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This study aimed to identify early clinical predictors of non-invasive ventilation (NIV) failure in children with Pediatric Acute Respiratory Distress Syndrome (PARDS) and to develop a model to predict NIV outcomes. A prospective observational study including children (0-15 years) who were supported by NIV and met PARDS criteria was performed in two public PICUs in Chile. Demographic, physiological variables, and clinical outcomes were recorded. Logistic regression was used to identify risk factors for NIV failure and develop a predictive model. Seventy-six patients were enrolled (median age 22 months [IQR 11-48]; weight 12.1 kg [9.6-18.3]). Eighteen patients (24%) failed NIV (Failure group), with a median NIV duration of 12.5 h (IQR 8-23.8). The Failure group showed a significant reduction in the SpO2/FiO2 ratio after 2 h of NIV (-59 [-124 to 5] vs -2 [-49 to 30], p = 0.03). In multivariate analysis, an increase in ΔSpO2/FiO2 (improvement in oxygenation) was associated with lower odds of NIV failure (OR 0.98; 95% CI 0.97-0.99; p = 0.006), indicating that worsening oxygenation was associated with a higher risk. The final prediction model included age and early changes in SpO2/FiO2, respiratory rate, and heart rate, demonstrating good discrimination (AUROC 0.764; 95% CI 0.641-0.888). In children with PARDS treated with NIV, a model including age and early changes in oxygenation, heart rate, and respiratory rate within the first 2 h predicts the need for intubation with good discrimination.
To develop and validate a prediction model combining Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI) diffusion-weighted imaging (DWI) parameters and clinicopathologic features for preoperative prediction of microvascular invasion (MVI) in hepatocellular carcinoma (HCC). This study applied a retrospective method to collect preoperative MRI imaging data of patients with HCC from January 2021 to June 2025. All 279 patients (mean age of 58, M:F=203:76, 195 cases in training set and 84 cases in validation set) underwent MRI by Gd-EOB-DTPA and received DWI imaging scan before surgery. The MRI imaging features were observed, and the apparent diffusion coefficient (ADC) of the tumor solid region and tumor-to-liver parenchyma relative intensity ratio (RIR) were measured. LASSO logistic regression algorithm and multivariate analysis method were conducted to analyze the correlation between preoperative MRI imaging features and MVI. The prediction model was established, and the efficiency evaluation of the model was performed. Among 279 patients, 66 cases (23.66%) were MVI-positive. The study subjects were assigned to a training set (195 cases) and a validation set (84 cases) at a 7:3 ratio. Twelve variables were selected by LASSO regression. Multivariate analysis identified RIR transitional phase (OR=0.21), tumor size (OR=4.52), and ADC (OR=0.63) as independent predictors of MVI (P=0.029, <0.001, 0.032). The model achieved an AUC of 0.85 in the training set and 0.83 in the validation set. The negative predictive value (NPV) was 0.94 and 0.90 in the training and validation sets, respectively, while the positive predictive value (PPV) was limited to 0.49 and 0.40. Calibration curve and decision curve analyses demonstrated good consistency and clinical utility. On the basis of clinicopathologic features, MRI imaging features, and DWI parameters, this study preliminarily constructs a prediction model for positive MVI risk in HCC patients. The model exhibits good discrimination and a high NPV for effectively ruling out MVI, but its limited PPV warrants cautious interpretation of positive predictions due to a high false-positive rate.
Type 2 diabetes mellitus (T2DM) is a group of metabolic diseases characterized by chronic hyperglycemia, primarily caused by insulin resistance and/or pancreatic beta cell dysfunction. Glibenclamide, a second-generation sulfonylurea oral hypoglycemic agent, plays a crucial role in managing T2DM. Our objective was to establish a population pharmacokinetic model of glibenclamide in Chinese healthy volunteers and use this model to guide the adjustment of individualized dosage regimens. We collected 476 concentration observations of glibenclamide from 20 Chinese healthy volunteers in a phase I clinical trial. A fundamental three-compartment pharmacokinetic model with instantaneous zero-order absorption and linear elimination was developed using the first-order conditional estimation method by NONMEM software. A covariate model was developed by screening for relevant covariates based on the base model. Internal validation of the final model was performed using visual predictive checks and bootstrap methods. The reference standard for the final model was used to assess the quality of the simulated doses. A PopPK model of glibenclamide in Chinese healthy volunteers was successfully established. Age significantly impacted the apparent distribution volume of the central compartment. Validation results indicate that the final model is stable. Simulation results indicate that the model has good goodness of fit. The established population model accurately represents the pharmacokinetics of glibenclamide in Chinese healthy volunteers and based on this model, can be further extrapolated to inform individualized medication strategies for glibenclamide in the treatment of T2DM in the future.
A Systematic Review and Bayesian Network Meta-Analysis. To compare the efficacy and perioperative outcomes of conservative medical treatment (CMT) and surgical interventions-including decompressive craniectomy (DC), craniotomy (CC), endoscopic surgery (ES), and minimally invasive puncture surgery (MIPS)-in patients with spontaneous intracerebral hemorrhage (ICH). Spontaneous intracerebral hemorrhage (ICH) is a severe neurological emergency associated with substantial mortality and long-term disability. Although several surgical strategies have been developed to reduce hematoma burden and secondary brain injury, the comparative effectiveness and perioperative trade-offs among different interventions remain controversial. Direct head-to-head randomized evidence comparing multiple surgical strategies is limited, complicating evidence-based clinical decision-making. We conducted a systematic review and network meta-analysis (NMA) in accordance with PRISMA 2020 and PRISMA-NMA guidelines. PubMed, Web of Science, and Cochrane Library were searched from inception to January 2026 for randomized controlled trials comparing CMT, DC, CC, ES, and MIPS in patients with spontaneous ICH. Primary outcomes included 6-month mortality and good functional outcome at 6 months. Secondary outcomes included hematoma clearance rate, operative time, intraoperative blood loss, and length of hospital stay. Pairwise meta-analysis was performed using Stata 18.0, and Bayesian NMA was conducted in R 4.3.1 using the gemtc and BUGSnet packages. Surface under the cumulative ranking curve (SUCRA) values were used to rank interventions. Eighteen randomized controlled trials involving 4,497 patients were included. For good functional outcome at 6 months, MIPS (SUCRA = 87.0) and ES (SUCRA = 84.6) ranked highest and were significantly superior to CC and CMT, whereas no significant difference was observed between MIPS and ES. For 6-month mortality, DC probabilistically ranked highest (SUCRA = 81.5), although most pairwise comparisons did not reach statistical significance. Regarding perioperative outcomes, both ES and MIPS significantly reduced operative time and intraoperative blood loss compared with CC, with MIPS showing the largest reductions. ES achieved higher hematoma clearance rates and shorter hospital stay, whereas MIPS demonstrated lower hematoma clearance. MIPS and ES may provide advantages in functional recovery and perioperative burden in spontaneous ICH, whereas DC may offer potential survival benefit, although current evidence remains uncertain. Clinical decision-making should balance long-term outcomes against perioperative trade-offs and be individualized according to disease severity and patient-specific risk factors. Additional high-quality multicenter randomized trials are needed to clarify the role of DC and define optimal indications for each surgical strategy.
We examined the association of COVID time periods and equity-related variables with pharmacotherapy in a large jurisdiction fracture liaison service (FLS). We did not observe a significant association between COVID time periods and medication prescription after adjusting for all covariates. This highlights another potential success of the FLS model. Our objective was to examine the impact of COVID on bone-active medication prescription in a fracture liaison service (FLS), after adjusting for fracture risk status and equity-related variables. We conducted a logistic regression analysis with medication prescription (prescription by a bone health specialist or primary care provider) as the outcome. The model included covariates COVID time periods (T1: "pre-COVID" (n = 2796); T2: "during COVID" (n = 1575); T3: "COVID recovery" (n = 2208)), fracture risk status (high risk/not high risk) and equity-related variables (sex, age, marital status, living arrangement, education status, geographic location, and presence of comorbidities). Goodness of fit was assessed with the area under the receiver operating characteristic curve (AUC) and the Hosmer and Lemeshow test. Fracture risk status was the primary driver of treatment with high-risk patients 7.8 times more likely to receive a medication prescription compared to patients who were not high risk, after adjusting for all covariates (OR = 7.80 [95% CI 6.91, 8.79]). COVID time period was not statistically significant. Female patients, those married or in a common-law relationship, living alone, or residing in urban areas were more likely to be prescribed medication. The model had good prediction power and fit the data well (AUC: 0.77; Hosmer-Lemeshow test p-value: 0.83). Among patients reached by the FLS, COVID time period was not significantly associated with medication prescription, although program reach decreased at T2 and T3. Fracture risk status, sex, marital status, living arrangement, and geographic location were significantly associated with medication prescription.
A copper-catalyzed sulfonylative cyclization of o-vinylanilides with sulfonyl chlorides has been developed, providing efficient access to sulfonylated 4H-benzo[d][1,3]oxazines under mild conditions. The transformation proceeds at room temperature and exhibits a broad substrate scope and functional-group compatibility, affording structurally diverse products in good to excellent yields. The method is amenable to the late-stage diversification of complex molecules. Preliminary mechanistic studies support a copper-mediated radical cyclization process.
The one-pot synthesis of uracil-benzofuran bis-heterocycles is reported via the base-catalyzed reaction of ortho-hydroxyphenyl propargylamines with 6-amino-1,3-dimethyluracil in good to excellent yields. This efficient protocol proceeds under mild conditions without the need for transition-metal catalysts or an inert atmosphere, offering a sustainable and practical synthetic route. The reaction mechanism involves a sequence of 1,4-conjugate addition, alkyne-allene isomerization, and 5-exo-dig cyclization processes. Furthermore, to validate the experimental results and provide deeper insight into the chemical behavior, the electronic structures and the relative energies of the products were investigated using Density Functional Theory (DFT) at the B3LYP/6-311++G** level. The calculated results showed excellent agreement with the experimental observations.
Relapsed/refractory follicular lymphoma (R/R FL) remains a clinically challenging condition, with progressively declining benefit across consecutive lines of therapy. While anti-Cluster of Differentiation 20 (CD20) antibodies remain the therapeutic backbone, the optimal targeted or immune-based partner remains undefined. A systematic review and network meta-analysis (NMA) of 5 phase III and 1 phase II trials (2500 patients) evaluated seven anti-CD20-based combination strategies. Primary end-points were overall survival (OS) and progression-free survival (PFS); secondary end-points included objective response rate (ORR) and grade ≥3 adverse events. Treatments were ranked using surface under the cumulative ranking (SUCRA) values. Immune-activating strategies ranked highest across efficacy end-points. Epcoritamab plus rituximab (R2) achieved the top SUCRA rankings for OS, PFS and ORR, while tafasitamab plus R2 consistently ranked second, with a better safety profile. R2 alone showed intermediate efficacy and good tolerability, whereas zanubrutinib plus anti-CD20 demonstrated modest efficacy with lower toxicity. Bortezomib and copanlisib-based combinations ranked lowest for efficacy, with phosphoinositide 3-kinase (PI3K) inhibitor-based regimens showing the least favourable benefit-risk profile. Anti-CD20 monotherapy was the safest but least effective option. This NMA indicates that immune-centric, anti-CD20-anchored combinations represent the most effective chemotherapy-free strategies for R/R FL. Combinations incorporating anti-CD19 or CD20/CD3 bispecific antibodies appear to offer deeper disease control, particularly in high-risk and rituximab-refractory disease.
The integration of clinical skills and humanistic literacy is a paramount objective in modern medical education. This study evaluates a novel tutorial-based model designed to promote early clinical-humanities integration for first-year medical students. A cross-sectional study was conducted at Zhejiang University School of Medicine. A self-reported questionnaire was administered to first-year medical students enrolled in the "Whole Life Cycle Health I" course (N = 275). The questionnaire assessed their adaptation to this model, learning interest, perceived promotion of clinical-humanities integration, module effectiveness, and self-rated competency improvement. Most students reported good adaptation (90.9%) and increased learning interest (88.0%). Although adaptation levels were comparable between genders, male students expressed significantly stronger agreement regarding enhanced interest and the model's effectiveness in fostering integration (p < 0.05). Key practical modules-including "Simulated Outpatient Role-Playing," "AI-Powered Science Video Production," and "Postpartum Home Visits"-were rated as highly effective. Students reported substantial improvement in patient communication (87.3%) and teamwork (85.1%), despite challenges like time constraints and task integration difficulties. The tutorial-based model is perceived by students as a feasible, promising, and well-received strategy for early clinical-humanities integration, demonstrating significant potential for broader implementation in medical education reform.
Simultaneous detection of biologically relevant thiols and toxic heavy metal ions is important for biomedical analysis, food safety, and environmental monitoring. Cysteine (Cys) is a key sulfur-containing amino acid involved in redox regulation, whereas mercury(II) (Hg2⁺) is a highly toxic pollutant that binds strongly to thiol groups. This Hg2⁺-thiol interaction provides a chemical basis for sequential Cys/Hg2⁺ sensing. However, many nanozyme-based optical assays rely on H₂O₂-dependent peroxidase-like activity, and the instability of H₂O₂ can compromise assay reproducibility and practical use. Here, we synthesized a core-shell Fe₃C@NC nanozyme through a two-step hydrothermal-calcination strategy. Fe₃C nanoparticles were encapsulated within a nitrogen-doped carbon shell to support stable oxidase-like catalysis. Fe₃C@NC catalyzed the H₂O₂-independent oxidation of o-phenylenediamine to fluorescent 2,3-diaminophenazine using dissolved oxygen. This reaction was coupled with Cys-mediated signal inhibition and Hg2⁺-induced signal recovery to construct a sequential ON-OFF-ON dual-readout platform. Cys suppressed fluorescence by scavenging reactive oxygen species, whereas Hg2⁺ restored the signal through coordination with the thiol group of Cys. The fluorescence detection limits were 28 nM for Cys and 12 nM for Hg2⁺. Smartphone-assisted RGB analysis enabled portable visual quantification and showed good consistency with fluorescence measurements. The method was validated in human serum, milk, and environmental water samples, giving satisfactory recoveries and acceptable precision. This work presents an H₂O₂-free Fe₃C@NC nanozyme platform that links oxidase-like OPD oxidation with thiol-mediated signal regulation, providing a simple strategy for sensitive laboratory analysis and portable visual detection in complex samples.
Cysteine (Cys), an essential endogenous biothiol, plays crucial roles in cellular redox homeostasis, metabolic regulation, and detoxification. Abnormal Cys fluctuations are closely associated with various pathological processes, including liver injury. Lipid droplets are dynamic organelles involved in lipid metabolism and stress responses and are highly relevant to hepatic injury progression. Thus, fluorescent probes capable of both lipid droplet localization and Cys-specific recognition are valuable tools for visualizing Cys fluctuations in drug-induced liver injury-related microenvironments. Herein, a diphenylamine-modified fluorescent probe, BDC, was designed and synthesized for selective Cys imaging. By tuning the electron-donating unit, the response pattern of BDC toward biothiols was regulated, enabling selective recognition of Cys. Spectroscopic investigations showed that BDC displayed a significant fluorescence enhancement toward Cys, together with good selectivity, anti-interference ability, sensitivity, photostability, and suitable pH adaptability. Bioimaging experiments demonstrated that BDC could effectively visualize endogenous and exogenous Cys in living cells and showed favorable lipid droplet localization. Moreover, BDC was successfully applied to monitor Cys fluctuations in zebrafish and an APAP-induced liver injury model. This work provides a practical molecular tool for visualizing Cys dynamics in drug-induced liver injury-related biological systems.
The study aimed to analyze maternal and neonatal outcomes of women with a history of three or four caesarean sections (CS) and to evaluate the feasibility and safety of vaginal birth after multiple caesarean sections (VBAC ≥ 3) in Polish clinical practice. A retrospective analysis was conducted on medical records of 186 women with three or four prior CS who delivered at St. Sophia Specialist Hospital in Warsaw between 2017 and 2024. Data on delivery mode, obstetric management, complications, and neonatal outcomes were assessed. Multivariate logistic regression was applied to identify factors associated with successful VBAC. Of the study group, 62 women attempted trial of labour after caesarean (TOLAC), resulting in 32 successful vaginal births (success rate 53.2%). 124 women chose Elective CS. Logistic regression showed that prior vaginal birth (OR = 20.34; p = 0.008) and the use of epidural anaesthesia (OR = 22.88; p = 0.006) significantly increased the likelihood of successful VBAC. Spontaneous onset of labour showed a positive but non-significant trend (OR = 2.52; p = 0.230). The model demonstrated a classification accuracy of 77.4% and a good overall fit (Nagelkerke R² = 0.456). Uterine rupture occurred in three cases (4.8%), while no maternal or neonatal deaths were reported. Vaginal birth after three or more CS may be a viable option for carefully selected women, provided it is offered in tertiary centers with immediate surgical readiness. Key predictors of success include prior vaginal birth and epidural anaesthesia. Further large-scale studies are needed to refine guidelines and inform clinical practice in this high-risk group.
Nanozymes with intrinsic enzyme-like activities have demonstrated considerable potential in diverse fields ranging from biosensing to therapeutics. However, their development remains compromised by scientific challenges such as insufficient catalytic efficiency and stability. Herein, we propose an innovative "nano-uniform distribution" strategy to engineer an Au-ceria heterostructure nanocatalyst by in situ anchoring ultrasmall cerium oxide nanoparticles onto Au nanorods. Under near-infrared (NIR) light irradiation, this nanocatalyst exhibits not only excellent photothermal properties but also a significantly enhanced enzyme-mimetic catalytic efficiency. Moreover, in the absence of light, it retains robust reactive oxygen species (ROS) scavenging capability and good biocompatibility. Subsequent evaluation using an epidermal infected wound model demonstrates that the nanocomposite catalyst exhibits an "all-temporal" therapeutic functionality: with NIR irradiation, the Au-ceria composite nanocatalyst synergistically combats bacterial infection through photothermal and enzymatic catalytic effects; without NIR irradiation, it effectively clears excess ROS and mitigates inflammatory responses. In summary, this study presents a "nano-uniform distribution" strategy that markedly improves the catalytic performance of nanozymes, offering valuable insights for the structural design of nanozymes and their biomedical applications.
Pancreatic ductal adenocarcinoma (PDAC) exhibits five-year survival rates below 10% with profound therapeutic resistance mediated by stromal barriers and immunosuppression (Rahib et al. 2014; Siegel et al. 2023). Recent evidence suggests intratumoral mycobiome alterations may influence disease progression (Aykut et al. 2019; Riquelme et al. 2019). We performed comprehensive network pharmacology analysis to elucidate potential therapeutic mechanisms of Saccharomyces boulardii (SB) and Clostridium histolyticum collagenase (CHC) in PDAC. Gene sets representing immune activation, metabolic competition, and stromal remodeling were analyzed using protein-protein interaction networks (STRING v11.5), functional enrichment (DAVID v2021), and pathway databases (KEGG, Reactome, WikiPathways). Structural assessment employed blind molecular docking (CB-Dock2) and coarse-grained molecular dynamics (CABS-flex). Computational analysis was performed on TCGA-PAAD data (n = 177 patients, 93 events) using Cox regression and five machine learning classifiers (Logistic Regression, Random Forest, Gradient Boosting, XGBoost, LightGBM) with Q1/Q3 survival stratification and strict fivefold nested cross-validation with within-fold feature selection (SelectKBest, k = 5). Random survival forest (RSF) incorporating 67 high-quality genes from four mechanistically curated modules was developed for time-to-event prediction, evaluated by AUC-ROC and Harrell's C-index. Permutation-based feature selection identified prognostic biomarkers. Network analysis identified TNF, IL6, IFNG, and TLR4 as central hubs (degree > 15) with dense interconnectivity (clustering coefficient = 0.78). Pathway enrichment revealed over-representation in IL-17, TLR, and IL-10 signaling (BH-FDR < 0.05). Molecular docking revealed high-affinity interactions with AKT1 (ΔG = - 7.2 kcal/mol), TLR2 (- 7.6 kcal/mol), TLR4 (- 6.9 kcal/mol), and KRAS-SOS1 interface (- 6.9 kcal/mol). Kaplan-Meier analysis demonstrated significant survival differences by composite immune-metabolic signature (log-rank p = 0.0001) and immune sub-signature (CXCL9, CXCL10, CXCL11; p = 0.0028). The metabolic sub-signature (LDHA, ALDH9A1) demonstrated a significant continuous prognostic effect by Cox regression (HR = 1.431, p = 0.0292), with median dichotomisation not reaching significance (log-rank p = 0.2164), indicating a gradient rather than threshold effect. Cox modelling of the composite five-gene score identified it as a strong negative prognostic factor (HR = 1.897, p < 0.0001). Machine learning classifiers achieved good-to-strong discrimination of survival extremes under strict nested cross-validation (AUC range: 0.631-0.745; Logistic Regression: AUC = 0.745 ± 0.036), confirmed by permutation testing (n = 1000 permutations, empirical p < 0.01). RSF modelling on the full cohort achieved C-index = 0.649 ± 0.040 using the top-5 gene signature, representing acceptable discrimination for PDAC. Permutation-based feature selection identified CXCL11, CXCL10, CXCL9, LDHA, and ALDH9A1 as top prognostic biomarkers. Tertile-based risk stratification demonstrated significant survival separation between Low and High Risk groups (log-rank p = 0.0005). Kinetic modeling showed 4.2-fold SB competitive advantage under tumor hypoglycemia (< 1 mM glucose). Network analysis, structural modeling, and machine learning support biological plausibility of SB anti-tumor activity through immune activation and stromal remodeling. RSF modelling (C-index = 0.649) and Cox regression (HR = 1.897, p < 0.0001) provide a computational framework for patient stratification. Identification of CXCL11, CXCL10, CXCL9, LDHA, and ALDH9A1 as prognostic biomarkers spanning immune and metabolic modules provides targets for clinical monitoring. This systems-level framework provides mechanistic rationale for clinical investigation of intratumoral S. boulardii as adjuvant PDAC therapy. The online version contains supplementary material available at 10.1007/s40203-026-00685-6.
To evaluate performance of MRI-based radiomics for evaluating response to neoadjuvant chemotherapy (NACT) in head and neck squamous cell carcinoma (HNSCC) patients. We performed a comprehensive search across four databases until July, 2025 to include studies evaluating diagnostic performance of MRI radiomics in response assessment. Methodological quality of studies was assessed using METhodological RadiomICs Score (METRICS). Using a random-effects bivariate model diagnostic values of area under the curve (AUC), sensitivity, and specificity were calculated. Meta-regression and subgroup analyses were used to explore the source of heterogeneity. Twenty-one studies were included. The overall predictive performance of MRI-radiomics in the validation set was good, with a summary AUC of 0.84 (95% CI: 0.81-0.87) in differentiation of complete or partial response (CR/PR) and non-responders as those with stable or progressive disease (SD/PD). High heterogeneity was observed, but there was no evidence of publication bias (Deeks' test p = 0.20). Subgroup analysis resolved the heterogeneity and showed similar performance of model across different therapeutic regimens, study designs, study qualities, and MRI magnitudes of strength. For classifying only CR as responders and PR + SD + PD as non-responders, MRI-radiomics achieved an AUC of 0.83 (95% CI: 0.79-0.86) with low heterogeneity. MRI radiomics demonstrated high predictive value in evaluating NACT response for HNSCC patients, showing consistent performance across different clinical scenarios. However, the current evidence base is largely retrospective, geographically limited, and predominantly derived from nasopharyngeal cancer cohorts; therefore, broader external validation and prospective multicenter designs are required before routine clinical implementation.
Accurate quantification of punch force is essential for performance assessment and training optimization in combat sports. This study introduces a Custom-Built Punch Force Dynamometer using two S-type load cells and evaluates its reliability, sensitivity, and partial ecological validity under sport-specific conditions. The device was mounted vertically on a wall and tested under both controlled and sport-specific conditions. Mechanical trials were assessed using a standardized drop-weight protocol with repeated trials. Partial ecological validity involved 11 experienced athletes from striking-based combat sports performing standardized straight punches across two lab visits. Reliability metrics included intraclass correlation coefficients (ICC), standard error of measurement (SEM), and smallest worthwhile change (SWC). The dynamometer demonstrated excellent reliability during mechanical trials (ICC > 0.90) and good to excellent reliability during partial ecological validity (ICC = 0.75-0.90). SEM values were consistently lower than SWC, indicating strong measurement sensitivity. These findings support the reliability and practical utility of this device for assessing punch force in both laboratory-based research and sport-specific applications.
To identify independent risk factors for postoperative proliferative vitreoretinopathy (PVR) in patients with primary rhegmatogenous retinal detachment (RRD) treated with scleral buckling surgery and to develop a nomogram for predicting postoperative PVR. Patients who underwent scleral buckling surgery for primary RRD were retrospectively enrolled. Patients were randomly assigned to a training cohort (n=515) and a validation cohort (n=55). Candidate variables included demographic characteristics, systemic comorbidities, preoperative ocular status, and retinal break features. Independent predictors of postoperative PVR were identified using univariate and multivariate logistic regression analyses. A nomogram was constructed to predict the risk of PVR at 1, 3, and 6mo after surgery. Model performance was evaluated using the concordance index (C-index), receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). A total of 570 eyes were included, with mean age of 52.65±15.70y, and 51.4% of patients were male. Postoperative PVR occurred in 28.8% of eyes overall, including 28.5% in the training cohort and 30.9% in the validation cohort. Postoperative PVR developed in a subset of patients during follow-up. Preoperative PVR, a history of diabetes mellitus, and more than four retinal breaks were identified as independent risk factors for postoperative PVR. In the training cohort, the C-indices of the nomogram at 1, 3, and 6mo were 0.888, 0.931, and 0.948, respectively, and 0.885, 0.885, and 0.909 in the validation cohort. ROC and calibration analyses demonstrated good discrimination and agreement, while DCA showed favorable net clinical benefit across a wide range of threshold probabilities. Preoperative PVR, diabetes mellitus, and more than four retinal breaks are independent predictors of postoperative PVR after scleral buckling for RRD. The proposed nomogram provides accurate individualized risk prediction at 1, 3, and 6mo postoperatively, and may assist clinicians in postoperative surveillance and decision-making.
Denosumab has transformed the management of giant cell tumor of bone (GCTB), particularly in cases that are unresectable or surgically morbid. However, accumulating reports of malignant transformation (MT) during or after therapy have raised concern about a potential causal association. We conducted a systematic review and meta-analysis to estimate the incidence of MT in denosumab-treated GCTB and to characterize the clinical, radiological, and pathological features of affected patients. We searched PubMed/MEDLINE, Scopus, and Web of Science to October 2025 for studies reporting denosumab-treated GCTB with MT. Clinical trials, cohort studies, case series, and case reports with original patient data were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. A random-effects meta-analysis was used to pool MT incidence. Twenty-four studies were included in the qualitative analysis, and 11 (800 denosumab-treated patients) contributed to the meta-analysis. MT was reported in 18 patients. The pooled incidence of MT was 3% (95% CI 2-7%; I2 = 49.2%). Patients who transformed typically had high-risk disease, characterized by axial or otherwise surgically challenging sites, multiple prior local procedures, recurrent disease, or previous radiotherapy. Among cases with available timing data, MT was diagnosed from 3 months to 6 years after denosumab initiation, although most transformations occurred during active treatment or within 1-3 years of treatment initiation. MT most often manifested as high-grade osteosarcoma or undifferentiated pleomorphic sarcoma, characterized by biphasic histology, a markedly increased Ki-67 index, and variable H3F3A status. The prognosis was poor despite aggressive multimodal treatment. Cohort studies were generally rated as fair to good quality, whereas non-randomized interventional studies had a serious to critical risk of bias. MT in denosumab-treated GCTB is rare and does not appear more frequent than historical baseline rates, but it predominantly affects a biologically and clinically high-risk subgroup. Vigilant clinical and radiological surveillance, prompt re-biopsy of atypical lesions, and referral to expert sarcoma centers are essential, and prospective registries with integrated molecular profiling are urgently needed.
Insulin resistance and metabolic dysregulation are increasingly recognized as contributors to myocardial remodeling and phenotypic heterogeneity in hypertrophic cardiomyopathy (HCM). While the triglyceride-glucose (TyG) index offers a simple surrogate marker of insulin resistance, its relationship with left ventricular outflow tract (LVOT) obstruction in HCM patients remains underexplored. This study aimed to investigate the association between the TyG index and LVOT obstruction in a retrospective observational cohort of 124 adult HCM patients. LVOT obstruction was defined as a resting or provoked gradient of ≥30 mmHg. Clinical, laboratory, and echocardiographic data were systematically evaluated. The TyG index was computed from fasting triglyceride and glucose levels. Multivariable logistic regression analysis, with the TyG index scaled per 0.1-unit increment, was used to assess independent associations. Receiver operating characteristic (ROC) curve analysis determined discriminatory performance. Patients with obstructive HCM exhibited significantly higher TyG index values compared to those without obstruction (9.07 ± 0.25 vs. 8.76 ± 0.21, p<0.001). The TyG index maintained an independent association with LVOT obstruction after adjusting for relevant clinical and echocardiographic covariates (per 0.1-unit increase: OR 1.84, 95% CI 1.40-2.42, p<0.001). Furthermore, the TyG index demonstrated moderate correlations with both resting (r=0.519, p<0.001) and provoked (r=0.557, p<001) LVOT gradients. ROC analysis indicated good discriminatory performance (AUC: 0.826, 95% CI: 0.752-0.901), with a cut-off value of 8.75 yielding 87.9% sensitivity and 47.0% specificity. In conclusion, the TyG index was independently associated with LVOT obstruction in HCM patients, with higher values observed in those with the obstructive phenotype. This suggests a potential link between metabolic status and disease manifestation in HCM. Given its cost-effectiveness and accessibility, the TyG index may offer valuable complementary clinical insights. However, this association requires cautious interpretation, and prospective studies are essential to establish its clinical and prognostic utility.