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PubMed2026

Toward personalized interventions for preventing depression in primary care: Qualitative and quantitative findings from the e-predictD pilot study.

BACKGROUND: The predictD intervention, delivered by family physicians (FPs), has demonstrated effectiveness and cost-efficiency in preventing depression and anxiety. The e-predictD study aims to design, develop, and evaluate a novel personalized intervention for depression prevention by integrating information and communication technologies (ICTs), risk prediction algorithms, and decision support systems (DSS) for both patients and FPs. OBJECTIVE: To evaluate the satisfaction, usability, and acceptability, of a beta version of the e-predictD intervention in primary care settings. METHODS: The e-predictD intervention follows a biopsychosocial approach, including an initial patient-FP interview, specific FP training, and an app. A β-version was tested in a pilot study without a control group over three months. The app integrates a validated depression risk prediction algorithm, decision algorithms, and a monitoring system supporting the DSS. The DSS generates a personalized prevention plan (PPP) from eight intervention modules: physical exercise, social relationships, problem-solving, communication skills, decision-making, assertiveness, sleep improvement, and cognitive restructuring. Patients and FPs discussed the PPP in a 15-minute baseline interview, selecting modules for implementation over three months. Semi-structured interviews gathered feedback. Assessments included depression (PHQ-9), anxiety (GAD-7), quality of life (SF-12), and major depression risk (predictD algorithm). RESULTS: Six FPs from six Spanish cities enrolled 56 non-depressed patients at moderate-to-high risk of depression; 47 (84%) completed follow-up. The app was used for a median of six days (interquartile range: 1-30). Both FPs and patients expressed satisfaction, leading to incorporated improvements. After three months, significant reductions in major depression risk and anxiety symptoms were observed, alongside improved mental quality of life. However, no significant changes were found in depressive symptoms or physical quality of life. CONCLUSION: This pilot study supports the feasibility and acceptability of the e-predictD β-version, despite lower-than-expected app usability. Health improvements were observed, warranting confirmation in a randomized controlled trial. TRIAL REGISTRATION: ClinicalTrials.gov NCT03990792.

Adult↗

PubMed2026

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans↗

PubMed2026

A risk-need-responsivity (RNR)-informed systematic review of needs during the pretrial period.

OBJECTIVE: Pretrial risk assessments are becoming increasingly popular in the United States. Despite the importance of assessing and intervening around "needs" in the risk-need-responsivity model, few pretrial risk assessments include comprehensive assessment of needs. We aim to provide a systematic review of the prevalence of and predictive utility of needs within the pretrial population. HYPOTHESES: There were no hypotheses given the nature of the study. METHOD: We conducted searches for articles in the EBSCO, ProQuest, and Google Scholar databases using key words related to 11 needs domains: antisocial personality, procriminal attitudes, procriminal associates, substance use, family/marital relationships, school/work, prosocial recreational activities, self-esteem, housing, mental health, and physical health. We identified 215 articles that reported on the prevalence of needs or explored their predictive associations with pretrial misconduct outcomes in adult populations. RESULTS: Overall, we find few comprehensive investigations of needs in the pretrial domain, apart from substance use. Variation in methodology and operationalization contributes to wide variability in prevalence estimates. We found only 15 articles that examined predictive associations between pretrial needs and outcomes, which were limited to investigations of behavioral health, employment, and housing needs. Substance use and housing needs emerged as the only consistent predictors of pretrial misconduct. CONCLUSIONS: Researchers should more directly assess the prevalence and predictive utility of needs within the pretrial period to bolster the evidence base for including these factors in pretrial risk assessments. (PsycInfo Database Record (c) 2026 APA, all rights reserved).

Humans↗

PubMed2026

Trade-offs in avian parental care: a review of theory and meta-analysis of brood size manipulations.

The selective forces shaping parental care have been studied for over 50 years. While theoretical and experimental work has yielded qualitative progress, the large body of empirical work testing predictions about parental investment based on life-history trade-offs has yet to be synthesized. We first provide an overview of the core life-history theory exploring how selection might shape parental care. We then conduct a systematic review and meta-analysis on studies that experimentally manipulated brood size in birds, a widely used experimental approach to manipulate parental investment. We extracted 313 estimates from 62 studies representing 31 species of birds from 19 different families and tested key predictions on trade-offs in parental care derived from theory. Our analysis provides strong support for some predictions about life-history trade-offs in parental care, but weak or equivocal support for others. Specifically, we found that overall, avian parents respond to brood size manipulations as predicted by life-history theory: they increased care in response to brood enlargement, and decreased care in response to brood reductions. Furthermore, for the same relative manipulation size, responses to brood reductions were greater than responses to brood enlargements. This finding is consistent with predictions derived from life-history theory based on some types of non-linear utility curves. However, many predictions derived from theory are not well supported by our comparative analysis. Species' life-history traits such as clutch size (a measure of current reproduction), adult survival, and broods per year (two measures of future reproduction), explained little, if any, among-species variation in response to brood size manipulations. Several factors may explain this. We highlight that brood size manipulations may affect more than just perception of the value of current reproduction, such as altering parents' perception of predation risk. Importantly, these unintended consequences could lead to asymmetric responses like those we observed. Other common experimental approaches - such as hormone manipulations, altering a partner's effort, and food supplementation - often affect multiple traits or fitness components simultaneously, or may involve cues that poorly match the evolved mechanisms guiding parental behaviour. Our review of both theory and experimental approaches suggests that there are multiple opportunities for more precise experiments. We offer several recommendations for effective designs. One is improved understanding of the biology underlying the functions relating to costs and benefits, with careful consideration of not only how the manipulation will affect only one of those, but also the mechanisms that might alter how parents perceive the manipulation. We also emphasize general principles, such as assessing alternative hypotheses and devising multiple independent tests. Armed with these recommendations, we believe there are new opportunities to increase the strength of inference achieved from studies aimed at understanding the trade-offs affecting the evolution of parental care.

Animals↗

PubMed2026

Clinical applications of digital twin technology in In Vitro Fertilisation.

BACKGROUND: Digital twin technology, originating from aerospace and manufacturing industries, has emerged as a transformative tool in healthcare. In vitro fertilisation (IVF) faces persistent challenges including suboptimal embryo selection, unpredictable treatment outcomes, and limited personalisation of protocols. Despite advances in assisted reproductive technology, existing literature exhibits fragmentation: artificial intelligence applications in embryo selection, ovarian stimulation, and endometrial assessment have been developed independently without systematic integration into comprehensive treatment frameworks. Digital twin technology offers unprecedented opportunities to create virtual replicas of biological systems, enabling real-time monitoring, predictive modelling, and personalised treatment strategies. AIM: This narrative review aims to critically examine the current applications of digital twin technology in IVF, evaluate its potential benefits and limitations, synthesize existing evidence into an integrative conceptual model, and identify future directions for implementation in reproductive medicine. METHOD: A comprehensive narrative review was conducted using PubMed, Scopus, Web of Science, and IEEE Xplore databases. A narrative review approach was selected over systematic review to accommodate the heterogeneity of evidence types in this emerging field, including theoretical frameworks, simulation studies, and proof-of-concept implementations that would be excluded from systematic reviews. Search terms included "digital twin," "IVF," "in vitro fertilisation," "assisted reproductive technology," "embryo selection," and "predictive modelling." Studies published between 2015 and 2025 were included, focusing on original research articles, systematic reviews, and proof-of-concept studies describing digital twin applications in reproductive medicine. RESULTS: Digital twin technology in IVF demonstrates significant potential across multiple domains including embryo development simulation, ovarian response prediction, endometrial receptivity modelling, and personalised stimulation protocols. Current applications integrate artificial intelligence, machine learning algorithms, time-lapse imaging, and omics data to create comprehensive virtual models. Early evidence suggests improvements in embryo selection accuracy, ovarian response prediction, and treatment protocol optimization, though large-scale randomized controlled trials remain limited. Implementation challenges include data integration complexity, computational requirements, regulatory considerations, and validation requirements. CONCLUSION: Digital twin technology represents a paradigm shift in IVF practice, offering personalised, predictive, and precision medicine approaches. This review synthesizes existing evidence to propose an integrative conceptual model for digital twin implementation across the IVF treatment spectrum, identifies critical knowledge gaps, and establishes research priorities to advance clinical translation. Despite current limitations, continued advancement promises improved success rates and patient outcomes.

Humans↗

PubMed2026

Association of the Charlson Comorbidity Index With 1-Year Outcomes in Patients With Macular Edema Secondary to Retinal Vein Occlusion.

OBJECTIVE: To determine the predictive value of the Charlson Comorbidity Index (CCI) for outcomes in patients with macular edema secondary to retinal vein occlusion (RVO). DESIGN: Retrospective clinical cohort study. SUBJECTS: Patients seen between 2013 and 2023 at the Cole Eye Institute, Cleveland Clinic, were included. All patients were >18, diagnosed with RVO (International Classification of Diseases (ICD)-9 and 10 codes), had a complete CCI score, and had at least 1 year of ophthalmic follow-up data after their first intravitreal injection (baseline). Patients with ocular surgery, trauma, or panretinal photocoagulation were excluded. METHODS: Age-adjusted CCI scores were calculated for each patient from chart review. For patients with bilateral RVO, one eye was selected randomly. Patients were stratified into tertiles by CCI distribution: tertile 1 (CCI 0-5; mean 3.4), tertile 2 (age-CCI 4.1-6; mean 4.9), and tertile 3 (CCI ≥ 8; mean 9.6). Multivariable linear regression was performed to determine the predictive value of CCI and other covariates on visual and anatomical outcomes. MAIN OUTCOME MEASURES: Best-corrected visual acuity (BCVA) and central subfield thickness (CST) at 1-year follow-up. RESULTS: A total of 972 patients met all criteria, with an average age-adjusted CCI score of 6.2. Each one-point increase in CCI predicted 0.38 fewer letters in BCVA at follow-up (P < .001). Baseline BCVA was a significant predictor of follow-up BCVA in all tertiles (P < .001). In the third tertile, each one-point increase in CCI was associated with a 0.72 letter reduction in follow-up BCVA (P < .001). For CST, baseline CST was strongly predictive of final CST (P < .001), while CCI was only significant in the first tertile, where each point increase in CCI predicted a 13.7 µm increase in CST (P = .02). In RVO subtype interaction models, the age-adjusted CCI × CRVO interaction was not statistically significant for either 1-year BCVA (P = .269) or 1-year CST (P = .695). CONCLUSIONS: Higher CCI scores are significantly associated with worse visual outcomes in patients with RVO, particularly in the combined population and most comorbid patients (tertile 3). CCI was significantly associated with higher (thicker) CST only among the least comorbid patients (tertile 1).

Humans↗

PubMed2026

Adverse Experiences in Brief Meditation Practices: Randomized Controlled Trial.

BACKGROUND: Meditation has become increasingly popular in recent decades. However, relatively little remains known about the prevalence of and risk factors for adverse experiences related to a single meditation practice. OBJECTIVE: The objective of our study was to examine adverse experiences associated with 3 brief, digitally delivered meditation practices (mindfulness, self-compassion, and gratitude) relative to using the internet as usual, as well as to investigate whether preintervention characteristics could predict such outcomes. METHODS: In a secondary analysis of a randomized controlled trial using samples that were representative of the US and UK adult populations with regard to ethnicity, sex, and age, we examined adverse experiences associated with 3 brief (ie, 5 or 10 minutes) meditation practices (ie, mindfulness, self-compassion, and gratitude) relative to using the internet as usual. We also investigated the potential of using preintervention characteristics to predict such outcomes. RESULTS: A total of 5049 participants completed all preintervention measures and were randomly assigned to meditation or control conditions. Across the sample, 4.1% (204/4925) of participants reported having a distressing experience during the intervention, and 7.1% (348/4908) of participants experienced an increase in negative affect from before to after the intervention. The results showed that participants who were randomized to a brief meditation intervention were no more likely to report a distressing experience than those who were randomized to use the internet as usual (odds ratio [OR] 1.05, 95% CI 0.76-1.47; P=.76). The results also showed that participants who were randomized to a brief meditation intervention were less likely to report clinically relevant increases in negative affect relative to using the internet as usual (OR 0.63, 95% CI 0.50-0.80; P<.001). Notably, participants in the 10-minute condition had a significantly higher likelihood of reporting a distressing experience than those in the 5-minute condition (OR 1.42, 95% CI 1.07-1.89; P=.02). Preintervention characteristics showed acceptable discrimination ability to predict a distressing experience (area under the curve=0.73) and slightly lower ability to predict increased negative affect (area under the curve=0.67). CONCLUSIONS: Taken together, we found that the brief, digitally delivered meditation practices tested in this study carry risks of adverse experiences that are comparable to or lower than those of typical activities on the internet; 10-minute condition was more likely to result in distressing experiences than 5-minute condition; and adverse responses to a brief meditation practice can, at least to a certain degree, be predicted using preintervention characteristics. TRIAL REGISTRATION: Open Science Framework 94HKS; https://osf.io/94hks/overview.

Humans↗

PubMed2026

Quantitative assessment of the fingerprint evidential value using machine learning.

Fingerprints as physical evidence have long supported criminal investigation and adjudication. In practice, however, fingerprint identification relies mainly on examiners' experience. Furthermore, expert opinions tend to be categorical, even though the opinions with the same conclusion could differ substantially in evidential strength. To quantitatively assess fingerprint evidential value, this study proposes a machine learning-based framework as an interpretable decision-support tool. A lightweight residual one-dimensional convolutional neural network was constructed, incorporating channel recalibration and a similarity-driven attention mechanism to learn adaptive contribution weights for different matched minutiae (minutiae for short). Controlled experiments revealed that the predicted evidential value increased with the number of minutiae and was significantly influenced by the quality of minutiae. With 10 minutiae, the mean predicted scores were 4.49, 7.00, and 9.09 for blurred, moderately blurred, and clear minutiae, respectively. Multiple regression analysis indicated that replacing a pair of blurred minutiae with a pair of clear minutiae increased the score by 0.492, whereas replacing it with a pair of moderately blurred minutiae increased the score by only 0.216. By mapping predicted scores to graded levels of evidential strength, the framework contributes to a paradigm shift from categorical expert opinions to graded ones, helping courts evaluate fingerprint evidence more scientifically.

Humans↗

PubMed2026

Impact of Diabetes on Outcomes of Contemporary PCI Guided by OCT vs Angiography: The ILUMIEN IV Trial.

BACKGROUND: Patients with diabetes are at higher risk for adverse events after percutaneous coronary intervention (PCI) compared with patients without diabetes. OBJECTIVES: This study sought to assess the influence of diabetes and complex lesions on the outcomes of patients undergoing PCI with and without optical coherence tomography (OCT) guidance during a follow-up period of 2 years. METHODS: Patients in ILUMIEN IV randomized to OCT-guided vs angiography-guided PCI were grouped into those with (n = 1,044) and without diabetes (n = 1,443). Study endpoints were target vessel failure (TVF) and serious major adverse cardiovascular events (MACE). RESULTS: After adjustment for differences in clinical and angiographic characteristics, the 2-year rates of both TVF (9.9% vs 6.3%; adjusted HR: 1.48; 95% CI: 1.09-2.02; P = 0.01) and serious MACE (5.3% vs 2.7%; adjusted HR: 1.77; 95% CI: 1.14-2.76; P = 0.01) were increased in diabetic compared with nondiabetic patients, consistently in patients with and without complex lesions (Pinteraction = 0.22 and 0.14, respectively), although the highest 2-year rates were in patients with diabetes and complex lesions. In all randomized patients, OCT guidance compared with angiography guidance did not reduce TVF or serious MACE. These effects were consistent in patients with and without diabetes (Pinteraction = 0.41 and 0.20, respectively), and were not modified by treatment of complex lesions. CONCLUSIONS: In the large-scale ILUMIEN IV trial, patients with diabetes remained at increased risk for adverse events after PCI compared with nondiabetic patients despite the use of OCT procedural guidance. Patients with diabetes and complex lesions were at particularly high risk for adverse outcomes after PCI.

Humans↗

PubMed2026

Automated CEAP Classification of Venous Duplex Reports Using Multimodal Artificial Intelligence.

OBJECTIVE: To develop and internally validate a prototype multimodal artificial intelligence system for automated CEAP (Clinical, Etiological, Anatomical and Pathophysiological) classification of venous duplex ultrasound (VDUS) reports, integrating natural language processing of free-text components with computer vision analysis of hand-drawn anatomical diagrams. METHODS: Single centre retrospective observational study using routinely collected clinical data. One thousand consecutive venous duplex ultrasound reports from Cambridge University Hospitals NHS Foundation Trust, UK (July 2024 - May 2025) were labelled according to the CEAP classification, excluding the Etiological component, which could not be reliably determined from duplex reports alone. Transfer learning was applied using ClinicalBERT for text and MobileNetV3 for diagrammatic data. Clinical classes were predicted from request line text. Text- and image-based pathophysiological models were developed for four anatomical territories (Great Saphenous Vein, Small Saphenous Vein, Deep system, Perforators), combined using late fusion with probability averaging. RESULTS: The clinical CEAP model achieved accuracy of 0.91, macro-F1 of 0.82, and macro-AUC of 0.98. Pathophysiological prediction varied, with text models broadly outperforming image models. Fusion yielded heterogeneous benefits, improving SSV performance but reducing Deep system accuracy. The performance of the final pathophysiological CEAP fusion models varied across anatomical territories: accuracy ranged from 0.70-0.92 and macro-AUC from 0.80-0.92. CONCLUSION: This study demonstrates the feasibility of automated CEAP classification from VDUS reports. Despite class imbalance affecting minority class predictions, the strong discriminatory performance validates this multimodal ML model for extracting clinically meaningful information from real-world data. This approach offers potential, pending external validation, to streamline vascular services through automated triage and guideline-compliant decision making.

Artificial intelligence↗

PubMed2026

Role of routine surveillance stress testing in patients with or without imaging-guided or physiology-guided PCI.

OBJECTIVE: The optimal follow-up strategy for high-risk patients who underwent imaging-guided or physiology-guided percutaneous coronary intervention (PCI) remains uncertain. We investigated whether routine surveillance stress testing after PCI provides clinical benefit when the procedure is guided by intravascular ultrasonography (IVUS) or fractional flow reserve (FFR). METHODS: In the Pragmatic Trial Comparing Symptom-Oriented vs Routine Stress Testing in High-Risk Patients Undergoing PCI randomised trial, 1706 high-risk patients who underwent PCI were assigned to either routine functional testing at 1 year or standard care alone. In this prespecified subgroup analysis, patients were subsequently categorised according to whether IVUS or FFR was used at the index procedure. The primary outcome was a composite of death, myocardial infarction or hospitalisation for unstable angina over 2 years. RESULTS: Among the randomised population, 74% underwent IVUS-guided intervention and 36% underwent FFR-guided intervention. At 2 years, rates of the primary outcome were similar between routine testing and standard care both in patients treated with IVUS guidance (5.3% vs 6.7%; HR 0.79; 95% CI 0.50 to 1.24) and without IVUS guidance (5.7% vs 3.8%; HR 1.52; 95% CI 0.63 to 3.68; interaction p=0.21). Comparable results were observed in patients with FFR guidance (2.6% vs 3.9%; HR 0.65; 95% CI 0.26 to 1.58) and without FFR guidance (7.0% vs 7.1%; HR 0.99; 95% CI 0.63 to 1.55; interaction p=0.59). Routine functional testing was consistently associated with higher use of invasive coronary angiography and repeat revascularisation, without improvement in clinical outcomes. CONCLUSIONS: Among high-risk patients who underwent PCI, routine surveillance stress testing did not reduce the risk of death, myocardial infarction or unstable angina, regardless of the use of IVUS or FFR at the index procedure. Routine functional testing increased downstream invasive procedures without clinical benefit. These findings support guideline recommendations against routine surveillance testing after PCI. TRIAL REGISTRATION NUMBER: NCT03217877.

Humans↗

PubMed2026

Axial Length Adjustment and AL/R Ratio Optimization of IOL Power Calculation in Extremely Long Eyes.

PURPOSE: To evaluate the accuracy of modern intraocular lens (IOL) power calculation formulas and axial length (AL) adjustment methods in eyes with AL ≥ 30.0 mm. DESIGN: Retrospective consecutive cross-sectional study. PARTICIPANTS AND CONTROLS: A total of 308 eyes (308 patients) with AL ≥ 30.00 mm were included. METHODS: Accuracy of modern online formulas, alone or with established AL adjustments methods, was analyzed. Subgroup analyses were performed based on AL, keratometry (K), anterior chamber depth (ACD), lens thickness (LT), and AL-to-corneal radius (AL/R) ratio. MAIN OUTCOME MEASURES: Predictive accuracy was evaluated using the formula performance index (FPI), root mean square absolute prediction error (RMSAE), standard deviation (SD) of prediction error (PE), and percentage of eyes within ±0.25 and ±0.50 diopters (D). RESULTS: Overall, Holladay 1 combined with the nonlinear polynomial Wang-Koch axial length adjustment (H1-PWK) demonstrated the best overall performance, achieving the lowest SD (0.40), RMSAE (0.40), and highest FPI (0.494). A tendency toward hyperopic error was observed in eyes with AL ≥ 32.0 mm, K ≥ 46.0 D. The AL/R ratio showed a significant positive correlation with PE in the Ladas Super formula, Barrett Universal II, EVO, PEARL-DGS, and Hoffer QST formulas. Spline-based regression analysis indicated that the transition point of AL/R from myopic to hyperopic PE varied across different formulas. CONCLUSIONS: H1-PWK provides robust refractive accuracy in extremely long eyes. The AL/R ratio may provide a useful composite biometric stratification parameter compared to AL alone.

Humans↗

PubMed2026

Neuroimaging anxious children and adolescents before and after cognitive behavioral therapy: a systematic review.

OBJECTIVE: This systematic review investigates brain changes in youths with anxiety disorders following cognitive behavioral therapy (CBT) and neural markers that predict CBT responses. METHODS: We conducted a systematic search using the electronic databases PubMed, Web of Science, and ProQuest. The inclusion deadline was set to October 27, 2025. We included fifteen peer-reviewed neuroimaging studies that examined the effects of CBT in youths under 19 years old with a primary clinical diagnosis of an anxiety disorder based on DSM-5 criteria. RESULTS: Although the existing literature is marked by substantial diversity in methods and outcomes, task-related neural response in the anterior cingulate cortex (ACC, 2/8, 25.0%), insula (1/8, 12.5%) increased from pre to post CBT and these changes were further correlated with clinical symptom improvements. Moreover, CBT outcomes were predicted by pre-treatment activity or connectivity in the ACC and amygdala (3/13, 23.0%). A smaller proportion of studies (2/13, 15.3%) found that activity or connectivity in the insula, precuneus/cuneus, postcentral gyrus, and activity or structure in the nucleus accumbens (NAcc) predicted response to CBT. The low consistency of these findings was driven by methodological variability, low reliability of the neural markers, and relatively small sample sizes. CONCLUSIONS: This review highlights promises of neural predictors and outcomes to enhance anxiety disorder treatments in children and adolescents, facilitating future personalized and effective CBT. Beyond this initial promise, the field is hindered by methodological inconsistencies and limited replications. While longitudinal and personalized approaches are important next steps, the central challenge remains: identifying neural markers that are both reliable and robust.

Adolescent↗

PubMed2026

Criteria for Safe Hospital Discharge in Bronchiolitis: A Systematic Review.

Bronchiolitis is the leading cause of hospital presentation and admission for infants in Australasia. We aimed to synthesise current evidence on the effect of discharge criteria for infants (aged < 12 months) who are presenting to or are admitted to hospital with bronchiolitis, to inform a binational guideline recommendation update. Systematic searches were conducted on MEDLINE, EMBASE, PubMed, Cochrane Library and CINAHL (last search 19 February 2025) for non-randomised studies evaluating hospital discharge criteria in bronchiolitis. The primary outcomes were length of stay (LOS) and readmission rates. The risk of bias (ROBINS-I) and certainty of the evidence (GRADE) were appraised, and findings were narratively synthesised. GRADE evidence-to-decision methodology, expert consensus voting and interest-holder consultation were used to finalise the recommendation update. Two retrospective observational studies were included (N = 2697) (low to very low quality), reporting on unique discharge criteria. In both studies, use of the discharge criteria was associated with a significant reduction in LOS relative to alternative protocols. There was no significant difference in readmission rates observed in either study. There was low to very low certainty evidence across outcomes due to risk of bias, indirectness and imprecision. The review findings informed a recommendation update for safe discharge criteria in the 2025 Australasian Bronchiolitis Guideline update. Updated, prescriptive discharge criteria and flow chart were developed, covering clinical stability, oxygen saturation/support, feeding difficulties, caregiver confidence and education on deterioration, social factors and follow-up. The revised criteria provide clinicians with increased certainty in decision-making in bronchiolitis, albeit with further research needed.

Humans↗

PubMed2026

Meta-analysis of growth and inactivation kinetics of Legionella.

Quantitative risk assessments intended to inform evidence-based water management plans and public health targets for Legionella in engineered water systems are constrained by fragmented and heterogeneous growth and inactivation kinetics. We conducted a meta-analysis of 25 growth and 39 thermal- and chemical-inactivation studies, fitting microbial persistence models to harmonize parameters. Nonlinear models outperformed first-order formulations, indicating that lag phases and resistant or protected subpopulations are central to Legionella persistence. Random forest analysis identified environmental and methodological drivers of variability based on 226 growth rates and reduction times for thermal (209) and chemical (135) inactivation. Growth was primarily governed by temperature, nutrient availability, and compatible Legionella-host pairings; thermal inactivation by quantification method, temperature, and turbidity; and chemical inactivation by inoculum size, disinfectant type, concentration, and host-associations. Accordingly, temperature-dependent growth parameters and exposure metrics for heat, free-chlorine, and monochloramine, expressed as TT (Temperature×time) and CT (Concentration×time), were derived as condition-specific inputs for predictive models. Growth optima around 37-40 °C, together with lag-time estimates, indicate that hot-water temperature setbacks and energy-saving practices may favor Legionella proliferation under repeated or prolonged lukewarm exposure. Culture- and viability-based TT differences highlight the need to consider viable‑but-non-culturable persistence in monitoring programs. CT comparisons suggest monochloramine may be advantageous because of its lower apparent sensitivity to host-associated protection. Although limited by restricted experimental conditions, the findings show that predictive models should account for microbial ecology, water matrix effects, and quantification endpoints. Future kinetic studies should prioritize realistic multi-host systems, strain pre-adaptation, complementary viability measurements, and standardized protocols and reporting to ensure reproducibility and enable robust system-level predictive modeling.

Legionella↗

PubMed2026

Prognostic Value of Circulating Tumor DNA-Based Minimal Residual Disease for Recurrence-Free Survival in Resectable Gastric Cancer: A Systematic Review and Meta-Analysis with Serial Monitoring Analysis.

BACKGROUND: Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) is an emerging biomarker, but its utility in resectable gastric cancer remains incompletely characterized. METHODS: We conducted a systematic review and meta-analysis of eight studies (520 patients) to evaluate the prognostic value of ctDNA-based MRD for recurrence-free survival (RFS) and overall survival (OS) in resectable gastric cancer. RESULTS: In localized resectable gastric cancer (Stage I-III), the setting in which postoperative ctDNA most coherently represents true molecular residual disease after curative-intent surgery, postoperative ctDNA positivity was associated with diminished recurrence-free survival (RFS: HR 12.26, 95% CI 3.30-45.52) and overall survival (OS: HR 8.57, 95% CI 3.06-23.98). The test for subgroup differences between localized and mixed-stage cohorts was not statistically significant (P = 0.57), and the numerically higher HR in the localized subgroup should therefore not be interpreted as evidence of a quantitatively stronger prognostic effect. Postoperative ctDNA detection demonstrated substantially stronger prognostic value (overall RFS: HR 10.00, 95% CI 4.53-22.10) compared to preoperative assessment (HR 2.17, 95% CI 1.10-4.28). Both tumor-informed and tumor-agnostic strategies effectively stratified high-risk patients. However, these effect sizes should be interpreted cautiously given the small number of studies and substantial heterogeneity (I2 = 65-72%). Results from mixed-stage cohorts including Stage IV disease are supportive but should not be considered equivalent to localized-disease findings, as ctDNA in metastatic disease reflects persistent systemic burden rather than minimal residual disease in the postoperative sense. CONCLUSIONS: Postoperative ctDNA-based MRD shows a consistent adverse prognostic association in resectable gastric cancer, with localized disease (Stage I-III) representing the most biologically and clinically coherent setting for interpretation. However, the large pooled hazard ratios (HR 10.00-12.26) should be interpreted as a directionally consistent signal rather than precise quantitative estimates, given the small number of studies, wide confidence intervals, and substantial heterogeneity (I2 = 65-73%). This heterogeneity is largely driven by substantial variation in postoperative sampling timing (4 days to 16 weeks) and ctDNA assay characteristics (platform, sensitivity, coverage, variant filtering, and positivity thresholds), which require standardization in future studies. While ctDNA is prognostically valuable, its clinical utility remains unestablished. Prospective randomized trials are needed to determine whether ctDNA-guided strategies improve patient outcomes before routine clinical implementation can be recommended.

Humans↗

PubMed2026

Ruling out pediatric bacterial epididymo-orchitis with urinalysis - The case for minimizing unnecessary antibiotic prescription.

INTRODUCTION: Epididymo-orchitis in pediatric patients is predominantly non-bacterial, often stemming from viral or reactive etiologies. Despite guidelines recommending conservative management for non-bacterial cases, antibiotic overtreatment remains prevalent in the outpatient setting. We evaluated the diagnostic accuracy of urinalysis in ruling out bacterial infection to support antibiotic stewardship in this population. METHODS: We conducted a cross-sectional diagnostic accuracy study using electronic health records from a large health maintenance organization in Israel. The cohort included patients younger than 18 years with a diagnosis of epididymo-orchitis or clinically overlapping entities (acute scrotum, appendage torsion) who had paired urinalysis and urine culture results within one week of diagnosis. Logistic regression and ROC curve analysis were performed to assess the ability of urinalysis parameters to predict positive urine cultures. RESULTS: Of 682 eligible cases, confirmed bacterial infection was rare, occurring in only 17 patients (2.5%). Nitrite positivity was the strongest independent predictor of infection (OR 43.98; p < 0.001). A prediction model incorporating all urinalysis parameters yielded an area under the curve (AUC) of 0.825 and achieved a 97.7% classification accuracy for correctly predicting negative cultures. Despite the low prevalence of infection, antibiotics were prescribed in 237 cases (34.7%). Urinary anatomic abnormalities were significantly associated with culture positivity. CONCLUSIONS: Bacterial coinfection in pediatric epididymo-orchitis is uncommon. Urinalysis serves as a highly accurate screening tool to rule out bacterial etiology. A negative urinalysis supports withholding antibiotics in this setting, reserving treatment for children with positive markers or known anatomic abnormalities. This evidence-based approach This evidence-based approach has the potential to reduce unnecessary antibiotic exposure, however prospective studies are needed to validate these findings before broad implementation.

Humans↗

PubMed2026

The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.

INTRODUCTION: Intimate partner violence (IPV), encompassing physical, sexual, emotional and economic abuse, remains a pervasive global health concern. Traditional prevention efforts face obstacles such as underreporting, delayed detection and limited personalised support. Emerging artificial intelligence (AI) approaches offer new opportunities to enhance IPV prevention. AIM: This systematic review maps and synthesises evidence on AI-driven tools in IPV prevention based on studies published between 2004 and 2024. METHODS: Following PRISMA 2020 guidelines and PROSPERO registration, we searched PubMed, Embase, CINAHL, PsycINFO, IEEE Xplore and Web of Science. Eligible studies explicitly evaluated AI technologies targeting IPV prediction, screening, intervention or support delivery. Study quality was appraised using the Mixed Methods Appraisal Tool (MMAT). RESULTS: Of 1304 records initially identified, 41 studies met eligibility criteria. AI applications ranged from machine learning (ML) for risk prediction and natural language processing (NLP) for IPV detection in clinical and social media data, to image analysis for forensic evaluation and chatbot-based support. Predictive modelling demonstrated strong discriminative performance, while NLP-based screening detected IPV with notable sensitivity. Chatbots showed feasibility and user acceptability, but evidence of their direct impact on reducing IPV incidence was limited, with one randomised controlled trial showing a modest reduction. Key challenges identified included algorithmic bias, data privacy risks and barriers to integration across health and social care systems. DISCUSSION: AI-informed interventions show promise for improving IPV detection, risk assessment, and scalable support, but questions remain about long-term effectiveness, ethical fairness, transparency and equitable implementation. Future interdisciplinary research should address these concerns to responsibly deploy AI in IPV prevention. RELEVANCE TO CLINICAL PRACTICE: The findings highlight the importance of trauma-informed, culturally responsive care and provider training in AI applications. Nurse-led innovation and policy advocacy will be crucial for safe, equitable integration of AI in IPV prevention.

Artificial Intelligence↗