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PubMed2026

Diagnostic value of blood p-tau subtypes in Alzheimer's disease progression and pathology: systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and the most likely to lead to dementia. With the availability of the latest therapies, the need for Alzheimer's disease diagnosis is now gradually increasing. Whereas blood phosphorylated-tau (p-tau) has demonstrated excellent performance in the prediction and diagnosis of disease progression and Aβ positivity in AD, there are differences between different p-tau subtypes. Therefore, a pooled analysis of different blood p-tau subtypes is of more important clinical value. METHOD: Relevant literature was screened by complete search in four databases, Pubmed, Embase, Cochrane Library and Scopus. Relevant data and AUC and their confidence intervals of the included literature were extracted and analyzed by classification according to p-tau subtypes. Quality assessment was performed using the QUADAS-2 tool. RESULT: Our results reveal that p-tau217 performs better in the diagnostic performance in most stages of AD, which is consistent with the guidelines. However, our results concluded that p-tau217 has poorer diagnostic performance in the stages of cognitive unimpaired or less cognitively impaired, especially in the Aβ positivity diagnosis of SCD and CU. Head-to-head meta-analyses formally confirmed that p-tau217 significantly outperforms p-tau181 across AD dementia, Aβ positivity, tau positivity, and biological staging (all P < 0.05), whereas no significant difference was observed between p-tau231 and p-tau181. CONCLUSION: By integrating single-arm pooled AUC estimates with formal head-to-head statistical comparisons, our study provides evidence-based support for plasma p-tau217 as the subtype with the most robust diagnostic performance across AD pathology and biological staging. Head-to-head analyses formally confirmed that p-tau217 significantly outperforms p-tau181 in Aβ positivity, Tau positivity, and biological staging.

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PubMed2026

Evaluation of a cornea-specialized large language model for diagnostic and management accuracy in complex corneal cases.

PURPOSE: To evaluate whether a cornea-specialized large language model (LLM) enhanced with retrieval-augmented generation (RAG) improves clinicians' diagnostic and management accuracy in complex corneal cases compared to a general-purpose GPT-4o model and unaided clinician performance. METHODS: This prospective, randomized, masked evaluation study involved three cornea trainees who each independently reviewed 39 real-world corneal cases under three experimental conditions: unaided, GPT-4o-assisted, and assisted by a cornea-specialized GPT-4o model. The cornea-specialized model was constructed by embedding over 200 publicly available Wikipedia articles into GPT-4o's RAG framework. Participants provided open-ended diagnoses and selected the next-step management options (multiple choice). They were allowed up to three GPT-4o queries per case, and the AI-assisted arms were randomized to minimize bias. Accuracy for both tasks was compared against expert reference standards using McNemar's test. RESULTS: Diagnostic accuracy was 48.7%, 20.5%, and 38.5% unaided, improving to 69.2%, 46.2%, and 59.0% with general GPT-4o (p<0.04). The cornea-specialized GPT-4o further improved accuracy to 71.8%, 48.7%, and 74.4%, with improvements over unaided performance for all clinicians (p<0.01). For next-step decisions, unaided accuracy was 76.9%, 87.2%, and 59.0%. With the specialized model, Ophthalmologist 3 improved to 71.8% (p<0.05), Ophthalmologist 1 remained high at 82.1%, and Ophthalmologist 2 declined to 64.1% (p<0.05). CONCLUSIONS: A cornea-specialized LLM enhanced with RAG improved diagnostic accuracy in complex corneal cases, particularly among clinicians with lower baseline performance. Effects on management accuracy were inconsistent. Future studies should explore the use of open-ended management tasks and examine whether smaller, curated retrieval corpora yield better model performance.

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PubMed2026

Complexity in disguise: a systematic review of fractal analysis in psychiatric neuroimaging.

OBJECTIVES: Psychiatric diagnosis and fractal studies are complex processes that extend beyond clinical evaluation and require careful methodological considerations in neuroimaging. Over the years, fractals have helped reduce these complexities in research, but they still cannot grant clinical diagnoses. Thus, the main objective was a systematic review exploring the potential applications of fractal analysis in characterizing psychiatric conditions through neuroimaging techniques-including both functional and structural MRI. MATERIALS AND METHODS: A systematic literature review was conducted on PubMed, identifying thirty-nine original studies that met the inclusion criteria. Areas showing statistical significance (p < 0.05) were reported. These studies were categorized according to DSM-V classification and examined for the description of psychiatric conditions through the fractal analysis. RESULTS: The review primarily focuses on young adults with psychiatric conditions compared to control groups. Schizophrenia and Autism Spectrum Disorder are major areas of investigation, and fractal dimension (FD) is the primary analysis method used to reflect brain patterns. Studies that calculated whole-brain FD may have underestimated local abnormalities due to the inclusion of a high percentage of tissue, potentially resulting in overlooked findings. Notably, abnormalities in the frontal cortex represent a common neurobiological feature across several psychiatric conditions. CONCLUSIONS: The findings from this systematic review shed light on the use of fractal analysis to quantify complex brain patterns in both psychiatric patients and healthy individuals. However, it is essential to recognize the need for further research to elucidate a fractal analysis protocol that allows for optimal extraction of psychiatric insights. KEY POINTS: Question Fractal analysis applied to structural and functional MRI help characterize brain alterations across psychiatric conditions. Findings This review shows consistent fractal patterns across multiple psychiatric disorders, especially in frontal regions. Despite heterogeneous methodologies, results highlight shared structural and functional abnormalities. Clinical relevance Fractal analysis may offer complementary characterization of subtle brain organization across psychiatric disorders. Its potential clinical utility-such as improving diagnostic characterization, earlier detection, among others-remains limited by the current absence of a standardized protocol.

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PubMed2026

Risk factors for leg wound infection after conventional and no-touch vein harvesting: insights from a multicentre randomised trial.

ClinicalTrials.gov: ID NCT03501303.

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PubMed2026

Whole-Exome Sequencing in a Consanguinity-Enriched South Indian Retinitis Pigmentosa Cohort: Diagnostic Yield and Molecular Spectrum.

PURPOSE: To determine the molecular diagnostic yield, variant spectrum, inheritance architecture, and influence of consanguinity on whole-exome sequencing outcomes in a South Indian retinitis pigmentosa (RP) cohort. DESIGN: Prospective, registry-based cohort study. SUBJECTS: A total of 113 affected participants were enrolled through the Aravind Registry for Inherited Diseases of the Eye, including 109 unrelated probands and 4 affected relatives from already represented families. Primary analyses were restricted to the 109 unrelated probands. METHODS: Whole-exome sequencing was performed using a clinical exome workflow. Variants were interpreted using American College of Medical Genetics and Genomics/Association for Molecular Pathology criteria and cases were categorized as solved, possibly solved, inconclusive, or unsolved using prespecified inheritance-aware rules. MAIN OUTCOME MEASURES: Molecular diagnostic yield, distribution of implicated genes and variant classes, inheritance architecture, and diagnostic yield stratified by consanguinity status. RESULTS: Among the 109 unrelated probands, mean age at testing was 39.3 ± 14.1 years and 58.7% were male. Whole-exome sequencing identified 186 distinct rare variants across 92 inherited retinal disease genes, including 26 pathogenic and 33 likely pathogenic variants. A molecular diagnosis was established in 50 of 109 probands (45.9%), including 42 solved and 8 possibly solved cases; 45 (41.3%) were inconclusive and 14 (12.8%) remained unsolved, including 4 (3.7%) in whom no candidate variant was identified. EYS, USH2A, and ADGRV1 were the most frequently implicated genes. Autosomal recessive (AR) disease predominated (44/50, 88.0%). Consanguineous AR cases were exclusively homozygous (17/17); notably, 68.0% of nonconsanguineous AR cases were also homozygous (P = 0.013). Diagnostic yield was higher in consanguineous probands (51.4% vs. 41.7%), without reaching significance. Recurrent alleles included an established South Asian founder variant (MFSD8 c.1361T>C) and candidate founder alleles in EYS (c.4321C>T) and ADGRV1 (c.14329C>T). CONCLUSIONS: Whole-exome sequencing established a molecular diagnosis in nearly half of this South Indian RP cohort and revealed a predominantly recessive, homozygosity-enriched architecture shaped by consanguinity. These findings define a region-specific variant landscape to support clinical interpretation, genetic counseling, and future trial enrollment in this underrepresented population. FINANCIAL DISCLOSURES: The authors have no proprietary or commercial interest in any materials discussed in this article.

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PubMed2026

Unraveling a Diagnostic Enigma: A TECPR2 Case Solved Through Multi-Omic Genomics.

TECPR2 is a key regulator of autophagy, encoded by the TECPR2 gene. Pathogenic variants in this gene have been linked to a rare hereditary sensory and autonomic neuropathy with intellectual disability (HSAN9). We report a teenage female with a syndromic intellectual disability disorder associated with neuromuscular abnormalities. Multi-omics analysis including genomics, transcriptomics, and proteomics, together with muscle biopsy from the affected individual, were used in this clinical case. Through trio exome sequencing we identified two heterozygous variants in the TECPR2 gene, NM_014844.4: c.480G>A; p.(Gln160=) and c.2846C>A; p.(Ala949Glu). Both were classified as variants of uncertain significance due to the lack of supporting evidence for pathogenicity. Subsequent long-read sequencing phased the variants and confirmed they were in trans. Additional functional studies using RNAseq and proteomics analyses verified the pathogenicity of the variants. This case study demonstrated the value of a multi-omics assisted analysis, which complemented the traditional phenotype-first approach in reaching a definitive clinical diagnosis.

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PubMed2026

Prenatal exome sequencing of fetuses with central nervous system anomalies based on prenatal ultrasound and magnetic resonance imaging diagnosis: A retrospective cohort study with a systematic review and meta-analysis.

INTRODUCTION: Fetal central nervous system (CNS) abnormalities have diverse etiologies, with genetic factors as a major contributor. Prenatal exome sequencing (ES) is a powerful tool for precise molecular diagnosis of CNS anomalies, but its diagnostic yield varies among studies. This study aimed to evaluate the additional diagnostic yield of prenatal ES compared with chromosomal microarray analysis (CMA) in fetuses with CNS anomalies detected by prenatal imaging. MATERIAL AND METHODS: We collected ES results from fetuses diagnosed with CNS anomalies by prenatal imaging (2019-2024) who had negative results. Subgroup analyses assessed phenotype-specific ES diagnostic yield for associated genes and variants. A systematic review and meta-analysis incorporating our data and published studies further explored the association between phenotype and diagnostic yield. RESULTS: In the cohort study of 219 cases, ES identified pathogenic/likely pathogenic single nucleotide variations in 36 cases (16%). The highest diagnostic yield of ES was in cases with multisystem malformations (25%, 14/55), followed by multiple CNS anomalies (15%, 2/13) and isolated CNS anomalies (13%, 20/151). The most commonly identified isolated CNS anomaly was agenesis of the corpus callosum (31%, 5/16). Neural tube defects with urogenital anomalies were associated with a positive ES finding in 57% (4/7) of cases. The meta-analysis of 989 cases from 22 studies showed a pooled diagnostic yield of ES of 27% (95% CI, 21%-34%). The highest diagnostic yield of ES was in cases of corpus callosum anomalies with facial abnormalities (75%, 8/11) and neural tube defects with urogenital malformations (80%, 12/15). The diagnostic yield of ES for three or more CNS abnormalities was 43% (95% CI, 31%-58%), significantly higher than that for only two abnormalities (10%, 95% CI, 4%-18%). No significant difference in diagnostic yield was found between cases identified by prenatal MRI combined with ultrasound (27%, 95% CI, 20%-36%) and those identified by ultrasound alone (25%, 95% CI, 17%-35%). CONCLUSIONS: ES provided a significantly higher diagnostic yield than CMA for fetal CNS abnormalities, with diagnostic yields varying by phenotype. The systematic review and meta-analysis confirmed that the complexity and combination of malformations are key factors associated with differences in ES diagnostic yield.

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PubMed2026

Hysteroscopic platelet-rich plasma and medically assisted reproduction outcomes: a systematic review and SWOT analysis.

BACKGROUND: Platelet-rich plasma (PRP) has been proposed as an adjuvant treatment in reproductive medicine. While most evidence refers to blind intrauterine instillation, subendometrial administration under hysteroscopic guidance allows targeted delivery under direct visualisation. This systematic review aimed to synthesise the available evidence on hysteroscopic PRP administration and its impact on clinical medically assisted reproduction (MAR) outcomes. METHODS: A systematic search was conducted from inception to December 2025 across major databases. Studies were included if they evaluated hysteroscopic PRP administration in women undergoing MAR, comparing reproductive outcomes between treated and control groups. RESULTS: Out of 142 records, 3 studies met the inclusion criteria. Study populations were heterogeneous and included women with refractory thin endometrium and/or a history of implantation failure. Hysteroscopic PRP administration protocols varied in timing, technique, and dosage. In a prospective case-control study, hysteroscopic intraendometrial PRP injection at a depth of 2-3 mm in the four uterine walls, using an ovum aspiration needle, on days 11-13 of the cycle prior to euploid frozen embryo transfer (ET), was associated with higher implantation (IR), clinical pregnancy (CPR), and live birth rates (LBR) compared with standard therapy. Conversely, no significant differences in CPR, miscarriage rate, or LBR were observed in an observational study evaluating a single intraendometrial PRP injection (35-40 mL, 2-3 mm depth), administered via endoscopic needle on days 6-8 of the menstrual cycle preceding frozen ET, alone or after electrical impulse therapy. A randomised controlled trial in women undergoing intrauterine insemination reported a significant improvement in CPR following hysteroscopic subendometrial PRP instillation in the four uterine walls (1.0 mL each). CONCLUSIONS: Current literature on hysteroscopic PRP administration in reproductive medicine is limited, and robust conclusions cannot yet be drawn. Well-designed randomised controlled trials with standardised protocols are needed to clarify its clinical role.

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PubMed2026

A narrative systematic review of definitions and diagnostic criteria for disordered eating and eating disorders in type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes and disordered eating (T1DE) affects 8-37.1% of adults and is associated with high rates of morbidity and mortality. The absence of a standardised case definition of T1DE and its severity hinders effective screening, diagnosis and treatment. This systematic review aimed to (1) synthesise existing case definitions and diagnostic criteria for T1DE in adults and (2) identify key characteristics to inform consensus for future diagnostic criteria. METHODS: A systematic review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidelines. Eligible studies involved adults (≥18 years) with type 1 diabetes assessing disordered eating; paediatric studies, mixed samples without disaggregated data, non-empirical designs and non-English publications were excluded. PubMed, MEDLINE, EMBASE, CINAHL and PsycINFO were searched up to November 2025 for peer-reviewed studies involving adults with T1DE. Qualitative and quantitative data on definitions, diagnostic criteria and assessment tools were extracted. Study quality was appraised using a modified Graphical Appraisal Tool for Epidemiological studies (GATE) checklist. Due to heterogeneity of data, a narrative synthesis of findings was performed to describe current definitions of T1DE. RESULTS: Sixty-one studies met the inclusion criteria, with a pooled sample of 111,208 participants (76% women) from over 22 countries. T1DE was defined using a heterogeneous array of terms, diagnostic frameworks and assessment tools (29 distinct methods). The Diabetes Eating Problem Survey-Revised (DEPS-R) was the most used questionnaire, but many studies relied on criteria adapted from general eating disorder classifications or generic questionnaires. Approximately three-quarters of the studies assessed insulin omission behaviours, but the operationalisation of the cognitions for insulin omission varied widely. Beyond physiological markers such as HbA1c and BMI, studies explored various diabetes-related and psychological constructs, although often considering diabetes and disordered eating separately rather than as an integrated condition. CONCLUSIONS/INTERPRETATION: This systematic review highlights the lack of a unified, evidence-based definition of T1DE, resulting in inconsistent screening, diagnostic and reporting practices. Establishing clear, consistent, evidence-based diagnostic criteria and screening questionnaires for T1DE is critical to improving early detection and developing targeted interventions. These findings provide a foundation for refining T1DE definitions as a stepping stone to an international consensus definition. STUDY REGISTRATION: PROSPERO registration no. CRD420250223622 FUNDING: King's College London and King's College Hospital through the KMRT KCH Joint Research Committee studentship. This work was also conducted as part of the National Institute for Health Research (NIHR; CS-2017-17-023)-funded STEADY project (Safe management of people with Type 1 diabetes and EAting Disorders studY). NZ's salary was part-funded by the NIHR via the NIHR Clinician Scientist award to MS; JT and KI are part-funded by the NIHR Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. MS was funded through her NIHR Clinician Scientist Fellowship (CS-2017-17-023).

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PubMed2026

Are There Any Effective Behavior Change Strategies for Communicating Genetic Risk in Obesity Prevention and Body Weight Reduction Interventions?

This systematic review examined how differences in intervention components may contribute to inconsistent findings in genetic risk communication studies, addressing obesity-related outcomes (e.g., weight reduction, nutrition behavior, exercise). The review was preregistered (PROSPERO #CRD42024524026) and followed PRISMA guidelines. Searches across eight databases identified 23 randomized controlled trials, covering 18 intervention trials. Risk of bias was assessed using the Risk of Bias 2 tool. A narrative synthesis was used to cluster studies by the content of intervention and control groups. Genetic risk communication alone (no behavioral counseling, addressing nutrition and exercise) or combined with phenotype-based risk was ineffective and sometimes counterproductive among low-risk individuals. When combined with personalized behavioral counseling, effectiveness improved, but only when compared to waitlist control groups or non-personalized behavioral counseling. Significant effects emerged in high-genetic risk subgroups within personalized behavioral counseling, using behavior change techniques such as problem-solving, feedback on behavior, self-monitoring, and environmental changes. The most promising results emerged from complex interventions integrating genetic risk communication into multiple sessions and combining numerous additional behavioral change techniques, such as social reward, cues/prompts, self-reward. Complex personalized interventions combining multiple behavior change techniques and prompting experiential genetic risk awareness show promise for improving weight, nutrition, and exercise-related outcomes.

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PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

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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.

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PubMed2025

A Systematic Review of Help-Seeking Barriers for Racial-Ethnic Minority Caregivers Accessing Autism Diagnostic and Intervention Services.

Caregivers play an essential role in early help-seeking and intervention for children with Autism Spectrum Disorder (ASD). Caregivers, therefore, provide a crucial role in helping to address the racial and ethnic disparity identified in accessing ASD intervention and diagnostic services (Bejarano-Martín et al., Journal of Autism and Developmental Disorders 50(9), 3380-3394, 2020). Unfortunately, racial-ethnic minority caregivers of children with autism (CCA) are less likely to contact a physician or healthcare professionals about their concerns and more likely to delay their contact to have their child evaluated (Zeleke et al., Journal of Autism and Developmental Disorders 49(10), 4320-4331, 2019). However, little evidence exists to explain why such a gap exists in the help-seeking behaviors between White and racial-ethnic minority CCA. To address this knowledge gap, we conducted a systematic literature review to identify articles that have studied barriers in help-seeking for racial-ethnic minority CCA. A broad literature search across four databases was conducted (i.e., PubMed, PsycINFO, Education Resources Information Center, and Child Development and Adolescent Studies). The coding team identified 17 articles on help-seeking barriers for racial-ethnic minority CCA. A thematic analysis was used to narratively synthesize the help-seeking barriers identified across these 17 studies. Four themes emerged from our findings: logistical barriers, provider competence, ASD literacy, and cultural stigma. We also provided clinical recommendations for healthcare providers working with families with racial-ethnic minority CCA.

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PubMed2026

Adding Rib Mobilization to Diaphragm Release Techniques in Patients With Non-Specific Neck Pain: Randomized Controlled Trial.

BACKGROUND: Non-specific neck pain (NSNP) is a frequent issue that can negatively affect both mobility and function. Recently, there has been growing interest in newer therapeutic approaches, including rib mobilization and diaphragm release techniques, as potential ways to address NSNP and support better outcomes for those affected. PURPOSE: To find out the immediate effects of how (DRT) combined with (RMT) affects the level of pain and the extent to which patients' functional abilities are improved in cases of NSNP. METHODS: For this prospective RCT, 96 participants aged 20 to 45 years were randomly assigned to one of three equal groups based on their pain score (VAS). Group B engaged in (DRT) for 40 minutes, three times weekly for 8 weeks, in contrast to Group A, which got both RMT combined with DRT. Group C (active control) received advice and some exercises. Measurements were collected before and after the intervention; the primary outcomes included pain severity, evaluated using a visual analog scale (VAS); active neck range of motion (ROM), measured with a cervical range of motion (CROM) device; and neck flexion endurance. Additionally, the secondary outcome of neck-related disability was assessed using the Neck Disability Index (NDI). RESULTS: No statistically significant difference was identified among the three groups at baseline; nevertheless, a treatment effect emerged after 8 weeks (p = 0.001 and f-value = 4.15, ƞ2 = 0.306). A statistically significant time-treatment interaction was seen when comparing the pre- and post-treatment periods in groups A and B (p = 0.001, f-value = 3.16, ƞ2 = 0.251). CONCLUSION: The addition of rib mobilization to diaphragm release techniques in patients with non-specific neck pain resulted in statistically significant improvements in pain intensity, cervical flexion, right lateral rotation, left lateral rotation, right rotation, and neck flexor endurance, with moderate to large effect sizes for pain reduction and cervical motion. However, no statistically significant differences were observed between groups for cervical extension, left rotation, or the Neck Disability Index (NDI), and only a marginal clinical improvement in NDI was noted in Group A. The observed benefits in the combined intervention group may not be attributable solely to rib mobilization. The increased treatment complexity and greater therapist interaction inherent in the combined approach could also have influenced the outcomes. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT07133646.

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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.

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PubMed2026

Outcomes at rapid diagnostic centres and the association between non-specific symptoms and cancer: A systematic review and meta-analyses of up to 21,392 patients.

INTRODUCTION: Cancer remains a leading cause of mortality and poses a significant public health challenge. Several non-specific symptoms (NSSs) often indicate non-serious disease but can also accompany malignancy even in the absence of organ-specific signs. Therefore, the aim of the study was to comprehensively delineate the association between the most common NSSs (weight loss, fatigue, pain and nausea/appetite loss) and cancer or non-cancer diagnoses. METHODS: Database searches of PubMed and Embase were conducted applying search criteria to identify studies that investigated common NSSs in cancer patients diagnosed through rapid diagnostic centres (RDCs). The quality of the included studies was assessed using a modified Newcastle-Ottawa Scale (NOS). For each symptom, pooled relative risks (RRs) with 95% confidence intervals were derived using random-effects meta-analysis. RESULTS: Eleven studies met the inclusion criteria. All studies were considered to be of high methodological quality. The most frequent disease locations for cancer entities included hematologic, lung and lower gastrointestinal. Together with miscellaneous, rheumatic, and musculoskeletal conditions, these were the most common for non-cancer diagnoses. Nausea/appetite loss showed a statistically significant association with cancer (RR=1.20, 95%-CI 1.07-1.35). Pain showed a non-significant association (RR=1.07, 95%-CI 0.75-1.53) with substantial between-study heterogeneity, and weight loss showed a non-significant inverse trend (RR=0.92, 95%-CI 0.84-1.02). Fatigue showed no association with cancer (RR=1.00, 95%-CI 0.85-1.18). DISCUSSION/CONCLUSION: NSSs may be valuable for cancer risk assessment, but the associations remain modest. The complexity of patients' clinical presentations suggests that additional factors likely influence the cancer risk. Future research should examine symptom combinations and, where data allow, perform subgroup analyses.

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PubMed2026

The musculoskeletal pain literacy questionnaire (MSK-PLq) - Part 1: Development of a preliminary version through a systematic review and Delphi consensus.

OBJECTIVE: Chronic musculoskeletal (MSK) pain is a leading cause of disability worldwide, and self-management is a first-line approach recommended by international clinical guidelines. Access to evidence-based information that enhances health literacy may support patients' engagement in their self-management and treatment decision-making, potentially reducing disease burden and pain. However, no tool currently exists to assess health literacy specifically in MSK pain. This study aimed to develop and describe the preliminary version of a knowledge-based questionnaire to evaluate MSK pain literacy, the Musculoskeletal Pain-Literacy questionnaire (MSK-PLq). METHODS: A systematic literature review identified existing health literacy instruments and generated a preliminary list of domains. A two-round Delphi study with 22 panellists (19 experts and three people living with chronic MSK pain), followed by consensus meetings, was used to refine domains and items (≥70% agreement). Readability was assessed using the Flesch Reading Ease (FRE) score and three stakeholders were consulted to review the questionnaire for comprehensibility, clarity, and face validity. RESULTS: Six domains were retained (Understand, Access, Appraise, Apply, Digital, Beliefs), comprising 20 items in the preliminary version of MSK-PLq. Readability was acceptable (mean FRE 74, indicating fairly easy reading), and subject feedback supported the questionnaire's clarity and face validity. CONCLUSIONS: The preliminary version of the MSK-PLq is proposed as the first knowledge-based tool to assess functional, interactive, and critical aspects of MSK pain literacy. It may have applications in clinical practice, research, education, and digital health, by informing tailored patient education and supporting self-management strategies, although further psychometric validation is required.

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PubMed2026

Diagnostic value of plasma cell-free DNA metagenomic next-generation sequencing in patients with suspected infections and exploration of clinical scenarios-a retrospective study from a single center.

BACKGROUND: Plasma cell-free DNA metagenomic next-generation sequencing (mNGS) is a non-invasive comprehensive method for the etiological diagnosis of various infectious diseases. However, research on the early diagnosis and real-world clinical impact of plasma mNGS in patients with suspected infection are still limited. MATERIALS AND METHODS: This study retrospectively included 140 patients with suspected infections who underwent early plasma mNGS and conventional culture testing. Referring to the clinical diagnosis of infectious diseases, the diagnostic performance of plasma mNGS and culture tests was compared, and the application scenarios and clinical effects of plasma mNGS were evaluated. RESULTS: The positive rate of plasma mNGS was significantly higher than that of culture methods (55.71% vs 25.10%, p < 0.001) and blood cultures (55.71% vs 12.86%, p < 0.001). Regarding clinical diagnosis, the sensitivity of plasma mNGS was significantly higher than that of culture (58.27% vs 37.80%, p = 0.002). The combination of mNGS and culture achieved a higher detection sensitivity (69.29%), especially in patients with multi-site co-infections (73.68%) and blood infections (73.17%). Plasma mNGS demonstrated higher sensitivity in patients with procalcitonin (PCT) index > 5 ng/ml or human neutrophil lipocalin (HNL) index > 200 ng/ml. In terms of treatment, a total of 69 patients (54.33%) benefited from plasma mNGS. CONCLUSION: This study highlights the significant improvement in pathogen detection performance by combining conventional culture with plasma mNGS detection, especially in patients with multi-site co-infections and blood infections. Early use of plasma mNGS as an adjunct to culture can better guide clinicians to initiate appropriate anti-infective therapy.

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