Introduction The use of health services expanded during the pandemic and became a regular part of healthcare. There is not a lot of information about how these services are used over the long term and how patients engage with them. This study examined how patients used telemental health services at King Abdulaziz Medical City (KAMC), Riyadh, Kingdom of Saudi Arabia, from 2019 to 2025. Objectives To evaluate how telemental health services were used and how patients engaged with them during the time before the pandemic, during the pandemic, and after the pandemic. The study also compared how many appointments were completed and the characteristics of patients who had virtual appointments versus in-person appointments. Methods This was a retrospective, repeated cross-sectional census study of electronic health record data on all scheduled mental health appointments, virtual and in-person, at KAMC from January 1, 2019, to December 31, 2025. All eligible encounters and unique patients across 12 facilities were included using total enumeration rather than sampling. Data were cleaned and analyzed in Python using Google Colab. Descriptive statistics were used to summarize appointment and patient characteristics. Chi-square tests were used to compare categorical variables, including appointment completion by encounter type, and the Mann-Whitney U test was used to compare patient age between virtual and in-person appointments. A binary logistic regression model was used to identify factors associated with appointment completion, including encounter type, pandemic period, and patient demographics. Results The study included 479,643 appointments with 51,323 patients at 12 facilities. Overall, 9% of the appointments were virtual. In 2019, there were no appointments, but their use increased during the pandemic and then stayed steady at around 11% to 12% per year after 2021. Overall, 55% of appointments were completed. Virtual appointments had a higher completion rate than in-person appointments, with 60% of virtual appointments being completed compared to 54% of in-person appointments. We also found that patients who had virtual appointments were substantially older and that virtual appointments were mostly used for follow-up visits rather than new patient appointments.  Conclusion Telemental health services went from being an emergency solution during the pandemic to a part of mental health services at the facility. The study found that virtual appointments were associated with patient engagement, which means that patients were more likely to complete their appointments. These findings support the continued use of a hybrid of in-person and virtual mental health services. The findings provide information to support the planning and development of telemental health services. Telemental health services are a part of the healthcare system, and they can be an effective way to deliver the services.
Functional health literacy (FHL) plays a dynamic role in diabetes care, yet research on its implications is erratic in Bangladesh. The aim of this study was to ascertain the level of FHL among patients with type 2 diabetes (T2D) in Dhaka and its correlation with their glycemic level, lifestyle, sleep quality, and sociodemographic characteristics. A total of 401 patients with T2D were included by simple random sampling method in this cross-sectional study from three diabetes centers in Dhaka. A Bengali adaptation of the S-TOFHLA (Short Test of Functional Health Literacy) and a semi-structured questionnaire was used to collect data on FHL and other study information. Bivariate analysis, multi-nominal regression, Pearson's χ2 test, and Cramér's V coefficient was used to assess the correlations between variables, with a significance threshold of p < .05. Among the 401 participants, 59% were female and 34.9% lived in rural areas; among whom only 27.3% had adequate FHL. Sex, occupation, education, income, physical activity regularity, diabetes treatment regimen, family history, current fasting blood sugar (FBS), 3-month average FBS, 3-month average 2-hour after breakfast blood glucose, and hemoglobin A1c showed significant associations (p < .0001) with the level of FHL. Higher education level significantly increased the odds for adequate FHL (adjusted odds ratios (AOR) = 5.70 to 78.81). Adequate FHL was significantly associated with higher sleep metrics (AOR = 5.67 and 9.17). Longer sleep duration and higher quality sleep increased the likelihood of having adequate FHL (AOR = 9.17 and 5.67, respectively; p < .05) and higher glucose levels were linked to reduced FHL odds (AOR <1). Higher FHL was associated with better diabetes management. FHL interventions should be evaluated to determine if increasing a patient's health literacy will improve their diabetes management. This cross-sectional study examined functional health literacy (FHL) among 401 patients with type 2 diabetes in Dhaka, Bangladesh, revealing that only 27.3% demonstrated an adequate understanding of basic health information. The researchers identified strong correlations between adequate FHL and several positive factors, most notably higher educational attainment, better sleep quality, and well-managed blood glucose levels. Conversely, poor glycemic control was significantly linked to lower health literacy. Ultimately, the findings indicate that a patient's ability to comprehend health information plays a crucial role in effective diabetes management, underscoring the need for targeted educational interventions to improve health literacy and, consequently, long-term patient outcomes.
Health services increasingly face decisions about how to integrate immersive technologies into routine practice. International guidance highlights the need for structured governance in digital health, yet extended reality (XR) initiatives are often launched through isolated pilots without a clear assessment of organizational readiness or implementation risk. Although factors influencing XR adoption are well documented, health care organizations and system-level decision-makers still lack practical, governance-oriented tools to translate these determinants into structured strategic decisions made before implementation. This study aims to develop multicriteria decision analysis for extended reality (MCDA-XR), a strategic governance framework that translates behavioral, organizational, and technical implementation determinants into a structured decision-support process for health care organizations. The study followed a sequential mixed methods design covering the first 2 phases of a 3-stage framework development and validation project. Phase 1 (identification) defined strategic criteria by integrating theoretical perspectives on organizational complexity, behavior change, technology acceptance, and immersive safety, together with a targeted review of XR implementation evidence. Phase 2 (construction) refined the framework through participatory sessions. A multidisciplinary group of 33 stakeholders, including professionals and managers from hospital and primary care settings, and postgraduate students, evaluated the proposed criteria for strategic relevance and operational clarity. This process resulted in a refined 10-criterion structure and the establishment of a dual-score assessment logic. Phase 3 (validation), planned as a subsequent step, will examine how the framework performs when applied prospectively in clinical settings. The development process yielded a framework comprising 10 operational criteria grouped into 3 conceptual domains (human, organizational, and technical). Stakeholder ratings indicated high strategic relevance across all criteria, with mean scores ranging from 4.03 (SD 0.95) for workflow integration to 4.61 (SD 0.56) for safety and comfort. The final instrument applies a dual-assessment approach in which each criterion is rated separately for strategic importance and organizational readiness. Mapping these dimensions enables organizations to identify priority gaps, particularly areas of high importance and low readiness, and to distinguish between manageable constraints and critical barriers requiring targeted preparatory action prior to implementation. MCDA-XR addresses a key governance gap in XR implementation by providing a structured way to align adoption decisions with institutional priorities and operational constraints. Rather than relying on descriptive feasibility assessments, the framework is intended to support explicit prioritization and action-oriented decision-making at the organizational level. MCDA-XR is positioned for Phase 3 evaluation, which will examine the practical utility, interpretability, and implementation relevance of the framework when applied prospectively in real-world clinical deployments.
Inference-time retrieval augmentation is increasingly used to improve the traceability and verifiability of large language model (LLM) applications in health care. Evaluation practices for text-based retrieval-augmented generation (RAG) and graph-structured RAG (GraphRAG) systems remain heterogeneous, which limits comparison across studies and complicates judgments about clinical readiness. This review mapped evaluation methods for inference-time retrieval-augmented and graph-structured retrieval-augmented LLM systems in health care and characterized how evaluation constructs are defined, operationalized, and reported across system layers and evaluation-setting categories. We conducted a scoping review in accordance with PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews), with search reporting informed by PRISMA-S (PRISMA literature search extension). Searches were conducted through May 14, 2026, in PubMed (MEDLINE), Web of Science Core Collection, IEEE Xplore, ACM Digital Library, arXiv, and medRxiv, with backward and forward citation tracking of included studies. Eligible records described health care-relevant LLM systems using inference-time RAG and reported at least 1 evaluation component. Data were charted on study characteristics, system design, retrieval-layer evaluation, evidence linkage, safety-related and GraphRAG-specific evaluation, and selected reporting and governance characteristics. We also constructed an evidence-and-gap map cross-classifying evaluation-setting categories with key evaluation domains. A total of 157 studies met the inclusion criteria. Clinical question answering was the most frequently represented application (89/157, 56.7%), followed by clinical decision support (70/157, 44.6%). Most evaluations were conducted in offline-only settings (140/157, 89.2%), whereas 17/157 (10.8%) studies reported workflow-facing, prospective, or deployment-level evaluation. Independent retrieval-layer evaluation was reported in 47/157 (29.9%) studies. Grounding and faithfulness evaluation was reported in 41/157 (26.1%) studies, and fine-grained evidence verification was reported in 22/157 (14%) studies. Human evaluation was reported in 94/157 (59.9%) studies, but interrater reliability was reported in 26/94 (27.7%) studies. LLM-as-judge evaluation was reported in 41/157 (26.1%) studies, with bias-control measures reported in 15/41 (36.6%) studies. Formal safety-related evaluation was reported in 45/157 (28.7%) studies. Among 27 (17.2%) GraphRAG studies, intermediate-artifact evaluation was reported in 11/27 (40.7%) studies, and graph construction evaluation was reported in 6/27 (22.2%) studies. The evidence-and-gap map showed limited coverage of fine-grained verification, contradiction handling, safety evaluation, LLM-as-judge safeguards, GraphRAG construction evaluation, and GraphRAG intermediate-artifact evaluation in workflow-facing, prospective, or deployment-level settings. Evaluation of health care RAG and GraphRAG systems has expanded rapidly, yet reporting and operational definitions remain inconsistent across evaluation layers. Current evidence remains concentrated in offline evaluation, with limited workflow-facing, prospective, or deployment-level assessment of retrieval quality, fine-grained evidence linkage, safety, LLM-as-judge safeguards, GraphRAG construction quality, and GraphRAG intermediate artifacts. This review maps these gaps across evaluation-setting categories and translates them into synthesis-informed evaluation considerations. These findings suggest that future evaluation may need to move beyond end-to-end benchmark performance toward more transparent, layer-specific, safety-oriented, and clinically contextualized assessment before workflow-facing implementation.
Vaccine hesitancy contributes to under-vaccination and recurring outbreaks of vaccine-preventable diseases in the United States. Rates are particularly low in rural areas. This qualitative study identified informational needs, trust in health information sources, and preferences for vaccine-related messaging to inform the design of a mobile application tailored to improve vaccine confidence and deliberative decision-making among rural caregivers. Parents or caregivers of children aged newborn to 3 years from Montana and Nebraska were recruited based on their level of childhood vaccination hesitancy using the Parent Attitudes About Childhood Vaccines (PACV) scale. Overall, 32 caregivers (18 fromF Montana, 14 from Nebraska), grouped by low (31%), medium (19%), and high (44%) hesitancy, participated in focus groups and follow-up individual interviews. Consensus coding and thematic analysis using NVivo software was used to identify key themes and patterns. Participants expressed key informational gaps, including questions about how vaccines work, safety testing, and the rigidity of immunization schedules. Gain-framed messages emphasizing benefits were consistently preferred over loss-framed messages, which were often perceived as judgmental or manipulative. Trust in local healthcare providers was a critical determinant of vaccine acceptance, surpassing trust in national health organizations. Participants advocated for non-judgmental, interactive, and personalized communication tools that mimic the relational trust found in provider interactions. Findings support vaccination communication strategies that integrate trusted local messengers, transparent and empowering framing, and participatory engagement. Insights directly inform the design of a parent-facing mHealth application customized according to preferences elicited from our diverse participant stakeholders.
The United States lags peer nations in infant mortality, with persistent racial and geographic inequities. In Missouri, Black infants experience mortality rates more than double those of White infants. Addressing these disparities requires community-driven interventions beginning before conception and extending beyond routine perinatal care. We describe the development and feasibility of Women & Person-Empowered Community Access for Reproductive Equity (WE CARE)-Jackson County (JC), a reproductive justice-informed intervention adapted from the Detroit WE CARE model to address reproductive health and infant mortality disparities. WE CARE-JC used a two-phase, mixed-methods design. Phase 1 included listening sessions with advocacy groups and reproductive-age women, and a community survey (N = 537) to identify needs, barriers, and engagement strategies. Phase 2 piloted the intervention in a safety-net hospital's emergency department. Intervention components included the "One Key Question," MyPath decision-support tool, community health worker-led counseling, and follow-up care navigation. Listening sessions identified trusted providers as preferred sources of family planning guidance, while stigma, limited provider access, and knowledge gaps were key barriers. Survey data showed social (13% housing, 22% food, and 35% transportation insecurity) and medical (51% comorbid condition) vulnerability. In the pilot, 45 women were enrolled (85% of those approached), of whom 58% scheduled follow-up care and 10 (39%) attended appointments. Feedback from eight attendees showed high acceptability of the MyPath tool, counseling, and navigation support. WE CARE-JC demonstrated feasibility and acceptability of a reproductive justice-informed, community-engaged model to reduce barriers and improve equitable access to reproductive health care. This model provides a scalable framework for addressing upstream drivers of infant mortality inequities.
Adverse drug reactions (ADRs) represent a significant challenge in pharmacovigilance, particularly for patients with chronic conditions like diabetes. Traditional reporting methods are often cumbersome and suffer from substantial underreporting. Mobile health applications with gamification elements offer a promising approach to enhance ADR reporting engagement. This study aimed to design, develop, and evaluate a gamified mobile application (RxFeedback) for ADR reporting among diabetic patients and healthcare professionals in Iran, with gamification mechanics (points, leaderboards, challenges) as the core engagement strategy. This analytical cross-sectional pilot study employed a user-centered design methodology in three phases: 1) Requirements gathering through literature review and stakeholder surveys (5 patients, 4 professionals); 2) Application development using Flutter framework with Dart programming language for Android platform; 3) Evaluation using Mobile Application Rating Scale (MARS) by 5 experts and Questionnaire for User Interaction Satisfaction (QUIS) by 20 patients. The RxFeedback application incorporated comprehensive ADR reporting features, medication management, and gamification elements (points system, leaderboards, challenges). Expert evaluation yielded a mean MARS score of 3.65/5, with highest scores in functionality (4.05) and lowest in aesthetics (3.40). Patient satisfaction assessment showed an overall QUIS score of 6.14/10, with highest satisfaction in application features (6.8) and lowest in terminology (5.7), though the limited sample size (n=20 patients, n=5 experts) and focus on usability should be noted as preliminary study constraints. RxFeedback demonstrated acceptable usability and quality (MARS: 3.65/5; QUIS: 6.14/10) in this pilot study. However, effectiveness in improving actual ADR reporting rates was not assessed. These findings establish preliminary acceptability as a foundation for future experimental studies.
To evaluate the real-world performance of a transformer-based natural language processing (NLP) system for extracting Social Determinants of Health (SDoH) from clinical notes, using survey-based SDoH measures a reference comparators. This study was conducted at the University of Florida Health in adults with at least 2 clinical encounters in the prior year. A research survey was completed by 1001 participants; sampling targeted 50% Black patients to support subgroup analyses. Comparative analyses were restricted to the 414 participants who also had Epic SDoH survey data and clinical notes available for NLP extraction. We compared concepts extracted by the SOcial DeterminAnts (SODA) NLP pipeline against the independently administered research survey, which served as the primary reference standard, and against the structured Epic-embedded SDoH questionnaire. Nine domains were evaluated: abuse, alcohol use, drug use, education, financial constraints, housing, physical activity, social cohesion, and transportation. Sensitivity, specificity, positive predictive value, negative predictive value, and F1 scores were calculated by domain. The NLP pipeline more consistently aligned with negative survey responses than with patient-reported social needs, although performance was lower in some domains, especially alcohol use and financial constraints. Sensitivity was higher only for alcohol use (55%); the lowest values were for abuse (5%), drug use (0%), and financial constraints (16%). These results cannot be attributed to SODA extraction alone. They reflect some combination of social information not being recorded in clinical notes, content that was recorded but not extracted, and mismatches between extracted concepts and survey definitions, and the present analysis cannot separate these contributions. The 2 surveys agreed only modestly with each other, so no single instrument provides a definitive ground truth. The pipeline more consistently aligned with negative survey responses than with patient-reported social needs. Because the 2 surveys agreed only modestly, the reference itself is imperfect, and apparent NLP performance depends in part on which survey is used as the comparator. Apparent gaps in NLP performance reflect both how social risks are recorded in clinical notes and how patients disclose them across different survey settings, in addition to limits of the extraction pipeline. Improving documentation practices, integrating locally tuned large language models, and monitoring subgroup performance may all be needed to make SDoH identification tools reliably detect social needs across patient populations.
This study aimed to assess the performance of federated learning (FL) models and compare their performance with local and centralized models. We conducted a systematic search of Ovid MEDLINE and PubMed from inception to June 10, 2025, to identify studies using patient data to train or validate FL algorithms and reporting at least one model performance outcome. Two reviewers independently screened articles and extracted data on study characteristics, FL frameworks and model training methodologies, and reported performance metrics. We summarized model performance using medians and interquartile ranges for federated, local, and centralized models. Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Diagnostic Test Accuracy Studies was followed. Thirteen studies involving 247 sites and 158,435 samples were included, with eight studies contributing to this meta-analysis. Most FL models (85%) used the Federated Averaging (FedAvg) algorithm for parameter aggregation across sites. FL model performance metrics were compared with local and centralized models within each machine learning task in each study. FL showed notable gains over local models, improving the AUC by 8.2%, F1 score by 7.9%, sensitivity by 4.1%, PPV by 26.1%, and PRAUC by 1.6%. Compared with centralized models, FL showed modest losses of 4.1% in AUC, 9.9% in F1 score, 9.3% in sensitivity, and 2.8% in PRAUC. FL outperformed local models and demonstrated comparable performance to centralized models while preserving data privacy. Standardized reporting and improved methodological transparency are needed to support its broader application in health research.
Youth suicide and depression rates increased during the COVID-19 pandemic. In Philadelphia, firearm violence surged and has since declined to pre-pandemic levels. We examined whether youth depression and suicide risk also declined and whether community firearm violence moderated these trajectories, given its documented associations with trauma and stress in youth. This cross-sectional study examined 71 663 well visits among youth aged 12 to 18 years in a pediatric primary care network in Philadelphia, 2017 to 2024. Youth were screened for depression and suicidality using the Patient Health Questionnaire, modified for teens. Three pandemic eras were defined by stay-at-home orders and the World Health Organization's declaration ending the global emergency. Neighborhoods were classified as firearm violence hot, neutral, and cold spots based on cumulative police-reported shootings. Period differences in mental health outcomes were evaluated using models accounting for patient clustering and interaction terms testing moderation by community violence. Among 35 137 patients (50% female, 67% non-Hispanic Black), community firearm violence moderated changes in youth suicide risk from the pre- to post-pandemic period: risk declined in cold spots (-2.2 percentage points [pp] [95 % CI -3.9 to -0.4]) but increased in neutral (+0.9 pp [0.1-1.6]) and hot spots (+2.0 pp [0.3-3.7]). Overall, suicide risk remained elevated post-pandemic (10.8% vs 9.6%, +1.1 pp [1.1-1.2]), particularly among non-Hispanic Black and Medicaid-insured youth, whereas depression returned to pre-pandemic levels (7.6% vs 7.3%). After the pandemic, suicide risk remained elevated among youth in areas with high community firearm violence. Beyond universal screening, addressing persistent pandemic-related stressors within the context of community firearm violence is critical for improving youth mental health.
People with dementia are often hospitalised due to comorbidities and superimposed delirium and have poorer outcomes in hospital compared to people without dementia, especially among under-served groups. Hospital at Home (HaH) schemes could reduce these inequalities by facilitating care in a familiar home environment that offers similar outcomes to acute hospital care with lower risks of harms. We aimed to investigate how dementia and cognitive impairment are considered within English health policy documents informing HaH implementation; considering potential impact on health inequalities and implications for future policy development. We searched websites, including UK governmental, NHS, social care and professional organisation sources, from 2015; and reference lists of included documents. We thematically analysed documents. We included 17 documents, comprising clinical guidelines (n = 5), government guidance (n = 4), policy papers (n = 3), service evaluations (n = 3), a strategy document (n = 1) and case study (n = 1). We developed three themes: (i) benefits of HaH for people with dementia, including more person-centred care and familiar treatment environments; (ii) how HaH can be inclusively designed for people with dementia, accommodating needs and mitigating concerns over digital exclusion and safety; and (iii) the critical role of family carers in enabling HaH, including potential carer burden. HaH models have potential to reduce health inequalities for people with dementia, but current implementation policies risk reinforcing inequalities, particularly among those without digital proficiency or carer support. Future policies should drive consistent inclusive eligibility criteria and processes for ensuring continuity with primary care, dementia care as a HaH staff core competency.
To investigate whether eligibility for Veterans Health Administration (VA)-purchased community care, which expanded Veterans' access to care outside VA, was associated with increased polypharmacy or potentially inappropriate medication use among older adult Veterans. Regression discontinuity design, leveraging the distance threshold for community care eligibility (residing > 40 miles from the nearest VA facility with ≥ 1 or more full-time primary care physician), to examine the effects of community care eligibility on polypharmacy and potentially inappropriate medication use among Veterans aged ≥ 65 years. VA pharmacy data for all prescriptions filled at VA facilities, VA Program Integrity Tool files for prescriptions paid by VA and filled in community pharmacies, and Medicare Part D data. Analyses included annual cross-sectional samples of Veterans 36-39 miles or 41-44 miles from their nearest VA facility during FY 2016-2019. The sample included 399,250 Veteran-year observations, of which 226,157 (56.6%) were 36-39 miles and 173,093 (43.4%) were 41-44 miles from the nearest eligible VA facility. Overall, we observed no discontinuities across the 40-mile threshold in the number of unique medications filled annually (-0.06 medications; 95% confidence interval [CI], -0.15 to 0.03). There were no discontinuities in proportions of Veterans filling ≥ 5 unique medications (-0.25 percentage points [pp]; 95% CI, -0.84 to 0.34), ≥ 10 medications (-0.55 pp.; 95% CI, -1.24 to 0.14), ≥ 1 medication on the Beers list (-0.02 pp.; 95% CI, -0.63 to 0.59), or ≥ 1 high-risk drug-drug interaction (-0.05 pp.; 95% CI, -0.17 to 0.07). Among Veterans with mental health conditions, exceeding the 40-mile threshold was associated with a higher likelihood of filling ≥ 10 unique medications annually (2.06 pp.; 95% CI, 0.42 to 3.70). We did not observe clinically or statistically significant discontinuities in other subgroups. Overall, eligibility for VA-purchased community care was not associated with increased polypharmacy or potentially inappropriate medication use among older adult Veterans.
The Cures Act Final Rule requires that patients have real-time access to their radiology reports, which contain terminology meant to communicate between healthcare providers and may be difficult for patients and families to comprehend. To evaluate family use of and experience with patient-friendly radiology reports provided through a patient portal for the pediatric population. Patient-friendly interactive radiology reports were made available to all patients and families with imaging exams performed from January 2024 through November 2025 at two children's health systems via a patient portal using commercially available software. Portal usage statistics were obtained, including report access rate and report view time of plain language explanations and interactive diagrams. Families were surveyed to assess experience with the reports and report comprehension. A total of 391,713 combined imaging exams were performed between the two institutions during the study period, of which 50.5% of standard reports were viewed. While only 9.0% of patient-friendly reports were viewed, this accounted for 17.7% of viewed standard reports. Reports of radiographs were accessed less than the pooled rates of other modalities. Families spent an average of 3.29 min (95% CI 3.25-3.32 min) viewing each patient-friendly report. An initiative at one children's hospital led to a sustained increase in view rates of patient-friendly reports. Results suggest that while initial utilization of the tool was low, providing patient-friendly interactive radiology reports is feasible for pediatric patients and may improve subjective comprehension of radiology reports.
Pregnancy involves dynamic metabolic changes that cannot be accurately interpreted using population reference intervals (RI). The aim was to develop continuous reference curves for common hematology and biochemistry laboratory analytes in pregnancy and to assess their agreement with the RIs for non-pregnant women, which are routinely reported for pregnant women. A prospective study was conducted at the Clinical Hospital Centre Rijeka, Croatia, from September 2022 to December 2025. Inclusion criteria were age ≥18 years, singleton pregnancy, normal ultrasound and prenatal screening findings, and favorable pregnancy outcome. Exclusion criteria were illness in the last month, pregnancy-related complications, medically assisted fertilization, and chronic medication use. All participants provided informed consent and completed a questionnaire on lifestyle habits and health status. Continuous reference curves for 43 laboratory analytes were generated using the mathematical-statistical GAMLSS model. Agreement with the discrete RI was expressed as the percentage deviation from the continuous reference curves. The analysis included 739 samples from 542 pregnant women between the 11th and 38th gestational weeks. Of the 43 laboratory analytes, 35 showed discrepancies when compared to non-pregnant RI. Falsely elevated interpretations ranged from 5.6 to 64.9 %, and falsely lowered from 3.4 to 62.0 %. Graphical representations of the continuous reference curves show pronounced dynamics compared to the existing discrete RI. The use of RIs for non-pregnant women results in substantial differences in the interpretation of laboratory results in pregnant women. Continuous gestational age-specific reference curves account for nonlinear physiological changes and provide a physiologically appropriate framework for interpreting laboratory results during pregnancy.
Persistent symptoms after a respiratory infection can impair daily life, as has been shown, for example, for "long COVID." In this study, we determined the frequency and impact of symptoms that persisted for 12 weeks or more after a respiratory infection. A further endpoint was health care utilization for such symptoms in the general population. A cross-sectional study was conducted within the population-based digital cohort DigiHero in Germany (DRKS00025600). 39.3% of invited participants responded by completing an online questionnaire. 46 915 adults were included in the analysis. Participants were asked about symptoms that persisted 12 weeks or longer after a respiratory infection between September 2024 and August 2025. 48.3% of participants (95% confidence interval: [47.9; 48.8]) reported having had at least one respiratory infection during the study period. Among them, 18.8% [18.3; 19.3] stated that they still had symptoms 12 weeks or more afterward. The frequency of persistent symptoms was higher in older persons (13.1% for ages 20 to 29, 21.4% for ages 60 to 69). Most (86.8%) of those affected reported at least moderate functional impairment, and 57.9% consulted a physician. The pathogen causing the original infection was known for 24.3% of those reporting persistent symptoms: there were 483 cases of SARS-CoV-2 infection, 102 of influenza, and 36 of RSV. The symptom duration, functional impairment, and symptom pattern were similar after infection with SARS-CoV-2 and influenza. The most common symptoms in all pathogen groups were impaired physical performance, shortness of breath, rapid exhaustion, and fatigue. Persistent symptoms after respiratory infections are common and similar across pathogens in frequency and severity.
The UK Biobank Imaging Study, with its dedicated cardiovascular magnetic resonance substudy, has redefined the scale and scope of cardiovascular research, generating high-quality imaging in 100 000 participants with linkage to rich genetic, demographic, lifestyle, and clinical data. The resource has enabled transformative discoveries across genomics, epidemiology, and biomedical engineering and has served as a global blueprint for population imaging studies. Its success has been accelerated by an equitable data access model that fosters international collaboration. The UK Biobank cardiovascular magnetic resonance experience illustrates the power of large-scale imaging cohorts and sets a benchmark for future initiatives aimed at improving cardiovascular health through integrated, collaborative science. Looking ahead, efforts should focus on harmonization across cohorts, adherence to rigorous methodological standards, and multidisciplinary collaboration to drive meaningful clinical translation. This article provides an overview of the UK Biobank and its cardiovascular magnetic resonance substudy, systematically reviews publications to date, discusses limitations and methodological considerations, and highlights future directions.
This systematic review aims to investigate the relationship between voxel value obtained from Cone Beam Computed Tomography (CBCT) in studies compared to Hounsfield of Multidetector Computed Tomography (MDCT) in homogeneous and heterogeneous samples. A literature search was carried out in the databases PubMed, Scopus, Embase, and Web of Science searching for relevant literature until February 2022 (updated at July 2023). A risk of bias assessment of the studies was performed using a modified checklist based on the Cochrane Collaboration's tool and the Journal of Biomedical Informatics. The software version 20.104 of MedCalc was used to conduct the meta-analysis of correlation coefficients. Out of 4750 articles in the initial search, 13 met the eligibility criteria. Out of the articles, eight studies were included in the meta-analysis. Both heterogeneous and homogenous samples showed a strong correlation between the voxel value of CBCT and Hounsfield Unit (HU), with high heterogeneity (r=0.900 and 0.998 respectively and I2>70%). Two other meta-analyses were conducted for kVp and voxel size, which showed a high correlation. The 95% confidence interval was used to present the estimated pooled correlation. The strong correlation of voxel value and HU indicates the possible potential of CBCT in radiographic bone density measurement. However, further research is needed to obtain an accurate conversion equation for translating voxel values of CBCT to HU. Calibration of voxel values within each scan using a reference object and consideration of both linear and non-linear regression could improve accuracy.
Oral cancer is among the ten most common malignancies worldwide and can be highly lethal if not diagnosed and treated promptly. Mapping the spatial and geographic distribution of this cancer can assist health authorities in planning effective prevention, control, and treatment strategies by identifying its geographic and demographic patterns. This study aimed to investigate the demographic characteristics and geographic distribution of oral cancer in Golestan Province, Iran, during the period 2014-2021. This trend study used data from the National Cancer Registry System of Golestan Province, Iran, covering the period from 2014 to 2021. Geographic mapping of the cities in Golestan Province was performed using ArcGIS software. The annual incidence of oral cancer was calculated for each city and expressed as the number of cases per 100,000 population per year. A total of 390 patients with oral cancer were identified in Golestan Province between 2014 and 2021. Of these, 200 (51.3%) were male and 190 (48.7%) were female. The mean age of the patients was 56.18 ± 17.37 years, ranging from 2 to 96 years. The standardized annual incidence rate of oral cancer in Golestan Province ranged from 4.25 to 6.75 cases per 100,000 population during the study period. Among the cities of the Province, Maraveh Tappeh showed the highest incidence rate, with an average incidence of 12.35 cases per 100,000 population. The incidence of oral cancer in Golestan Province demonstrated temporal fluctuations during the study period, with higher rates observed in several northern cities. Geographic mapping of the disease may provide valuable insights into the potential influence of environmental, cultural, and lifestyle factors on the distribution of oral cancer and can support more targeted prevention and control strategies.
To assess the risk of major congenital anomalies (MCAs) and other adverse outcomes following prenatal exposure to modafinil. This retrospective cohort study used the French national healthcare database (SNDS) to include singleton children born between January 2009 and September 2024 of women aged 15-55 years. Prenatal exposure to psychostimulants was defined as maternal dispensation during pregnancy. Children prenatally exposed to modafinil were compared with two control groups: children prenatally exposed to methylphenidate and children prenatally unexposed to any psychostimulant matched to the exposed group using propensity-score matching (PSM). Outcomes included MCAs, neurodevelopmental disorders (NDs), and specialized consultations. Analyses included descriptive statistics, survival analysis, regression models, and dose-response analyses. Of 10 955 766 included children, 865 were prenatally exposed to modafinil and 950 to methylphenidate. Exposure to modafinil during the first trimester of pregnancy was statistically associated with increased risk of MCA compared to methylphenidate, although the confidence interval was wide and close to the null (aRR = 1.77 [1.01-3.07]). Comparison with PS-matched unexposed population indicated a possible modest increase in risk, albeit with a wide confidence interval crossing the null (aRR = 1.23 [0.76-1.99]), showing no clear association. Occurrence of NDs (aHR = 0.96 [0.56-1.65]), and specialized consultations (aHR = 1.08 [0.91-1.28]) were similar in the modafinil and PSM unexposed groups but were higher in the methylphenidate group (NDs: aHR = 0.48 [0.29-0.80]; specialized consultations: aHR = 0.71 [0.59-0.85]). This study shows no increase in neurodevelopmental risk, while a moderate MCA risk cannot be excluded. This study looked at whether taking modafinil during pregnancy increases the risk of major birth defects or other health problems in children. We analyzed data from nearly 11 million children born in France between January 2009 and September 2024. We compared children exposed to modafinil before birth with those exposed to another drug, methylphenidate, and those not exposed to any psychostimulant but with similar characteristics. The main focus was on birth defects, but other issues such as fetal growth and neurodevelopmental issues were also analyzed. We found a slight increase in birth defects among children exposed to modafinil compared to the methylphenidate group and no increase compared to the unexposed group. Rates of neurodevelopmental issues were similar between the modafinil group and unexposed children, and actually lower than in the methylphenidate group. Overall, the findings suggest that a large increase in the risk of adverse outcomes following exposure to modafinil during pregnancy is unlikely; however, a moderate increase in risk of birth defects cannot be excluded.
We examined associations between patients' socioeconomic and clinical factors and the thoroughness of clinical notes for children visiting the pediatric emergency department (ED) for headache. This is a secondary analysis of data from a retrospective chart review of first-time visits for patients (ages 5-17) seen for headache at 1 pediatric ED, excluding visits related to infection or injury. We extracted fields from the provider note relevant to headache diagnosis (eg, pain severity) and used backward stepwise log-binomial regressions to identify demographic and clinical factors associated with missing data for a single field. For our sensitivity analysis, we included imputed pain severity as another predictor. From 1000 randomly selected ED visits, we found 629 eligible visits, skewing toward adolescents (median: 13.0 y [IQR: 10.0-15.8 y]) and females (58.5%). Non-Hispanic black children had lower odds of being triaged at moderate or severe acuity even after adjusting for pain severity, age, and sex assigned at birth (OR: 0.07 [95% CI: 0.03-0.16]). Older patients (RR 0.99 per year [0.98-0.99], P<0.001) and those with moderate (0.79 [0.75-0.82], P<0.001) or high-acuity (0.90 [0.85-0.96], P=0.001) triage scores had a decreased risk of missing data; boys had an increased risk (1.04 [1.00-1.08], P=0.046). After pain severity was included, patients with severe pain (0.92 [0.88-0.97], P=0.003) had a decreased risk of missing data while sex differences became nonsignificant (P=0.063). Provider notes for children seen in the ED for headache are less thorough for younger patients, boys, and those with lower triage acuity scores. After accounting for pain severity, patients reporting mild pain also had less thorough notes. If the quality of medical documentation represents the health care interaction, relationships between missingness and demographic factors such as sex warrant exploration of potential interventions.