Tag: pubmed

JNCI Cancer Spectr. 2026 Aug 24:pkag086. doi: 10.1093/jncics/pkag086. Online ahead of print.

ABSTRACT

PURPOSE: Cancer-related cognitive impairment is common in patients receiving cancer treatment but may be under detected by clinician-graded adverse events (AEs) alone. Patient-reported outcomes and cognitive screening may improve identification of cognitive symptoms.

METHODS: We conducted a secondary analysis of the nationwide, multicenter GAP70+ trial of adults aged ≥70 years with advanced cancer starting systemic therapy. Cognitive symptoms were assessed longitudinally using patient-reported and clinician-graded cognitive AEs, and Mini-Cog screening at baseline, 4-6 weeks, 3 months, and 6 months. We examined prevalence, longitudinal trajectories, and associations with Mini-Cog impairment. Statistical significance was set at two-sided p< 0.05.

RESULTS: Among 704 participants (mean age, 77.2 years; range, 70 to 96 years), patient-reported cognitive AEs were more prevalent than clinician-graded cognitive AEs at all timepoints: 19% vs 0.48% at 4 to 6 weeks, 18% vs 2.5% at 3 months, and 22% vs 0.44% at 6 months at 6 months (all p < 0.001). Patient-reported cognitive AEs also fluctuated within patients over time. Impaired Mini-Cog was associated with higher patient-reported cognitive AEs at all post-baseline timepoints: 31% vs 15% at 4 to 6 weeks, 34% vs 14% at 3 months, and 49% vs 15%at 6 months (all p < 0.001). In contrast, associations with clinician-graded cognitive AEs were observed only at 3 months (p = 0.004) and 6 months (p = 0.04).

CONCLUSIONS: Cognitive symptomatic AEs are common and often under detected by clinician grading alone in older adults with advanced cancer. Combining patient-reported AEs with brief cognitive screening may improve detection during treatment.

PMID:42636266 | DOI:10.1093/jncics/pkag086

Expert Rev Anti Infect Ther. 2026 Aug 24. doi: 10.1080/14787210.2026.2723576. Online ahead of print.

ABSTRACT

INTRODUCTION: Marburg virus disease (MVD) is a highly lethal filovirus infection with case fatality rates of up to 88%. Although no virus-specific interventions have yet been approved, recent laboratory breakthroughs have markedly accelerated translational progress in vaccine and therapeutic development.

AREAS COVERED: A hybrid methodological design was employed, combining macro-level bibliometric analysis with a targeted qualitative narrative review. As per the findings, the human monoclonal antibody MR191N provides complete post-exposure protection in non-human primates. Advanced RNA-targeted siRNAs, antisense oligonucleotides, and small-molecule nucleoside analogues (e.g. galidesivir) demonstrate robust preclinical efficacy in suppressing viral replication. Prophylactic platforms – including adenovirus-vectored (ChAd3-MARV), rVSV-MARV, and mRNA-based vaccines – are progressing through early-phase clinical and preclinical evaluation. Bibliometric analysis, however, reveals pronounced geographic disparities: high-income nations dominate scientific output (United States: 31.7%), while endemic African countries remain severely underrepresented in global collaboration networks.

EXPERT OPINION: Addressing MVD requires a coordinated transition from experimental research to licensed, field-ready interventions. This necessitates adaptive trial designs, expanded diagnostic models, and synergistic combination therapies. Ultimately, correcting global research inequities and embedding robust, cross-border One Health surveillance infrastructure are essential to transforming scientific advances into equitable, rapid-response solutions for endemic regions.

PMID:42636264 | DOI:10.1080/14787210.2026.2723576

PLoS One. 2026 Aug 24;21(8):e0353483. doi: 10.1371/journal.pone.0353483. eCollection 2026.

ABSTRACT

BACKGROUND AND AIMS: Malaria remains a public health concern in Bangladesh, despite a notable decline in reported cases since 2012 and a brief resurgence in 2014. Aligned with the United Nations Sustainable Development Goal (SDG) 3.3, which targets the elimination of malaria by 2030, Bangladesh has implemented multiple control and prevention strategies. This study assesses the significance of the decline in malaria cases and applies Bayesian hierarchical models to capture spatial dynamics of malaria-related vulnerability, map district-level risk, and inform targeted interventions.

METHODS: A nationwide spatial analysis was conducted using district-level malaria data from the Bangladesh Disaster-related Statistics (BDRS) 2021, which report cumulative counts of “population suffering from malaria due to disaster” for 2015-2020. These data were used as a proxy indicator of relative malaria vulnerability. National malaria time-series data were obtained from Bangladesh’s National Strategic Plan for Malaria Elimination (2021-2025) published by the Asia Pacific Malaria Elimination Network (APMEN), together with malaria surveillance summaries from the World Malaria Reports (2024,2025) published by the World Health Organization (WHO). District-level rainfall data were obtained from the Bangladesh Water Development Board. Bayesian hierarchical disease mapping models were used to assess spatial dependence and district-level malaria risk. Spatial visualization and autocorrelation analyses (Global Moran’s I, Geary’s C, and Local Moran’s I) were performed using R (version 4.4.0), and Bayesian model estimation was carried out using WinBUGS via Markov Chain Monte Carlo methods.

RESULTS: The analysis showed evidence of a trend in decreasing malaria cases by a value of -0.691 in the Mann-Kendall trend test. However, spatial analysis revealed significant clustering and geographic heterogeneity. Persistent high-risk clusters were identified in the southeastern hilly regions. Additionally the presence of excess zeros in the data justified the use of zero-inflated models.

CONCLUSION: The findings show significant national decline and offer valuable insights into the geographical variability in malaria-related vulnerability in Bangladesh. Rather than being direct indicators of malaria transmission, the results should be understood as representing relative risk patterns based on data related to disasters. Under current data limitations, these results provide evidence to boost spatially informed malaria control methods and assist geographically focused interventions.

PMID:42636262 | DOI:10.1371/journal.pone.0353483

J Rural Health. 2026 Jun;42(3):e70209. doi: 10.1111/jrh.70209.

ABSTRACT

PURPOSE: Previous research demonstrates that excessive alcohol use behaviors, alcohol-related harms, and the prevalence of mental health conditions disproportionately impact rural communities, with mixed findings on rural-urban differences in behavior uptake. This study aims to examine rural-urban differences in the prevalence of excessive alcohol use among individuals with selected self-reported mental health conditions.

METHODS: The 2021 and 2022 National Survey on Drug Use and Health (NSDUH) data was used to obtain prevalence estimates for self-reported past-year any mental illness (AMI), lifetime depressive symptoms (DS), past-month excessive alcohol use alone, and past-month excessive alcohol use among individuals reporting either past year AMI or lifetime DS using survey-weighted descriptive statistics. Bivariate associations and survey-weighted multivariable logistic regression models were used to determine the odds of having the selected outcomes across levels of residence (large urban, small urban, and rural).

FINDINGS: Around half of all individuals reported past month excessive alcohol use; rates were slightly higher among small urban residents compared to rural and large urban residents. Prevalence for past year AMI, lifetime DS, and past month excessive alcohol use alone were highest among small urban residents. After adjusting for sociodemographic characteristics, no significant differences were observed by residence for AMI and excessive alcohol use or for DS and excessive alcohol use.

CONCLUSIONS: These results add to a limited availability of updated and generalizable research examining differences in self-reported mental health conditions and excessive alcohol use behaviors across a comprehensive rural-urban continuum and can be used to inform targeted policy solutions and intervention strategies.

PMID:42635621 | DOI:10.1111/jrh.70209

J Health Organ Manag. 2026 Aug 25:1-30. doi: 10.1108/JHOM-02-2026-0248. Online ahead of print.

ABSTRACT

PURPOSE: This study examines how managerial perception of digital transformation (DT), patient-centered strategy (PCS) and leadership support for innovation (LSUP) relate to patient experience and engagement (PXE) in Ugandan health facilities.

DESIGN/METHODOLOGY/APPROACH: Drawing on the Technology-Organization-Environment (TOE) framework and Dynamic Capabilities Theory (DCT), the study adopts a mixed-methods design. Quantitative data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) for managerially perceived patient-centered outcomes, complemented by qualitative interviews from managers and patients to contextualize and explain the statistical relationships.

FINDINGS: The results show that the direct effect of digital transformation on patient experience and engagement is not statistically significant (β = 0.207, p = 0.078). There is a strong, statistically significant effect of digital transformation on patient-centered strategy (β = 0.600, p < 0.001). Patient-centered strategy positively and significantly affects patient experience and engagement (β = 0.306, p = 0.046). Patient-centered strategy plays a meaningful mediating role in the relationship between Digital Transformation and Patient Experience. While leadership support for innovation on patient experience and engagement does not moderate the relationship (ß = 0.112, p = 0.294). Qualitative findings reveal that digital technologies primarily create value by enabling patient-centered care redesign rather than directly shaping patient perceptions.

RESEARCH LIMITATIONS/IMPLICATIONS: Despite offering valuable insights into the effects of digital transformation, patient-centered strategy and leadership support for innovation on patient experience and engagement in Ugandan health facilities, this study has several limitations. First, the cross-sectional design limits the ability to establish causal relationships, as the structural model identifies associations rather than causal effects; therefore, longitudinal studies are needed to capture the dynamic influence of digital adoption and strategic interventions over time. xD; xA; A limitation is the small, purposively selected sample of 67 senior leaders, which constrains statistical power and generalizability. Although supported by 48 key informant interviews from senior leaders and patients’ perspectives were incorporated. Though PLS-SEM accommodates small samples, caution is warranted in hypothesis testing (Hair et al., 2022). Although patient qualitative interviews strengthened contextual understanding and validation of findings, future studies could further enhance measurement precision by incorporating large-scale quantitative patient-reported outcome measures and patient satisfaction surveys directly into the structural model. Nonetheless, such samples are acceptable for exploratory digital health research, but findings require validation using larger, multi-stakeholder datasets (Dwivedi et al., 2023). Second, the study relied largely on self-reported data from healthcare providers and administrators, which may introduce response bias or social desirability effects. Although patient experience and engagement were conceptually addressed, patient-reported outcomes were not consistently measured, potentially limiting generalizability. Third, while Ugandan health facilities represent a relevant low- and middle-income country (LMIC) context, variations in infrastructure, digital literacy and organizational readiness may restrict the applicability of the findings to other LMIC settings. The non-significant results for H1 and H5 further suggest that technology and leadership effects may vary under different institutional conditions. Additionally, the study examined a limited set of variables, excluding factors such as organizational culture, staff workload, policy incentives and patient socioeconomic conditions. Finally, practical implementation challenges such as limited training, financial constraints and infrastructural gaps may affect the translation of these findings into practice, highlighting the need for context-sensitive implementation and further research.

PRACTICAL IMPLICATIONS: The findings suggest that healthcare organizations in resource-constrained contexts should align digital initiatives with patient-centered strategies and leadership practices to realize experiential gains.

SOCIAL IMPLICATIONS: By demonstrating how digital transformation and patient-centered strategies influence engagement and experience, the study has broad societal relevance. Effective deployment of digital health solutions, coupled with patient-focused organizational strategies, can improve access, equity and quality of care for underserved populations in LMICs. Enhanced patient engagement fosters trust, satisfaction, and adherence to treatment, ultimately contributing to better population health outcomes. Moreover, a culture of patient-centered innovation supports community empowerment, strengthens health system responsiveness and promotes social well-being, thereby addressing systemic healthcare disparities.

ORIGINALITY/VALUE: The study advances health management literature by integrating TOE and DCT to explain how digital transformation creates patient-centered value in LMIC healthcare settings.

PMID:42635585 | DOI:10.1108/JHOM-02-2026-0248

Lab Chip. 2026 Aug 24. doi: 10.1039/d6lc00324a. Online ahead of print.

ABSTRACT

We present a unified digital-to-experimental workflow that advances the integration of single-image diffusion-based rock generation with connectivity conditioning, scalable texture synthesis, and microfluidic experimentation, enabling statistically realistic generated images to be converted into hydraulically functional, fabrication-ready porous media. For each reference rock image across multiple lithologies, a separate SinDiffusion model is trained to generate statistically consistent pore-scale realizations that preserve key features of the input structure. Quantitative evaluation using intensity statistics, porosity, Minkowski functionals, connectivity metrics, and pore-shape eccentricity confirms preservation of multi-scale morphological characteristics. The generated images are further processed through percolation-constrained thresholding and texture synthesis to produce fabrication-ready designs with controlled connectivity and arbitrary geometries. Additional geometric and flow-property analyses across the four workflow stages show that the final designs retain comparable structural and transport-relevant characteristics while satisfying microfluidic fabrication requirements. The digital layouts are translated into rock-on-chip microfluidics via maskless photolithography and used for CO₂ drying and salt precipitation experiments. Homogeneous and artificially fractured sandstone-like configurations demonstrate the workflow’s ability to resolve structure-dependent drying and precipitation patterns, with fractures promoting localized deposition and delayed clogging. Experiments on multiple realizations generated from the same input image show a consistent qualitative sequence of CO₂ displacement, brine depletion, and salt accumulation, while capturing realization-specific variability in phase evolution.

PMID:42635571 | DOI:10.1039/d6lc00324a

Int J Nurs Knowl. 2026 Apr;37(2):147-155. doi: 10.1177/20473087261449888. Epub 2026 Aug 24.

ABSTRACT

PurposeTo verify the association of the nursing diagnosis (ND) Ineffective Health Self-Management (IHS) (00276) with severe radiodermatitis in individuals with anal and/or rectal canal cancer.MethodsCohort study, secondary to a clinical trial. Data were extracted from 57 participants undergoing radiotherapy (RT) for anal and/or rectal cancer so that a panel of experts could assess the presence of the defined characteristics and the ND of IHS. Descriptive and inferential statistical analysis was performed. Univariate analyses and bivariate analyses were applied using Fisher’s exact test and chi-square test.FindingsThe ND had a high prevalence. There was an association among participants with three or more defining characteristics (DC) of that diagnosis in patients experiencing severe radiodermatitis.ConclusionsAn association was identified between the presence of three or more DC in the onset of severe radiodermatitis in individuals with anal and/or rectal canal cancer.Implications for nursing practiceThe study contributes to incorporating the association between a human response and an adverse event in the nursing standards or guidelines related to the context of RT.

PMID:42635549 | DOI:10.1177/20473087261449888

Int J Nurs Knowl. 2026 Apr;37(2):176-189. doi: 10.1177/20473087261450289. Epub 2026 Aug 24.

ABSTRACT

BackgroundFamily engagement is crucial for achieving successful outcomes for both patients and hospitals. It supports safe transitions between care settings, providers, and ultimately, as illness progresses. However, in the hospital setting, family engagement is poorly operationalized. While the existing literature acknowledges its benefits, it does not adequately define the specific domains of family engagement, the roles families play during inpatient care, or whether these factors differ across patient populations.AimsThis research aims to describe family engagement in the hospital setting and examine whether differences exist in documentation across various populations.MethodsA retrospective chart review (RCR) was conducted using data extracted from the electronic medical records (EMRs) of adult patients admitted to neuroscience units at an academic medical center. Descriptive statistics were calculated for continuous and categorical variables. Chi-square analysis was performed on categorical variables (e.g., race, social deprivation index [SDI], cognitive impairment) to identify statistically significant differences between groups, with a threshold of p < 0.05.FindingsThe RCR included data of 293 patient records. The results reveal what is documented regarding family engagement in the EMR, who is documenting it, and where it is recorded. No differences were found in the documentation of engagement domains between Black and White patients, between patients with high and low SDI, or between patients with cognitive impairment and those without. However, differences were observed in documentation related to discharge placement.ConclusionThese results have implications for further research, policy development, and provider education. They underscore the need for a structured template in the EMR and suggest potential implications for nursing diagnoses and interventions to better support family engagement in the hospital setting.

PMID:42635539 | DOI:10.1177/20473087261450289

J Speech Lang Hear Res. 2026 Aug 24:1-20. doi: 10.1044/2026_JSLHR-25-00969. Online ahead of print.

ABSTRACT

PURPOSE: Despite almost complete cochlear maturity at birth, distortion product otoacoustic emission (DPOAE) levels in neonates and infants are typically higher than those measured in older children and adults, depending on the type and frequency stimulus, which suggests functional immaturity of the cochlea as well as the role of the outer and/or middle ear. This study aimed to investigate the relationship between outer and middle ear characteristics, using wideband tympanometry (WBT), and DPOAEs and to evaluate the applicability of normative criteria at reduced stimulus intensities in children aged between 6 days and 5 years.

METHOD: A total of 109 ears from 60 participants were examined and categorized into three age groups: newborns, infants (6-8 months), and children (3-5 years). The following measurements were analyzed: ear canal volume, compensated acoustic admittance (with 1-kHz probe tone and 226-Hz probe tone), acoustic absorbance, and DPOAEs with two stimulus intensity protocols (L₁–L₂ = 65-55 and 55-45 dB SPL). Statistical analyses included nonparametric tests and correlation models.

RESULTS: WBT measures reflect the age-related maturation of the conductive pathway. Absorbance, DPOAE response levels, and signal-to-noise ratios (SNRs) were higher in neonates and 6- to 8-month-olds than in the 3- to 5-year group, especially at high frequencies. Lower stimulus levels (L₁–L₂ = 55-45 dB SPL) led to reduced DPOAE amplitudes and increased rates of absent responses across all groups, although the SNR remained above 6 dB in most ears.

CONCLUSIONS: The findings suggest that the structural characteristics of the outer and middle ears alter both the forward and reverse sound transmission properties, impacting DPOAE detectability. Reducing stimulus intensities affected DPOAE measures differently across age groups; however, the use of age-specific normative data may improve the accuracy of result interpretation.

PMID:42635534 | DOI:10.1044/2026_JSLHR-25-00969

Chaos. 2026 Aug 1;36(8):083141. doi: 10.1063/5.0335659.

ABSTRACT

We establish a definition of ordinal patterns for multivariate data sets based on the concept of Tukey’s halfspace depth. Given the definition of these depth patterns, we are interested in the probabilities of observing specific patterns in time series. For this, we consider the relative frequency of depth patterns as natural estimators for their occurrence probabilities. Depending on the choice of reference distribution and the relation between reference and data distribution, we distinguish different settings that are considered separately. Within these settings, we study the statistical properties of depth pattern probabilities, establishing consistency and asymptotic normality under the assumption of weakly dependent time series. Since our concept depends only on ordinal depth information, the resulting values are robust under small perturbations and measurement errors. We emphasize the applicability of our method by analyzing the depth patterns, which are found in seal pubs’ movement. We use our approach in order to choose an appropriate model out of a range of two-dimensional random walks, which are commonly used in mathematical biology.

PMID:42635513 | DOI:10.1063/5.0335659