systems (MISes), which have been in use for over 15 years in health centers across the Republic of Serbia. This paper presents a human-centered AI approach that emphasizes physician decision-making supported by AI models. This study presents two developed and implemented deep neural network (DNN) models in the EHR. Both models were based on data that were collected during the COVID-19 outbreak. The models were evaluated using five-fold cross-validation. The convolutional neural network (CNN), based on the pre-trained VGG19 architecture for classifying chest X-ray images, was trained on a publicly available smaller dataset containing 196 entries, and achieved an average classification accuracy of 91.83 ± 2.82%. The DNN model for optimizing patient appointment scheduling was trained on a large dataset (341,569 entries) and a rich feature design extracted from the MIS, which is daily used in Serbia, achieving an average classification accuracy of 77.51 ± 0.70%. Both models have consistent performance and good generalization. The architecture of a realized MIS, incorporating the positioning of developed AI tools that encompass both developed models, is also presented in this study. Full article

The restrictions on business and social activity during the COVID-19 pandemic have led to significant changes in consumption patterns worldwide. Such changes are causing structural shifts in the markets of goods and services, thus affecting regional resilience. In this article, we aim to assess the changing structure of the consumption of goods and services in highly urbanized Russian regions under the impact of the COVID-19 pandemic and to analyze its effects on the lifestyle of the population. According to our results, some Russian regions demonstrate a return to previous consumption levels, while others exhibit the emergence of new dynamics. The conclusion is made that COVID restrictions have invoked a paradigm shift in consumer behavior toward investment in self-development, safety, and comfort. This observation should be taken into account when developing strategies for the recovery growth of regional economies. Full article

Background/Objectives: mRNA vaccines introduced during the COVID-19 pandemic were a significant step forward in the rapid development and deployment of vaccines in a global pandemic context. These vaccines showed good protective efficacy, but—due to limited breadth of the immune response—they required frequent boosters with manufactured spike sequences that often lagged behind the circulating strains. In order to enhance the breadth, durability, and magnitude of immune responses, we studied the effect of combining priming with an RNA vaccine technology with boosting with protein/adjuvant using a TLR4-agonist based adjuvant. Methods: Specifically, four proprietary adjuvants (EmT4^TM, LiT4Q^TM, MiT4^TM, and AlT4^TM) were investigated in combination with multiple modes of SARS-CoV-2 vaccination (protein, peptide, RNA) for their effectiveness in boosting antibody responses to SARS-CoV-2 spike protein in murine models. Results: Results showed significant improvement in immune response strength and breadth—especially against more distant SARS-CoV-2 variants such as Omicron—when adjuvants were used in combination with boosters following an RNA vaccine prime. Conclusions: The use of novel TLR4 adjuvants in combination with protein or RNA vaccinations presents a promising strategy for improving the efficacy of vaccines in the event of future pandemics, by leveraging rapid response using an RNA vaccine prime and following up with protein/adjuvant-based vaccines to enhance the breadth of immunity. Full article

Background: As a disease with a still largely unknown course, post-COVID requires a comprehensive multidimensional perspective and structured monitoring, as offered by the C19-YRSm. There has not yet been a German version of the scale. Methods: After the translation of the COVID-19 Yorkshire Rehabilitation Scale (modified version, C19-YRSm) into German, we conducted an online survey with it between 23 May 2023 and 10 May 2024 for patients with post-COVID condition. Participation took place twice; people received either only the German version or both the German and the original English versions of the scale at one-week intervals. Based on the results, reliability and validity of the German version of the C19-YRSm were extensively tested. Results: Data of 414 participants were analysed, 156 of whom took part twice at least seven days apart. Cronbach’s alpha coefficients of the subscales of the German version ranged from 0.75 to 0.93. In the English version, it ranged from 0.82 to 0.93. All the subscales correlate with each other with p < 0.001. For the overall scale and for three of the four subscales, the intraclass coefficients, as a measure of the agreement between measurement results at two points in time, showed good consistency. Conclusions: This study confirmed the reliability, applicability, and clinical utility of the C19-YRSm, aligning with previous studies. With its multidimensional structure and excellent quality criteria, the C19-YRS is a valuable asset for clinical practice and research. The validated German C19-YRSm holds significant potential to facilitate tailored interventions, destigmatise post-COVID conditions, and enhance patient care in medical contexts. Full article

Background and Objectives: Hospital mortality rates have repeatedly been used as important indicators of the quality of care provided and as a good monitoring and evaluation tool. Studies on hospital mortality in Saudi Arabia are scant, with most of the available literature focusing on the COVID-19 era. In this study, the patterns and trends in inpatient mortality at King Fahad Central Hospital in southwest Saudi Arabia from 2018 to 2022 were analyzed. Mortality characteristics, including age-specific mortality rates and associated factors, were also investigated. Materials and Methods: This was a retrospective study analyzing hospital mortality data in King Fahad Central Hospital (KFCH) from 2018 to 2022 using the largest hospital discharge database in the Jazan region. The mortality rates were calculated, and 95% confidence intervals (CIs) were reported. The analysis also documented some associations using logistic regression models. Results: Of the 62,534 patients admitted, 36,971 (59.1%) were females, and 25,543 (40.9%) were males. The mean age (standard deviation) was 24.6 (22.8) years. The overall hospital mortality was 4.8% [95% CI: 4.6–5.0] and was significantly higher among males [7.0%, 95% CI: 6.7–7.3] than females [3.2% 95% CI: 3.1–3.4] (p < 0.05). Mortality was significantly higher in the population aged 60 years and above [17.25%, 95% CI: 16.3–18.2] (p < 0.001). During the five-year period analyzed, mortality was low in 2018 (3.3%), with remarkably high rates during the COVID-19 period of 2020 and 2021 (5.6% and 6.0%, respectively). The disease groups with the highest prevalence of mortality include certain conditions originating in the perinatal period. In the logistic regression model, the male sex [odds ratio OR = 2.3, 95% CI = 2.01–2.43) was associated with an increased mortality risk. Compared to intensive care beds, general bed departments are associated with a 98% lower risk of mortality [OR = 0.015, 95% CI = 0.014–0.017]. Conclusions: This analysis of hospital data statistics revealed a relatively low hospital mortality rate in Jazan. However, the high mortality rates among male patients require further analysis and investigation. Customized interventions targeting high-mortality diseases are recommended. Full article

Prognostic scores that help allocate resources and time to the most critical patients could have potentially improved the response to the SARS-CoV-2 pandemic. We assessed the performance of five risk scores in predicting death or transfer to the intensive care unit (ICU) or sub-intensive care unit (SICU) in hospitalised patients with SARS-CoV-2 infection, with the three aims of retrospectively analysing the effectiveness of these tools, identifying frail patients at risk of death or complications due to infection, and applying these tools in the event of future pandemics. A retrospective observational study was conducted by evaluating data from patients hospitalised with SARS-CoV-2 infection. Among 134 patients considered, 119 were enrolled. All patients were adults, with a mean age of 64 years, and were hospitalised in the Infectious Diseases Division. We compared the five scores using receiver operating characteristic curves and calculation of the areas under the curve (AUCs) to determine their predictive performance. Four of the five scores demonstrated a high accuracy in predicting mortality among COVID-19-positive patients, with AUCs between 0.749 and 0.885. However, only two of the five scores showed good performance in predicting transfer to the ICU or SICU, with AUCs ranging from 0.740 to 0.802. The 4C Mortality Score and COVID-GRAM presented the highest performance for both outcomes. These two scores are easy to apply and low cost. They could still be used in clinical practice as predictive tools for frail and elderly patients with SARS-CoV-2 infection, as well as in the event of future pandemics. Full article

Background: Studies have suggested a synergism between lenalidomide (LEN) and ibrutinib (IBR) in multiple myeloma (MM). Both downregulate IRF4, a key target and master transcriptional factor regulating myeloma cell survival. Method: A 3 + 3 phase I trial was conducted to determine the maximum tolerated dose (MTD) of IBR in combination with LEN + dexamethasone (DEX) in patients with relapsed/refractory (RR) MM who had at least one prior line of therapy. Three dose levels (DLs) were planned. The cycle length was 28 days. IBR was administered orally daily in doses of 560 mg on DL1-2 and 840 mg on DL3, LEN was administered orally on days 1–21 in doses of 15 mg on DL1 and 25 mg on DL2-3, and DEX was administered orally on days 1, 8, 15, and 22 in a dose of 40 mg if age < 75 years or in a dose of 20 mg if it was ≥75 years for DL1-3. Patients with a glomerular filtration rate (GFR) <60 but ≥30 mL/min were treated in accordance with the manufacturer’s instructions with LEN 10 mg. Dose-limiting toxicities (DLTs) included the following: grade 4 neutropenia lasting more than 5 days, thrombocytopenia, febrile neutropenia, nausea, vomiting or diarrhea; grade 3 thrombocytopenia with bleeding or platelet transfusion; and grade 3–4 hyperglycemia or a thrombotic/embolic event, and other nonhematologic toxicities. The overall response rate (ORR) was defined as the percentage of patients with a partial response (PR), very good partial response (VGPR), or complete response (CR) according to IMWG criteria on two consecutive evaluations at least 4 weeks apart. The clinical benefit rate (CBR) was defined as the percentage of patients with stable disease (SD) or a better outcome on two consecutive evaluations at weeks apart. Results: Fourteen patients (DL1: six patients; DL2: three patients; DL3: five patients) were registered for the study from March 2019 to May 2023, prior to its closure due to limited accrual. Thirteen patients are included in the summary of toxicities and response as one patient on DL3 halted participation prior to the start of the treatment. Two patients on DL3 were excluded from the determination of MTD: one having discontinued cycle 1 treatment due to COVID-19 infection and the another having mistakenly taken 280 mg/day of IBR instead of the assigned 840 mg/day dose during cycle 1. Only one patient developed a DLT, on DL1 with grade 3 non-viral hepatitis. The median number of cycles administered was 4 (range: 1–56). Severe toxicities reported included grade 4 lymphocytopenia (1), grade 4 thrombocytopenia (1), and grade 5 sepsis in the setting of PD (1). Disease responses included a VGPR on DL1 and CR on DL3. Thus, the ORR was 15.4% (90% CI: 2.8–41.0%). One patient on DL1 maintained SD for 4.6 years before discontinuing the treatment to undergo an alternative therapy. Another five patients maintained SD for ≥ 2 consecutive cycles. Thus, the CBR was 61.5% (90% CI: 35.5–83.4%). Conclusions: The combination of LEN with IBR in RR MM proved feasible, with manageable toxicities and the majority of discontinuations being due to disease progression. Full article

Background/Objectives: Mobile healthcare units (MHUs) comprise flexible, ambulatory healthcare teams that deliver community care services, particularly in underserved or remote areas. In Greece, MHUs were pivotal in epidemiological surveillance during the COVID-19 pandemic and are now evolving into a sustainable and integrated service for much-needed community-based healthcare. To support this expanded role, targeted, competency-based training is essential; however, this can pose challenges, especially in coordinating synchronous learning across geographically dispersed teams and in ensuring engagement using an online format. Methods: A nationwide, online training program was developed to improve the knowledge of the personnel members of the Hellenic National Public Health Organization’s MHUs. This program was structured focusing on four core themes: (i) prevention–health promotion; (ii) provision of care; (iii) social welfare and solidarity initiatives; and (iv) digital health skill enhancement. The program was implemented by the University of Crete’s Center for Training and Lifelong Learning from 16 January to 24 February 2025. A multidisciplinary team of 64 experts delivered 250 h of live and on-demand educational content, including health screenings, vaccination protocols, biomarker monitoring, chronic disease management, treatment adherence, organ donation awareness, counseling on social violence, and eHealth applications. Knowledge acquisition was assessed through a pre- and post-training multiple-choice test related to the core themes. Trainees’ and trainers’ qualitative feedback was evaluated using a 0–10 numerical rating scale (Likert-type). Results: A total of 873 MHU members participated in the study, including both healthcare professionals and administrative staff. The attendance rate was consistently above 90% on a daily basis. The average assessment score increased from 52.8% (pre-training) to 69.8% (post-training), indicating 17% knowledge acquisition. The paired t-test analysis demonstrated that this improvement was statistically significant (t = −8.52, p < 0.001), confirming the program’s effectiveness in enhancing knowledge. As part of the evaluation of qualitative feedback, the program was positively evaluated, with 75–80% of trainees rating key components such as content, structure, and trainer effectiveness as “Very Good” or “Excellent.” In addition, using a 0–10 scale, trainers rated the program relative to organization (9.4/10), content (8.8), and trainee engagement (8.9), confirming the program’s strength and scalability in primary care education. Conclusions: This initiative highlights the effectiveness of a structured, online training program in enhancing MHU knowledge, ensuring standardized, high-quality education that supports current primary healthcare needs. Future studies evaluating whether the increase in knowledge acquisition may also result in an improvement in the personnel’s competencies, and clinical practice will further contribute to assessing whether additional training programs may be helpful. Full article

This study analyzes the comparative performance of ten hospitals in the Kadutu Health Zone in the Democratic Republic of Congo using the EGIPSS model. This study was carried out at the height of the COVID-19 pandemic in August and September 2021, in a changing global context where health systems were called upon to improve their resilience capacity while maintaining high levels of performance. This is a descriptive observational study using documentary review, interviews with 85 key informants, and participatory observation at ten hospitals selected based on several criteria, including the organization of a complete complementary package of activities assigned to a hospital in the DR Congo. This study mainly reveals three facts, namely that (i) university hospitals show the best performance, (ii) adaptive capacity considerably influences the other dimensions of the EGIPSS model and the overall performance of the hospital, and (iii) to adapt, hospitals need resources and good management and governance. Adapting hospitals in the Kadutu Health Zone to the changing context requires a holistic approach that combines clinical work with research, investments in infrastructure (often dilapidated and not modern), training, technology, and governance. It also involves learning from practices implemented in more efficient hospitals. Full article

Background: Hospitalized COVID-19 patients are particularly vulnerable to secondary bacterial infections, which can significantly worsen clinical outcomes. The aim of the study was to identify the cause of bacteremia in a group of hospitalized COVID-19 patients and find out the source of the outbreak to prevent further spread. Methods: Pathogen identification in blood cultures and sensitivity testing were carried out using the automated VITEK2 system. A total of 110 samples were tested; these were collected from patients’ colonization sites and from surfaces, materials and fluids used in the setting. Furthermore, multilocus sequence typing (MLST) and next-generation sequencing (NGS) were employed to characterize the isolates. Results: Achromobacter xylosoxidans was detected in the blood of nine hospitalized patients and in cotton used for disinfection; all isolates presented an identical antibiotic resistance pattern, and all carried the bla_OXA-114 gene which is intrinsic to this species. Infection control measures were implemented promptly. With one exception, all patients recovered and were discharged in good health. Conclusions: This outbreak underscores the urgent need for investigation and control of hospital infections, as bacteremia is associated with increased morbidity, mortality, hospitalization time, and cost. It also highlights the importance of close collaboration among healthcare professionals. Full article

Under the international globalized environment, the impact of the financial crisis of 2008 and the recent financial effect of the COVID-19 economic recession have generated a new role for the state aimed at reducing vulnerability to a new financial shock. Cost analysis is currently an issue among public authorities, inhibiting enhanced productivity and the effectiveness and utility of public services and goods. This article aims to showcase that the basic priorities of a high degree of transparency and accountability of public spending are becoming more and more essential. The need for cost allocation is essential for states to be resilient under the current ‘spin’ of crises. Full article

In the past two decades, particularly through the pandemic, the demand for real-time logistics has significantly increased. Cold chain logistics ensures specific temperature conditions for perishable goods such as food and pharmaceuticals, which is crucial for maintaining product quality, safety, and regulatory compliance. The integration of the Internet of Things (IoT) into cold chain logistics has transformed supply chain operations. The COVID-19 pandemic and the global urgency for vaccine distribution accelerated the adoption of cold chain technologies, emphasizing their role in preserving perishable goods’ integrity. IoT enables real-time monitoring, remote control, predictive analytics, and data-driven decision-making, all of which are essential for modern logistics. We conducted a bibliometric analysis of 50 publications from 1997 to 2024 to examine IoT’s role in cold chain management. Through co-occurrence and co-citation network analysis, core themes, influential works, and major contributors were identified. Thematic mapping highlighted the importance of temperature monitoring, logistics optimization, and risk management. Additionally, the transition from conventional logistics practices to IoT-driven methodologies was investigated in cold chain operations. The findings of this study provide a basis for understanding the structural properties of co-citation and co-occurrence networks in cold chain logistics and the evolving landscape of cold chain technology, and its impact on logistics, emphasizing the importance of intelligent, reliable, and sustainable cold chain systems to meet the growing demands in global supply chains. Full article

Background: Fear of childbirth (FOC) or tokophobia has a detrimental impact on women during and after pregnancy. Childbirth fear is multidimensional and may differ across nations and cultures. We aimed to determine the psychosocial determinants of tokophobia among Asians. Methods: We conducted a systematic literature search using the PubMed, Scopus, and Web of Science databases in September 2023. Included were original English-language articles that focused on Asian cohorts. We identified independent variables associated with maternal childbirth fear based on multivariable logistic and linear regression analysis. Results: Twenty-three studies are discussed in this review. We categorized the factors into (1) psychiatry, (2) psychology, (3) perception and experience, (4) relationships and support, (5) spirituality, and (6) COVID-19. The studies involved 10,538 women with overall FOC prevalence ranging between 56.6% to 82.1%. Maternal history of psychiatric disorder, depression, and anxiety were positive predictors of childbirth fear. Childbirth self-efficacy protects Asian mothers against tokophobia. A reduced level of fear was associated with higher maternal psychological and spiritual well-being, as well as stronger maternal resilience. Spousal and social support alongside good family function were shown to exert a protective effect against childbirth fear. Intimate partner abuse was associated with an increased risk of tokophobia in women. Studies during the pandemic indicated that maternal fear, obsession, and anxiety about COVID-19 were positively correlated to fear of childbirth. Conclusions: Childbirth fear among Asian women is greatly influenced by various psycho-social factors. More culturally driven research is needed to help develop relevant interventions that will enhance maternal psychological and spiritual well-being and reduce the fear of childbirth. Full article

COVID-19’s effects on mortality are hard to quantify. Issues with attribution can cause problems with resulting conclusions. Analyzing excess mortality addresses this concern and allows for the analysis of broader effects of the pandemic. We propose separate ARIMA models to analyze excess mortality for several countries. For the model of joint excess mortality, we suggest vine copulas with Bayesian pair copula selection. This is a new methodology and after its discussion we offer an illustration. The present study examines weekly mortality data from 2019 to 2022 in the USA, Canada, France, Germany, Norway, and Sweden. Previously proposed ARIMA models have low lags and no residual autocorrelation. Only Norway’s residuals exhibited normality, while the remaining residuals suggest skewed Student t-distributions as a plausible fit. A vine copula model was then developed to model the association between the ARIMA residuals for different countries, with the countries farther apart geographically exhibiting weak or no association. The validity of fitted distributions and resulting vine copula was checked using 2023 data. Goodness of fit tests suggest that the fitted distributions were suitable, except for the USA, and that the vine copula used was also valid. We conclude that the time series models of COVID-19 excess mortality are viable. Overall, the suggested methodology seems suitable for creating joint forecasts of pandemic mortality for several countries or geographical regions. Full article

The COVID-19 pandemic highlighted the need for rapid, cost-effective tools to monitor transmission and immune response. We developed two novel paper-based colorimetric biosensors using glutaraldehyde as a protein dye—its first use in this context. Glutaraldehyde reacts with amino groups to generate a brown color, enabling detection of SARS-CoV-2 antibodies. Wathman filter paper was functionalized with (3-aminopropyl)triethoxysilane (APTES) to immobilize virus-like particles (VLPs) and nucleocapsid protein (N-protein) as biorecognition elements. Upon incubation with antibody-containing samples, glutaraldehyde enabled colorimetric detection using RGB analysis in ImageJ software. Both sensors showed a linear correlation between antibody concentration and RGB values in buffer and serum. The VLP sensor responded linearly within the range of 1.0–20 µg/mL (green coordinate) in 500-fold diluted serum and the N-protein sensor from 1.0–40 µg/mL (blue coordinate) in 250-fold diluted serum. Both sensors demonstrated good selectivity, with glucose causing up to 18% interference. These biosensors represent a paradigm shift, as they provide a sensitive, user-friendly, and cost-effective option for semi-quantitative serological analysis. Furthermore, their versatility goes beyond the detection of SARS-CoV-2 antibodies and suggests broader applicability for various molecular targets. Full article