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PubMed2026

An Assessment of Reliability Estimation Methods for Binomial Health Care Quality Measures.

We evaluated the performance of commonly used methods for estimating the reliability of binomial health care quality measures using simulated datasets spanning a range of performance score means and variances, numbers of entities, and patient sample sizes. For each simulation, reliability was estimated for all selected methods and compared with the known true reliability derived from the simulation parameters, with methods assessed on their accuracy and precision. Logistic regression with reliability estimated on the outcome scale demonstrated the highest accuracy and precision among all methods evaluated. The widely used Adams beta-binomial method performed poorly, although a modification recommended by Nieser and Harris substantially improved its performance. These approaches are applicable only to binomial measures. Among methods that can be applied to both binomial and continuous measures, permutation resampling of the Spearman rank correlation coefficient was the most accurate and precise, outperforming other commonly used approaches. Overall, for binomial quality measures, logistic regression on the outcome scale is the preferred method for reliability estimation, followed closely by the modified beta-binomial approach, while for non-binomial measures, permutation-based Spearman rank correlation appears to be the most suitable method.

Reproducibility of Results↗

PubMed2026

Re-evaluating pediatric laryngoscope blade size recommendations: Comparable intubation performance across blade sizes in pediatric manikin models.

BACKGROUND: Pediatric airway management traditionally emphasizes strict adherence to age-based laryngoscope blade size recommendations, despite limited empirical validation. OBJECTIVES: To evaluate whether intubation performance varies across a range of blade sizes, and whether a Macintosh 2 blade performs comparably across multiple pediatric age groups in a simulation setting. METHODS: We conducted a randomized crossover simulation study using three pediatric airway manikins (neonate, infant, and child age groups). Emergency medicine residents and faculty physicians performed intubations using multiple laryngoscope blade types and sizes, including standard and nonstandard options. Primary outcomes were intubation time and first-attempt success. Secondary outcomes included complications and operator-rated ease of glottic view and tube passage. Between-blade differences were estimated with 95% confidence intervals. RESULTS: Across manikin sizes and blade types, intubation times were short and first-attempt success rates exceeded 98% in most conditions. Performance remained consistent even with blade sizes outside conventional age-based recommendations. Between-blade differences in intubation time were small, and complication rates were low across conditions. The Macintosh 2 blade performed comparably across all manikin sizes, with similar intubation times, high success rates, and favorable ease ratings. CONCLUSIONS: Intubation performance in pediatric manikin models was similar across a wide range of blade sizes. These hypothesis-generating findings warrant prospective clinical evaluation of simplified blade selection strategies for pediatric intubation.

Manikins↗

PubMed2026

Cost-Effectiveness of Electronic Patient-Reported Outcome Measure Interventions in Cancer: Systematic Review and Parameter Extraction for Economic Modeling.

BACKGROUND: Complex digital interventions that integrate electronic patient-reported outcome measures (ePROM) into clinical practice in cancer have the potential to improve quality of life, increase survival, and reduce health resource use and costs. Such systems can help patients with cancer self-manage chemotherapy symptoms, reduce clinicians' workloads through automated decision support, and resolve problems earlier. However, more research on the cost-effectiveness of ePROM monitoring is needed. OBJECTIVE: This paper comprises two complementary components: (1) a systematic literature review summarizing and evaluating the quantitative and qualitative evidence related to the cost-effectiveness of ePROM monitoring and (2) a health economic model parameter extraction. We also conducted supplementary targeted searches and scoping to provide context to our findings. METHODS: We searched Ovid (including MEDLINE and Embase), Scopus, and the International Health Technology Assessment Database for original English-language papers published on or before March 2025 using search strings that combined terms related to ePROMs, health economics, and cancer/oncology. We included papers reporting health economic-related outcomes for ePROM interventions designed for adult cancer populations and excluded screening tools and conference abstracts. RESULTS: We included 34 publications from 27 unique studies and identified and analyzed 26 ePROM-integrated interventions within these. Most (23/26) of the included interventions explicitly described some form of alert handling and automated decision support based on remote ePROM monitoring. Of the 34 publications, 5 presented full cost-effectiveness analysis results, of which 3 were highly uncertain and lacked clear differences in costs and health outcomes between ePROMs and standard care; conversely, 2 presented strong evidence of cost-effectiveness due to quality-of-life improvements, reduced hospitalizations, and potentially more autonomy in health-related travel (eg, ePROM-monitored patients can drive or walk to the hospital instead of using taxis or ambulances). A further 5 publications reported partial health economic results (eg, cost-consequence and budget impact), of which 1 detected no difference in strategies; in contrast, 4 reported lower health resource use and costs of ePROMs, mainly due to hospitalization reductions. Overall, 12 of the 27 studies included a qualitative component but mostly focused on user experience and design-related themes; only 2 of these addressed economic-specific themes (eg, changes in workflow and resource use due to ePROM implementation and integration), indicating some potential for time saving due to ePROM monitoring. CONCLUSIONS: Some ePROM-integrated interventions demonstrated cost-effectiveness in cancer care, but the evidence base remains limited. Where evidence does exist, cost-effectiveness appears driven by reduced hospitalization and improved quality of life. Qualitative research within the included studies rarely addressed economic questions. We provide a detailed parameter extraction for use in future economic modeling and recommend research priorities, including quantitative mapping of ePROM symptom data onto health resource use patterns, and qualitative work exploring how ePROM implementation affects clinical workloads and patient-perspective costs.

Humans↗

PubMed2026

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 × 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (β=0.087; P=.003), injunctive norms (β=0.078; P=.009), perceived susceptibility (β=0.051; P=.03), perceived benefits (β=0.253; P<.001), and trust (β=0.33; P<.001), and negatively associated with perceived severity (β=-0.047; P=.049) and privacy concerns (β=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans↗

PubMed2026

Assessment of Genetic Diversity and Population Structure on Azadirachta indica A. Juss. in an Urban Metropolitan: Ahmedabad, India.

Azadirachta indica (A. indica) A. Juss., commonly known as Neem, is a valuable multipurpose tree with profound medicinal properties and socioeconomic importance, widely recognized since ancient Ayurvedic times. Despite its prominence, knowledge about its genetic diversity within the metropolitan area of Ahmedabad is limited. This study marks the first in-depth exploration of the genetic diversity and population structure of A. indica in Ahmedabad. The authenticity of the species was validated through DNA barcoding, and a Geographical Information System (GIS) was used to collect the samples. A total of 35 A. indica accessions were analyzed using five Inter Simple Sequence Repeat (ISSR) primers. Genetic diversity and population structure were evaluated using Inter Simple Sequence Repeat (ISSR) markers through polymorphism assessment, clustering, ordination, and Bayesian population structure analyses. ISSRs revealed a high level of polymorphism (75.66%), indicating substantial genetic variability among accessions. An analysis of genetic diversity indices revealed low to moderate diversity (Hs = 0.14, Ht = 0.217, I = 0.217). Analysis of Molecular Variance (AMOVA) analysis depicted 81% variation within the population and 19% among the population. Low to moderate genetic differentiation (Gst = 0.319) and moderate gene flow (Nm = 1.06) indicated that urban development has not hindered gene flow among populations. Mantel's test revealed a weak but significant correlation between genetic and geographic distances, suggesting limited isolation by distance. The estimated ΔK using STRUCTURE exhibited two subpopulations, representing two gene pools for A. indica accessions (K = 2). Collectively, these patterns indicate that urbanization has not severely disrupted genetic connectivity in A. indica, reflecting its resilience and adaptive potential in a metropolitan environment. These findings provide pivotal knowledge for further understanding the genetic diversity and population structure of A. indica in one of the fastest-growing cities in India, which can be utilized for new breeding programmes, sustainable development and future conservation strategies around the globe.

India↗

PubMed2026

Liver Cancer Risk and Incidence Attributable to Human Immunodeficiency Virus: A Meta-Analysis and Population-Attributable Modeling Study of Over 1.2 Million Individuals.

HIV-induced immune suppression and chronic inflammation elevate the risk of cancer progression. We conducted a systematic review and meta-analysis of studies published between January 1, 1984 and October 13, 2023 to assess the association between HIV infection and liver cancer. People living with HIV (PLHIV) had a higher risk (pooled relative risk = 3.36, 95% CI: 2.72-4.15). The global PAF for HIV-attributed liver cancer was 1.43% in 2019, with a three-fold increase over the past 30 years. The Asia-Pacific region recorded the second highest new cases of HIV-attributed liver cancer in 2019, and the highest age-standardized incidence rate (ASIR) in Eastern and Southern Africa. Particularly, the ASIR of HIV-attributed liver cancer increased rapidly in Eastern Europe and Central Asia, with the highest estimated annual percentage change reaching 22.98%. PLHIV have an increased risk and incidence of liver cancer. In regions with high burden of HIV-attributed liver cancer, it is essential to integrate prevention and effective treatment for HIV, viral hepatitis, alcoholic liver disease, nonalcoholic steatohepatitis, and liver cancer.

Humans↗

PubMed2025

Coupling of spectroscopy and nitrogen-oxygen isotopes unveils the mechanisms of dissolved organic matter and nitrate pollution in lakes within the agro-pastoral transition zone.

Lakes in arid and semi-arid regions are subjected to severe ecological stress, such as organic pollution, eutrophication, and salinization, due to climate change and human activities. This study investigates Chagannur Lake, a typical arid-region lake that is representative and ecologically sensitive in Northern China's agro-pastoral ecotone, to uncover its pollution characteristics and mechanisms. We employed fluorescence spectroscopy and stable isotope analysis to trace dissolved organic matter (DOM) and nitrate sources. The DOM composition was dominated by microbial metabolic byproducts and protein-like substances, suggesting that microbial processes are key to organic matter transformation. Source apportionment revealed that pollutants primarily originated from livestock and poultry manure (37.6 %), agricultural fertilizers (35.6 %), and soil erosion (24.7 %), with agricultural fertilizers contributing most significantly in the Gogstai River (63.3 %). A structural equation model (SEM) coupling spectral and mass spectrometric data revealed that microbial transformation significantly impairs the lake's self-purification capacity, thereby promoting pollutant accumulation (path coefficient = 0.91,*p < 0.05). Moreover, microbial processes link endogenous and exogenous pollution, a mechanism effectively traced by isotopic and fluorescence indices (path coefficient = 0.55, ⁎⁎p < 0.01). These findings enhance the understanding of pollution sources and transformation mechanisms in arid-region lakes and offer foundational theoretical support for policymakers engaged in pollution control strategies.

Lakes↗

PubMed2026

Spinal meningiomas: histopathological grading using a benchmark radiomics model with notes on disease control.

OBJECTIVE: Spinal meningiomas (SMs) are common primary spinal tumors for which surgery is considered the first-line treatment when safe and feasible. The ability to extrapolate the tumor grade from preoperative imaging may significantly inform early patient expectation-setting regarding recurrence. Building on radiomics studies in cranial meningiomas, the authors aimed to construct a benchmark radiomics model to preoperatively identify the histological grade of SMs. METHODS: Institutional surgical records from May 2012 to November 2025 were queried for pathology-confirmed meningiomas below the foramen magnum, with preoperative contrast-enhanced imaging available for segmentation. SMs were classified as low-grade (WHO grade 1) and high-grade (WHO grade 2 tumors and grade 1 tumors with atypia). Tumors were manually segmented, and features were extracted using the PyRadiomics software package. An ensemble model of k-nearest neighbors, random forest, and support vector machine classifiers was trained using nested cross-validation on a subset of 10 features to differentiate tumor grades. Clinical data for the cohort were also extracted, and disease control in an adjunctive clinical series was assessed. RESULTS: Seventy-four patients were included in radiomics analysis, with an area under the receiver operating characteristic curve of 0.879 and a mean F1 score of 0.748. The model's top 5 features were all texture features that differed significantly (p < 0.05) across low- and high-grade SMs. These included measures of tumor textural and contrast-enhancement heterogeneity, with overlap with features reported in radiomics models for histological grading of intracranial meningiomas. Fifty-five patients with a median radiographic follow-up of 22.2 (range 1.9-86.4) months remained for clinical analysis after exclusion of patients with less than 1 month of follow-up and syndromic meningiomas. Four recurrences occurred at a median of 20.8 (range 1.8-41.8) months. High-grade tumor pathology did not significantly impact progression-free survival (p = 0.682, log-rank test; Cox regression high vs low grade hazard ratio [HR] 0.62, 95% CI 0.06-6.11, p = 0.685). Subtotal resection was associated with poorer progression-free survival than gross-total resection (p = 0.004, log-rank test; Cox regression subtotal vs gross-total resection HR 10.62, 95% CI 1.46-77.05, p = 0.019). These findings remain contextualized within a relatively limited follow-up window and small recurrence event count, suggesting a need to characterize the interplay between tumor grade and extent of resection as drivers of local disease control in SMs. CONCLUSIONS: A preoperative radiomics model can stratify high-grade SMs using open-source tools applied to single-institution data.

Humans↗

PubMed2026

Systematic evaluation of one-dimensional-to-two-dimensional near-infrared spectroscopy transformations with deep learning for quantifying coconut sap adulteration.

Near-infrared (NIR) spectroscopy have limitations when combined with deep learning (DL) algorithms because they rely on low-dimensional datasets. Therefore, we investigated the potential of transforming one-dimensional (1D) NIR spectra into two-dimensional (2D) spectrograms using synchronous and asynchronous techniques and the continuous wavelet transform (CWT) and their effectiveness by integrating with DL for detecting adulteration in coconut sap. NIR spectra (12,500-4000 cm-1) were collected from binary mixtures (0%-100%;w/w). The performance of all DL (convolutional neural networks-CNN, AlexNet and ResNet) models was compared with that of partial least squares (PLS). The models were ranked in the mentioned order based on their performances: 2D-CWT > 2D-asynchronous > 2D-synchronous > 1D/2D-PLS. The important features of the best model can be explained and visualized using gradient-weighted-class-activation-mapping. The findings highlight that the 1D-to-2D NIR data transformation combined with DL is a highly robust approach because it addresses the feature representation gap in NIR data and effectively captures the spatial-spectral correlations.

Spectroscopy, Near-Infrared↗

PubMed2026

Differential contributions of mt-Tr and Cs variants to developmental cochlear defects and mitochondrial dysfunction in A/J mice.

A/J mice exhibit early-onset hearing loss linked to Cdh23, mitochondrial tRNA-Arg (mt-Tr), and citrate synthase (Cs) variants. Although developmental cochlear defects have been identified in juvenile A/J mice, the hierarchical contributions of mt-Tr versus Cs remain unclear. Using reciprocal intercross-derived strains to decouple mitochondrial haplotypes from nuclear factors, we demonstrate that the mitochondrial background is the primary determinant of auditory dysfunction. Mice with A/J mtDNA (AXB strains) displayed significantly higher ABR thresholds, accelerated hair cell attrition, and severe stereocilia dysmorphology compared to those with B6 mtDNA (BXA strains), occurring largely independently of the Cs genotype. While the Cs mutation exacerbated hearing loss, its impact was secondary to that of the dominant mitochondrial background. Systemic behavioral assessments and mitochondrial assays confirmed that A/J mitochondria exert a more profound metabolic impact than the Cs mutation. Our findings establish that the mitochondrial genomic background, with the mt-Tr locus as a prominent candidate variant, serves as the principal driver of developmental cochlear defects and early-onset hearing loss in A/J mice, while the nuclear Cs mutation acts as a synergistic modifier. This study underscores the critical role of mitonuclear crosstalk in inner ear maturation and provides new insights into the etiology of hereditary hearing loss.

Animals↗

PubMed2026

Occupationally relevant vibrations and the brain: frequency-dependent proteomics signatures in a rat model.

INTRODUCTION: Occupational exposure to whole-body vibration (WBV), particularly in agricultural environments, has been associated with adverse cognitive and physiological effects. This study examined the neurophysiological impact of WBV in a rat model at 4 Hz and 30 Hz, frequencies representative of off-road and on-road vehicle operation. METHODOLOGY: Forty-four Sprague-Dawley rats were assigned to control (0 Hz), low-frequency (4 Hz), or high-frequency (30 Hz) vibration conditions. After three days of exposure, brain tissues were collected and analyzed using mass spectrometry-based proteomics to identify differentially expressed proteins. RESULTS: Proteomic profiling revealed distinct, frequency-dependent alterations in brain protein expression. Compared with controls, 32 cognition-related proteins were differentially regulated at 4 Hz and 29 at 30 Hz, with 13 differing between the two vibration conditions. Principal component analysis showed clear separation among groups, indicating unique proteomic signatures for each exposure frequency. Functional enrichment and protein-protein interaction analyses demonstrated involvement of synaptic plasticity, cytoskeletal organization, calcium regulation, and neurotransmitter release. Exposure to 4 Hz was associated with the upregulation of proteins involved in calcium homeostasis and synaptic integrity, suggesting potential disruption of cognitive processes. In contrast, 30 Hz increased the expression of proteins related to axonal guidance and neuroprotection, indicating a less clearly adverse response that may reflect adaptive or potentially beneficial effects. DISCUSSION: These findings provide new insight into biological mechanisms underlying WBV-induced cognitive changes and underscore the importance of vibration frequency in shaping neurophysiological outcomes. They also establish a foundation for future studies integrating proteomics with behavioural assessments in animals and humans.

Animals↗

PubMed2026

Triazole resistance in clinical Aspergillus fumigatus isolates in India, a multicenter surveillance study.

BACKGROUND: Triazole resistance in Aspergillus fumigatus is a global public health concern associated with treatment failure, notably in invasive aspergillosis. However, population-level data on triazole resistance from India remain limited, with most reports originating from single-center studies. METHODS: We conducted a multicenter surveillance study to assess the prevalence of triazole resistance among clinical A. fumigatus isolates across India. Antifungal susceptibility testing was performed using the CLSI broth microdilution method (M38-Ed3), and molecular characterization was conducted on resistant isolates. A total of 518 isolates were analyzed: 115 prospectively collected from 13 tertiary-care hospitals from 2015-2020, and 403 archived isolates obtained from the National Culture Collection of Pathogenic Fungi (1994-2020). RESULTS: The overall pooled prevalence of non-wildtype isolates was 4.1% for itraconazole (95% CI: 2.54-6.17%), 3.9% for posaconazole (95% CI: 2.39-5.94%), while 1.4% were resistant to voriconazole (95% CI: 0.55-2.77%). One multi-azole-resistant isolate from an immunocompromised, mold-active triazole-naïve patient carried the TR34/L98H mutation, suggesting environmental acquisition. Prevalence of resistance did not differ significantly across geographic regions or between public and private sector hospitals. Linear regression analysis revealed a significant temporal increase in median MICs of all three licensed triazoles between 1994 and 2020. Approximately 29% of isolates exhibited amphotericin B MICs exceeding the epidemiological cutoff value; however, the clinical significance of this finding remains uncertain. CONCLUSIONS: Azole resistance among clinical A. fumigatus isolates in India remains uncommon (<5%), supporting the continued use of triazoles as first-line therapy. However, the observed temporal increase in triazole MICs underscores the need for sustained national surveillance to detect emerging resistance trends.

Aspergillus fumigatus↗

PubMed2026

Can ChatGPT Replace Human Clinical Coders? A Comparative Study in Otology Billing.

OBJECTIVE: Evaluate the utility of the large language model (LLM), ChatGPT, for the analysis of operative notes and the generation of Current Procedural Terminology (CPT) codes in comparison to human clinical coders. STUDY DESIGN: CPT billing codes assigned by ChatGPT were compared to existing billing data. Otology practice within a tertiary academic center. METHODS: About 191 operative notes from a single surgeon (9/2022-10/2023) were analyzed. ChatGPT-3.5 and 4 models were prompted for CPT codes based on operative notes. Assessment included determining exact and partial match rates, sensitivity and specificity for targeted procedures, and work Relative Value Units (wRVU) differences between ChatGPT-generated and human-assigned codes. RESULTS: ChatGPT-3.5 achieved exact matches in 22% of cases and partial matches in 32%, while ChatGPT-4 achieved 14% exact and 33% partial matches. When cochlear implantation (CI) was excluded, performance dropped significantly. For CI, ChatGPT-3.5 demonstrated a sensitivity of 94% and specificity of 90%, while ChatGPT-4 showed a sensitivity of 96% and specificity of 92%. In contrast, performance on cartilage grafting was poor, with sensitivities of 4.2% for ChatGPT-3.5 and 0% for ChatGPT-4. ChatGPT-3.5 and 4 showed moderate CPT code matching accuracy among themselves, with slight agreement to human coders. Both models tended to underbill for wRVUs compared to human coders, with significant differences in the values generated. CONCLUSION: This study assessed ChatGPT's effectiveness in automating CPT code assignment for otologic surgeries. While the models achieved high sensitivity values for assigning codes related to cochlear implantation, both models struggled with complex cases, failed to apply modifiers, and often assigned fewer wRVUs. The findings highlight ChatGPT's potential in medical billing but indicate a need for further refinement.

Humans↗

PubMed2026

Real-world clinical utility of exome sequencing in pediatric drug-resistant epilepsy: Experience from a tertiary center in Thailand.

BACKGROUND: Genomic testing has increasingly contributed to the diagnosis and management of pediatric drug-resistant epilepsy (DRE), particularly in patients with suspected genetic etiologies. This study evaluated the diagnostic yield and real- world clinical utility of whole-exome sequencing (WES) in children with DRE. METHODS: Children with DRE and seizure onset before 15 years of age were enrolled between January 2020 and December 2023. Clinical data, including demographics, seizure characteristics, developmental history, electroencephalography (EEG), brain magnetic resonance imaging (MRI), and prior investigations, were reviewed. WES was performed in all probands and, when available, their parents. Variants were interpreted according to standard guidelines. Clinical utility and 1-year seizure and developmental outcomes were assessed from follow-up records. RESULTS: Fifty-six patients (23 males, 33 females) were included. The median age at seizure onset was 1 year (interquartile range [IQR] 0.3-4 years), and 96.4% had developmental comorbidities. Pathogenic or likely pathogenic variants were identified in 39% (22/56), with the highest diagnostic yield in children with seizure onset before 3 years of age. Channelopathies accounted for most genetically solved cases (68%), predominantly involving sodium channel genes. Genetic diagnoses provided clinical utility in 73% (16/22) of solved cases by guiding treatment and precision management. At 1-year follow-up, genetically solved patients showed more favorable seizure and developmental outcomes than those with genetically unsolved patients. CONCLUSION: WES achieved a 39% diagnostic yield and substantial clinical utility in pediatric DRE, particularly in early-onset and channelopathy-related disorders. These findings support early molecular diagnosis to facilitate genotype-informed management in appropriately selected children. However, the more favorable developmental and seizure outcomes observed in genetically solved patients should be interpreted with caution, as they may have been influenced by multiple factors beyond genetic diagnosis. In resource-limited settings, careful clinical phenotyping remains essential for treatment decisions and for prioritizing children for genomic testing.

Clinical utility↗

PubMed2026

Machine learning-based prediction of unplanned readmission and construction of an online calculator for elderly patients with mild ischemic stroke.

OBJECTIVE: To screen for independent risk factors for unplanned readmission in elderly patients with mild ischemic stroke, and to construct and validate an online risk prediction calculator based on an interpretable machine learning model, thereby providing a promising practical tool for accurate clinical assessment of 30‑day all‑cause unplanned readmission risk in this population. METHODS: A prospective cohort study was conducted, including 1050 patients aged ≥ 60 years with mild ischemic stroke admitted between August 2023 and September 2024. Participants were randomly divided into a training set (840 cases) and a test set (210 cases) at a ratio of 8:2. Risk factors were screened by univariate analysis and multivariable Logistic regression. Four machine learning models, namely LightGBM, XGBoost, Random Forest, and K‑Nearest Neighbors (KNN), were developed and their performance was evaluated using AUC, accuracy, sensitivity, and specificity as metrics. The SHAP framework was used for interpretability analysis, and an online calculator was subsequently developed based on the optimal model. RESULTS: Univariate analysis showed significant differences (P < 0.05) in 13 factors including age, smoking, AIP, TyG index, HALP score, etc. Multivariable Logistic regression identified age (OR = 9.752), smoking (OR = 5.171), AIP (OR = 6.691), TyG index (OR = 4.393), HALP score (OR = 2.831), and ≥ 2 comorbidities (OR = 3.664) as independent risk factors. All four machine learning models demonstrated good predictive performance. Based on a comprehensive evaluation of multiple metrics and computational efficiency, the LightGBM model exhibited the best predictive performance (AUC = 0.884, accuracy = 0.829, sensitivity = 0.812, specificity = 0.875). SHAP analysis showed that age, AIP, TyG index, smoking, and HALP score were key predictors. An online calculator developed based on this model enables individualized risk predictions. CONCLUSION: Key risk factors associated with 30‑day unplanned readmission in elderly patients with mild ischemic stroke were identified. The LightGBM model demonstrated high predictive accuracy, and together with the interpretability analysis and online calculator, offers a practical tool to support clinical risk assessment. However, this tool requires future external validation.

Humans↗

PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗

PubMed2026

Characteristics of p53 and Smad4 immunohistochemistry in pancreatic ductal adenocarcinoma and validation by next-generation sequencing.

BACKGROUND: Mutations in four major driver genes -KRAS, CDKN2A, TP53, and SMAD4- are central to the pathogenesis of pancreatic ductal adenocarcinoma (PDAC) and critically inform diagnosis, therapeutic decision-making, and prognostic assessment. Although next-generation sequencing (NGS) is widely regarded as the gold standard for detecting these mutations, its clinical application is often limited by suboptimal analytical efficiency and substantial economic cost. Among these genes, immunohistochemical (IHC) staining for the proteins encoded by TP53 and SMAD4 has been extensively adopted in routine pathology practice. However, standardized IHC pattern classification schemes and rigorous validation of their predictive accuracy for underlying genomic alterations remain lacking in PDAC. METHODS: We retrospectively enrolled 63 PDAC patients and systematically characterized the typical IHC expression patterns of p53 and Smad4. Targeted NGS was subsequently performed on all available tumor specimens, and the resulting mutational profiles were correlated with corresponding IHC findings. Diagnostic performance including sensitivity, specificity and accuracy of p53 IHC for predicting TP53 mutations and of Smad4 IHC for predicting SMAD4 mutations was rigorously evaluated. RESULTS: Among the four canonical driver genes, co-occurring double- or triple-gene mutations were prevalent; within TP53 and SMAD4, missense mutations constituted the most frequent variant type. Using NGS as the reference standard, we validated the diagnostic utility of a three-tiered p53 IHC classification system, particularly in fine-needle biopsy (FNB) specimens. Furthermore, we proposed a novel, refined Smad4 IHC pattern classification that incorporates an "intermediate" category, thereby expanding upon conventional binary interpretation. This new scheme achieved markedly improved mutation prediction accuracy (0.76) compared with traditional approaches (0.57). CONCLUSION: Our study highlights the complementary diagnostic value of p53 and Smad4 IHC relative to molecular testing in PDAC, especially when tissue is limited, as commonly encountered in FNB specimens. The newly established Smad4 IHC classification system, which integrates an intermediate expression category into the conventional two-tier framework, demonstrates superior clinical utility and enhances predictive accuracy for SMAD4 genomic alterations.

Humans↗

PubMed2026

A systematic review and network meta-analysis of single nucleotide polymorphisms associated with oral submucous fibrosis risk.

BACKGROUND: Oral submucous fibrosis (OSF) is a chronic and insidious oral disease characterized by hyalinization of the subepithelial connective tissue and progressive fibrosis of the oral submucosa. It is a precancerous condition of oral squamous cell carcinoma. Studies have demonstrated that single nucleotide polymorphisms (SNPs) are closely associated with susceptibility to OSF. This study aims to comprehensively evaluate the association between SNPs and OSF risk and to rank the strength of the association between different genetic models and OSF susceptibility. METHODS: Literature related to OSF was comprehensively searched from PubMed, Web of Science, Embase, Cochrane Library, CNKI, and Wangfang databases up to July 2025. Full-text case-control studies with patients diagnosed with OSF were included. Quality assessment was performed to evaluate the risk of bias. RevMan 5.4, GeMTC 0.14.3, and STATA 17.0 were used for the pairwise and Bayesian network meta-analysis. RESULTS: A total of 24 studies with 2545 cases and 3772 controls, covering 13 SNPs in 11 genes, were included in our meta-analysis. We found that CYP1A1 rs4646903:T>C, CYP1A1 rs1048943:A>G, GSTT1 null genotype, GSTM1 null genotype, and XRCC3 rs861539:C>T were associated with an increased risk of OSF, while MMP2 rs243865:C>T and MMP3 rs3025058: 5A>6A were associated with a decreased risk of OSF. Further Bayesian network meta-analysis indicated the top 5 genetic models with the highest association with OSF risk in network group 1 were the dominant model, homozygous model, allelic model, and recessive model of CYP1A1 rs1048943:A>G (ranked 1-4), and the heterozygous/dominant model of CYP1A1 rs4646903:T>C (both ranked 5). While the allelic models of XRCC3 rs861539:C>T and MMP3 rs3025058: 5A>6A ranked first for predicting OSF in group 2 and group 3, respectively. CONCLUSION: Some specific SNPs are significantly related to the risk of OSF. Among them, the dominant model of CYP1A1 rs1048943:A>G may be the most strongly associated genetic model with OSF risk. Future large-sample, well-designed studies with detailed genotype data are needed to validate the roles of these SNPs in OSF risk.

Humans↗