SEARCH · Search PubMed

Results for “price elasticity of demand”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

2,200 records · Page 2Linked to original sources

PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

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

Plasticity of hepatic metabolism in Arctic char (Salvelinus alpinus) in response to cyclic hypoxia.

The emergence of cyclic hypoxia puts aquatic organisms' homeostasis under significant strain. Energetic metabolism as well as protein synthesis and folding are particularly altered during hypoxia, while reoxygenation imposes an oxidative challenge. Currently, little is known about how hypoxia-sensitive organisms respond to large oxygen fluctuations. Our previous work on Arctic char revealed that this salmonid, despite being strongly affected by acute hypoxia and reoxygenation (H/R), can successfully reestablish homeostasis, notably through adjustments to hepatic mitochondrial metabolism. However, the mechanisms underlying this acclimation remain poorly understood. We hypothesized that Arctic char remodel their hepatic proteome to optimize energy metabolism, reorganize oxygen-demanding pathways, and maintain cellular homeostasis during repeated H/R cycles. By exposing Arctic char to two or fifteen days of diel cyclic hypoxia, we confirmed this species' limited capacity to respond to acute H/R. Nevertheless, after fifteen cycles, fish adjusted their energetic metabolism through coordinated regulation of carbohydrate and lipid pathways and upregulation of amino acid metabolism. Mitochondrial metabolism was strongly reorganized, particularly at the ubiquinone-Complex III interaction level, alongside adjustments in proline utilization and protein processing. Moreover, protein processing and folding pathways were stimulated in both mitochondria and the endoplasmic reticulum. However, chronic cyclic hypoxia may still promote non-mitochondrial ROS production, DNA replication stress, and impaired immune function. This study highlights how a hypoxia-sensitive fish progressively reorganizes its metabolism and oxygen-demanding pathways to establish a phenotype adapted to chronic cyclic hypoxia, while also revealing the physiological costs associated with this acclimation.

Animals↗

PubMed2026

Dual-tasking reveals severity-dependent reorganization of cortical beta energy landscapes in Parkinson's disease.

Dual-task impairment is a hallmark of Parkinson's disease (PD), yet the large-scale neural mechanisms underlying postural-motor interference remain poorly understood. In particular, it is unclear how cortical network dynamics reorganize across disease severity when postural control competes with concurrent task demands. This study investigated EEG-derived beta-band cortical energy landscapes in healthy older adults, early-stage PD, and mid-stage PD during single- and dual-task conditions. Dual-task behavioral cost increased with disease severity for concurrent manual performance (p < 0.001), whereas a quadratic pattern was observed for postural performance. Energy landscape analysis revealed severity-dependent reconfiguration of cortical beta dynamics. Dual-task-related landscape changes in effective network flexibility (ΔNeff), landscape geometry (ΔEvar and ΔGmag), and dominant low-energy attractor organization (ΔLow mass and ΔLow area) showed significant monotonic trends (p < 0.05), reflecting progressive constrained cortical network dynamics with advancing PD severity. In addition, dual-task-related landscape alterations were associated with clinical severity, as indexed by Hoehn and Yahr stage (|r| = 0.353-0.423, p = 0.016-0.048), and showed associations with motor impairment, as measured by MDS-UPDRS part III scores (|r| = 0.333-0.455, p = 0.009-0.063). These findings demonstrate that dual-task demands induce severity-dependent reconfiguration of cortical beta energy landscapes in PD. Energy landscape geometry may capture systems-level neural constraints associated with dual-task susceptibility in PD, providing a physiologically grounded framework to characterize disease-related functional vulnerability.

Humans↗

PubMed2026

Implementing a novel digital health platform for self-management of postmenopausal osteoporosis: A qualitative study of user experiences, perspectives and implementation outcomes.

BACKGROUND: Osteoporosis self-management requires scalable support, and digital health platforms may meet this need. This study aimed to characterise the experiences and perspectives of postmenopausal women who participated in a 12-month randomised controlled trial (RCT) of a digital voice assistant (DVA) delivered osteoporosis self-management intervention, and to assess key implementation outcomes. METHODS: This was a qualitative analysis of interviews with postmenopausal women from the intervention arm (DVA group) of the RCT. The DVA program broadcast education videos, medication reminders, home-based exercise, nutrition advice and monthly quizzes through a DVA device. Semi-structured interviews were recorded, transcribed and managed in NVivo through reflexive thematic analysis, guided by the Practical Planning for Implementation and Scale-Up and Proctor's implementation outcome taxonomy frameworks. Evidence weighting summarised participant coverage and code density. RESULTS: Twenty-two of 25 (88%) DVA group participants completed semi-structured interviews. Thematic analysis identified seven themes mapped to Proctor's implementation outcomes. Evidence weighting indicated strong support for the intervention's appropriateness and acceptability, moderate support for its adoption, fidelity, feasibility and sustainability, and limited support for costs. Participants valued clear audiovisual guidance, conversation-based interactions with natural language, and flexible home-based access to self-management. CONCLUSION: Digital health platforms for osteoporosis self-management appear feasible, acceptable and sustainable among postmenopausal women. Findings indicate that these platforms are approaching readiness for evaluation in implementation-focused settings, contingent on streamlined content, reliable delivery modalities, accessible user support, clear privacy regulations and pragmatic pricing models.

Humans↗

PubMed2026

Targeting SIRT6: the design and therapeutic implications of activators and inhibitors.

Sirtuin 6 (SIRT6) is an NAD+-dependent deacylase that maintains genomic stability, regulates metabolism, and influences aging, making it an attractive but challenging therapeutic target. Pharmacological modulation of SIRT6 holds promise for cancer and metabolic disorders, yet its context-dependent functions demand precise intervention strategies. Potent, selective, and drug-like chemical probes are therefore essential to dissect SIRT6 biology and to validate its therapeutic potential. This review critically evaluates recent medicinal chemistry advances in SIRT6 modulation. We focus on structure-guided design strategies and structure-activity relationships (SAR) that have transformed initial hits into optimized leads for both activators and inhibitors, highlighting the remaining challenges in achieving isoform selectivity and drug-like properties.

Sirtuins↗

PubMed2026

From prediction to mechanism: Explainable AI uncovers plasma and CSF proteomic signatures of Alzheimer's disease.

Alzheimer's disease (AD) plasma and cerebrospinal fluid (CSF) proteomics can distinguish AD from cognitively normal controls, but the generalizability of machine learning performance and the recurrence of biological signals across datasets require cautious interpretation. We developed an explainable artificial intelligence framework spanning two fluids and four ADNI proteomic datasets, covering 2082 modality specific samples, all analysed internally within ADNI. Phase 1 analysed plasma using a 119 analyte NULISA and targeted UPENN panel (n = 727; 216 CE, 511 controls). Phase 2 extended the analysis to CSF using SOMAscan7k, TMT-MS and targeted SET2, with Elecsys Aβ42, Aβ40, total tau and p-tau181 as anchor biomarkers. Only SOMAscan was subject-independent relative to Phase 1 plasma; TMT-MS and SET2 overlapped with Phase 1 for 96.0% and 97.7% of subjects and therefore are not independent replication cohorts. Under subject-level splits with fold internal preprocessing, we compared Elastic Net, Explainable Boosting Machines and gradient boosted trees with SHAP-based explanations. Among the candidate pipelines, we selected the pipeline with the highest held-out test ROC AUC for each platform; the selected values were 0.927 in plasma and 0.954-0.973 across the three CSF datasets. Because the same held out test performance was used for pipeline selection and headline reporting, these are optimistically selected single-holdout estimates, not unbiased estimates of generalizable or clinical performance. Explanations identified five recurring biological axes within ADNI: cholinergic (ACHE), tau/14-3-3 (YWHAG, YWHAZ, YWHAB, YWHAE), neuro-axonal (NEFL, NEFH), microglial/complement (CHIT1, SMOC1, CHI3L1, C7, CFH) and synaptic (NPTXR, NPTX2, DLG4, SYT5, VSNL1, ELAVL2). CSF analyses showed synaptic vesicle-cycle enrichment (q = 2 × 10-6), and CSF YWHAG correlated strongly with total tau (ρ = 0.87). Cross-fluid directional concordance was modest overall (54-57%) but increased to 73-80% among mapped analyte/protein rows reaching q < 0.05 in CSF. These findings provide hypothesis-generating, internally supported evidence within ADNI. Independent external cohorts with locked pipelines are required to evaluate generalizable performance and biological reproducibility; the overlapping TMT-MS and SET2 analyses should not be interpreted as independent replication.

Alzheimer Disease↗

PubMed2026

Discovery and characterization of multifunctional bioactive peptides from Alaska Pollock (Gadus chalcogrammus) milt: hybrid in silico, in vitro, and proteomic approaches.

The growing demand for multifunctional bioactive peptides has sparked interest in underutilized marine by-products as sustainable bioresources. This study explored Alaska Pollock (Gadus chalcogrammus) milt protein as a novel source of peptides with anti-inflammatory, anti-hypertensive, and anti-diabetic effects. Protein composition was analyzed via LC-MS, followed by in silico digestion and bioactivity prediction. Molecular docking identified peptides targeting DPP-IV, α-glucosidase, ACE, GLP-1 receptor, COX-2, MuRF1, and the 20S proteasome. Among the candidates, a promising peptide (CLPPH) was synthesized and validated in vitro, demonstrating inhibitory effects on nitric oxide production, DPP-IV, ACE, and α-glucosidase. These results highlight CLPPH's potential as a multifunctional bioactive peptide and support the valorization of Alaska Pollock milt as a sustainable source for functional foods and nutraceutical applications.

Animals↗

PubMed2026

Evaluation of Physical and Mental Workload and Transfusion Time in Trauma Resuscitation.

BACKGROUND: Trauma resuscitation is time sensitive and complex. Whole blood (WB) and blood components are standard treatments for trauma related hemorrhage, yet their nursing workload and transfusion time have not been well evaluated. PURPOSE: To assess feasibility of a simulation-based crossover trial and obtain preliminary estimates comparing nursing workload and transfusion completion time between WB and blood component administration. METHODS: A randomized crossover pilot study using in situ simulation was conducted with experienced trauma nurses. Time-motion analysis measured transfusion completion time, and the National Aeronautical and Space Administration Task Load Index assessed workload domains. RESULTS: Strong feasibility was demonstrated across recruitment, retention, adherence, and completion. WB was associated with significantly shorter transfusion time, lower overall workload and mental demand, less effort, and better perceived performance. CONCLUSIONS: These findings support the feasibility and justify a fully powered trial. WB may improve resuscitation efficiency and reduce cognitive burden, with potential implications for patient outcomes and nursing workflow.

Humans↗

PubMed2026

External load metrics and monitoring in women's football match play: A systematic review.

This systematic review aimed to identify the most commonly used variables for monitoring external load during elite women's football matches and to compare reporting practices internationally and in Brazil. Searches were conducted in Web of Science, PubMed, and SciELO using the PICOS framework between February and March 2026, resulting in the inclusion of 35 studies. The main outcomes analysed were total distance covered (TD), distance covered across speed zones (HSR, VHSR, sprint), number of accelerations and decelerations, and maximum speed. TD and distance covered across speed zones were the most frequently reported indicators (94.3%), followed by HSR (82.8%) and sprint distance (68.5%). Considerable variability was observed in the classification of speed zones and thresholds used to define accelerations and decelerations, limiting comparisons between studies. External load values varied according to playing position and competition level, with international matches generally imposing greater demands than national competitions. Brazilian research remains limited and demonstrates notable methodological variability. This review proposes standardised speed and acceleration/deceleration thresholds based on the most recurrent ranges reported in the literature, supporting improved consistency in monitoring practices across elite women's football contexts.

Humans↗

PubMed2026

"Out of sync and overlooked" - Relationship between social jetlag and anxiety in adolescents: Systematic review and meta-analysis.

Anxiety is the most prevalent mental health difficulty in adolescence, a period characterised by a shift towards an eveningness chronotype that is not aligned with societal demands (i.e., school start times). Experiencing "social jetlag" (SJL), a discrepancy in weekday-weekend sleep timing, is proposed to be associated with increased anxiety. A PRISMA-compliant systematic review and meta-analysis was conducted to investigate the relationship between SJL and anxiety in adolescents (age range: 12-18 years). Systematic searches were conducted in PsycINFO, Web of Science, Embase, PubMed, MEDLINE, and ProQuest Dissertations & Theses Global on 14th November 2024 to retrieve empirical studies analysing the relationship between SJL and anxiety in 12-18-year-olds. A multi-level random-effect meta-analysis was conducted in R to estimate the magnitude of the association between SJL and anxiety. After screening 2,138 records, 18 studies were included in the systematic review, with 12 included in the meta-analysis (235,526 participants in total) and six in a narrative review. A small association was found between increased SJL and more severe anxiety (Fisher's z = 0.0614, 95% CI [0.0268, 0.0961], p = 0.0011). These findings highlight the importance of addressing behavioural strategies targeting healthy regular sleep as a tool to improve mental health in adolescence.

Adolescent↗

PubMed2026

A systematic review of human avoidance learning: Cognition, computation, and methods.

Avoidance behaviour is fundamental for survival but can become maladaptive in clinical conditions. A large body of literature has accumulated on the dynamics of human avoidance learning. However, current theories and overviews do not provide an exhaustive account of this evidence. In this systematic review, we identify N = 116 studies on human avoidance learning. We analyse these studies with the goal of distilling robust empirical phenomena as a basis for theory-building, and examine their diagnostic value in differentiating between competing theories. We find that the evidence is difficult to reconcile with foundational two-factor and classical safety-signal accounts, and most strongly supports expectancy- and inference-based views, in which avoidance responses are selected with respect to represented consequences. At the same time, no current framework provides a complete account of the evidence: several findings point to an additional role for operant valuation, Pavlovian influences, and contextual or latent-state control over the expression of avoidance. Methodologically, we observe that the problem setting in the most common experimental paradigms is radically simpler than real-world avoidance and therefore unlikely to expose the limits of inferential or reflective mechanisms. Consequently, we argue that paradigms with greater computational demands and more realistic action affordances are required to identify the mechanisms underlying avoidance learning. Collectively, these insights provide a foundation for theoretical refinement, computational modelling, and methodological innovation, with implications for advancing interventions targeting maladaptive avoidance.

Humans↗

PubMed2026

Access Block and Ambulance Ramping: The Canaries of the Healthcare System.

OBJECTIVE: To identify evidence-based factors leading to the global challenge of hospital access block and inform strategies to improve emergency access performance. METHODS: A mixed methods approach was followed comprising an umbrella review of published systematic reviews, qualitative analysis of the perspectives of patients and healthcare workers, and quantitative analysis of contextual factors and 6 years of ambulance, emergency inpatient and ward movement records for the 25 largest public hospitals in Queensland, Australia. RESULTS: A key set of findings and recommendations were identified to improve emergency access that are practical and actionable. These comprise the introduction of inpatient discharge metrics and monitoring to shift focus from the front door of hospitals to the 'back door'; increasing support for primary care, community care, aged care, NDIS and vulnerable groups; maintaining demand-side strategies such as increasing inpatient-equivalent care alternatives (e.g., hospital in the home, acute care within nursing home services); investment in prehospital flow; improving hospital processes such as extended-hour discharge lounges; improving workforce; and revising funding policies. CONCLUSIONS: The study findings fill a gap in the evidence regarding challenges and recommendations for improving patient flow within hospital emergency departments and across the broader health system. Focussing efforts at the 'back end' of the inpatient journey is a critical step to improve emergency care outcomes.

Humans↗

PubMed2026

Prevalence and risk factors of nutritional anaemia among adolescents in India: a systematic review with meta-analysis of prevalence.

BACKGROUND: Nutritional anaemia is a major public health concern among adolescents in India, threatening physical growth, cognitive development, and future maternal health. This systematic review with meta-analysis of prevalence aimed to estimate the pooled prevalence of nutritional anaemia among Indian adolescents aged 10-19 years and identify key associated risk factors. METHODS: A systematic search was conducted across PubMed, Embase, Web of Science, and Scopus up to February 2025. Data were extracted on study design, setting, diagnostic methods, prevalence, and risk factors. Quality was assessed with a modified Newcastle-Ottawa Scale. A random-effects meta-analysis estimated pooled prevalence, with subgroup analyses by state and gender, and pooled odds ratios for risk factors. RESULTS: Forty-five studies encompassing diverse Indian regions and 159,979 adolescents were included. The pooled prevalence of nutritional anaemia was 56% (95% CI: 49%-63%), with higher rates among girls (62%) than boys (39%). Iron deficiency (OR 2.38-4.68), other micronutrient deficiencies, low socioeconomic status, poor dietary diversity, female gender, and inadequate supplementation were consistently associated with higher anaemia risk. CONCLUSION: Nutritional anaemia impacts more than half of Indian adolescents, with notable regional and gender differences. Its complex nutritional, socioeconomic, and behavioural causes demand targeted, context-specific interventions to enhance adolescent health nationwide.

Humans↗

PubMed2026

A black soybean yoghurt fermented with a reusable probiotic cellulose gel: beneficial effects and metabolic characteristics.

The demand for plant-based yoghurts is continuously increasing. However, achieving stable physicochemical properties and acceptable flavor of the plant-based yoghurts remains challenging. In our previous work, we encapsulated Lactiplantibacillus plantarum (L. plantarum) LCC-605 biofilm into bacterial cellulose (BC), obtaining a LP605@BC gel. LP605@BC gel exhibited excellent harsh-environment resistance abilities and storage stability, and is very suitable as a starter culture. In this work, we used LP605@BC as a starter culture to prepare the fermented plant-based yoghurt (e.g., black soybean yoghurt, BSY-LP605@BC). After fermentation, the inverted nonflowing yoghurt was formed due to the strong interaction between protein and exopolysaccharide (EPS) produced by LCC-605 during fermentation. In addition, the water holding capacity (67.2%) of BSY-LP605@BC was also greatly improved. The viable bacterial counts in BSY-LP605@BC reached 11.2 log CFU/mL after 21 days of storage. BSY-LP605@BC showed increased antioxidant, cholesterol-lowering abilities, and hypoglycemic potential compared with the unfermented black soybean milk. Interestingly, LP605@BC could be reused at least 5 times, demonstrating excellent sustainability. Significant metabolomic differences between BSY-LP605@BC and the black soybean milk were observed via untargeted metabolomic analysis, further proving the beneficial effects of BSY-LP605@BC. Overall, our work developed an effective reusable starter culture for preparing the plant-based yoghurt in a sustainable manner, providing a new design direction and form of starter culture.

Yogurt↗

PubMed2026

Temporal redistribution of control reveals age-related differences in task switching at the level of preparation.

Task-switching studies often report minimal age-related differences in switch costs, leading to the conclusion that switching-related control processes are relatively preserved in aging. However, this conclusion is based on paradigms that confound preparatory and execution processes. This study examined whether age-related differences in semantic task-set reconfiguration may be underestimated due to this confound. In Experiment 1 (36 young and 30 older adults), participants performed an externally paced task-switching paradigm without control over preparation. In Experiment 2 (28 young and 28 older adults), a self-paced paradigm allowed participants to initiate stimulus onset, enabling measurement of preparation time. Across both experiments, reaction time (RT) and error rate (ER) showed reliable age effects but no interactions between age and condition, whereas switching-related condition effects varied across measures and experiments. The expression of switching-related costs differed across measures and task structures. Local switch costs were expressed in ER in Experiment 1 but in RT in Experiment 2. Global switch costs (all-switch vs. all-repeat) were observed in execution measures only in Experiment 1. In Experiment 2, preparation time showed reliable mixing, local, and global switching effects, with age-related amplification emerging specifically for global switching. These findings indicate that switching-related costs are redistributed across processing stages and behavioral measures. The results suggest that age-related modulation of semantic task-set reconfiguration may emerge more clearly during preparation than task execution, particularly under continuous switching demands. Preparation time is interpreted cautiously as reflecting participant-regulated preparatory processes rather than a pure measure of preparation efficiency.

Humans↗

PubMed2026

Continuous Ultrasound-guided Erector Spinae Plane Block Versus Thoracic Paravertebral Block for Postoperative Analgesia in Patients Undergoing Thoracotomy.

OBJECTIVES: To compare postoperative analgesia using continuous ultrasound-guided erector spinae plane block (ESPB) versus thoracic paravertebral block (TPVB), with dynamic visual analog scale (VAS) during coughing as the primary outcome. Secondary outcomes included static VAS (at rest), hemodynamic changes, side effects, total opioid consumption, time of first rescue analgesia, length of hospitalization, anesthesia recovery time, postanesthesia care unit stay, time to first ambulation, and patient satisfaction. METHODS: The study included 40 cases scheduled for elective thoracotomy admitted to the cardiothoracic surgery unit of Menoufia University Hospital. Patients were equally randomized into 2 groups, 20 patients each receiving either ultrasound-guided ESPB or TPVB (control group). Both groups received 20 mL of 0.25% bupivacaine as a loading dose followed by continuous infusion of 0.125% bupivacaine at 5 mL/h, with patient-controlled boluses of 20 mL on demand. RESULTS: Dynamic visual analogue pain scale scores were significantly lower in the ESPB group at 6, 9, 12, and 24 hours ( P =0.008, 0.035, 0.001, 0.006). Morphine consumption was significantly reduced in the ESPB group ( P < 0.001). Hypotension was more frequent in TPVB (40% vs. 10%, P =0.028). No significant differences were observed in hospital stay or patient satisfaction. DISCUSSION: The utilization of continuous ultrasound-guided ESPB demonstrated better postoperative visual analogue pain scale scores and a significant decrease in opioid consumption, with fewer side effects than TPVB.

Humans↗

PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗