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PubMed2026

Measuring economic efficiency in adult intensive care units: A systematic review of methods, metrics, and evidence.

OBJECTIVES: Intensive care units (ICUs) consume substantial hospital resources, yet "efficiency" is inconsistently defined and measured. This study systematically reviewed how economic efficiency has been conceptualised and quantified in adult ICUs and appraised the quality of evidence. METHODS: Following PRISMA 2020 and a PROSPERO-registered protocol (CRD420251107866), we searched MEDLINE, Embase, CINAHL, Cochrane Library and Web of Science (2000-August 2025), plus global grey sources. Eligible studies explicitly defined efficiency and reported an efficiency metric/model linking ICU inputs (e.g., staff, beds/capacity, time, consumables, or costs) to outputs/outcomes (e.g., throughput/discharges, length of stay/resource use, risk-adjusted mortality). Dual independent screening and extraction were performed. Study quality was appraised using MMAT, and findings were synthesised narratively (SWiM), given heterogeneity. RESULTS: 39 studies (2001-2025) from 17 countries were included, all from high-income or upper-middle-income settings. Four methodological families were identified: (1) frontier modelling (predominantly DEA; occasional SFA/RFDH), (2) benchmarking indicators (risk-adjusted mortality and LOS/resource-use ratios; "efficiency matrix" quadrant classification), (3) cost-outcome evaluations, and (4) operational/process metrics. Across families, variation in decision-making units, input/output selection, and risk adjustment limited comparability; long-term and patient-reported outcomes were absent, and equity considerations were uncommon. CONCLUSIONS: ICU efficiency research is feasible but fragmented and often methodologically limited. Standardised definitions, validated risk adjustment, uncertainty quantification, and inclusion of patient-centred and equity-relevant outcomes are needed before efficiency metrics can reliably inform value-based decision making.

Intensive Care Units↗

PubMed2026

Diagnostic performance of machine learning models for malignant and non-malignant pleural effusion: Systematic review and meta-analysis.

BACKGROUND: Accurately distinguishing malignant pleural effusion (MPE) from non-malignant pleural effusion is clinically important, but the generalisability and methodological quality of machine-learning (ML) models remain uncertain. METHODS: We searched eight databases to 23 April 2026. Diagnostic performance was pooled using random-effects and Reitsma bivariate models, and study quality was assessed using PROBAST+AI. RESULTS: Forty-two studies were included; 17 contributed to the AUC meta-analysis and 14 to the bivariate analysis. The pooled AUC was 0.90 (95 % CI 0.85-0.94; 95 % prediction interval 0.62-0.98), with sensitivity of 0.80 (95 % CI 0.77-0.83) and specificity of 0.87 (95 % CI 0.79-0.92). Only nine studies reported external, temporal or independent validation. Externally validated studies had a lower pooled AUC than studies without external validation (0.83 vs 0.92), with lower specificity observed in the two externally validated studies contributing sensitivity and specificity data. All 42 development assessments had high overall quality concerns, and all 42 model evaluations were judged at high risk of bias. CONCLUSIONS: ML models showed good apparent accuracy for distinguishing MPE from non-MPE, but the evidence was limited by substantial heterogeneity, high risk of bias and scarce external validation. The pooled estimates reflect the average performance of different selected models rather than the expected accuracy of a single clinical test. ML models should be regarded as adjuncts to existing diagnostic pathways until they are confirmed by rigorous multicentre prospective external validation and clinical-impact studies.

Humans↗

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

Xerophthalmia and ocular manifestations of vitamin A deficiency in children in high-income countries: A systematic review.

Xerophthalmia is a vision-threatening eye condition caused by vitamin A deficiency (VAD). Cases of xerophthalmia in high-income countries (HICs) are vulnerable to misdiagnosis, causing delays in treatment and adverse visual outcomes. We define the features, causes and complications of VAD and xerophthalmia in children of HICs. Our study followed the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines (CRD42024492023). We performed a search for eligible articles on Scopus, Web of Science, Cochrane, PubMed and Medline. Cases reporting on children under 18 years of age residing in HICs with ocular features of VAD were eligible for inclusion. The search yielded 2474 results; 43 case reports and case series met the inclusion criteria consisting of a total of 61 cases (mean age 9.9 ± 4.2 years, range 3-17 years). Xerophthalmia was graded according to the most advanced finding for each case: 21.3% had night blindness only; 29.5% had conjunctival xerosis or Bitot spots; 29.5% had corneal xerosis, ulceration or scarring; 1.6% had xerophthalmia fundus only; and 18.0% had ocular manifestations associated with VAD that are not encompassed under the WHO classification. These features included swollen optic discs, optic neuropathy, or ocular dryness. Restrictive dietary practises were the most common mechanism of deficiency (75%), and autism was the most common underlying condition (49%). This shows that VAD remains a cause of severe visual impairment in HICs, especially when associated with delays in diagnosis and treatment. Further research is required to establish the prevalence of xerophthalmia in HICs.

Humans↗

PubMed2026

Distress Intolerance, Social Anxiety, and Depressive Symptoms in Adolescents: Evidence from Random-Intercept Cross-Lagged Panel and Cross-Lagged Panel Network Analyses.

Social anxiety and depressive symptoms frequently co-occur during adolescence, yet the mechanisms underlying their longitudinal associations remain insufficiently understood. Distress intolerance has been proposed as a transdiagnostic risk factor implicated across internalizing symptoms. However, it remains unclear whether distress intolerance is predicted by social anxiety and depressive symptoms, as well as the underlying mechanisms among these three constructs. The specific symptoms most centrally involved in these cross-domain associations remain poorly understood. The present study investigated the longitudinal associations among distress intolerance, social anxiety, and depressive symptoms using a dual-method framework combining random-intercept cross-lagged panel models (RI-CLPM) and cross-lagged panel network (CLPN) analyses. A total of 1,378 Chinese adolescents (Mage = 12.57, SDage = 0.63; 50.4% female) were assessed at three time points with six-month intervals between waves. The RI-CLPM analyses revealed that higher distress intolerance prospectively predicted subsequent increases in both social anxiety and depressive symptoms, whereas elevated social anxiety and depressive symptoms in turn predicted subsequent increases in distress intolerance. Moreover, distress intolerance mediated the longitudinal associations between social anxiety and depressive symptoms. Additionally, distress intolerance was also indirectly associated with its own subsequent levels through social anxiety and depressive symptoms. The CLPN analyses revealed that fear of negative evaluation and fatigue were the strongest predictors of other network nodes from T1 to T2 and from T2 to T3, respectively. In contrast, distress intolerance symptoms were predominantly predicted by other nodes in both cross-lagged networks. These findings extend prior views of distress intolerance as a unidirectional vulnerability by showing that distress intolerance is also predicted by social anxiety and depressive symptoms and accounts for part of their longitudinal associations across adolescence.

Humans↗

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

Routine methods misidentify Serratia spp.: Limitations of MALDI-TOF MS revealed by whole-genome sequencing.

Accurate species-level identification within the genus Serratia remains challenging due to extensive phenotypic overlap and high genomic relatedness among closely related and recently described taxa. This study presents an evaluation of routine and genome-based identification approaches applied to clinical Serratia isolates, integrating phenotypic assays, MALDI-TOF MS (Bruker Daltonics), 16S rRNA gene sequencing, and Whole-Genome Sequencing (WGS). A total of 103 isolates collected from a teaching hospital were analyzed. WGS was performed on a subset of isolates. Conventional biochemical methods classified all isolates as Serratia marcescens, whereas MALDI-TOF MS identified 60.1% as S. marcescens, 11.6% as S. ureilytica, and 28.1% just at the genus level. Peak analysis from MALDI-TOF MS revealed specific peaks associated with S. marcescens and S. ureilytica, but limited discriminatory power. WGS of six isolates initially identified as S. ureilytica by MALDI-TOF MS revealed reclassification as Serratia sarumanii (n = 5) and Serratia montpellierensis (n = 1), supported by Average Nucleotide Identity (ANI), Average Amino Acid Identity (AAI), and Digital DNA-DNA Hybridization (dDDH) thresholds. In contrast, 16S rRNA analysis showed limited species-level resolution. Phylogenomic and SNP-based analyses confirmed these classifications with strong support. Overall, this study underscores the critical role of high-resolution genomic approaches for precise species identification and highlights the need for continuous expansion and curation of MALDI-TOF MS reference databases to support reliable clinical diagnostics and epidemiological surveillance of emerging Serratia species.

Spectrometry, Mass, Matrix-Assisted Laser Desorpti↗

PubMed2026

Longitudinal Relations among Perceived Economic Stress, Teacher-Student Relationships, and Cybervictimization: Exploring Within-Person Links.

Family economic hardship has been identified as a risk factor for adolescents' cybervictimization. Nevertheless, existing studies have primarily focused on objective economic conditions, and little is known about the within-person association between perceived economic stress and adolescents' cybervictimization and the mediating mechanisms underlying this association. To fill these gaps, the random intercept cross-lagged model was employed to examine the dynamic relations among perceived economic stress, teacher-student relationships, and cybervictimization. The data were obtained from a sample of 2407 Chinese adolescents (Mage = 12.75, SD = 0.58, 50.23% girls at baseline) recruited from seven schools and assessed at three time points over one year. At the between-person level, there were no significant associations among perceived economic stress, teacher-student relationships, and cybervictimization. At the within-person level, perceived economic stress positively predicted later cybervictimization over time, and this effect was unidirectional. The bidirectional relations between perceived economic stress and teacher-student relationships remained stable over time. Cybervictimization significantly and negatively predicted subsequent teacher-student relationships across time, indicating a unidirectional predictive effect. Additionally, perceived economic stress indirectly predicted cybervictimization through teacher-student relationships. The findings highlight the importance of distinguishing within-person from between-person processes and shed light on the longitudinal role of teacher-student relationships in the association between perceived economic stress and cybervictimization.

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

Lateral Femoral Condyle Angle Is an Anatomic Risk Factor for Anterior Cruciate Ligament Primary Injury and Secondary Graft Rerupture.

PURPOSE: To define the lateral femoral condylar angle (LFCA)-a parameter measuring condylar inclination-and assess its predictive capacity for primary and recurrent anterior cruciate ligament (ACL) injuries. METHODS: Patients aged 18 to 50 years who underwent primary ACL reconstruction between 2017 and 2022 were screened. Those with graft rerupture were matched 1:1:1 by sex, age, body mass index, and meniscal status to ACL-intact controls and patients without graft failure during a minimum 48-month follow-up. LFCA was measured as the angle between the long axis of the distal femur and the axis of the lateral femoral condyle, alongside 38 established parameters using preoperative 3.0-T magnetic resonance imaging scans. Intergroup differences were assessed with one-way analysis of variance; multivariate regression and receiver operating characteristic analyses identified independent predictors and evaluated predictive performance. RESULTS: The study included 540 patients (180 per group: primary ACL injury, rerupture, controls). One-way analysis of variance revealed a significant gradient in LFCA across controls (81.3°, 95% CI: 80.8-81.8°), primary injuries (81.9°, 95% CI: 81.5-82.3°), and reruptures (84.2°, 95% CI: 83.7-84.6°) (P < .001). In multivariate models adjusted for baseline factors, LFCA independently predicted primary injury (odds ratio [OR] = 1.27, 95% CI: 1.13-1.42, P < .001; area under the curve [AUC] = .576) and rerupture (OR = 1.46, 95% CI: 1.21-1.76, P < .001; AUC = .704). Combined models incorporating LFCA with tibial slopes, notch angle, and notch height achieved an AUC of .847 for primary injury prediction, whereas models with LFCA, lateral condylar flexion curvature radius, slope asymmetry, and tibial AP distance reached an AUC of .817 for rerupture. LFCA alone with lateral condylar flexion curvature radius yielded an AUC of .777 for rerupture prediction. Sex-stratified analyses confirmed LFCA predicted rerupture in both male patients (OR = 1.44, 95% CI: 1.19-1.75) and female patients (OR = 1.49, 95% CI: 1.16-1.92), and primary injury in male patients (OR = 1.30, 95% CI: 1.15-1.48). CONCLUSIONS: LFCA is an independent predictor of ACL injury, showing particular strength in identifying Asian patients at high risk for graft rerupture. LEVEL OF EVIDENCE: Level III, retrospective case-control study.

Humans↗

PubMed2026

Psychiatric Diagnoses and Psychotropic Medications Among Military-Affiliated Adolescents and Young Adults With Polycystic Ovary Syndrome.

PURPOSE: To study rates of psychiatric diagnoses and psychotropic medication prescription among U.S. military-affiliated adolescents and young adults (AYA) with polycystic ovary syndrome (PCOS). METHODS: This retrospective matched cohort study included U.S. military-affiliated AYA (aged 15-21 years) enrolled in TRICARE Prime for at least 6 months during the surveillance period (January 2016 to October 2023). Military-affiliated AYA were grouped into three categories: individuals diagnosed with PCOS (N = 6,911), age-matched individuals with no diagnosed PCOS symptoms (N = 35,814), and individuals with diagnosed symptoms suggestive of PCOS (N = 2,136). The presence of a psychiatric diagnoses and prescriptions for psychotropic medications were obtained via the International Classification of Diseases, 10th Revision, Clinical Modification codes and National Drug codes, respectively. RESULTS: AYA with diagnosed PCOS had higher odds of having a psychiatric diagnosis and being prescribed a psychotropic medication compared to an age-matched comparison group (psychiatric diagnosis odds ratio [OR] = 2.48 [2.35-2.62], medication OR = 2.14 [2.03-2.25]) and individuals with symptoms suggestive of PCOS (psychiatric diagnosis OR = 1.11 [1.003-1.23], medication OR = 1.16 [1.05-1.28]). DISCUSSION: The odds of psychiatric comorbidities and psychotropic medication prescription were more than twice as high as among U.S. military-affiliated AYA with PCOS. More research is needed to determine whether health-care utilization and military-related factors impact mental health outcomes among AYA with PCOS. Additionally, tailored, multidisciplinary mental health services for AYA with PCOS are needed.

Humans↗

PubMed2026

Screening for neurofibromatosis type 1-related optic pathway gliomas: a systematic review.

BACKGROUND: Neurofibromatosis-type 1 (NF1) is a genetic disorder characterized by developing optic pathway gliomas (OPGs) in 15%-20% of patients with higher estimates where consanguinity is prevalent. Clinically, NF1-OPG might be unpredictable with the risk of OPG progression and visual impairment. The optimal time for screening is controversial. We aim to identify the mean/median age at diagnosis of NF1-OPG and its clinical spectrum. METHODS: A systematic review of PubMed, Web of Science, and Embase databases was conducted for English-language publications from January 1993 to October 2025, exploring the visual screening of OPGs in NF1 patients, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and registered in the Prospective Register of Systematic Reviews (PROSPERO ID: CRD420251036244). Inclusion criteria focused on studies reporting the age at OPG diagnosis and visual manifestations in NF1 patients. Data were extracted on demographics, age at NF1 and OPG diagnosis, tumour location (using the Dodge classification), and presenting symptoms. Sixteen studies met the inclusion criteria. RESULTS: Among 4 739 NF1 patients, 818 had OPGs, with prevalence ranging from 4.2% to 46.7%. The age at NF1 diagnosis ranged from 0 to 132 months (mean: 18-38 months), and at OPG diagnosis from 0-240 months (median: 29-58 months). Approximately 58.4% of OPGs were asymptomatic, and 25% were above the age of 5 years. Among symptomatic patients, the most frequent presentations included decreased visual acuity (62%), abnormal optic disc (45%), proptosis (20%), strabismus (12%), and visual field defects (7%). CONCLUSIONS: NF1-related OPGs typically present early within 6 years of age. Early ophthalmologic and/or radiologic screening at the time of NF1 diagnosis enhances the detection of silent OPGs.

Humans↗

PubMed2026

From commensal to pathobiont: The emergence of virulence-enhanced Escherichia coli in China's food-animal systems - insights with future implications.

A fundamental shift in Escherichia coli epidemiology is being driven by convergence of virulence determinants and antimicrobial resistance within linked human-animal-environment systems. In China, the rapid growth of food-animal production, extensive antimicrobial use, and complex food networks are accelerating the emergence and dissemination of virulence-enhanced E. coli pathobionts. This review synthesizes recent epidemiological, genomics, and outbreak data to characterize China's evolving landscape of food-animal-associated E. coli. We highlight a significant shift from classical pathotypes to hybrid lineages that simultaneously carry virulence factors and last-resort antibiotic resistance determinants, including mcr-1, tet(X4), and blaNDM. These traits disseminate rapidly via plasmid-mediated horizontal gene transfer, facilitating rapid adaptation and enabling cross-sectoral One Health transmission. National surveillance, foodborne outbreak investigations, and whole-genome sequencing data show that food-animal reservoirs are active evolutionary niches that drive pathogen diversity and fitness, rather than serving merely as contamination sources. Whole-genome sequencing also pinpoints high-risk clones (e.g., ST394) and plasmid-mediated co-selection of virulence and AMR. The emergence of hybrid pathotypes (e.g., STEC/ETEC) and AMR-virulence co-selection challenges traditional classification and limits the effectiveness of conventional surveillance approaches. The 2017 colistin ban reduced mcr-1, yet ongoing resistance and emerging tet(X4) demand integrated surveillance. Collectively, these findings call for reconceptualizing E. coli as a dynamic genomic entity embedded within a unified ecological network. Addressing this threat requires an integrated One Health strategy including genomic surveillance, agricultural antimicrobial stewardship, and coordinated food-environment-clinical monitoring to prevent high-risk clone emergence and global spread.

Animals↗

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

Relationships among mechanisms in psychosocial treatments for chronic pain: mechanism to mechanism lagged effects and relationships with outcomes.

Results suggest that psychosocial treatments for chronic pain work via several mechanisms, and that they often do so to similar degrees and in similar ways. Extant research, however, has focused on individual and/or independent effects of mechanisms on outcomes. Whether successful outcomes are also partly because of sequential and meaningful relationships among and between mechanisms-mechanism-to-mechanism effects-has not been examined. Secondary analyses were conducted of an RCT that compared cognitive therapy, mindfulness-based stress reduction, and behavior therapy to treatment as usual in a sample (N = 521) of people with chronic low back pain. Results of hierarchical linear modeling revealed that (1) Treatment Condition × Mechanism interactions predicting changes in other mechanisms were nonsignificant; (2) lagged prior session mechanism changes predicted next session changes in another mechanism; (3) lagged relationships between pain catastrophizing and pain self-efficacy were reciprocal, whereas links between lagged pain catastrophizing and mindfulness changes and lagged pain catastrophizing changes and behavioral activation changes were unidirectional; and (4) individual differences in the strengths of mechanism-to-mechanism relationships predicted pre- to post-treatment changes in outcomes. Results reveal heretofore hidden therapeutic processes that cognitive therapy, mindfulness-based stress reduction, and behavior therapy may share. Namely, that mechanism-to-mechanism lagged effects do indeed emerge beyond mechanism-to-outcome effects. Findings show not only that mechanisms may change in definable sequences relative to each other but that individual differences in the strengths of mechanism-to-mechanism relationships may themselves be predictive of outcomes.

Humans↗

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

New Evidence in Heart Failure: 2026 Update.

Heart failure (HF) remains a major cause of morbidity, mortality, impaired quality of life and healthcare expenditure worldwide. The global burden of HF continues to increase due to population aging, improved survival, and the growing prevalence of cardiovascular, renal, and metabolic comorbidities. Simultaneously, the pace of scientific progress in HF has accelerated considerably. Recent advances have refined our understanding of HF epidemiology, prognosis, and disease trajectories, including emerging concepts of HF improvement, remission, and recovery. The Second Universal Definition of HF has also updated the classification framework, moving beyond the traditional ejection fraction-based categories. HF is now broadly classified into two major phenotypes: heart failure with reduced ejection fraction (HFrEF) and heart failure with preserved ejection fraction (HFpEF). Novel mechanistic insights highlight the role of inflammation, immune activation, metabolic dysfunction, mitochondrial biology, and multisystem interactions in HF progression. There has also been significant progress in the characterization and management of major comorbidities, including chronic kidney disease (CKD), diabetes, obesity, atrial fibrillation (AF), pulmonary hypertension, frailty, malnutrition, and cancer. Diagnostic innovations include novel biomarkers, multi-omics technologies, artificial intelligence-based approaches, advanced imaging techniques, congestion assessment tools, and emerging digital health solutions. Important advances have occurred in specific HF aetiologies, including cardiomyopathies, cardiac amyloidosis (CA), myocarditis, arrhythmia-induced cardiomyopathy (AiCM), and Chagas cardiomyopathy. Therapeutic developments continue to reshape HF management across the spectrum of left ventricular ejection fraction. Recent evidence has focused on optimization of guideline-directed medical therapy in HFrEF, expansion of evidence-based therapies in HFpEF, and growing roles for sodium-glucose cotransporter-2 inhibitors, finerenone, incretin-based therapies, and transcatheter valve interventions. Collectively, these advances support the transition from a predominantly phenotype-based approach towards a more personalized and biologically informed model of HF care, with the potential to further improve outcomes across the entire HF spectrum.

Journal Article↗

PubMed2026

Quality assessment, prognostic factors, and biomarkers for brain tumor analysis: a comprehensive systematic review.

The brain tumors possess different causative factors and properties, making their diagnosis and treatment difficult. Growth of these cancers usually leads to compression of the adjacent nerves and obstruction of the flow of cerebrospinal fluid, thus leading to increase in intracranial pressure. This affects the working of brain in many ways; thus, the difficulty involved in its treatment. With the improvements in technology in neuroimaging, including Diffusion Tensor Imaging (DTI), Positron Emission Tomography (PET), and multiparametric Magnetic Resonance Imaging (mpMRI), the diagnosis process has become easy. The effectiveness of any form of therapy in such patients depends primarily on their prognosis. While it is a common practice that physicians determine the prognosis of the disease by considering the age of the patient, histological grade of the tumor, and resection status, now this method has become more comprehensive by adding molecular signature and genetic analyses to the list of criteria. Next-generation sequencing (NGS) allows a reliable molecular classification. It increases the level of risk stratification, facilitating the application of therapies tailored to individual patients. Thus, molecular oncology has greatly changed our views on brain tumors' pathology and prognosis while neoadjuvant treatments aim at increasing the survival rate. On the other hand, radiogenomics is a field of study that combines non-invasive imaging phenotypes and genomic information in order to find unique molecular signatures of tumors without collecting samples from tumors. Molecular biomarkers are absolutely essential in the diagnosis of cancer, treatment monitoring, and recurrence of cancer. Advances in liquid biopsy technology, particularly the methods for circulating tumor DNA (ctDNA) and Extracellular Vesicle (EV) based analysis, have enabled the possibility of non-invasive monitoring of the progression of the tumors over time. This review highlights key studies and important scientific works about imaging technologies, biomarkers, and prognostic factors of malignant brain tumors.

Humans↗