SEARCH · Search PubMed

Results for “Prenatal Diagnosis”

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.

182 records · Page 2Linked to original sources

PubMed2026

A Systematic Review of Lived Experiences of Receiving a Diagnosis of ADHD in Adulthood.

OBJECTIVE: With rising numbers of adults seeking and receiving ADHD diagnoses, understanding their first-hand experiences of the diagnostic process is key for sensitive support and service design. This systematic review collates, evaluates and synthesises the existing evidence-base on lived experiences of adult ADHD diagnosis. METHOD: Keyword searches of six databases generated 10,357 citations, which were subjected to a systematic screening process that identified 21 relevant studies. Findings were analysed using thematic synthesis. RESULTS: Analysis generated three overarching themes, elaborating how diagnostic experiences are shaped by adults' Relationship with Self, Relationship with Others, and Relationship with Systems. Personally, diagnosis was widely experienced as a pivotal identity event, triggering biographical reflection that could foster greater self-compassion, but also grief, anger and identity confusion. Socially, diagnosis facilitated interpersonal understanding and communication, but also exposed adults to stigma and introduced dilemmas about diagnostic disclosure. Systemically, adults experienced the diagnostic process as beset by barriers and delays, and reported highly variable access to post-diagnosis supports or treatment. CONCLUSION: Results suggest receiving an ADHD diagnosis in adulthood is a complex relational process that can be both validating and destabilising, with variation in experiences resulting from individual biographies, interpersonal resources, stigma climates, and service structures.

Humans↗

PubMed2026

Sitosterolemia: evolving strategies for earlier diagnosis.

PURPOSE OF REVIEW: Sitosterolemia is a rare autosomal recessive lipid disorder caused by biallelic pathogenic variants in ABCG5 or ABCG8 , resulting in excessive intestinal absorption and impaired biliary excretion of plant sterols. Although historically considered exceptionally rare, recent genetic studies suggest the disorder is substantially underdiagnosed, with marked phenotypic heterogeneity ranging from xanthomas and premature atherosclerosis to hematologic abnormalities, and frequently mimics familial hypercholesterolemia. This review summarizes recent advances in the clinical, biological, and genetic diagnosis of sitosterolemia, with a focus on strategies that may facilitate earlier detection. RECENT FINDINGS: Phytosterol quantification, particularly sitosterol, campesterol, and stigmasterol, remains indispensable for accurate diagnosis. Hematologic abnormalities, including hemolytic anemia, stomatocytosis, and macrothrombocytopenia, are increasingly recognized as valuable diagnostic clues complementing the biochemical approach. Expanded variant catalogs for ABCG5/ABCG8 and genome-wide association studies have revealed potentially polygenic contributions to phytosterol metabolism extending beyond these two genes. However, no specific guidelines have yet been established for cascade screening. SUMMARY: Earlier diagnosis requires integration of clinical, biochemical, hematologic, and genetic data. Plasma phytosterol measurement remains the diagnostic cornerstone. Improved disease awareness, broader access to sterol testing, and expanded genetic screening may reduce diagnostic delays and enable timely management, including ezetimibe and dietary phytosterol restriction.

Humans↗

PubMed2026

Efficacy of current approaches to non-invasive diagnosis of skin cancer and the potential impact of artificial intelligence: A systematic review and meta-analysis.

BACKGROUND: Skin cancer is one of the most prevalent malignancies worldwide, particularly within Caucasian populations. This systematic review and meta-analysis aimed to quantitatively review the current literature on non-invasive diagnosis of skin cancer and evaluate the current evidence to support the use of tools in addition to, or in replacement of clinician face-to-face assessment. METHODS: A literature search was conducted for publications in PubMed, Medline and Embase databases. Articles describing accuracy, sensitivity, specificity and outcomes of their mode of assessment were included. A total of 208 articles met the inclusion criteria. RESULTS AND CONCLUSION: This systematic review and meta-analysis showed that the diagnostic performance of artificial intelligence (AI) in the interpretation of dermatoscopic images was high for melanoma diagnosis, basal cell carcinoma or malignancy, in comparison to dermatoscopic assessment alone by clinicians and experts. Although AI interpretation of images demonstrated higher sensitivity for melanoma diagnosis in comparison to clinical assessment combined with dermatoscopic assessment, it is unclear if this is also the case for basal cell carcinoma and squamous cell carcinoma diagnosis. Reflectance confocal microscopy, a non-invasive high resolution imaging technique, is known to have a high sensitivity for diagnosing cutaneous malignancy, and this may have applications within secondary care. Therefore, AI could help reduce resource burden and aid in clinical assessment, particularly within primary care settings.

Humans↗

PubMed2026

Combining neuromelanin-sensitive MRI and quantitative susceptibility mapping for enhanced diagnosis and differentiation of parkinson's disease: A systematic review.

BACKGROUND: Loss of dopaminergic neurones and iron deposition in the substantia nigra pars compacta (SNpc) are two major pathological hallmarks of Parkinson's disease (PD). Such changes can be visualised by advanced techniques including neuromelanin-sensitive MRI (NM-MRI) and quantitative susceptibility mapping (QSM). This systematic review investigates the diagnostic performance and methodological development of the integrated use of NM-MRI and QSM in PD. METHODS: The systematic search was performed in four databases (Scopus, PubMed, ScienceDirect, and Web of Science) according to the PRISMA 2020 guidelines until July 2026. Bias was assessed using QUADAS-2 and certainty of evidence was assessed using GRADE. RESULTS: Seventeen studies with 2228 participants were included. Combined NM-MRI and QSM consistently showed reduced neuromelanin volume/contrast and increased iron deposition in the SNpc of PD patients compared to healthy controls. Multimodal integration yielded a significant improvement in diagnostic accuracy (AUC values 0.86-0.99), and was able to successfully differentiate PD. Recent methodological advances included simultaneous acquisition sequences (e.g. MTC-GRE, STAGE, setMag) and AI-driven automated segmentation, which led to significantly reduced scan times and improved reproducibility. CONCLUSION: The combination of NM-MRI and QSM has a synergistic effect and provides powerful complementary biomarkers for the diagnosis and differential diagnosis of PD.

Humans↗

PubMed2026

Artificial Intelligence for Diagnosis, Risk Stratification, and Prognosis of Neuroblastoma - A Systematic Review and Meta-Analysis.

PURPOSE: To synthesizes evidence on artificial intelligence (AI) performance in neuroblastoma (NB) diagnosis, risk stratification, prognosis, and genomic characterization. MATERIALS AND METHODS: A systematic review and meta-analysis was conducted following PRISMA 2020 guidelines (PROSPERO: CRD42024539475) across five databases. Meta-analyses used random-effects models with logit-transformed Area Under the Curve (AUCs) and cluster-robust standard errors. AI models were classified as Machine Learning Models (MLM) or Hybrid Nomograms (HN) based on their construction methodology. RESULTS: Of 3,742 articles identified, 53 were included. MLMs demonstrated higher point estimates than radiologists in differential diagnosis (AUC: 0.87 vs. 0.83), though this difference was not statistically significant and carried substantial uncertainty. HNs achieved stronger performance in risk stratification (AUC: 0.87). AI-derived nomograms (AUC: 0.9) and gene signatures (AUC: 0.8) outperformed conventional prognostic markers descriptively. Chemotherapy response prediction remained below clinical utility thresholds across all model types. Only 33.9% of models reported calibration and 24.5% underwent external validation. CONCLUSIONS: AI demonstrates proof-of-concept across multiple NB clinical domains. However, clinical adoption remains premature given persistent gaps in external validation, calibration, dataset size, and pediatric-specific model development. Future studies should test these models prospectively in multicenter pediatric cohorts, ideally through COG or SIOPEN, using shared definitions for diagnosis, risk group, treatment response, and survival outcomes.

Humans↗

PubMed2026

Non-motor symptoms and healthcare utilization before diagnosis of myasthenia gravis: a nationwide cohort study.

BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.

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

The environmental impact of diagnosis and therapy in obstructive sleep Apnea: A systematic review.

Healthcare contributes significantly to global greenhouse gas (GHG) emissions, yet the environmental impact of sleep medicine, particularly the diagnosis and therapy of obstructive sleep apnea (OSA), remains poorly characterized. We systematically searched PubMed, Scopus, and Embase (2015-2025) for studies on OSA care reporting environmental metrics (carbon footprint, energy use, resource consumption) or healthcare resource utilization. Supplementary searches identified additional non-peer-reviewed sustainability-focused studies that have been presented at conferences. Of 19 primary peer-reviewed studies on OSA care and utilization, only one reported environmental metrics (telemedicine CO2 savings related to reduction in travel-related emissions). Supplementary sources revealed that OSA care has a measurable carbon footprint driven by disposable equipment, device electricity, and travel and that OSA diagnostics create significant solid waste with opportunities for waste reduction through the use of reusable equipment. This review shows that while the environmental impact of sleep medicine has been rarely studied to this date, available evidence suggests significant opportunities for sustainability through virtual care, home testing, and equipment optimization. Future research should incorporate environmental impact into the assessment of clinical pathways.

Humans↗

PubMed2026

Blood Bile Acids for Inflammatory Bowel Disease Diagnosis and Disease Activity Assessment: A Metabolomics Meta-Analysis.

Alterations in circulating bile acids (BAs) have been reported in inflammatory bowel disease (IBD), but the consistency of these changes across clinically relevant comparisons remains unclear. Our goal was to investigate systemic BA alterations in IBD using a metabolomics meta-analysis with an exploratory analysis of BA-related gene expression as a supporting context. A systematic review and meta-analysis of 28 metabolomics studies examined blood BA profiles associated with IBD, IBD diagnosis, and disease activity assessment. Univariate analysis and logistic regression modeling of two independent IBD cohorts explored the blood BA-related genes and IBD. Across 28 studies that comprised 5056 IBD patients, 1721 healthy controls, and 314 non-IBD patients, 131 BAs were reported. Eight predefined clinical comparisons were eligible for the meta-analysis. Lower secondary BA levels were consistently observed in IBD patients compared with controls, between UC and CD, and in active versus remission patients. Deoxycholic acid, glycodeoxycholic acid, and taurodeoxycholic acid were frequently decreased, whereas glycocholic acid was increased in certain comparisons. Transcriptomics analyses revealed differential expression of several BA-related genes in blood, including SLC51A, ABCB4, and ACOT8, across the comparisons. Our findings identify consistent circulating BA alterations in IBD and highlight the relevance of blood BA for future biomarker research in the diagnosis and disease activity assessment.

Humans↗

PubMed2026

Integrated genomic and biochemical diagnosis of a novel homozygous start-loss variant in AKR1D1 associated with neonatal cholestasis.

INTRODUCTION: Congenital bile acid synthesis defects are rare autosomal recessive disorders that typically present in early infancy with cholestasis, progressive liver dysfunction, and, in severe cases, acute liver failure. These conditions may mimic other metabolic diseases detected in newborn screening, complicating early diagnosis. The AKR1D1 gene encodes Δ4-3-oxosteroid 5β-reductase, a key enzyme in primary bile acid synthesis, and pathogenic variants cause bile acid synthesis defect type 2 (OMIM #235555). CASE DESCRIPTION: We report a 3-month-old male infant with severe neonatal cholestasis and a history of elevated tyrosine levels in newborn screening. Pregnancy was high risk and unmonitored, with birth outside a hospital. Parental consanguinity was first-degree. Early metabolic evaluation showed transient normalization of tyrosine levels, but subsequent analyses revealed recurrent hyper-tyrosinemia. Urinary organic acids showed increased 4-hydroxyphenyl metabolites, with absent succinylacetone, excluding tyrosinemia type I. Progressive cholestasis developed, accompanied by coagulopathy, hyperbilirubinemia, hyperammonemia, and markedly elevated alpha-fetoprotein. Imaging revealed no structural liver abnormalities. Clinical exome sequencing identified a novel homozygous start-loss variant in AKR1D1, likely abolishing functional enzyme production. Metabolic studies confirmed increased urinary excretion of 3-oxocholenoic acids consistent with abnormal bile acid synthesis and supporting a diagnosis of bile acid synthesis defect type 2. Oral cholic acid therapy led to stabilization and improvement in clinical and biochemical parameters. DISCUSSION/CONCLUSION: This case illustrates the diagnostic complexity of neonatal cholestasis, particularly when initial metabolic findings suggest alternative etiologies. It highlights the importance of newborn screening as a tool for broader diagnostic suspicion and the critical role of early molecular diagnosis and multidisciplinary care. Timely recognition and targeted therapy can improve outcomes, prevent liver transplantation, and enable accurate genetic counseling, especially in consanguineous families.

Humans↗

PubMed2026

Applications of quantum AI in brain disorder diagnosis: A systematic review.

BACKGROUND AND OBJECTIVE: Brain disorder diagnosis and prediction remain challenging because neuroimaging, electrophysiological, behavioral, and multimodal data are high-dimensional, noisy, heterogeneous, and limited by small clinical cohorts. This systematic review synthesised applications of quantum artificial intelligence (QAI) for brain disorder diagnosis, prediction, detection, and monitoring. METHODS: Following PRISMA guidelines, studies published from 2016 to 13 January 2026 were retrieved from Scopus, Web of Science, and IEEE Xplore. After screening, 36 studies met the eligibility criteria and were qualitatively analysed according to disorder category, data modality, QAI method, implementation setting, validation strategy, and performance. RESULTS: At the broader disease-group level, neurodegenerative disorders were the most frequently investigated, followed by mental health and psychiatric disorders. At the individual level, Parkinson's disease and schizophrenia were the leading applications, followed by depression, anxiety, Alzheimer's disease, and stress-related tasks. MRI-based modalities were the most frequently used data source, followed by multimodal data and EEG. Methodologically, primary QAI approaches were dominated by quantum neural and QDL architectures, followed by quantum-inspired optimization or feature-selection methods and quantum-kernel/conventional QML classifiers. Qiskit/IBM Quantum and PennyLane were the most frequently reported quantum software frameworks. However, most studies relied on simulators, classical quantum-inspired implementations, or unclear implementation settings, with limited real-hardware evaluation. CONCLUSIONS: QAI shows emerging potential for brain disorder analysis, particularly through hybrid quantum-classical learning, quantum neural architectures, quantum-kernel methods, and quantum-inspired optimization. Nevertheless, current evidence remains preliminary and requires larger datasets, subject-level and external validation, fair classical benchmarking, noise-resilient circuits, real quantum hardware evaluation, explainability, and clinical validation.

Humans↗

PubMed2026

Diagnostic Value and Limitations of Dermoscopy in Humans and Animals: A Critical Comparative Analysis.

BACKGROUND: Dermoscopy is a noninvasive imaging technique that is well-established in human dermatology, where it enhances the diagnosis of neoplastic, inflammatory, infectious, and alopecic skin disorders. In veterinary dermatology, its use is expanding yet remains heterogeneous and largely descriptive, despite growing evidence of conserved dermoscopic patterns across species. HYPOTHESIS/OBJECTIVES: To review the applications of dermoscopy in veterinary dermatology, and to provide a comparative analysis of dermoscopic features observed in dogs, cats, and horses in relation to corresponding findings in human dermatology. MATERIALS AND METHODS: A systematic review of the literature reporting dermoscopic findings in veterinary dermatology was conducted in accordance with PRISMA guidelines. PubMed, Scopus and Google Scholar were searched for studies published up to 30 July 2025. Eligible studies included original articles describing dermoscopic features in dogs, cats, or horses. Extracted data included species, dermatological condition, dermoscopic findings, device type and histopathological correlation, when available. Levels of evidence were assessed using the Oxford Centre for Evidence-Based Medicine criteria. RESULTS: Thirty studies met the inclusion criteria. Most were descriptive case reports or case series. Dermoscopy was applied to a wide range of conditions, including alopecias, parasitic infestations, dermatophytosis, neoplastic and sebaceous lesions, inflammatory dermatoses, and congenital vascular anomalies. Recurrent dermoscopic features showed strong similarities to those described in human dermatology, although species-specific anatomical differences influenced interpretation. CONCLUSIONS: Dermoscopy represents a valuable adjunct diagnostic tool in veterinary dermatology, with clear translational relevance. Standardisation of terminology and further prospective studies are required to support its broader clinical integration.

Animals↗

PubMed2026

Glucocorticoids and placental 11βHSD2 - A systematic review of human studies and animal models.

CONTEXT: Elevated prenatal glucocorticoid (GC) exposure is linked to adverse offspring outcomes. The placental enzyme 11β-hydroxysteroid-dehydrogenase-type-2 (11βHSD2) protects the fetus by converting maternal derived cortisol to inactive cortisone. Although in vitro studies suggest GC mediated upregulation of 11βHSD2, in vivo evidence remains inconclusive. METHODS: PubMed, Embase, and PsycInfo were searched in October 2024 for human and mammalian animal studies on endogenous or exogenous GCs during pregnancy and associations with placental 11βHSD2 (mRNA, protein, activity, gene methylation). Narrative synthesis was conducted due to heterogeneity precluding meta-analysis. RESULTS: Eighteen studies (eight human, ten animal populations) met inclusion criteria. Exogenous GC exposure was associated with modifications in placental 11βHSD2 expression in animal models, with effects varying by substance, timing, and species. Dexamethasone trended towards increased expression in rodents, whereas betamethasone increased expression in non-human primates but not rodents. Human studies on endogenous GCs showed inconsistent associations with 11βHSD2 changes. In asthmatic pregnancies, moderate inhaled GC-use maintained enzyme activity compared to untreated patients. No convincing sex-specific trend emerged. CONCLUSIONS: GC exposure alters placental 11βHSD2 in a substance- and species-specific way; translational relevance remains limited based on current literature. Future studies should employ technological advances and include GC-sensitive biomarkers to clarify mechanisms of maternal-fetal stress transmission.

Female↗

PubMed2026

Early infantile developmental and epileptic encephalopathy: clinical spectrum, diagnosis, outcomes, and evolving treatment strategies.

Early infantile developmental and epileptic encephalopathy (EIDEE) is among the most severe epilepsy syndromes, with onset before three months of age and an estimated incidence of approximately 10 per 100,000 live births. The 2022 International League Against Epilepsy classification unified the historically distinct Ohtahara syndrome and early myoclonic encephalopathy under a single diagnostic framework defined by frequent drug-resistant tonic and/or myoclonic seizures, an abnormal neurological examination, and an abnormal interictal electroencephalogram-most characteristically a burst-suppression pattern. This narrative review synthesizes the clinical, electrophysiological, neuroimaging, genetic, and therapeutic literature within the EIDEE framework. The clinical phenotype is characterized by central hypotonia, postnatal microcephaly, cortical visual impairment, and age-dependent syndromic evolution toward infantile epileptic spasms syndrome or Lennox-Gastaut syndrome in the majority of patients. Electroencephalography remains essential for syndromic classification, while systematic metabolic screening and early trio whole-exome or whole-genome sequencing are central to the etiologic workup, achieving diagnostic yields of 60-65%. The most commonly identified genetic causes include STXBP1, KCNQ2, and SCN2A variants. Outcomes are poor overall and strongly etiology-dependent: vitamin-responsive disorders carry a substantially more favorable prognosis, whereas mortality reaches 25% in genetic cohorts. Genotype-guided pharmacotherapy is now applicable to a clinically meaningful subset of patients, with sodium channel blockers, potassium channel openers, and emerging antisense oligonucleotide therapies representing important therapeutic advances. Gene therapy trials are underway but have encountered early safety signals, underscoring the vulnerability of this population. Critical unmet needs include earlier molecular diagnosis, precision therapies targeting developmental outcomes beyond seizure control, and prospective international registries to characterize the long-term natural history of EIDEE.

Humans↗

PubMed2026

Journey Mapping of the Patient Experience from Diagnosis to End of Life in Lung Cancer: A Qualitative Meta-Synthesis.

OBJECTIVES: This study aimed to systematically synthesize the lived experiences and journey narratives of lung cancer patients across disease stages, and identify key tasks and pain points during the disease course through patient journey mapping, providing evidence for comprehensive disease management throughout the patient journey. METHODS: Ten databases, including PubMed, Embase, Web of Science, Scopus, PsycINFO, CINAHL, Cochrane Library, CNKI, Wanfang, and SinoMed, were systematically searched, with a search period from database inception to August 15, 2025. The JBI Critical Appraisal Tool for qualitative studies was used to evaluate the quality of studies, and the results were integrated using a meta-aggregative approach. RESULTS: Thirteen studies were included. Based on the patient journey mapping, the lung cancer patient journey comprises four potential stages: evaluation and diagnosis, initial treatment, maintenance therapy, and end-of-life. A total of 30 themes emerged within three dimensions: tasks, emotions, and pain points. Each dimension of each stage consists of 2-3 themes. CONCLUSION: The journey of lung cancer patients is protracted and complex, characterized by stage-specific needs and challenges. Future management strategies should be tailored to these distinct phases, providing precision supportive care to optimize treatment outcomes and enhance patients' quality of life. IMPLICATIONS FOR NURSING PRACTICE: This Patient Journey Map integrates routine clinical pathways with patients' lived experiences across each stage, revealing stage-specific challenges and providing targets for tailored nursing interventions. The framework promotes multidisciplinary, digitally enabled supportive care and indicates the importance of including patients' social circles to enhance patient-centered outcomes.

Humans↗

PubMed2026

Premature closure underlies bias in medical diagnosis in students: A randomised controlled experiment.

OBJECTIVE: The purpose of the study reported in this article was to shed light on the cognitive mechanism mediating between biasing information and diagnostic error. The literature suggests at least two different hypotheses: premature closure leading biased participants to spend less time on diagnosis or increased competition between diagnostic hypotheses. The latter hypothesis predicts that biased participants would spend more time reaching a diagnosis. METHOD: Using the salient distracting findings (SDF) experimental paradigm, we biased 58 fourth-year medical students while diagnosing 12 clinical vignettes in a within-group incomplete block design under three conditions: cases presented without SDF, with SDF at the beginning and with SDF at the end. For each of these conditions, diagnostic accuracy, the number of SDF-related mistakes and time per word needed to process the case were recorded. The data were analysed using linear mixed modelling. Estimated marginal mean scores were reported. RESULTS: Participants confronted with salient distracting features (SDFs) at the beginning of a clinical case demonstrated significantly lower diagnostic accuracy (mean 0.11) compared with the No-SDF condition (0.27), representing a 61% reduction (F2,693 = 11.995, p < 0.001), and made more SDF-related mistakes (F2, 693 = 16.395, p < 0.001). When SDFs were presented at the end of the case, diagnostic accuracy was also reduced (mean 0.17; 36% reduction), but processing time did not differ from the No-SDF condition. Only early presentation of SDFs was associated with reduced processing time per word (F2,636 = 4.799, p < 0.01), consistent with premature closure. CONCLUSION: These findings demonstrate that biasing information increases diagnostic error in medical students and that only early bias is associated with reduced information processing. The data do not support the competition hypothesis for early bias, as processing time did not increase under biasing conditions. Premature closure can therefore be directly observed rather than inferred, inviting further research.

Humans↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

Prion disease mimicking rapidly progressive Alzheimer disease: case series and systematic review.

BACKGROUND: Prion disease and Alzheimer disease (AD) are common causes of rapidly progressive dementia (RPD). Although most patients with prion disease are distinguished by MRI and CSF findings, selected cases mimic rapidly progressive AD. We characterized AD-prion disease mimics within a prospective cohort and the extant literature to identify the clinical features and tests that support accurate diagnoses in these patients. METHODS: Patients with prion disease initially diagnosed as rapidly progressive AD were identified from a prospective cohort study at Mayo Clinic (February 2020-June 2026) and through systematic review of MEDLINE and Embase. RESULTS: Of 204 patients with RPD, five (2.5%) were initially diagnosed with clinically probable AD but ultimately determined to have prion disease. Systematic review identified 10 additional cases (n=15, median age-at-onset, 59 years; 67% male). Presentations reproduced amnestic (53%), dysexecutive (27%), primary progressive aphasia (13%), and posterior cortical atrophy (7%) AD phenotypes; median time from AD diagnosis to consideration of prion disease was 2 months. Diffusion-weighted MRI abnormalities were absent in Mayo Clinic cases and absent/equivocal (n=2) or overlooked (n=8) in published cases. CSF biomarkers were consistent with AD in 6/9 tested patients, with elevated total tau levels in 11/13 patients and total-tau/p hosphorylated-tau181 ratios in 5/9 patients. Real-time quaking-induced conversion assays for prions were positive in the CSF of 9/12 patients. Prion disease was confirmed by neuropathology (n=7), genetics (n=2), or real-time quaking-induced conversion (n=6) assays. CONCLUSIONS: Prion disease may rarely mimic rapidly progressive AD. Disproportionate elevations in CSF total-tau levels or total-tau/p hosphorylated-tau181 ratios should prompt consideration of prion disease.

Humans↗