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PubMed2026

Compound muscle action potential amplitudes in newborn screen positive spinal muscular atrophy.

OBJECTIVE: To evaluate the utility of compound muscle action potential (CMAP) amplitudes as biomarkers of disease severity in newborn screening (NBS)-positive infants with spinal muscular atrophy (SMA). METHODS: We conducted a retrospective review of 21 infants identified through SMA NBS (11 with 2 SMN2 copies and 10 with 3 SMN2 copies). Baseline and serial right median, ulnar, and fibular motor nerve CMAP amplitudes (millivolts, mV) were obtained during the study. Functional outcomes were assessed using the Children's Hospital of Philadelphia Infant Test of Neuromuscular Disorders (CHOP-INTEND). RESULTS: At baseline, infants with 2 SMN2 copies demonstrated significantly lower median, ulnar, and fibular CMAP amplitudes compared with infants with 3 SMN2 copies (p < 0.05). In contrast, baseline CHOP-INTEND scores did not differ significantly between the two groups. Prior to genetic confirmation, a right median CMAP amplitude ≥3.2 mV predicted ≥3 SMN2 copies. Following treatment, right median and fibular CMAP amplitudes demonstrated significant improvement over time, including in analyses accounting for SMN2 copies number. CONCLUSION: CMAP amplitudes obtained from multiple upper- and lower-extremity motor nerves provided objective electrophysiological measures that distinguished infants with two versus three SMN2 copies, despite similar baseline CHOP-INTEND scores. Furthermore, CMAP abnormalities were detectable in some cases before confirmatory genetic testing results became available. Serial CMAP measurements demonstrated significant longitudinal changes following treatment, whereas functional assessments approached ceiling values, supporting the potential value of electrophysiological monitoring in the era of disease-modifying therapies. SIGNIFICANCE: CMAP assessment is a useful adjunct in the evaluation of infants identified through SMA NBS.

Humans↗

PubMed2026

Predictive Models for Hypoglycemia Risk in Haemodialysis Patients With Diabetic Kidney Disease: Systematic Review and Meta-Analysis.

AIM: To provide evidence for selecting and developing reliable clinical assessment tools for hypoglycemia in diabetic kidney disease patients during haemodialysis. DESIGN: Review. METHODS: Systematic searches were performed in 9 Chinese and English databases to collect literature regarding the development of hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease. Two reviewers independently performed literature screening, data extraction, risk-of-bias assessment, and applicability evaluation. The Prediction Model Risk of Bias Assessment Tool was used to assess the risk of bias and applicability of the included studies. Meta-analysis was conducted using R software. DATA SOURCES: CNKI, Wanfang, VIP, CBM, PubMed, Cochrane Library, EMbase, Web of Science, and CINAHL. The search period covered from the establishment date of each database to December 2025. RESULTS: Six studies, comprising six prediction models, were included. Two studies performed internal validation, and three conducted external validation. All models reported the area under the curve, ranging from 0.813 to 0.866, and calibration measures. Four studies were rated as having a high risk of bias, while all six demonstrated good overall applicability. The meta-analysis showed that the pooled AUC value of the six studies was 0.846 (95% CI: 0.823-0.867). CONCLUSION: Research on hypoglycemia risk prediction models in haemodialysis patients with diabetic kidney disease remains in the developmental stage. Although the included prediction models exhibited satisfactory apparent discriminatory ability and clinical applicability, most of the original studies suffered from a high risk of bias and lacked adequate validation. The true predictive performance and clinical application value of these models remain to be further verified. Accordingly, routine and unconditional clinical application is not recommended at this stage. Future studies should include more high-quality, multicenter external validation and develop models with high generalizability, favourable clinical applicability, and robust predictive performance to facilitate early identification of hypoglycemia risk in this population. IMPACT: This study systematically evaluated the hypoglycemia risk prediction models for diabetic kidney disease patients during haemodialysis, and the research on hypoglycemia risk prediction models for maintenance haemodialysis patients during dialysis is still in the development stage. This study provides a reference for clinical medical staff to select or develop hypoglycemia risk prediction and assessment tools for diabetic kidney disease patients during haemodialysis. REPORTING METHOD: This study was conducted in accordance with the relevant guidelines of the EQUATOR Network and followed the TRIPOD-SRMA Checklist. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution. TRIAL REGISTRATION: PROSPERO: CRD420251243352.

Humans↗

PubMed2026

Swab Testing to Optimize Pneumonia Treatment With Empiric Vancomycin: A Randomized Controlled Trial.

BACKGROUND: Fear of methicillin-resistant Staphylococcus aureus (MRSA) as a cause of community-acquired pneumonia (CAP) frequently leads to empiric vancomycin coverage. Data evaluating the use of MRSA polymerase chain reaction (PCR) nasal swab testing to guide vancomycin de-escalation is limited for patients in the intensive care unit (ICU). METHODS: Swab Testing to Optimize Pneumonia Treatment With Empiric Vancomycin (STOP-Vanc) is a pragmatic, prospective, single-center, non-blinded randomized trial in which adult ICU patients with suspicion of CAP were randomized 1:1 to receive usual care either with (intervention) or without (control) the addition of MRSA nares PCR testing following ICU admission. The primary outcome was vancomycin-free hours alive, defined as the expected number of hours alive and free of vancomycin use within the first 7 days of trial enrollment as estimated using a longitudinal proportional odds state transition model adjusted for baseline covariates. RESULTS: A total of 277 adult ICU patients were randomized. Methicillin-resistant Staphylococcus aureus PCR nasal swab testing had a negative predictive value (NPV) of 98.9% in the intervention arm. The primary endpoint, vancomycin-free hours alive, was 105.7 in the control arm and 109.7 in the intervention arm (adjusted difference, 4 hours; 95% CI, -9.5-18.2; P = .458). CONCLUSIONS: Despite MRSA PCR nasal swab testing demonstrating a high NPV in this critically ill population, MRSA PCR nasal swab testing did not decrease the duration of vancomycin use or 30-day mortality among ICU patients with suspected CAP. Additional clinician education and antimicrobial stewardship interventions might be needed to reduce vancomycin use in this patient population. CLINICAL TRIALS REGISTRATION: ClinicalTrials.gov NCT06272994 (STOP-Vanc).

Humans↗

PubMed2026

Mul-PheG2P: decoupled learning and prediction-space fusion enables robust and interpretable multi-phenotype genomic prediction.

Genomic prediction of multiple phenotypes is crucial in modern plant breeding; however, existing methods struggle with negative transfer and lack interpretability, particularly across high-dimensional small-sample data and diverse species. To address this, we propose Mul-PheG2P, a novel paradigm based on decoupled learning and predictive space fusion. It employs a two-stage design: first training phenotype-specific encoders using genetic data, then decoupling phenotype-specific learning from cross-phenotype aggregation via an interpretable prediction layer. Mul-PheG2P outperforms existing methods across diverse crop datasets, including maize (Zea mays), wheat (Triticum aestivum), and tomato (Solanum lycopersicum). It provides a multi-scale interpretability chain: at the macro level, it quantifies phenotypic contributions via attention-based weighting; at the micro level, Integrated Gradients reveal the genetic basis of predictions. Notably, the model successfully identified the CCT (CONSTANS, CO-like, and TOC) motif regulating photoperiodism and the SQUAMOSA (SQUAMOSA promoter binding protein) promoter for inflorescence development, confirming its ability to capture functional biological mechanisms. These results highlight the high performance and interpretability of Mul-PheG2P, showcasing its value for low-cost, large-scale screening to advance precision breeding.

Phenotype↗

PubMed2026

Avian egg incubation period: Revisiting existing allometric relationships via surface area-to-volume ratio of an egg.

The incubation period (I) for bird eggs varies among species and is used in establishing allometric relationships. Research on variations in I shed light on the evolutionary mechanisms that gave rise to the differentiation of embryonic development in distinct taxa of birds. Here, using a sampling of 444 images from 444 avian species, 89 families and 30 orders, we calculated their major geometric dimensions: volume (V) and surface area (S). An assessment of the relationship between I and the measured and calculated egg parameters demonstrated the closest and most significant correlation (R = -0.760) between I and the S/V ratio that was adopted as a conditional indicator and reflects the embryo's metabolic rate. Approximation of the values of these parameters made it possible to derive a power-law dependence for the prediction of I depending on the S/V value of a particular egg (R2 = 0.757). The prediction accuracy was higher (R2 = 0.783) if the eggs of the family Procellariiformes (petrels), whose I value is characterized by a longer time, were removed from the general sampling computation. We conclude that the value of the S/V ratio can characterize both the metabolism of an embryo and the conditional thermal conductivity of an egg, which aids in ensuring the temperature regime of egg incubation.

Animals↗

PubMed2026

Age at menopause and subjective cognitive symptoms predict digital cognitive outcomes at the gynecological Well-Woman visit.

INTRODUCTION: Women are at increased risk for Alzheimer's Disease (AD). Growing evidence suggests that the menopausal transition may represent a vulnerable window for development of AD-related pathology. Yet, women are diagnosed with AD later than men. Conducting routine cognitive screenings and integrating information about both cognitive symptoms and age at menopause may help address sex-based disparities in detection and prevention. This study investigated whether subjective cognitive symptoms, in combination with age at menopause, were associated with performance on a digital cognitive task in postmenopausal women. METHODS: 183 postmenopausal women (mean age = 63.8, range = 45-85) were recruited after their Well-Woman visit. Participants completed the Screener for Cognitive Problems in Everyday Life (SCoPE) to assess subjective cognitive symptoms, followed by a sensitive measure of objective cognition: the Linus Health Digital Clock and Recall (DCR™). Information was also collected on age at menopause. We examined associations of subjective cognitive symptoms and age at menopause with digital cognitive performance, adjusting for age, education and depression. Model fit was evaluated using adjusted R2, AIC, and BIC. RESULTS: 48.1% of women reported one or more cognitive symptoms on the SCoPE. On objective testing, 73.2% scored in the normal range, 20.8% in the borderline range, and 6.0% in the impaired range. SCoPE total score was negatively associated with objective cognitive performance in adjusted models (B = -.12, p = .03). Age at menopause showed a significant quadratic association with cognitive performance (B = -0.006, p<.001). SCoPE total was not associated with DCR subtests, while age at menopause predicted both Delayed Recall and Clock Drawing. CONCLUSION: Subjective cognitive symptoms and age at menopause were associated with lower performance on a sensitive, objective cognitive test. Findings support routine cognitive screening and suggest that subjective cognitive symptoms as well as age at menopause are associated with cognitive function.

Humans↗

PubMed2026

HPV circulating tumor DNA as a potential prognostic and predictive biomarker in head and neck squamous cell carcinoma: a systematic review.

PURPOSE: Human papillomavirus circulating tumor DNA (HPVctDNA) has emerged as a promising prognostic biomarker in HPV-related head and neck squamous cell carcinoma (HNSCC). This systematic review aimed to synthesize current evidence on the diagnostic accuracy and prognostic value of HPVctDNA in HNSCC management. MATERIAL/METHODS: We systematically reviewed a PubMed-indexed database of studies published between January 2012 and September 2025. Eligible studies were assessed for design, primary tumor site and stage, treatment modality, HPVctDNA detection method, diagnostic accuracy (sensitivity and specificity), and reported clinical endpoints. Descriptive syntheses were performed; sensitivity and specificity were standardized to proportions and summarized as median values per group. RESULTS: A total of 60 studies, including 8,234 patients were analyzed, of which 41 (68.3%) focused exclusively on oropharyngeal squamous cell carcinoma (OPSCC) and 17 (28.3%) included mixed HPV-related HNSCC subsites and HPV-positive cancers of unknown primary. The median follow-up across the included studies was 23 months. Among the included studies, 19 were retrospective (31.7%) and 33 were prospective (55.0%), with a small proportion of cross-sectional and randomized clinical trials. Overall, 40 (66.7%) evaluated the role of HPVctDNA in a curative setting. Plasma was the most common sample type, analyzed in 55 studies (91.7%), while 5 studies also included saliva. Detection methods varied: 40 employed droplet digital PCR (ddPCR), 16 used quantitative PCR (qPCR) and 4 applied NGS-based assays. Most of these studies (38, 63.3%) evaluated the prognostic utility of HPVctDNA, while only 4 (6.7%) assessed HPVctDNA in a screening or diagnostic setting. Regarding diagnostic accuracy, the median sensitivity across evaluable studies was 91.1%, while the median specificity was 99.4%. In OPSCC-only cohorts, the median sensitivity and specificity were 89.4% and 99.4%, respectively. Dynamic changes in HPVctDNA levels during or after treatment were consistently associated with outcomes: clearance or sustained negativity correlated with higher response rates, improved progression-free survival and overall survival, while persistent positivity or increasing levels predicted disease progression and recurrence. CONCLUSIONS: HPVctDNA demonstrates high diagnostic and prognostic accuracy in HPV-related HNSCC, especially OPSCC, supporting its use for prognosis, treatment monitoring and early detection of recurrence. However, prospective interventional studies are still required to demonstrate that HPVctDNA-guided treatment decisions improve clinical outcomes before routine implementation.

Humans↗

PubMed2026

Test-retest reliability of spatiotemporal, kinematic, and kinetic measures in marker-based 3D gait analysis: A systematic review.

BACKGROUND: Marker-based 3D gait analysis (3DGA) is widely used to quantify impairments and evaluate treatment effects. For longitudinal clinical interpretation, clinicians and researchers need reference values for inter-session measurement error. For this purpose, this systematic review synthesized Standard Error of Measurement (SEM) values for spatiotemporal, kinematic, and kinetic (moments) outcomes obtained from marker-based 3DGA studies. METHODS: PubMed and Scopus were searched (final search: 11 December 2025). Studies reporting inter-session test-retest SEM and/or MDC for steady-state overground or treadmill walking using marker-based motion capture were included. Two authors screened records and appraised methodological/reporting quality using a custom tool informed by COSMIN, GRRAS, and biomechanics-specific items. Due to heterogeneity, results were synthesized descriptively using study-level median SEM values, stratified by joint, plane, population (healthy, pathological, single subgroups), and walking condition. Minimal Detectable Change (MDC) values were computed for all available data. RESULTS: Thirty-four studies (762 participants, 44.2% females) were included, with substantially more evidence for overground than treadmill walking. Overground spatiotemporal outcomes showed low errors (walking speed SEM of 0.06 m/s; timing typically ≤0.03 s; spatial parameters generally ≤0.03 m). For joint kinematics during overground walking, median SEMs were 2.4° (sagittal), 1.9° (frontal), and 3.3° (transverse). The corresponding joint-kinetic SEMs were approximately 0.06, 0.04, and 0.03 Nm/kg, respectively. Treadmill data followed similar patterns. SIGNIFICANCE: Marker-based 3DGA allows for accurate assessment of spatiotemporal, kinematic, and kinetic gait features. We provided detailed SEM/MDC lookup tables to support clinical decision-making. Results further offer a benchmark for validating emerging gait assessment technologies (e.g., markerless systems) against realistic limits of marker-based 3DGA.

Humans↗

PubMed2026

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/µm, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1 µm change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans↗

PubMed2026

Development and Validation of a Predictive Model for Identification of Cognitive Impairment Risk in Older Adults with Subjective Cognitive Decline：A Longitudinal Study.

BACKGROUND: Subjective cognitive decline (SCD) is a transitional state between objective cognitive impairment and cognitively intact mental status, providing a critical window for implementing preventive interventions to delay objective cognitive decline. AIMS: We aimed to develop a predictive model for SCD progression in older adults with mild cognitive impairment (MCI). This model will facilitate the identification of risk factors and establishment of targeted interventions for community-based SCD management. METHODS: Data from the China Health and Retirement Longitudinal Study (CHARLS) was utilized in this study, extracting 18 indicators. Potential predictors selected through univariate Cox regression and LASSO regression analyses were sequentially incorporated into a multivariable Cox regression model. A nomogram was constructed to establish a predictive model. Model validation encompassed Area Under Curve (AUC) metrics for discriminative capacity, complemented by quantitative assessments using calibration curve analysis for precision verification and decision curve analysis (DCA) for clinical utility evaluation. RESULTS: A total of 1099 older adults with SCD were included in the final analysis, of whom 114 (10.3%) developed MCI. Multivariable Cox regression identified residence, marital status, educational level, social participation, gait speed, and baseline cognitive function. The model demonstrated time-dependent AUC values of 0.885, 0.830, 0.839, and 0.836 in the training set when evaluating discriminative capacity at 2-, 4-, 7-, and 9-year, respectively. The predictive model showed excellent predictive ability according to AUC, calibration curve, and DCA. CONCLUSIONS: A predictive model was created to estimate the risk of developing MCI in older individuals with SCD, offering clinician-actionable intervention benchmarks for preventive care.

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

A machine learning-derived and functionally validated circadian rhythm signature predicts clinical outcomes and in silico drug sensitivity in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) displays considerable heterogeneity in clinical outcomes, highlighting the need for reliable prognostic biomarkers. While the aberrant expression of circadian rhythm-related genes has been implicated in cancer pathogenesis, its comprehensive role in CRC progression and predicted therapeutic vulnerabilities remains inadequately characterized. METHODS: Bulk and single-cell RNA-sequencing data were integrated from multiple CRC cohorts. A circadian rhythm signature (CRS) was developed through machine learning algorithms and validated for prognostic value. Comprehensive analyses of tumor microenvironment, genomic alterations, and drug sensitivity were performed. Furthermore, the biological function of the core gene, BHLHE40, was validated in CRC cell lines through CCK-8, EdU, and wound healing assays. RESULTS: Single-cell analysis demonstrated an elevated expression signature of circadian rhythm-related genes in dendritic cells. The optimized CRS, comprising 14 circadian rhythm-related genes, successfully categorized patients into high- and low-risk groups. Patients with a high CRS showed markedly poorer overall survival and computationally inferred immunosuppressive features, including reduced CD8+ T cell infiltration and increased M2 macrophage polarization. Genomic analysis revealed enhanced mutation burden in TP53 and alterations in RTK-RAS/WNT pathways. Notably, in vitro assays confirmed that BHLHE40 is significantly overexpressed in CRC cells. Knockdown of BHLHE40 markedly inhibited tumor cell proliferation and migration. Drug sensitivity profiling identified bexarotene and SMER-3 as potential therapeutic options for high-CRS patients. A nomogram integrating CRS with clinical parameters demonstrated superior predictive accuracy for 1-, 3-, and 5-year survival. CONCLUSIONS: The CRS represents a promising prognostic biomarker that reflects tumor immune status and genomic features, providing valuable insights for personalized treatment strategies in CRC.

Circadian rhythm↗

PubMed2026

Association of the Charlson Comorbidity Index With 1-Year Outcomes in Patients With Macular Edema Secondary to Retinal Vein Occlusion.

OBJECTIVE: To determine the predictive value of the Charlson Comorbidity Index (CCI) for outcomes in patients with macular edema secondary to retinal vein occlusion (RVO). DESIGN: Retrospective clinical cohort study. SUBJECTS: Patients seen between 2013 and 2023 at the Cole Eye Institute, Cleveland Clinic, were included. All patients were >18, diagnosed with RVO (International Classification of Diseases (ICD)-9 and 10 codes), had a complete CCI score, and had at least 1 year of ophthalmic follow-up data after their first intravitreal injection (baseline). Patients with ocular surgery, trauma, or panretinal photocoagulation were excluded. METHODS: Age-adjusted CCI scores were calculated for each patient from chart review. For patients with bilateral RVO, one eye was selected randomly. Patients were stratified into tertiles by CCI distribution: tertile 1 (CCI 0-5; mean 3.4), tertile 2 (age-CCI 4.1-6; mean 4.9), and tertile 3 (CCI ≥ 8; mean 9.6). Multivariable linear regression was performed to determine the predictive value of CCI and other covariates on visual and anatomical outcomes. MAIN OUTCOME MEASURES: Best-corrected visual acuity (BCVA) and central subfield thickness (CST) at 1-year follow-up. RESULTS: A total of 972 patients met all criteria, with an average age-adjusted CCI score of 6.2. Each one-point increase in CCI predicted 0.38 fewer letters in BCVA at follow-up (P < .001). Baseline BCVA was a significant predictor of follow-up BCVA in all tertiles (P < .001). In the third tertile, each one-point increase in CCI was associated with a 0.72 letter reduction in follow-up BCVA (P < .001). For CST, baseline CST was strongly predictive of final CST (P < .001), while CCI was only significant in the first tertile, where each point increase in CCI predicted a 13.7 µm increase in CST (P = .02). In RVO subtype interaction models, the age-adjusted CCI × CRVO interaction was not statistically significant for either 1-year BCVA (P = .269) or 1-year CST (P = .695). CONCLUSIONS: Higher CCI scores are significantly associated with worse visual outcomes in patients with RVO, particularly in the combined population and most comorbid patients (tertile 3). CCI was significantly associated with higher (thicker) CST only among the least comorbid patients (tertile 1).

Humans↗

PubMed2026

Secretory Phospholipase A2 in Patients With Sickle Cell Disease Hospitalized for Vaso-Occlusive Pain Episodes.

BACKGROUND: Secretory phospholipase A2 (sPLA2) is an inflammatory mediator linked to acute chest syndrome (ACS) in sickle cell disease (SCD), a serious complication that can develop during an acute vaso-occlusive pain episode (VOE). Plasma sPLA2 levels have been proposed as a potential biomarker for predicting ACS onset. OBJECTIVE: To assess serial plasma sPLA2 levels in 105 pediatric patients hospitalized for SCD-VOE and determine the effects of arginine therapy compared to placebo. PROCEDURES: This is a pharmacokinetics/pharmacodynamics and randomized controlled trial of intravenous arginine therapy. Statistical methods included t-tests, chi-square, and correlation analyses. RESULTS: Mean age was 12.7 ± 3.7 years, 48% were male, 67% had Hb-SS, and 70% were prescribed hydroxyurea. Using a previously established SCD-specific cutoff of 48 ng/mL, presenting sPLA2 levels were elevated in 33% of patients (mean sPLA2 level 85.7 ± 32.9 ng/mL). SPLA2 elevation in the emergency department was more common in patients with ACS compared to those without ACS (64% vs. 30%; p = 0.02; negative predictive value of 94%). Peak sPLA2 levels were significantly higher in febrile (n = 34) versus afebrile patients (n = 71;101.0 ± 45.3 vs. 48.7 ± 35.4 ng/mL; p < 0.0001). Among subjects with elevated baseline sPLA2, arginine therapy resulted in a significant reduction in sPLA2 levels by discharge compared to placebo (-27.8 ± 38.1 ng/mL; p = 0.002; n = 23 vs. -15.0 ± 41.2 ng/mL; p = 0.23; n = 12). CONCLUSIONS: SPLA2 is an underutilized biomarker of ACS given accumulating evidence of its role. In particular, low levels may identify patients at low risk for ACS. Arginine therapy may modulate inflammation in patients with SCD during VOE and/or ACS. TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT02447874; NCT02536170.

Humans↗

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.

Humans↗

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.

Humans↗

PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Repeated scoring with the adult appendicitis score improves the sensitivity and the specificity of appendicitis diagnosis in patients with early equivocal signs of appendicitis: a secondary analysis.

PURPOSE: The utilization of computed tomography in the early stage of acute appendicitis may result in overdiagnosis and unnecessarily expose patients to ionising radiation. The Adult Appendicitis Score (AAS) can be used to select patients for imaging. Observation and re-scoring in the DIAMOND trial reduced the need for imaging. Now, we wanted to determine if the change in AAS (∆AAS) can serve as a diagnostic tool to select patients for imaging even more precisely. METHODS: Eighty-eight patients with early equivocal appendicitis participated in the observation arm of the DIAMOND trial. The data for these patients were reanalysed, and ∆AAS during the observation was calculated. The baseline AAS, final AAS, and the change in C-reactive protein (∆CRP) were selected as reference standards. RESULTS: Eighty-three patients with complete data were included in the analysis. The AUROC (Area Under the Receiver Operating Characteristic) values are as follows: ∆AAS, 0.932 (95% CI 0.868-0.996); baseline AAS, 0.629 (95% CI 0.498-0.760); final AAS, 0.936 (95% CI 0.886-0.987); and ∆CRP, 0.796 (95% CI 0.696-0.897). Using receiver operating characteristic curves, we established the thresholds for low (AAS ≤ -2), intermediate (AAS -1 to 0), and high (AAS ≥ 1) probability of appendicitis. The negative predictive value for the low-probability group and the positive predictive value for the high-probability group concerning acute appendicitis were 97% and 94%, respectively. CONCLUSION: Patients with equivocal signs of appendicitis may benefit from short observation and the calculation of ∆AAS to reduce overdiagnosis and exposure to excessive imaging. REGISTRATION: The DIAMOND trial was officially registered on ClinicalTrials.gov (NCT02742402) on April 13, 2016.

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