Tag: statistics

Diabetes Metab Syndr. 2026 Jul 15;20(6):103454. doi: 10.1016/j.dsx.2026.103454. Online ahead of print.

ABSTRACT

BACKGROUND: Metabolic disorders may progress sequentially from fatty liver to hypertension and diabetes, but this cascade has not been well characterised in lean Asian populations. We aimed to quantify this progression and develop practical risk prediction tools in a large longitudinal Japanese cohort.

METHODS: We analysed 75,781 health examination records from 24,718 Japanese adults between 2009 and 2019. Continuous-time multistate modelling quantified transitions across four states: no fatty liver, hypertension, or diabetes; fatty liver alone; fatty liver with hypertension; and fatty liver with hypertension and diabetes. Individual risk prediction tools were developed and internally validated.

FINDINGS: Among 38,858 observed transitions, 2880 were prespecified forward cascade-transition events. Annual transition intensities were 0.699 for state 0 to 1, 0.809 for state 1 to 2, and 0.769 for state 2 to 3, corresponding to a summed mean progression time of 3.97 years. Normal-range body mass index accounted for 1394 cascade events (48.4%), whereas obesity accounted for 238 events (8.3%). The simplified clinical score showed moderate discrimination (C-statistic, 0.63; 95% confidence interval, 0.58-0.68) and good calibration.

INTERPRETATION AND FUNDING: Metabolic disease progressed rapidly and sequentially in this Asian cohort, frequently among adults without obesity. These findings support earlier body mass index-independent metabolic screening and prospective evaluation of shorter surveillance intervals in Asian populations.

PMID:42462329 | DOI:10.1016/j.dsx.2026.103454

Food Chem. 2026 Jul 12;525(Pt 1):150382. doi: 10.1016/j.foodchem.2026.150382. Online ahead of print.

ABSTRACT

Apples are widely recognized for their potential health benefits, partly attributed to their phenolic compounds. However, their impact on human metabolism remains incompletely understood. This study investigated metabolic effects of apple-derived phenolic compounds using untargeted metabolomics approach across multiple biofluids. In a crossover intervention study, 30 healthy men consumed a phenolic-rich apple juice or a placebo for two weeks. Blood, urine and saliva samples were collected before and after each intervention and analyzed by direct infusion ultra-high resolution mass spectrometry. Consumption of apple phenolic compounds resulted in significant alterations of the human metabolome, including increased levels of phenolic-derived degradation products and microbial-associated metabolites across all biofluids. Pathway enrichment analysis revealed pronounced effects on phenylalanine and tyrosine metabolism, as well as linoleic and arachidonic acid metabolism, Overall, these findings demonstrate that apple phenolic compounds induce measurable, microbiota-associated and systemic metabolic changes, providing new insights into their metabolic fate and biological relevance.

PMID:42462304 | DOI:10.1016/j.foodchem.2026.150382

Gynecol Oncol. 2026 Jul 16;211:217-223. doi: 10.1016/j.ygyno.2026.06.027. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the clinical impact of Sentinel Lymph Node (SLN) biopsy in women with preoperative diagnosis of Atypical Endometrial Hyperplasia/Endometrial Intraepithelial Neoplasia (AEH/EIN), focusing on surgical safety and feasibility and adjuvant treatment decisions.

METHODS: Multicenter retrospective study which included 411 patients with preoperative diagnosis of AEH/EIN who underwent total hysterectomy between 2014 and 2025. Demographic, preoperative, surgical, pathological and adjuvant treatment data were collected from prospectively maintained databases and outcomes were compared between patients who underwent SLN biopsy and those who did not. Descriptive statistics were used.

RESULTS: Occult endometrial cancer (EC) was diagnosed in 47% of overall patients at final pathology; of whom 16% was classified within the intermediate to high-risk cases. SLN mapping was associated with slightly longer operative time. SLN metastases were found in 4.7% of patients with EC. SLN assessment modified treatment decisions in 11 of 22 patients (50%) receiving adjuvant therapy within the SLN cohort. Positive SLN findings led to chemotherapy escalation in 5 patients, while negative SLN status supported chemotherapy omission in 6 high to intermediate risk cases. No patients in the non-SLN group received chemotherapy.

CONCLUSION: SLN biopsy in AEH/EIN is a feasible and safe procedure that provides staging information in the subgroup with occult EC. Regardless of metastasis frequency, SLN status provides actionable prognostic information. Whether positive or negative, SLN findings refine risk stratification and may guide the escalation or de-escalation of adjuvant therapy, supporting the consideration of SLN biopsy in AEH/EIN patients.

PMID:42462287 | DOI:10.1016/j.ygyno.2026.06.027

EBioMedicine. 2026 Jul 16;130:106387. doi: 10.1016/j.ebiom.2026.106387. Online ahead of print.

ABSTRACT

BACKGROUND: The determinants of the species barrier preventing human infections with avian influenza A viruses (IAV) are incompletely understood. We previously identified loss-of-function variants of the interferon-regulated antiviral factor MxA as a genetic factor for increased susceptibility to infections with the H7N9 subtype. Given the central role of type I IFNs (IFN-I) in antiviral defence, we hypothesised that IFN-I-neutralising autoantibodies may similarly predispose to zoonotic H7N9 infection.

METHODS: In this observational case-control study, serum samples collected between 2013 and 2017 from 199 Chinese patients with laboratory-confirmed H7N9 infection and 531 healthy, uninfected controls (269 poultry workers, 262 close contacts) were screened for IgG autoantibodies binding IFNα₂, IFNβ_1b, or IFNω using a multiplex bead-based assay. Positive samples were tested for IFN-neutralising activity in a luciferase-based reporter assay. To confirm their ability to block IFNα₂-mediated antiviral activity, selected samples (n = 19) were analysed in IAV infection experiments. Associations between age, sex, H7N9 case status, case fatality, and the presence of neutralising autoantibodies were evaluated by logistic regression. Available whole-genome sequencing data from 26 individuals with neutralising autoantibodies were screened for variants in genes linked to IFN-I autoimmunity.

FINDINGS: Neutralising autoantibodies against at least one IFN-I were detected in 19.1% (38/199) of patients but in only 1.1% (6/531) of controls, consistent with published general population data. Most patient sera targeted IFNα₂ and/or IFNω (35/199), and 18.1% (36/199) neutralised even high IFN-I concentrations of 1-10 ng/ml. The presence of neutralising autoantibodies was associated with 8.2- to 25.3-fold higher odds of H7N9 infection (p < 0.0001), depending on antibody specificity and reference group. Autoantibody prevalence increased significantly with age in patients (44.8% ≥70 years; OR = 1.05; 95% CI 1.02-1.07; p = 0.0001), but was not associated with sex (OR for males vs. females = 0.52; 95% CI 0.23-1.14; p = 0.106). All selected sera containing neutralising autoantibodies blocked IFNα₂-induced antiviral activity in cell culture. No known genetic predisposition for IFN-I autoimmunity was identified.

INTERPRETATION: Our findings suggest that IFN-I-targeting autoimmunity is associated with susceptibility to zoonotic IAV infection with the H7N9 subtype, and possibly also other subtypes, including panzootic H5N1. Given the ease of implementation, screening for anti-IFN-I autoantibodies could be readily integrated into surveillance or targeted testing. This could be relevant in environments with increased exposure to zoonotic IAVs.

FUNDING: Shenzhen Medical Research Fund, National Natural Science Foundation of China, Non-profit Central Research Institute Fund of Chinese Academy of Medical Sciences, Guangdong Provincial Science and Technology Program, Program for Youzuzhikeyan of Shenzhen University, German Research Foundation, Swiss National Science Foundation.

PMID:42462284 | DOI:10.1016/j.ebiom.2026.106387

EBioMedicine. 2026 Jul 16;130:106391. doi: 10.1016/j.ebiom.2026.106391. Online ahead of print.

ABSTRACT

BACKGROUND: Alzheimer’s Disease (AD) is a complex neurodegenerative disorder, with women comprising nearly two-thirds of individuals with AD. However, sex-specific heterogeneity in AD progression remains insufficiently understood. A data-driven approach is needed to characterise such heterogeneity from longitudinal electronic health records (EHRs).

METHODS: We developed a deep learning-based framework to uncover sex-specific AD sub-phenotypes using longitudinal EHRs from OneFlorida+ Clinical Research Consortium. We constructed temporal representations of these EHRs and employed an autoencoder architecture to generate latent embeddings, followed by clustering to derive sex-specific sub-phenotypes with associated progression patterns. We also performed statistical and survival analyses to unravel the characteristics of our identified sub-phenotypes.

FINDINGS: From 1665 individuals with AD (961 females, 704 males), we identified five major sex-specific sub-phenotypes of AD with distinct progression pathways and comorbidity patterns. Female-dominant sub-phenotypes presented later AD onset, longer disease duration, and enrichment of respiratory and neurological disorders. Male-dominant sub-phenotypes exhibited earlier onset, shorter duration, and higher prevalence of endocrine and metabolic conditions. Survival analysis showed significant differences in time to AD onset across sub-phenotypes.

INTERPRETATION: Our findings revealed distinct disease trajectories and comorbidity patterns between male- and female-dominant subgroups with AD. This study provides insight into sex-specific AD progression and demonstrates a data-driven framework for characterising disease heterogeneity using longitudinal EHRs.

FUNDING: This study was supported by grants from the Florida Department of Health, the Centers for Disease Control and Prevention, the National Institute of Environmental Health Sciences, and the NIHNational Center for Advancing Translational Sciences.

PMID:42462283 | DOI:10.1016/j.ebiom.2026.106391

EBioMedicine. 2026 Jul 16;130:106371. doi: 10.1016/j.ebiom.2026.106371. Online ahead of print.

ABSTRACT

BACKGROUND: Benefits from clinical guidelines often only exceed harms after 10 years (payoff time). Based on population norms, guidelines are often discontinued at 75 years of age, but survival likely differs for those with complex chronic disease. We compare estimates based on age alone versus the physiologically based Veterans Ageing Cohort Study-Charlson Comorbidity Index (VACS-CCI) among all patients in care, and among patients with diabetes or HIV.

METHODS: Estimates for patients in care within the US Veterans Health Administration (VHA) with a clinic visit in 2007-17 (followed thru 2021) were compared using C-statistics, Brier Scores, and calibration curves. “Physiological age” was defined as the chronological age at which median VACS-CCI matched US population survival estimates. Among those with 10-year follow-up, we compared percent correctly classified using age ≥75 years vs. VACS-CCI score of ≥42.

FINDINGS: Among 6.6 million (51.4% ≥ 65 years; 25.2% with diabetes; 0.5% with HIV) VACS-CCI improved discrimination over age (Overall C-statistic: 0.81 vs. 0.74; Brier Score 0.239 vs. 0.262). Among 65-year-old males-females, “physiological age” exceeded chronological age by 4.6-3.1 years overall; 8.6-7.8 years for diabetes; and 13.5-11.6 years for HIV. Compared to age ≥75 years, VACS-CCI improved correct classification of survival for 1 in 13.3 overall; 1 in 7.8 with diabetes; and 1 in 6.4 with HIV.

INTERPRETATION: Compared to chronological age alone, VACS-CCI offers an improved method to identify those likely to reach minimum payoff time, especially for those with complex chronic diseases. Use of clinical data to assess “physiological age” could improve healthcare value.

FUNDING: This work was supported by National Institutes of Health NIAAA: P01 AA029545, U24 AA020794 and the Emory Center for AIDS Research (P30AI050409).

PMID:42462282 | DOI:10.1016/j.ebiom.2026.106371

JMIR Form Res. 2026 Jul 16;10:e86214. doi: 10.2196/86214.

ABSTRACT

BACKGROUND: Completion of homework, defined as therapeutic activities assigned between sessions to reinforce skills and promote behavior change, is strongly linked to therapy outcomes. Yet, homework compliance remains low, potentially due to outdated delivery methods such as paper or email. Mobile health technologies may improve engagement by digitizing therapy tasks and tracking progress. Yosa is a mobile health app designed to facilitate homework delivery and enhance engagement between sessions for patients in therapy.

OBJECTIVE: The primary aim of this study was to evaluate the perceived acceptability of Yosa among licensed therapists and individuals currently receiving therapy. A secondary aim was to examine whether key Technology Acceptance Model (TAM) constructs predicted attitudes toward and intention to use Yosa. Qualitative feedback was also collected to inform iterative development and future deployment.

METHODS: Two cross-sectional surveys were conducted: study 1 with licensed therapists (N=45) and study 2 with current therapy patients (N=96). Participants viewed video demonstrations of Yosa, learned about Yosa’s features, and rated the app on TAM constructs, including perceived usefulness, perceived ease of use, perceived risk, attitude toward, and intention to use Yosa, using 0-100 scales. For most constructs, higher scores reflected more favorable evaluations, whereas lower perceived risk scores reflected more favorable evaluations. Descriptive statistics and 95% CIs were generated for each construct in both samples, with scores interpreted relative to the neutral midpoint (50). Multiple regression analyses were conducted to examine predictors of attitude and intention to use. Qualitative feedback from the surveys was analyzed thematically.

RESULTS: Therapists and patients reported generally favorable perceptions of Yosa across TAM domains. Among therapists and patients, ratings of the perceived usefulness of the homework feature, therapy journal, and overall app; perceived ease of use; attitudes toward Yosa; and intention to use were all above the midpoint. Perceived risk scores were mild to moderate in patients and moderate in therapists, respectively. Regression analyses indicated that perceived usefulness was a positive predictor of both attitude toward and intention to use Yosa across therapists and patients, while perceived risk was negatively associated with these outcomes in several models. Qualitative themes included requests for additional features, usability enhancements, and data privacy concerns.

CONCLUSIONS: Therapists and patients reported generally favorable perceptions of Yosa after reviewing descriptions and video demonstrations of the platform, particularly in terms of usefulness and ease of use, supporting favorable perceptions of its potential acceptability as a digital tool for between-session therapy support. Qualitative feedback informed refinements aimed at reducing perceived risks and enhancing the intention to use.

PMID:42462276 | DOI:10.2196/86214

JMIR Res Protoc. 2026 Jul 16;15:e93097. doi: 10.2196/93097.

ABSTRACT

BACKGROUND: The cognitive paradigm in medical education is undergoing a transition from traditional knowledge transmission to learner-centered knowledge construction. In China, this shift is aligned with the Outline of the Plan for the Construction of China into an Education Powerhouse (2024-2035), which mandates high-quality, intrinsic development in nursing curricula. While constructivist learning theory (CLT)-based teaching methods (eg, problem-based learning, case-based learning, and situational simulation) have been widely explored across Chinese nursing institutions, the evidentiary base remains geographically fragmented and methodologically heterogeneous. A systematic synthesis is required to inform national, evidence-based educational reforms.

OBJECTIVE: This protocol describes a systematic review and meta-analysis designed to evaluate the effectiveness of CLT-based teaching methods vs traditional lecture-based models on Chinese nursing students’ theoretical knowledge, practical skills, self-directed learning ability, and critical thinking disposition.

METHODS: A comprehensive systematic search will be conducted across 9 electronic databases: PubMed, Web of Science, the Cochrane Library, Embase, CINAHL, China National Knowledge Infrastructure, Wanfang Data, VIP Database (Chinese Scientific and Technological Journal Database), and China Biology Medicine. The search period spans from database inception to September 27, 2025, with a planned update through June 11, 2026, before final synthesis. Randomized controlled trials and quasi-experimental studies involving Chinese nursing students will be included. Two independent reviewers will screen records, perform full-text assessment, extract data using standardized forms, and code composite CLT interventions, digital or technology-enhanced components, and cluster- or class-based designs using prespecified decision rules. Risk of bias will be assessed using the Cochrane Risk of Bias tool 2 (RoB 2) for randomized trials and the Joanna Briggs Institute critical appraisal tools for quasi-experimental studies. Meta-analysis will be performed using RevMan 5.4 and Stata 18.0, with random-effects models and prespecified subgroup and sensitivity analyses.

RESULTS: This protocol was finalized in February 2026. A preliminary systematic search conducted on September 27, 2025, identified 990 records before deduplication. As of February 6, 2026, deduplication had been completed and title and abstract screening had been initiated. Data extraction, risk-of-bias assessment, and statistical synthesis had not yet started at the protocol stage and will be conducted only after completion of the updated search, final study selection, and full-text eligibility assessment. The final search update was scheduled through June 11, 2026, before data synthesis. The results manuscript will be submitted after completion of all prespecified review steps, with the timeline depending on the number and complexity of newly identified studies.

CONCLUSIONS: This review will provide a robust evidentiary foundation for the strategic deployment of constructivist methodologies in Chinese nursing education, specifically addressing the needs of vocational and undergraduate programs in the era of digital transformation.

PMID:42462270 | DOI:10.2196/93097

J Med Internet Res. 2026 Jul 16;28:e80960. doi: 10.2196/80960.

ABSTRACT

BACKGROUND: Malawi was a pioneer among African countries in implementing a coordinated, government-led effort to streamline COVID-19 support using digital health tools. In response to the pandemic, a COVID-19 WhatsApp chatbot was developed to support the public with information, symptom reporting, and service navigation during the pandemic.

OBJECTIVE: This study describes the national deployment, functionality, and use patterns of the WhatsApp chatbot during the COVID-19 pandemic in Malawi.

METHODS: A retrospective descriptive analysis of chatbot interaction data from May 2020 to May 2023 was conducted. User engagement with key chatbot functions was summarized using descriptive statistics, and time-series analysis was used to compare trends in reported COVID-19 cases with access patterns to the chatbot, the emergency operation call center, and Chipatala cha pa Foni (a national hotline initiative).

RESULTS: The chatbot was accessed 347,117 times, with 70.8% (n=245,895) of validated WhatsApp accesses focused on COVID-19 statistics. Chatbot use patterns showed temporal alignment with COVID-19 case trends, particularly during the first and second pandemic waves and increases observed after lockdown events. Throughout the pandemic, chatbot downtime occurred in 38% (407/1070) of days, with the most prolonged period coinciding with the national vaccine rollout in 2021, during which vaccine-related functionalities were introduced. Following this expansion, the chatbot recorded 198 COVID-19 vaccine-related rumors and 644 accesses to vaccine frequently asked questions. Compared with call-based services, the chatbot recorded higher overall interactions, whereas symptoms were more frequently reported through call center platforms.

CONCLUSIONS: This study provides a descriptive account of the development and use of a national COVID-19 WhatsApp chatbot in Malawi. The findings highlight patterns of information-seeking behavior, variation in feature use, and the influence of system availability on engagement. These insights may inform the design, implementation, and sustainability of digital health communication tools in similar settings.

PMID:42462223 | DOI:10.2196/80960

JMIR Med Inform. 2026 Jul 16;14:e82230. doi: 10.2196/82230.

ABSTRACT

BACKGROUND: Effective risk stratification in sepsis remains a critical clinical challenge. Serum lactate is a cornerstone biomarker of metabolic dysfunction, yet its predictive limitations-particularly in patients without severe hyperlactatemia-are well recognized. The lactate-to-albumin ratio (LAR), a composite mixed-unit index integrating markers of acute metabolic dysfunction and systemic inflammation, has emerged as a promising predictor; however, its incremental discriminative advantage over lactate had not been formally tested in a large multicenter cohort using paired statistical methodology.

OBJECTIVE: This study aims to determine whether LAR provides statistically significantly higher prediction of 28-day mortality than lactate alone in adult intensive care unit (ICU) patients with sepsis, using threshold effect analysis, restricted cubic splines, DeLong test, and 9 interpretable machine learning models.

METHODS: We conducted a retrospective analysis of 3637 adult patients with sepsis from the multicenter eICU Collaborative Research Database (eICU-CRD; 208 hospitals, United States, 2014-2015). The primary outcome was 28-day all-cause in-hospital mortality among patients surviving the initial 48-hour ICU admission period. We used multivariable logistic regression (LR), Cox proportional-hazards regression, threshold effect analysis, restricted cubic spline modeling, DeLong test for area under the receiver operating characteristic curve (AUC) comparison, and machine learning models evaluated with Shapley additive explanations (SHAP) for interpretability. The cohort was divided 70/30 (stratified) into training and held-out test sets; the Synthetic Minority Oversampling Technique was applied exclusively within the training partition to prevent data leakage.

RESULTS: LAR consistently demonstrated stronger and more stable associations with mortality than lactate across all subgroups. DeLong test confirmed statistically significantly higher AUC for LAR: 28-day hospital mortality (AUC_LAR=0.646, 95% CI 0.623-0.670 vs AUC_lactate=0.617, 95% CI 0.593-0.641; Z=6.37; P<.001; ΔAUC=0.029) and 28-day ICU mortality (AUC_LAR=0.642 vs AUC_lactate=0.621; Z=3.71; P<.001). A nominally significant Acute Physiology and Chronic Health Evaluation IV (APACHE IV) × LAR interaction (hospital mortality, P for interaction=.02) indicated stronger LAR prognostic effects in lower-severity patients (APACHE IV≤70), representing within-biomarker effect modification requiring prospective validation. Among 9 machine learning models for ICU mortality, LR, random forest (RF), and gradient-boosting decision tree (GBDT) achieved the 3 highest AUCs (0.727, 0.726, and 0.725); Light Gradient Boosting Machine (LightGBM) demonstrated the best calibration (Brier score 0.096, the only model below the null Brier of 0.101 at the natural prevalence of 11.4%); GBDT achieved the highest precision-recall AUC (0.293). SHAP identified LAR among the top 10 predictive features in 3 of 4 models for hospital mortality (RF rank 4, LR rank 7, and LightGBM rank 8) and 1 of 4 for ICU mortality (RF rank 4).

CONCLUSIONS: LAR demonstrates statistically significantly higher discrimination than lactate alone for 28-day sepsis mortality prediction. LAR may offer greater prognostic utility in patients without severe hyperlactatemia, a population in whom early risk stratification may be particularly relevant.

PMID:42462220 | DOI:10.2196/82230