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PubMed2026

Digital healthcare solutions in preoperative care: A systematic review.

OBJECTIVE: Active participation in preoperative anesthesia preparation is crucial to ensure safe and efficient care. Compliance with preoperative instructions improves clinical outcomes, enhances patient satisfaction and optimizes use of healthcare resources. As digital communication becomes increasingly integrated into healthcare, interactive digital tools such as smartphone applications and Short Message Service (SMS) reminders may offer a valuable means of engaging patients in their own care. In this review, we evaluated the role of digital tools in guiding patients during their preoperative care pathway for anesthesia. METHODS: Following registration (CRD420250655119), we conducted a systematic review of studies evaluating the use of smartphone applications or SMS reminders designed to support preoperative preparation for anesthesia or procedural sedation in adult patients undergoing elective procedures. The primary outcome was compliance with preoperative instructions. Secondary outcomes included rate of late cancellations, patient satisfaction and cost-effectiveness. Studies were eligible if they reported at least one of these outcomes. RESULTS: Ten studies (1 RCT and 9 observational studies), including 11501 participants, were identified. Compliance with preoperative instructions was assessed in 8 studies, most of which reported higher compliance in patients receiving digital interventions across multiple instruction domains, although statistical significance was not consistently observed. Evidence suggested a beneficial effect on reducing late cancellations and improving patient satisfaction. However, results varied across study designs, and data on cost-effectiveness were limited. CONCLUSIONS: Digital tools for preoperative anesthesia guidance were associated with higher compliance and showed potential reduction of late cancellations and increase of patient satisfaction. However, the current evidence is predominantly observational and heterogeneous, limiting the strength of conclusions. PRACTICAL IMPLICATIONS: With healthcare systems under pressure, digital technologies may offer a scalable and patient-centered care solution to support preoperative anesthesia preparation. Nonetheless, further high-quality research is needed to evaluate their long-term clinical, economic and equity implications.

Humans↗
PubMed2026

Post-intervention effectiveness of a computerized personalized cognitive stimulation program adapted according to cognitive reserve in older adults without cognitive impairment in Primary Care: A randomized clinical trial.

BACKGROUND: Cognitive reserve may influence responsiveness to cognitive interventions, yet it is rarely used to tailor computerized stimulation. OBJECTIVE: To evaluate the effectiveness of a computerized cognitive stimulation program personalized according to cognitive reserve on cognition, reserve-related activities, and digital competence in community-dwelling older adults without cognitive impairment in Primary Care. METHODS: In this randomized clinical trial, 102 adults aged ≥65 years with normal cognitive performance were recruited from three primary care centers in Zaragoza, Spain, and stratified by cognitive reserve level before random allocation to intervention or control. The intervention comprised digital literacy sessions followed by 8 weeks of home-based computerized cognitive stimulation tailored to participants' cognitive reserve profiles and life history. Controls received a single group-based health education session focused on maintaining everyday cognitive activity. Outcomes were assessed at baseline and post-intervention using global cognition (MEC-35), the Cognitive Reserve Questionnaire, the Mobile Device Proficiency Questionnaire-16, and domain-specific neuropsychological tests. A total of 100 participants completed the final evaluation and were included in complete-case analyses. RESULTS: Compared with controls, the intervention group showed greater adjusted post-intervention improvements in global cognition (MEC-35 between-group difference: 1.8 points) and several cognitive measures, including temporal orientation, calculation, attention, praxis, verbal fluency, processing speed, executive functions, and verbal learning. CRQ scores and digital competence also improved, with small-to-large effect sizes. CONCLUSIONS: A computerized cognitive stimulation program adapted according to cognitive reserve appears feasible in Primary Care and may improve cognition, engagement in reserve-related activities, and digital competence in older adults without cognitive impairment.

Humans↗
PubMed2026

Patient-reported outcome measures within European cohorts of severely injured patients: a systematic review and meta-analysis.

PURPOSE: Severe injury affects multiple health-related domains, yet comprehensive European data on patient-reported outcomes remain limited. This systematic review and meta-analysis evaluates patient-reported outcome measures (PROMs) use and outcomes in severely injured European cohorts. METHODS: A systematic search of four databases up to October 14, 2025, identified European studies from 2000 onward reporting PROMs in severely injured patients. Severe injury was defined as an Injury Severity Score ≥ 16, Glasgow Coma Scale ≤ 8, intensive care unit admission, spinal cord injury, traumatic amputations, or pelvic fractures. Two reviewers independently screened records, with disagreements resolved by a third reviewer. Meta-analysis was performed when ≥ 3 studies reported comparable PROMs at similar follow-up timepoints. RESULTS: Of 2,479 studies, 119 were included. Most cohorts originated from the Netherlands (26%), Norway (18%), and Germany (16%). General severely injured cohorts were most frequently studied (61%), followed by traumatic brain injury (17%), and spinal cord injury (15%). In total, 94 PROMs were used across 277 follow-up timepoints. Health-related quality of life was assessed most frequently (63%), after that anxiety/depression (14%), post-traumatic stress (9%), and social functioning (6%). At one year follow-up, the pooled EuroQol-5D-3 L index score was 0.70 (95% CI 0.62-0.77) and VAS score was 68 (95% CI 60-75), indicating persistent impairment compared to population norms. CONCLUSION: Severely injured patients show persistent impairments with incomplete restoration of pre-injury functioning. Despite increased PROMs use, heterogeneity in selection and outcome reporting limits comparability, underscoring the need for standardised PROM assessment to improve outcome evaluation after severe injury.

Humans↗
PubMed2026

Genome-wide characterisation of the myosin light chain gene family in Chinese perch (Siniperca chuatsi) and its expression patterns in muscle fibre types and injury response.

The Class II myosin light chain (myl) genes in Chinese perch (Siniperca chuatsi) have not yet been systematically characterised, and relationships with muscle fibre specification, development, and injury-associated remodelling remain unclear. In this study, fast and slow muscle fibres were initially distinguished using myofibrillar ATPase histochemistry. Subsequently, genome-wide mining identified 16 Class II myl genes, comprising eight essential and eight regulatory light-chain subunits. Their conserved-domain features, chromosomal distribution, phylogenetic relationships and expression profiles were analysed. Transcriptomic profiling showed that summed myl transcript abundance was higher in fast muscle than in slow muscle, accounting for 67.2% of the pooled myl transcript pool across the two muscle types (paired t-test, raw P = 0.036). mylpfa, myl1 and mylz3 were the major fast-muscle-associated genes, whereas myl10, myl2b and myl13 were preferentially expressed in slow muscle at the transcript level. These patterns support these genes as candidate fibre-type-associated expression markers. Developmental profiling identified stage-associated myl expression patterns, including a possible expression shift between mylpfb and mylpfa. In the descriptive injury-repair time course (d0-d7), FPKM profiles indicated that fast-muscle-associated genes (mylpfa, mylz3 and myl1) were lower at d1 and recovered by d3, whereas several slow-muscle-associated genes showed biphasic transcript-level increases. The slow-muscle-associated RLC gene mylpfb showed a delayed expression peak at d7. Notably, the embryonic isoform myl6l showed a modest increase from approximately 2 FPKM at d0 to 4-5 FPKM after injury, suggesting a possible injury-associated expression pattern that requires further validation. Together, these findings provide a genome-wide description of the Chinese perch myl gene family and identify candidate fibre-type-associated genes and descriptive injury-associated isoform expression patterns.

Animals↗
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

Multi-omics reveals that burdock seed aglycone alleviates renal fibrosis by restoring mitochondrial oxidative phosphorylation function.

Renal fibrosis (RF), a common pathological process driving chronic kidney disease (CKD) progression to end-stage renal failure, is closely associated with oxidative phosphorylation (OXPHOS). Arctigenin (ATG), the main active component of burdock seed, exhibits anti-inflammatory and anti-fibrotic activities, but its mechanisms in RF treatment remain unclear. Here, we performed integrated transcriptomic and proteomic analyses to identify key targets and pathways of ATG in a unilateral ureteral obstruction-induced rat RF model. Multi-omics enrichment analysis revealed that NDUFS8 and NDUFS2 were the core targets of ATG, with the OXPHOS pathway as the central intersecting pathway. Our results suggest that ATG exerts anti-renal fibrosis effects by targeting the OXPHOS pathway to inhibit excessive reactive oxygen species production and oxidative stress. SIGNIFICANCE: Chronic kidney disease (CKD) continues to impose an escalating global health and socioeconomic burden, while renal fibrosis (RF), as the convergent pathological endpoint of virtually all progressive nephropathies, remains the principal determinant of irreversible renal failure and adverse clinical outcomes. Despite extensive efforts to develop antifibrotic therapies, effective clinical interventions remain elusive, largely due to the complex and multifactorial nature of RF pathogenesis. In this study, we employed an integrated multi-omics framework encompassing transcriptomics, proteomics, and metabolomics to systematically decipher the antifibrotic mechanism of arctigenin (ATG), a bioactive natural compound derived from traditional Chinese medicine. Our findings identify mitochondrial oxidative phosphorylation as the pivotal regulatory axis underlying the renoprotective effects of ATG and further establish key catalytic subunits of mitochondrial complex I as its direct molecular targets. Mechanistically, ATG not only restores complex I activity and reprograms mitochondrial energy metabolism but also preserves the intracellular stability and localization of these subunits, thereby preventing their aberrant release-mediated inflammatory activation and disrupting the self-perpetuating cycle linking metabolic dysfunction, inflammation, and fibrosis progression. Beyond revealing a previously unrecognized dual mechanism integrating metabolic and inflammatory regulation, this study provides compelling evidence that mitochondrial dysfunction is not merely a secondary consequence of tissue injury but a fundamental driver of fibrotic remodeling. Importantly, our work highlights the translational potential of natural product-based mitochondrial interventions for CKD treatment and supports a broader conceptual shift toward metabolism-centered therapeutic strategies for chronic fibrotic diseases. Given the central role of mitochondrial dysfunction across multiple organs, these findings may also have far-reaching implications for the treatment of systemic fibrosis-related disorders beyond the kidney.

Animals↗
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

Effect of Local Anesthetic Solution at Different Temperatures for Epidural Labor Analgesia on Intrapartum Fever: A Randomized Clinical Trial.

BACKGROUND: Whether heating local anesthetic solutions to core body temperature (37°C) for epidural labor analgesia reduces intrapartum fever incidence remains undefined in the current literature. METHODS: This double-blind randomized controlled trial (RCT) enrolled 220 nulliparous parturients (18-35 years, American Society of Anesthesiologists [ASA] physical status II, term singleton pregnancy). Participants were randomized to receive epidural labor analgesia with 0.075% ropivacaine + 0.5 µg/mL sufentanil at 37°C (warmed group) or 22°C (room-temperature group). Epidurals were placed at L3-L4 with a test dose of 3 mL of 1.5% lidocaine at room temperature, followed by programmed bolus epidural analgesia (initial 10 mL, 10 mL/h) and patient-controlled epidural analgesia (PCEA) 5 mL (30-minute lockout). Tympanic temperature was measured every 30 minutes from epidural initiation to delivery, defining intrapartum fever as ≥38°C. The primary outcome was fever incidence, on which the power analysis was based, and also maximum temperature and shivering. Secondary outcomes comprised analgesia onset, block level, labor durations, neonatal Apgar scores, umbilical cord blood pH and BE, and maternal adverse events. RESULTS: A total of 220 parturients were included (warmed group, n = 110; room-temperature group, n = 110). The warmed group had a lower intrapartum fever incidence (15.5% [17/110] vs 30.9% [34/110], relative risk [RR] 0.5 [95% confidence interval {CI}, 0.298-0.840]; P = .007); however, the reduction of 49.8% did not reach the preset clinically meaningful difference of 60% reduction proposed in the power analysis. The maximum body temperature was also lower in the warmed group: median (interquartile range [IQR]) 37.4 (IQR, 37.2-37.7) °C vs 37.6 (IQR, 37.3-38.0) °C, median difference -0.2 (95% CI, -0.3 to -0.1) °C ( P = .006). Shivering incidence was not different between groups (10.9% [12/110] vs 14.5% [16/110]; P = .418). No statistically significant differences were observed between groups in any of the secondary outcomes assessed, including block characteristics, local anesthetic consumption, labor duration, neonatal outcomes, and maternal adverse events. CONCLUSION: Although we found a 50% reduction in the incidence of temperature rise using warmed (37°C) local anesthetics for epidural labor analgesia, this did not reach our preset threshold of 60% reduction.

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

Navigating Social Media: Balancing Connectivity With Media Literacy to Combat Misinformation and Protect Mental Well-Being.

BACKGROUND: The pervasive use of social media has created a complex digital ecosystem where high connectivity coexists with significant challenges, including the rapid spread of misinformation, particularly regarding mental health, and documented negative impacts on psychological well-being. Platform architectures designed for engagement maximization have been identified as central factors in both issues. OBJECTIVE: This paper critically analyzes the interconnected relationships between social media use, misinformation dissemination, and mental health impacts, with particular attention to psychiatric misinformation across diagnostic categories (e.g., depression, anxiety, ADHD). A primary objective is to evaluate the potential of advanced critical digital literacy frameworks to serve as protective mechanisms against these dual threats. METHODS: A systematic search was conducted following PRISMA 2020 guidelines across APA PsycInfo, PubMed, JSTOR, and Google Scholar for literature published between January 2018 and March 2026 (updated from the original 2023 search). The search yielded 2672 records. After removing 624 duplicates, 2048 records underwent title and abstract screening, with 1802 excluded. The remaining 246 full-text articles were assessed for eligibility, resulting in 86 studies included in the final qualitative synthesis. Inter-rater reliability was established (Cohen's κ = 0.82). Quality assessment was conducted using the Joanna Briggs Institute Checklist, AXIS, and CASP tools, with findings weighted by methodological quality. A thematic analysis was undertaken to synthesize findings. RESULTS: The analysis reveals that core architectural features of social media platforms, algorithmic curation and engagement-based metrics, simultaneously foster environments ripe for misinformation spread and contribute to psychological distress, including anxiety, depression, and harmful social comparison. Psychiatric misinformation specifically (e.g., inaccurate claims about treatment effectiveness, diagnostic criteria, and medication side effects) represents a growing concern, particularly on image- and video-based platforms. The findings indicate that conventional media literacy approaches focused solely on fact-checking are insufficient. Instead, a critical digital literacy framework encompassing algorithmic awareness, data literacy, and emotional awareness is essential for building user resilience, with evidence from high-quality systematic reviews supporting this approach. CONCLUSIONS: Navigating the complexities of modern social media requires an integrated approach combining "pedagogies of play" for experiential skill development with advocacy for structural change (e.g., algorithmic transparency, well being by design principles). This dual strategy empowers individual users to critically engage with digital content while advocating for ethical platform design, thereby safeguarding both mental well-being and democratic discourse. Implications for educators, mental health professionals (including competencies for addressing patient encounters with psychiatric misinformation), policymakers, and platform designers are discussed.

Humans↗
PubMed2026

Characterisation of HIV-1 Gag Cytotoxic T-Lymphocyte Epitopes in the Southern African Region-A Systematic Review.

During early HIV-1 infection, robust Cytotoxic T-lymphocyte (CTL) responses are mostly targeted at immunodominant Gag p24 epitopes to reduce HIV-1 viraemia to a set-point. The aim of this study was to review the current body of knowledge on HIV-1 Gag CTL epitopes in the southern African region where subtype C is prevalent. Peer-reviewed records were obtained from three databases: PubMed Central, Web of Science Core Collection, and Scopus, using the following search terms: HIV subtype C Gag epitopes, and HIV clade C Gag epitopes. The search results were restricted to countries within the southern African region, and only data published in English and between the years 2000-2025 were considered for this review. The search from the three databases produced a total of 2103 peer-reviewed records, and 49 records were included in the review. The majority of studies (58.44%) were conducted in South Africa, followed by Botswana (15.58%), Zambia (10.39%), Malawi (7.79%), Zimbabwe (6.49%) and Angola (1.30%). There were no studies identified from other southern African countries. A total of 60 Gag CTL epitopes were identified, of which 17 (28.33%) were located within the matrix protein (p17), 33 (55.00%) within the capsid protein (p24), and 4 (6.67%) within the Gag polyprotein (p2p7p1p6). The commonly detected immunodominant epitopes were mostly located within the Gag p24 protein; and included TPQDLNTML (TL9, Gag p24 48-56) and TSTLQEQIGW (TW10, Gag p24 108-117) present at 16.00% and 13.3%, respectively. The proportion of HLA-A, B and C allotypes in this systematic review were 18%, 78%, and 4%, respectively. The more common HLA-B allotypes that restrict immunodominant Gag epitopes and facilitate better control of HIV-1 were HLA-B*57, -B*58:01, -B*42:01 and -B*81:01. This systematic review has provided important insights into the description of immunodominant Gag epitopes and HLA-I alleles that contribute to the control of HIV-1 viraemia in the southern African region. It has also exposed that some CTL epitopes identified in the southern African studies are not reported on the Los Alamos HIV database (LANL HIV database). This highlights a need to have this database updated with this information as it is used as a reference for epitopes. This review could provide insights into the design of an epitope-based HIV-1 vaccine that would also be effective in the southern African region.

Humans↗
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↗