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PubMed2026

Comparative Effectiveness of Pharmacogenomics for Treatment of Depression.

PURPOSE/BACKGROUND: Pharmacogenomics (PGx), or the use of genetic information to assess drug-gene interactions, is an important step toward precision medicine. It is unclear if clinician use of PGx yields better outcomes for their patients. This study compared the effectiveness of combinatorial PGx-guided plus guideline-informed treatment (PGx+GIT) with guideline-informed treatment (GIT) alone to improve well-being in individuals with major depressive disorder. METHODS/PROCEDURES: Eligible participants (N=201) were randomized to PGx+GIT or GIT alone. PGx was measured with the proprietary GeneSight combinatorial test. PGx+GIT participant clinicians received test results within 2 business days to inform decisions about medication changes. Participants completed the World Health Organization Well-Being Index (WHO-5), Patient Health Questionnaire (PHQ-9), and PROMIS Profile physical functioning and social roles and activity domains every 2 weeks for 2 months and then every 2 months for the remaining 10 months. Monthly medication changes operationalized as necessary clinical adjustments were tracked with the medication recommendation tracking form. FINDINGS/RESULTS: Both groups improved average well-being over the 12-month study period (model-based change in WHO-5 per log (week) [95% CI]: 4.1 [3.3, 5.0] PGx+GIT and 4.8 [4.0, 5.5] GIT). PGx+GIT did not result in superior improvement in well-being (model-based difference [95% CI]: -0.6 [-1.8, 0.5], P =0.270), or any secondary outcomes. The effect of randomized treatment on well-being was not moderated by depression severity, number of previous failed medications for major depressive disorder, or presence of a comorbid condition. IMPLICATIONS/CONCLUSIONS: These data suggest PGx+GIT was not superior to GIT alone, possibly due to a ceiling effect of GIT, or PGx did not yield better results.

Humans↗

PubMed2026

Effects of hospital planning reforms on access, costs, efficiency, and quality of care in OECD countries: Systematic review and meta-analysis.

BACKGROUND: Many OECD countries have implemented hospital planning reforms to rising healthcare costs, demographic changes, and concerns about access, efficiency, and quality of care. Despite broad implementation, evidence on effectiveness remains fragmented and country-specific. OBJECTIVE: To synthesize evidence on the effects of hospital planning reforms aross four outcome domains: access, costs, efficiency, and quality of care. METHODS: We conducted a systematic review following Cochrane methodology, searching PubMed and Web of Science (January 2000 - September 2025). Studies were categorized into four intervention types - centralization, minimum volume requirements (MVR), performance-based targets, and governance and ownership restructuring. Risk of bias was assessed using Joanna Briggs Institute checklist for quasi-experimental designs. Where data permitted, random-effects meta-analyses pooled standardized mean differences (SMD) for access and efficiency and risk differences (RD) for quality outcomes. RESULTS: 26 studies from 12 countries were included. Centralization increased patient travel distances and reduced length of stay (SMD -0.09, 95% CI -0.17 to -0.01) and complications (RD -14.52 pp, -25.95 to -3.09), and, jointly with performance-based targets, 30-day readmissions (RD -0.43 pp, -0.65 to -0.22). Mortality effects varied by timepoint and intervention: short-term endpoints were largely non-significant, whereas 90-day mortality was reduced under centralization (RD -0.80 pp, -1.25 to -0.35) and 60-day mortality under MVR (RD -2.00 pp, -2.82 to -1.18). Survival was non-significant throughout. No study examined costs. CONCLUSION: The absence of cost evidence is a critical gap. Substantial heterogeneity reflects variation in reform design and context, underscoring the need to interpret findings by intervention and country conditions.

Humans↗

PubMed2026

The role of artificial intelligence in the diagnosis and prognosis of traumatic brain injury based on brain CT scans: a systematic review.

Traumatic brain injury (TBI) is a leading cause of emergency department visits and a major contributor to injury-related mortality and long-term neurological disability. Non-contrast computed tomography (CT) is the gold-standard imaging modality for the rapid diagnosis of TBI. Clinical outcomes depend strongly on early detection and prompt acute management. Artificial intelligence (AI)-based models may support faster automated identification of traumatic findings and early prediction of patient prognosis. A systematic literature search was conducted in PubMed/MEDLINE, Scopus, IEEE Xplore, ACM Digital Library, and the Cochrane Library in accordance with PRISMA 2020 guidelines to evaluate AI-based models for automated detection of TBI-related findings on CT and for prediction of clinical outcomes. Risk of bias and applicability were assessed using QUADAS-2 for diagnostic accuracy studies and PROBAST + AI for prediction model studies. Twenty-two studies were included. Sixteen studies evaluated diagnostic tasks and 10 evaluated prognostic outcomes, with four studies contributing to both categories. Diagnostic performance was generally high, with many studies reporting AUC values approaching or exceeding 0.90, particularly for larger lesion volumes.Prognostic performance was more variable, with moderate to high discrimination and substantial heterogeneity. Only 9 studies incorporated independent external validation, and performance was frequently lower in external cohorts. All prognostic model studies were judged to be at high overall risk of bias using PROBAST + AI, and most diagnostic accuracy studies also demonstrated high or unclear risk of bias in at least one QUADAS-2 domain, most frequently in patient selection. AI-based models applied to brain CT demonstrate strong technical performance for both diagnostic and prognostic tasks in TBI. However, most studies relied on retrospective designs and lacked independent external validation which limits models generalizability and raises concern for potential overfitting. Prospective, multicenter studies with standardized methodologies and rigorous external validation are required before widespread clinical implementation.

Humans↗

PubMed2026

Clinical Performance in Critical Care Simulation under Sleep Deprivation: Effects of Power Napping in the Recovery Napping Protocol for Anesthesiologist Performance (R-NAP) Randomized Controlled Trial.

BACKGROUND: Sleep deprivation is common among anesthesia residents and impairs both technical and nontechnical skills such as leadership. Napping is recommended in fatigue management across healthcare and other safety-sensitive sectors, yet its effectiveness for healthcare providers remains underexplored. This study evaluated whether a 30-min nap opportunity improved simulated crisis performance after a 24-h shift. METHODS: Residents were tested twice: once rested and once using a 24-h shift to induce partial sleep deprivation. Between sessions, they were trained in fatigue management. In the sleep-deprived condition, they were randomized to a nap opportunity or a control condition. Actigraphy objectively assessed sleep and nap duration. The primary endpoint was overall simulated clinical performance (0 to 200; combined technical and nontechnical scores). Secondary endpoints were technical and nontechnical subscales. Group effects were primarily tested using intention-to-treat regression models adjusted for rested performance, previous sleep, and critical care experience. RESULTS: Thirty-five residents were enrolled (nap opportunity, n = 19; control, n = 16). In the primary analysis sample (n = 27), clinical performance was 14.8 points higher after the nap opportunity compared with controls (95% CI, 2.8 to 26.9; P = 0.018), corresponding to a 7.4% improvement. Technical skills did not differ significantly between groups, although more sleep was associated with better technical performance. Nontechnical skills were higher in the nap opportunity condition (+11.0 points; 95% CI, 2.2 to 19.8; P = 0.016), including significant effects of leadership and resource utilization. Exploratory analyses suggested associations between longer nap duration and multiple performance domains, strongest for technical skills ( P = 0.010). CONCLUSIONS: Napping appears to enhance clinical performance, while the nap opportunity, nap duration, and previous sleep deprivation each influenced technical and nontechnical performance in distinct ways. These findings support integrating napping and recovery into medical education and scheduling.

Adult↗

PubMed2026

Effectiveness of hyperbaric oxygen in traumatic brain injury patients: A systematic review and meta-analysis.

BACKGROUND: Traumatic brain injury (TBI) is the most common neurological disorder and a leading cause of global mortality and disability. Although growing evidence suggests potential benefits of Hyperbaric Oxygen Therapy (HBOT) for TBI, its efficacy remains controversial. METHODS: We systematically searched PubMed, Embase, Cochrane Library, and Web of Science from inception to March 2026. Randomized controlled trials (RCTs) evaluating HBOT versus any comparator including sham, standard care and no treatment in adults with TBI were included. Two independent reviewers screened records, extracted data, and assessed risk of bias using the Cochrane Risk of Bias tool. Heterogeneity was assessed using the I² statistic. Effect sizes were pooled using random/fixed-effects models per heterogeneity results. RESULTS: 8 studies involving 570 participants were included. HBOT significantly improved computerized cognitive performance (SMD = 0.23, 95% CI: 0.07-0.40, p = 0.004, I² = 0%), executive function and processing speed (SMD = -0.59, 95% CI: -0.93 to -0.26, p = 0.0005, I² = 30%), memory function (SMD = 0.33, 95% CI: 0.03-0.63, p = 0.03, I² = 0%), and sleep quality (MD = 1.98, 95% CI: 0.07-3.88, p = 0.04, I² = 65%). No significant benefits were observed for Glasgow Outcome Scale (RR = 1.57, 95% CI: 0.55-4.44, I² = 87%), PTSD symptoms (MD = -3.05, 95% CI: -7.05-0.95, I² = 67%), neurobehavioral symptoms (MD = -9.06, 95% CI: -32.13-14.00, I² = 97%), and emotional distress (SMD = 0.25, 95% CI: -0.32-0.81, I² = 85%). Most adverse events were mild and transient. CONCLUSION: HBOT demonstrates domain‑specific benefits for cognitive function and sleep quality in TBI patients, predominantly those with mild TBI. However, evidence for PTSD, neurobehavioral symptoms, and emotional distress remains uncertain. Furthermore, the applicability of current evidence to moderate-to-severe TBI populations is restricted.

Humans↗

PubMed2026

Multicenter randomized effectiveness/implementation trial of a digital self-management support tool to improve the quality of life during adjuvant hormonal therapy for patients with early breast cancer: The HOPE trial.

BACKGROUND: For patients with hormone receptor (HR) positive early breast cancer (BC), adjuvant endocrine therapy (ET) represents the cornerstone of treatment. However, 75% of patients experience ET-related symptoms that negatively affect their quality of life (QOL). Despite their high prevalence, these symptoms are often underestimated and under-addressed during consultations. As a result, non-adherence to ET is common and remains a major barrier for optimal disease and survival outcomes. METHODS: National, prospective, randomized, open-label hybrid type 1 effectiveness/implementation trial conducted in France comparing a personalized digital health pathway plus standard of care (SoC) vs. SoC alone in patients with HR+ early BC reporting ET-related symptoms. 180 patients will be randomized 1:1 to receive either 12 weeks of the digital health pathway or 12 weeks of SoC. The intervention is anchored by the Resilience© digital companion including remote symptom and needs assessment, an introductory nurse-navigator phone call, and access to personalized, symptom-specific online educational and self-management programs (physical activity, yoga, meditation or cognitive behavioral therapy). In both arms, patients will be invited to wear a wearable device to objectively monitor behavioral parameters. The primary endpoint is the ET symptoms scale of the European Organization for Research and Treatment of Cancer (EORTC) QLQ-BR45 over 12-weeks. Secondary endpoints include other QOL domains, self-reported ET adherence, eHealth literacy, self-efficacy, and evaluation of the implementation process. DISCUSSION: This study should provide evidence on the effectiveness and real-world implementation of a personalized digital health pathway to improve QOL in patients experiencing ET-related symptoms. TRIAL REGISTRATION: ClinicalTrials.gov NCT06781996; Protocol version 3.0.

Humans↗

PubMed2026

Ageing effects on chemical, physical, mechanical, and morphological properties of clear aligners - a systematic review.

BACKGROUND: Clear aligner (CA) therapy has experienced rapid use over the past two decades to treat orthodontic malocclusions. However, evidence on CA material degradation in the oral environment remains limited and often focuses on single brands or isolated material properties. OBJECTIVES: To investigate CA ageing characteristics across different materials and brands and evaluate the chemical, physical, mechanical, and morphological changes following simulated or intraoral ageing. SEARCH METHODS: Five databases (PubMed, Web of Science, MEDLINE [Ovid], ProQuest, and Scopus) were searched to 18 March 2026, with no restrictions. ELIGIBILITY CRITERIA: Studies assessing CA properties after intraoral use or simulated ageing (thermocycling, cyclic loading, or liquid immersion) were included. DATA COLLECTION AND ANALYSIS: Study selection followed PRISMA 2020. RoB was assessed using QUIN for purely in vitro studies, JBI for cohort in vivo studies, and Cochrane RoB 2 for RCTs. Results were synthesised narratively and organised by property domain, as substantial methodological heterogeneity precluded formal meta-analysis. Where protocols were comparable, a simple pooled weighted mean was calculated and presented graphically. RESULTS: Ninety-five studies were included. RoB was low in eight studies, moderate in sixty-two, and high in twenty-five. Chemical composition remained largely stable during ageing, though some brands showed trace elemental release. Physical, mechanical, and morphological properties showed material-dependent deterioration. Pooled discolouration was greatest with coffee (weighted mean ΔE = 70.9), versus tea (ΔE = 18.4) and red wine (ΔE = 11.5), with Invisalign® consistently exceeding the clinically perceptible threshold. Force decay of 40-90% typically occurred within 48 h. Thermoplastic polyurethane (TPU)-based and directly printed aligners (DPAs) generally showed greater susceptibility than polyethylene terephthalate glycol-modified (PETG)-based aligners, though findings on hardness, roughness, and stiffness were inconsistent. CONCLUSIONS: CA materials undergo clinically relevant degradation during use, particularly in TPU-based and DPAs aligners. Clinicians may need to prioritise material-specific protocols, reinforce dietary and cleaning instructions, and consider force decay when determining aligner replacement intervals. PROSPERO number: CRD420251110248.

Humans↗

PubMed2026

Diagnostic performance of machine learning models versus established risk stratification for intracranial aneurysm rupture: a systematic review and bivariate meta-analysis.

BACKGROUND: Machine learning (ML) models have been proposed to improve the discrimination of intracranial aneurysm rupture status beyond established clinical risk stratification tools. However, reported performance is heterogeneous and the relative contribution of model architecture and feature dominance remains unclear. METHODS: We performed a Preferred Reporting Items for Systematic Reviews and Meta-Analyses-diagnostic test accuracy systematic review and diagnostic meta-analysis of studies evaluating ML models for intracranial aneurysm rupture discrimination. PubMed, Embase and CENTRAL were searched to February 2026. Sensitivity and specificity were pooled using a bivariate random-effects model, with summary receiver operating characteristic curves generated across training, internal testing and external validation datasets. Models were compared with regression-based approaches and Population, Hypertension, Age, Size of aneurysm, Earlier subarachnoid haemorrhage, Site of aneurysm (PHASES) scores. Subgroup and meta-regression analyses explored associations between algorithm family and feature domain. RESULTS: Sixty-two retrospective cohorts (29 709 patients 209 models) met the inclusion criteria. In training datasets, pooled sensitivity and specificity for ML were 0.81 (95% CI 0.75 to 0.85) and 0.83 (0.80-0.86), with an area under the curve (AUC) of 0.878, exceeding PHASES (AUC 0.667). In testing datasets, ML retained higher discrimination (AUC 0.837) than regression models (0.806) and PHASES (0.646). In external validation, sensitivity was preserved (0.82), but specificity declined (0.66). Deep learning demonstrated the highest AUCs (training and testing). Incorporation of haemodynamic or radiomic features improved pooled discrimination relative to morphology alone. Evidence of small-study effects and mostly unclear Prediction Model Risk Of Bias Assessment Tool ratings were observed. CONCLUSIONS: ML approaches demonstrate higher pooled discrimination for aneurysm rupture status than conventional risk scores in retrospective datasets, but reduced external validation specificity and heterogeneity limit confidence for clinical translation. Prospective, externally validated, calibrated models are required before integration into routine cerebrovascular risk stratification.

Humans↗

PubMed2026

Data-centric, robust, and explainable multimodal deep learning for clinical decision support: A systematic review.

PURPOSE: Multimodal deep learning is increasingly proposed for clinical decision support (CDS) under a "data-centric" framing that prioritizes label quality, missing-modality robustness, distribution shift, calibration, and explainability. Prior reviews have examined multimodal medical AI, CDS, and data-centric methods separately, but none address their intersection. We mapped the modalities, fusion strategies, and data-centric and explainability techniques used in this recent literature, quantified how often each is implemented rather than merely mentioned, assessed deployment-relevant evidence (external validation, clinical-outcome measurement, equity), and formally appraised study-level risk of bias. METHODS: Following the PRISMA 2020 statement (PROSPERO CRD420261427815; registered retrospectively), we screened 150 records and included primary, clinical, multimodal studies that applied machine or deep learning to a decision-support task and reported at least one quantitative result. Two reviewers screened and extracted data with consensus adjudication. Each study was coded against pre-specified operational definitions, separating implemented or empirically evaluated techniques from those only mentioned. Study-level risk of bias was assessed with PROBAST + AI. Synthesis was narrative. RESULTS: Thirty-one studies met inclusion; 30 (97%) were published between 2024 and 2026, with a median of three modalities (range 2-6), most commonly structured EHR (71%) and imaging (39%). Data-centric techniques were frequently reported (74-84% across label-noise, distribution-shift, calibration, missing-modality and class-imbalance handling; equity 61%). However, external validation was reported in only 4/31 studies (13%), a clinical or provider outcome in 3/31 (10%), and no study reported routine deployment. Overall risk of bias was high in 27/31 studies (87%), driven by the analysis domain. CONCLUSION: Within this recent, self-selected slice of the field, technical robustness and explainability techniques are widely reported but rarely validated out-of-distribution or against clinical outcomes, and the underlying evidence is at high risk of bias. Progress requires external multi-site validation, clinical-outcome measurement, formal bias appraisal, and adherence to AI reporting standards (e.g., TRIPOD + AI) before deployment can be justified.

Deep Learning↗

PubMed2026

Phenotypic and transcriptomic characterization of biallelic RNU2-2 developmental and epileptic encephalopathy.

OBJECTIVE: A significant proportion of individuals with suspected genetic developmental and epileptic encephalopathies (DEEs) remain unsolved following whole genome sequencing (WGS). Here we describe biallelic RNU2-2 variants causing a recently reported, severe, recessive DEE. METHODS: We screened individuals who have received WGS analyses at the Genomic Medicine Centre Karolinska for Rare Diseases for biallelic RNU2-2 variants. Deep phenotyping was performed through reviewing entire medical histories and phenotypic traits were transcribed to their corresponding Human Phenotype Ontology (HPO) term. HPO terms were used to generate pairwise phenotypic similarity scores and assess for significantly shared phenotype enrichment in the RNU2-2 sub-cohort. RNA sequencing analyses were performed in fibroblast and blood tissues to compare splicing events between RNU2-2 individuals and two independent control groups. RESULTS: We identified 14 individuals from nine families with 12 ultra-rare biallelic RNU2-2 variants clustering in the conserved 5' domains. Genotype data from 13 of 14 individuals has been reported previously as part of a larger cohort. All individuals presented with a highly concordant, severe DEE, characterized by severe to profound intellectual disability, inability to walk or communicate, hyperkinesia, and refractory seizures. Infantile spasms and tonic seizures were the predominant seizure types and a Lennox-Gastaut syndrome-like phenotype was common. These individuals had a significantly similar phenotypic signature when compared with 703 individuals with complex pediatric epilepsies (two-sided Monte Carlo permutation test, p = .005). RNA sequencing analyses showed aberrant splicing, with the most pronounced effects in fibroblast tissues in mutually exclusive exon and alternate 3' splice-site events, which were not detectable in blood. SIGNIFICANCE: We present deep phenotyping data and transcriptomic analyses that provide support for rare, 5' clustering biallelic RNU2-2 variants causing this novel, severe DEE. We propose an RNA sequencing methodology on fibroblast tissue for future validation of RNU2-2 variants.

autosomal recessive disease↗

PubMed2026

Contrast Heat-Cold Versus Thermoneutral Showering in Trained Combat Sport Athletes: A Randomized Field Trial of Recovery Outcomes.

Contrast heat-cold showering is popular for recovery, but multisystem evidence and persistence after cessation remain unclear. To evaluate whether a 4-week post-training contrast heat-cold shower intervention produces an integrated recovery profile across four domains (autonomic, endocrine, perceptual, and microvascular) rather than testing a single isolated physiological pathway, across baseline (T0), post-intervention (T1), and 2-week wash-out (T2). Sixty combat-sport athletes were randomized to contrast showers (10 min alternating warm 38-40°C and cold 13-15°C) or an active thermoneutral-shower comparator (10 min, 32-34°C) after training for 4 weeks. Primary analyses were per-protocol (≥ 75% compliance; n = 57), with intention-to-treat sensitivity analyses. Outcomes were Total Quality Recovery (TQR), morning salivary cortisol (two mornings averaged), resting HRV, and post-occlusive reactive hyperemia (PORH). From T0 to T1, favorable between-group changes were observed for resting HR (ΔΔ -2.10 bpm, 95% CI -2.24 to -1.96; g -0.65; p < 0.001), lnRMSSD (ΔΔ 0.123 log units, 95% CI 0.108 to 0.137; g 0.74; p < 0.001), with similar T1 effects for RMSSD and SDNN, and TQR (ΔΔ 0.61 points, 95% CI 0.27 to 0.95; g 0.80; p < 0.001). These T1 autonomic and perceptual changes were not maintained at T2 (all T2-T0 ΔΔ p > 0.05). Cortisol and PORH-derived outcomes showed no statistically clear between-group differences at T1 or T2 (all p > 0.05). Compared with thermoneutral showering, 4 weeks of post-training contrast heat-cold showering produced short-term favorable between-group changes in autonomic regulation and perceived recovery, but not in morning cortisol or PORH-derived microvascular reactivity. These effects were not maintained after wash-out; therefore, causal attribution to the shower intervention alone and claims of persistent physiological adaptation should be made cautiously. Trial registration: ISRCTN15418049.

Humans↗

PubMed2026

Evaluating a culturally adapted question prompt list to improve end-of-life communication among indonesian migrant caregivers: A randomized controlled trial with qualitative insights.

OBJECTIVE: Indonesian caregivers serve as essential providers of end-of-life (EOL) care in Taiwan. But often face communication challenges due to language, cultural, and hierarchical barriers. This study evaluated the effectiveness of a culturally adapted Question Prompt List (QPL). METHODS: This study employed a two-arm randomized controlled trial design supplemented with qualitative interviews. The study was conducted in a hospice ward and home care setting within a medical center in Taiwan. A total of sixty Indonesian caregivers were recruited and randomly assigned to either the intervention group (n = 30) or the control group (n = 30). The intervention group received routine end-of-life (EOL) education along with a culturally adapted Question Prompt List (QPL), which consisted of 37 items covering domains including the dying process, emotional support, communication, symptom management, and care decision-making. The control group received routine EOL education. Outcome measures included caregiving preparedness, communication self-efficacy, satisfaction, and question-asking behavior. In addition, semi-structured interviews were conducted with eight participants, and the data were analyzed using thematic content analysis. RESULTS: Analysis of covariance revealed no statistically significant between-group differences in caregiving preparedness (F = 1.58, p = .215 [-0.41, 0.44]) or communication selfefficacy (F = 0.83, p = .366 [-0.44, 0.79]). However, communication satisfaction was significantly higher in the intervention group (F = 4.19, p < .05 [0.04, 0.44]). The number of questions asked was also significantly higher in the intervention group (t = -4.35, p < .001 [-5.41, -1.98]). Thematic analysis of qualitative data identified 4 themes and 14 subthemes, illustrating how the QPL reduced anxiety, clarified care needs, and improved confidence. CONCLUSIONS: A culturally adapted QPL can enhance communication engagement and satisfaction among migrant caregivers. PRACTICE IMPLICATIONS: Integrating culturally tailored QPLs into caregiver education and palliative care practice may promote more inclusive and effective communication.

Humans↗

PubMed2026

Comparing trajectories of cognitive functioning in treatment-resistant and non-resistant depression: a multicentre linear mixed-effects analysis.

BACKGROUND: Impaired cognitive functioning is a severe symptom in major depressive disorder (MDD). Recent evidence suggests it may be a central characteristic in its treatment resistant form (TRD), potentially constituting a clinical marker for treatment resistance and a target amenable to intervention. To date, cognitive functioning in TRD remains poorly understood and longitudinal investigations are scarce. METHODS: This observational prospective cohort study, including 320 patients diagnosed with MDD from the multicentre PROMPT study, examined differences in cognitive functioning between 118 TRD and 202 non-TRD patients over a period of twelve weeks in a real-world setting, using linear mixed modelling. Patients that failed to respond to at least two prior antidepressants trials at baseline were classified as TRD. RESULTS: TRD patients showed significantly poorer baseline performances than non-TRD patients in attention/processing speed (β = -0.45; 95%CI[-0.70, -0.19]; FDR-p = 0.003) and verbal memory (β = -0.45; 95%CI[-0.72, -0.18]; FDR-p = 0.003). Significant time × group interactions were observed in motor speed and verbal fluency tasks. Post-hoc-analyses revealed stagnation in TRD patients and significant improvement in non-TRD patients. Across all other tasks improvement was observed in both groups, and random effects showed large heterogeneity between patients, indicating notable individual differences in cognitive performances. CONCLUSIONS: The results suggest distinct recovery patters between non-TRD and TRD patients, and diminished functioning in TRD patients at the domain level. However, intact and diminished performances likely occur in both groups, warranting further investigation of cognitive heterogeneity. These short-term findings highlight the need for more comprehensive longitudinal research on cognition in TRD.

Humans↗

PubMed2026

Genome-wide identification and expression profiling of HSD3B and SDR42E1 genes in the Pacific oyster (Crassostrea gigas): potential associations with gonadal development.

Sex steroids are lipid-soluble signaling molecules that regulate sex differentiation, reproductive development and physiological homeostasis in animals. 3β-Hydroxysteroid dehydrogenase/Δ5-Δ4 isomerase (3β-HSD) is a key steroidogenic enzyme, whereas SDR42E1, an extended short-chain dehydrogenase/reductase, has been implicated in sterol- and steroid-related metabolism. However, the composition, evolutionary relationships and expression patterns of the HSD3B- and SDR42E1-related genes in bivalve gonadal development remain poorly characterized. In this study, five PF01073-containing genes, comprising three CgHsd3b and two CgSdr42e1 genes, were identified in the Pacific oyster Crassostrea gigas. Phylogenetic analysis separated the proteins into HSD3B-related and SDR42E1-related groups, and gene-structure and motif analyses indicated subfamily-level divergence. All five proteins retained the SDR domain but differed in exon-intron structure and motif composition. Each contained the extended-SDR TGxxGxxG motif, whereas exact classical [ST]GxxxGxG and NNAG motifs were absent. Tyr- and Lys-equivalent residues were conserved, while the HSD3B1 Ser-equivalent position contained Thr in two C. gigas proteins and Ser in one. These features support their classification as extended-SDR proteins but do not establish enzymatic activity or substrate specificity. The three CgHsd3b genes were dispersed on one chromosome, whereas CgSdr42e1-1 and CgSdr42e1-2 were adjacent on another chromosome, suggesting a possible local duplication event for the CgSdr42e1 pair. Public RNA-seq data showed distinct tissue- and gonadal-stage expression patterns, with several genes displaying gonad-biased or female-stage-associated expression. Independent RT-qPCR profiling of the representative genes CgHsd3b-3 and CgSdr42e1-1 detected stage-dependent expression, although tissue rankings differed from those in the public RNA-seq datasets. These differences may reflect the use of independent biological samples, tissue composition, normalization procedures, and platform-specific measurements. Because enzymatic assays, metabolite measurements, cellular localization, and functional perturbation were not performed, the results identify candidate genes whose expression is associated with gonadal development rather than demonstrating regulatory roles. This study provides a comparative framework for future functional investigation of sterol- and steroid-related metabolism in bivalves.

Animals↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Comparative effectiveness of torsemide vs furosemide in the management of heart failure patients: Win-ratio reanalysis of the TRANSFORM-HF trial.

BACKGROUND: Loop diuretics are widely used for managing congestion in patients with heart failure (HF). The TRANSFORM-HF trial is a multicenter randomized study that enrolled heart failure patients, comparing a strategy of torsemide vs furosemide. The time-to-event analysis demonstrated neutral effects on all-cause death at 30 months and the composite of all-cause death and first rehospitalization at 12 months. We evaluated whether a hierarchical win-ratio (WR) framework integrating mortality, recurrent hospitalization, and patient-reported health status provides additional interpretive insight. METHODS: This study is a secondary analysis of the pragmatic, multicenter, open-label, randomized TRANSFORM-HF trial, conducted across 60 US hospitals that randomized 2,859 patients hospitalized with HF to torsemide or furosemide. The primary 12-month hierarchical composite outcome was defined as (1) all-cause mortality, (2) recurrent all-cause hospitalizations, and (3) lack of improvement in the Kansas City Cardiomyopathy Questionnaire Clinical Summary Score (KCCQ-CSS). The primary statistical method was a WR analysis adjusting covariates via inverse probability weighting. Subgroup analyses evaluated potential heterogeneity across patient demographics and clinical characteristics. RESULTS: In the primary 12-month intention-to-treat analysis, the adjusted WR was 1.07 (95% CI, 0.98-1.16; P = .13), indicating no significant difference between torsemide and furosemide. A supplementary 30-month analysis with extended mortality follow-up yielded a similar estimate (adjusted WR, 1.06; 95% CI, 0.98-1.16; P = .14); hospitalization and KCCQ-CSS components were assessed through 12 months. As-treated sensitivity analyses were consistent with the neutral primary findings. Exploratory subgroup analyses were not adjusted for multiplicity and should be considered hypothesis-generating. CONCLUSIONS: The overall WR comparison between torsemide and furosemide showed no statistically significant difference in the primary 12-month analysis. The WR framework provided an interpretive decomposition across outcome domains but did not establish superiority of either loop diuretic strategy. All findings should be considered exploratory. TRIAL REGISTRATION: ClinicalTrials.gov, NCT03296813, https://clinicaltrials.gov/study/NCT03296813.

Aged↗

PubMed2026

Teach-Back in Clinical Communication: A Systematic Review and Meta-analysis.

BACKGROUND: Teach-back has been identified as a high-quality clinical communication strategy. Our aim was to synthesize current literature on teach-back effectiveness. METHODS: We searched MEDLINE, Embase, and CINAHL Complete databases to identify relevant studies published between 2018 and 2026. We also included pre-2018 studies identified in prior systematic reviews. Studies were eligible for inclusion if they involved adult patients and/or care partners, delivered teach-back in a single encounter, had a comparator group, and reported proximal/intermediate patient outcomes (as defined in our conceptual model). Two independent investigators screened each citation at the title/abstract and full-text levels and assessed risk of bias. Study characteristics and results were extracted. When meta-analysis was performed, we used standardized mean differences (SMD) to estimate summary effects. We assessed certainty of evidence (COE) using Grading of Recommendations Assessment, Development and Evaluation (GRADE) domains. RESULTS: Our systematic review included 18 randomized controlled trials (RCTs) involving 1985 participants. Across 9 RCTs assessing knowledge acquisition, conceptual inconsistencies precluded meta-analysis. Overall, there was no clear pattern of the effect of teach-back on knowledge (very low COE). In a meta-analysis of 5 RCTs assessing self-efficacy (416 participants), we found that teach-back interventions led to a large increase in self-efficacy relative to usual care (SMD = 2.40; 95%CI 0.37-4.44) (very low COE). In a meta-analysis of 7 RCTs assessing adherence to health behaviors (571 participants), teach-back interventions led to a large increase in adherence (SMD = 1.04; 95%CI 0.45-1.64) (low COE). Meta-analyses for both self-efficacy and adherence had large confidence intervals that ranged from small to large effect sizes and had substantial heterogeneity. DISCUSSION: In this systematic review and meta-analysis, we did not identify a clear benefit of teach-back on knowledge acquisition but did find evidence that teach-back improves self-efficacy and self-reported, short-term adherence to health behaviors.

clinical communication↗

PubMed2026

Clinical Utility of Ultra-Widefield Swept-Source OCT for Intraocular Tumors: Comparison With Ultrasonography, SD-OCT, and MRI.

PURPOSE: To evaluate the clinical performance of ultra-widefield swept-source optical coherence tomography (UWF-OCT) in the assessment of choroidal tumors and to compare it with ultrasonography (US), spectral-domain (SD)-OCT, and magnetic resonance imaging (MRI). DESIGN: Retrospective diagnostic comparison. SUBJECTS: Thirty-nine eyes from 39 patients diagnosed with choroidal tumors at a single tertiary referral center. METHODS: This retrospective diagnostic comparison evaluated patients diagnosed with choroidal tumors at a single tertiary referral center between January 2023 and August 2025. All patients underwent UWF-OCT imaging at diagnosis. Tumor measurements obtained with UWF-OCT were compared with US, SD-OCT, and MRI. Comparative analysis among imaging modalities and predictors affecting UWF-OCT applicability was performed. MAIN OUTCOME MEASURES: Tumor thickness (mm) and largest basal diameter (LBD, mm) measurements, and complete measurability rate across different tumor size categories. RESULTS: Thirty-nine eyes from 39 patients (mean age 59.2 ± 16.9 years) were analyzed, including 27 choroidal melanomas (69.2%), 5 metastatic tumors (12.8%), 4 hemangiomas (10.3%), 2 osteomas (5.1%), and 1 (2.6%) indeterminate choroidal melanocytic lesion. UWF-OCT successfully measured both tumor thickness and largest basal diameter (LBD) in 100% (31/31) of small and medium choroidal tumors, substantially outperforming SD-OCT (complete measurement achieved in 63.6% of small tumors, and 0% of medium or large tumors). UWF-OCT measurements were systematically smaller than ultrasonography (thickness: -32.3%, P < .01; LBD: -11.1%, P < .01) and MRI (thickness: -29.2%, P < .01). Mushroom-shaped tumor morphology was the strongest negative predictor of UWF-OCT quality (OR = 0.015, 95% CI 0.001-0.196, P < .01). UWF-OCT's complete measurability was limited in large tumors (12.5%, 1/8). CONCLUSIONS: UWF-OCT provides precise, noninvasive, single-scan assessment of small-to-medium choroidal tumors with detailed structural visualization. It may be particularly useful for dome-shaped tumors, while multimodal imaging with US and MRI remains optimal for complex morphologies. Overall, UWF-OCT represents a valuable tool for diagnosis and treatment planning, with potential utility for longitudinal follow-up in choroidal tumor management.

Humans↗