This paper presents a control strategy of demand pulled spare parts inventory. It establishes a spare part demand prognosticating model based on reliability analysis. Through parts reliability data the model gets the...This paper presents a control strategy of demand pulled spare parts inventory. It establishes a spare part demand prognosticating model based on reliability analysis. Through parts reliability data the model gets the reliable life function of spare parts and determines parts demand time, depending on part life at given reliabilities. Moreover, a case study is taken to illuminate the demand prognostication and inventory control of on condition maintenance rotables.展开更多
BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are p...BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.展开更多
Based on the El Nino event data sequence from 1854 to 1993, the nature of sequences was de-termined by using statistical normal and independent tests, etc. With the Markov random process and first order auto-regressio...Based on the El Nino event data sequence from 1854 to 1993, the nature of sequences was de-termined by using statistical normal and independent tests, etc. With the Markov random process and first order auto-regression predictive model, we set up the prognostication mode and give the time limit of the occurrence of next El Nino event, which probably occurs around 2002.The occurring probability for 2001 is 44 %, and it is 61 % for 2002.展开更多
The systemic response to tissue injury, regardless of cause is characterized by a cytokine-mediated alteration in the hepatic synthesis of a number of different plasma proteins,known collectively as 'acute pha... The systemic response to tissue injury, regardless of cause is characterized by a cytokine-mediated alteration in the hepatic synthesis of a number of different plasma proteins,known collectively as 'acute phase reactants'. These proteins include C-reactive protein, serum amyloid A protein, alphal glycoprotein, ceruloplasmin, alpha macroglobulins, complement components (C1-C4, factor B, C9, C11), alpha1antitrypsin, alpha1 antichymotrypsin, fibrinogen, prothrombin,factor Ⅷ, plasminogen, haptoglobin, ferritin, immunoglobulins and lipoproteins. The initiation of the acute phase response is linked to the production of hormone-like polypeptide mediators now called cytokines, namedly, interleukin 1(IL-1),tumor necrosis factor, interferon gamma, interleukin 6 (IL-6),leukemia inhibitory factor, ciliary neurotropic factor, oncostatin M, and interleukin 11 (IL- 11).……展开更多
Background:Liver resection and local ablation are the only curative treatment for non-cirrhotic hepatocellular carcinoma(HCC).Few data exist concerning the prognosis of patients resected for non-cirrhotic HCC.The obje...Background:Liver resection and local ablation are the only curative treatment for non-cirrhotic hepatocellular carcinoma(HCC).Few data exist concerning the prognosis of patients resected for non-cirrhotic HCC.The objectives of this study were to determine the prognostic factors of recurrence-free survival(RFS)and overall survival(OS)and to develop a prognostication algorithm for non-cirrhotic HCC.Methods:French multicenter retrospective study including HCC patients with non-cirrhotic liver without underlying viral hepatitis:F0,F1 or F2 fibrosis.Results:A total of 467 patients were included in 11 centers from 2010 to 2018.Non-cirrhotic liver had a fibrosis score of F0(n=237,50.7%),F1(n=127,27.2%)or F2(n=103,22.1%).OS and RFS at 5 years were 59.2%and 34.5%,respectively.In multivariate analysis,microvascular invasion and HCC differentiation were prognostic factors of OS and RFS and the number and size were prognostic factors of RFS(P<0.005).Stratification based on RFS provided an algorithm based on size(P=0.013)and number(P<0.001):2 HCC with the largest nodule≤10 cm(n=271,Group 1);2 HCC with a nodule>10 cm(n=176,Group 2);>2 HCC regardless of size Conclusions:We developed a prognostication algorithm based on the number(≤or>2)and size(≤or>10 cm),which could be used as a treatment decision support concerning the need for perioperative therapy.In case of bifocal HCC,surgery should not be a contraindication.展开更多
This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma pa...This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma patients undergoing combined camrelizumab and lenvatinib therapy.While we acknowledge the study’s clinical relevance in proposing an easily accessible metabolic biomarker,we delve into the mechanistic plausibility linking insulin resistance to immunotherapy response and angiogenic inhibition.We further critically examine the methodological limitations,including the retrospective design,the populationspecific TyG cut-off value,and unaddressed metabolic confounders.We highlight the imperative for future research to validate its utility across diverse etiologies and treatment settings,and to unravel the underlying immunometabolic pathways.展开更多
AIM:To evaluate the clinical characteristics and risk factors associated with visual prognosis in patients with open globe injuries(OGIs)treated at Vietnam National Eye Hospital.METHODS:A prospective observational stu...AIM:To evaluate the clinical characteristics and risk factors associated with visual prognosis in patients with open globe injuries(OGIs)treated at Vietnam National Eye Hospital.METHODS:A prospective observational study included patients with OGIs treated between June 2023 and June 2024.Data on demographics,injury features,and clinical findings were extracted from medical records.Poor visual outcome was defined as final best-corrected visual acuity(BCVA)worse than 20/400 or no light perception.Multivariable logistic regression was performed to identify independent risk factors.RESULTS:Among 509 patients(636 eyes),the mean age was 35.13y(range 20–51y),and 67.6%were male.After treatment,the proportion of eyes achieving≥20/40 increased from 12.6%to 42.1%,while no light perception decreased from 29.1%to 9.4%.Independent predictors of poor visual outcomes included delayed admission[>4h,odds ratio(OR)=3.33,95%confidence intervals(CI):1.76–6.33,P<0.001],Zone III injury(OR=5.90,95%CI:2.85–12.24,P<0.001),wound length>10 mm(OR=2.59,95%CI:1.60–4.18,P<0.001),relative afferent pupillary defect(RAPD,OR=1.65,95%CI:1.03–2.64,P=0.039),endophthalmitis(OR=1.75,95%CI:1.01–3.03,P=0.047),retinal detachment(OR=3.32,95%CI:2.02–5.45,P<0.001),and eyelid lacerations(OR=1.94,95%CI:1.13–3.33,P=0.016)associated with OGIs.Vitreous hemorrhage(OR=0.44,95%CI:0.22–0.89,P=0.023)was associated with better outcomes,and female gender appeared protective.CONCLUSION:Poor visual outcomes remain common after OGIs,despite improve visual acuity in many cases.Several clinical and injury-related factors are strongly associated with prognosis.Early recognition of these predictors can support risk stratification and improve trauma care in similar settings.展开更多
Ossiculoplasty remains a challenging surgical procedure,with outcomes heavily influenced by diverse anatomical and pathological factors.Over the decades,numerous scoring systems have been developed to predict the prog...Ossiculoplasty remains a challenging surgical procedure,with outcomes heavily influenced by diverse anatomical and pathological factors.Over the decades,numerous scoring systems have been developed to predict the prognosis of ossiculoplasty,each emphasizing different variables such as ossicular status,middle ear environment,and surgical history.This paper provides a comprehensive review of the evolution of prognostic scoring systems,including Austin's original ossicular classification,Bellucci's otorrhea staging,the Middle Ear Risk Index(MERI),the Ossiculoplasty Outcome Parameter Staging(OOPS),and the recently introduced Ear Environment Risk(EER)scale.While these systems have significantly contributed to preoperative assessment,each presents notable limitations in encompassing all variables affecting surgical success.Therefore,the aim of this paper is to provide a review of the ossiculoplasty prognostic scores and show the benefits,innovations and gaps associated with each.To address these gaps,a novel,modified scoring system is proposed,incorporating previously overlooked but clinically significant factors such as tympanic membrane status,type of tympanoplasty,ossicular replacement material,CT scan findings,and the presence of complicated ear conditions.By synthesizing elements from historical scores with updated clinical insights,the proposed system aims to provide a more holistic and predictive framework for preoperative evaluation.Future multicenter studies are encouraged to validate the efficacy and prognostic power of this new scoring system,with the goal of improving surgical planning and patient counseling in ossiculoplasty.展开更多
According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HC...According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HCC)accounts for approximately 85%−90%[2,3].Its incidence and mortality rates remain persistently high worldwide.However,China has the highest incidence and mortality rates of the disease in the world[4].And the majority of patients are diagnosed at intermediate or advanced stages.Thus,identifying novel tumor biomarkers for early detection and implementing precision therapy has long been a key focus of research.展开更多
Male breast cancer(MBC)is rare,representing 0.5%–1%of all breast cancers,but its incidence is increasing due to improved diagnostics and awareness.MBC typically presents in older men,is human epidermal growth factor ...Male breast cancer(MBC)is rare,representing 0.5%–1%of all breast cancers,but its incidence is increasing due to improved diagnostics and awareness.MBC typically presents in older men,is human epidermal growth factor receptor 2(HER2)-negative and estrogen receptor(ER)-positive,and lacks routine screening,leading to delayed diagnosis and advanced disease.Major risk factors include hormonal imbalance,radiation exposure,obesity,alcohol use,and Breast Cancer Gene 1 and 2(BRCA1/2)mutations.Clinically,it may resemble gynecomastia but usually appears as a unilateral,painless mass or nipple discharge.Advances in imaging and liquid biopsy have enhanced early detection.Molecular mechanisms involve hormonal signaling,HER2/epidermal growth factor receptor(EGFR)pathways,tumor suppressor gene alterations,and epigenetic changes.While standard treatments mirror those for female breast cancer,emerging options such as cyclin-dependent kinase 4 and 6(CDK4/6),and poly(ADP-ribose)polymerase(PARP)inhibitors,immunotherapy,and precision medicine are reshaping management.Incorporating artificial intelligence,molecular profiling,and male-specific clinical trials is essential to improve outcomes and bridge current diagnostic and therapeutic gaps.展开更多
Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A d...Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A deep learning model was trained on 340 WSIs and externally validated using 81 TCGA cases.Image-derived features extracted through convolutional neural networks were integrated with clinicopathological variables.Model performance was assessed using ROC curve analysis,and interpretability was evaluated by correlating image features with mRNA-seq data and characteristics of the immune microenvironment.Results The model achieved AUCs of 0.86 and 0.75 in the training and validation cohorts,respectively.Analysis using HoVer-Net indicated that lymphocyte abundance was associated with recurrence risk.Texture-related features showed significant correlations with immune cell infiltration and prognostic gene expression profiles.Conclusion This study demonstrates that deep learning can enable accurate prognostic prediction in early-stage TNBC,with interpretable image features that reflect the tumor immune microenvironment and gene expression profiles.展开更多
Objective:We investigated the clinical value of a novel circulating tumor cell(CTC)detection method—subtraction enrichment combined with immunostaining and fluorescence in situ hybridization(SEi FISH)—in ovarian can...Objective:We investigated the clinical value of a novel circulating tumor cell(CTC)detection method—subtraction enrichment combined with immunostaining and fluorescence in situ hybridization(SEi FISH)—in ovarian cancer(OC).This study evaluated the diagnostic and prognostic significance of chromosome 8aneuploidy in CTCs and circulating tumor endothelial cells(CTECs)for preoperative diagnosis,treatment efficacy assessment,and recurrence monitoring.Methods:A total of 331 patients were enrolled,including 56 with newly diagnosed primary OC,265 with benign ovarian tumors,and 10 with borderline tumors.Peripheral blood CTCs and CTECs were detected using SEi FISH;their quantity and ploidy characteristics were analyzed in relation to clinical indicators.To assess dynamic CTC changes during disease progression and treatment response,72 patients were followed longitudinally,of whom 19 experienced recurrence.Results:The CTC detection rate in OC patients was 92.9%,with significantly higher counts than that in the benign tumor group(median 5 vs.2).Receiver operating characteristic analysis demonstrated good diagnostic performance for total CTCs[area under the curve(AUC)=0.699],with triploid CTCs achieving the highest efficacy(AUC=0.792),surpassing carbohydrate antigen 125(CA125)(AUC=0.702).Postoperative follow-up showed that70%of patients exhibited concurrent decreases in CTCs and CA125 levels,indicating disease improvement.In30%of patients,CTC levels did not correlate with changes in CA125 levels.Individual case evidence suggests that CTC alterations may serve as an early indicator of recurrence or metastasis.Among the 19 recurrent cases,73.7%showed elevated CTCs at recurrence that decreased following treatment.In four patients,CTCs reflected disease progression earlier than CA125,indicating higher sensitivity for recurrence monitoring.Conclusions:CTCs with chromosome 8 aneuploidy demonstrate significant clinical value in the preoperative diagnosis,treatment efficacy evaluation,and recurrence monitoring of OC.Dynamic CTC changes may serve as a more sensitive indicator than CA125 for disease surveillance,supporting the translational potential of CTC-based biomarkers in OC.展开更多
BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initi...BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initiation,progression,metastasis,therapeutic resistance,and disease recurrence.Cancer stem cells possess selfrenewal capacity,multipotent differentiation potential,and enhanced tumorigenic activity,but their molecular characteristics and regulatory mechanisms require further investigation.AIM To comprehensively characterize the molecular features of BCSCs through multiomics approaches,construct a prognostic prediction model based on stem cellrelated genes,reveal cell-cell communication networks within the tumor microenvironment,and provide theoretical foundation for personalized treatment strategies.METHODS Flow cytometry was employed to detect the expression of BCSC surface markers(CD34,CD45,CD29,CD90,CD105).Transcriptomic analysis was performed to identify differentially expressed genes.Least absolute shrinkage and selection operator regression analysis was utilized to screen key prognostic genes and construct a risk scoring model.Single-cell RNA sequencing and spatial transcriptomics were applied to analyze tumor heterogeneity and spatial gene expression patterns.Cell-cell communication network analysis was conducted to reveal interactions between stem cells and the microenvironment.RESULTS Flow cytometric analysis revealed the highest expression of CD105(96.30%),followed by CD90(68.43%)and CD34(62.64%),while CD29 showed lower expression(7.16%)and CD45 exhibited the lowest expression(1.19%).Transcriptomic analysis identified 3837 significantly differentially expressed genes(1478 upregulated and 2359 downregulated).Least absolute shrinkage and selection operator regression analysis selected 10 key prognostic genes,and the constructed risk scoring model effectively distinguished between high-risk and low-risk patient groups(P<0.001).Single-cell analysis revealed tumor cellular heterogeneity,and spatial transcriptomics demonstrated distinct spatial expression gradients of stem cell-related genes.MED18 gene showed significantly higher expression in malignant tissues(P<0.001)and occupied a central position in cell-cell communication networks,exhibiting significant correlations with tumor cells,macrophages,fibroblasts,and endothelial cells.CONCLUSION This study comprehensively characterized the molecular features of BCSCs through multi-omics approaches,identified reliable surface markers and key regulatory genes,and constructed a prognostic prediction model with clinical application value.展开更多
Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including ...Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.展开更多
AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospecti...AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospective cohort study enrolled 29 patients diagnosed with OA-DLBCL based on histopathological biopsy between 2006 and 2023.Patients were stratified into two subgroups:primary OA-DLBCL(no prior history of lymphoma)and secondary OA-DLBCL(history of DLBCL at non-ocular adnexal sites).OS was defined as the time interval from OA-DLBCL diagnosis to death from any cause.Survival analysis was performed using the Kaplan–Meier method,and prognostic factors affecting OS were identified using multivariate Cox proportional hazards regression with a stepwise selection approach.RESULTS:The cohort included 24 patients with primary OA-DLBCL(13 males,11 females;mean age:61.36±18.29y)and 5 patients with secondary OA-DLBCL(2 males,3 females;mean age:50.94±18.17y).Among the primary OA-DLBCL subgroup,12 patients(50%)presented with advanced disease(Ann Arbor stage IIIE–IV),and 16 patients(66%)were classified as T4 disease according to the tumor-node-metastasis(TNM)staging system.The mean final visual acuity was 1.72±1.10 in the primary group and 0.90±1.18 in the secondary group.The 5-year OS rate for the entire cohort was 27.7%.Multivariate analysis identified five factors significantly associated with poor survival outcomes:epiphora[adjusted hazard ratio(aHR),36.95],atherosclerotic cardiovascular disease(aHR,10.08),human immunodeficiency virus(HIV)infection(aHR,12.47),M1 stage(aHR,6.99),and secondary OA-DLBCL(aHR,6.03;all P<0.05).The median OS was 1.68y for primary OA-DLBCL and 1.12y for secondary OA-DLBCL.CONCLUSION:A substantial proportion of patients with primary OA-DLBCL present with advanced-stage disease at diagnosis.Epiphora,atherosclerotic cardiovascular disease,HIV infection,M1 stage,and secondary OA-DLBCL are independent prognostic factors for poor survival outcomes.These findings emphasize the urgent need for optimized therapeutic strategies and early screening protocols to improve the management of OA-DLBCL,particularly in developing countries.展开更多
Background:Currently,surgical resection is the mainstay for colorectal liver metastases(CRLM)management and the only potentially curative treatment modality.Prognostication tools can support patient selection for surg...Background:Currently,surgical resection is the mainstay for colorectal liver metastases(CRLM)management and the only potentially curative treatment modality.Prognostication tools can support patient selection for surgical resection to maximize therapeutic benefit.This study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong Kong.Methods:Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the study.Survival analysis was performed using Cox proportional hazards(CPH).A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator(LASSO)regression was applied to a multiply-imputed dataset to build a prediction model.The model was validated in the validation set,and its performance was compared with that of Fong Clinical Risk Score(CRS)using concordance index.Results:A total of 572 patients were included with a median follow-up of 3.6 years.The full models for overall survival(OS)and recurrence-free survival(RFS)consist of the same 8 established and novel variables,namely colorectal cancer nodal stage,CRLM neoadjuvant treatment,Charlson Comorbidity Score,pre-hepatectomy bilirubin and carcinoembryonic antigen(CEA)levels,CRLM largest tumor diameter,extrahepatic metastasis detected on positron emission-tomography(PET)-scan as well as KRAS status.Our CRLM Machine-learning Algorithm Prognostication model(CMAP)demonstrated better ability to predict OS(C-index=0.651),compared with the Fong CRS for 1-year(C-index=0.571)and 5-year OS(C-index=0.574).It also achieved a C-index of 0.651 for RFS.Conclusions:We present a promising machine learning algorithm to individualize prognostications for patients following resection of CRLM with good discriminative ability.展开更多
Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al report...Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al reports on red cell distribution width(RDW)/platelet ratio(RPR)as a non-invasive biomarker in predicting decompensation of metabolic dysfunction-associated steatotic liver disease(MASLD)-related cACLD.Differently from other biomarkers and algorithms,RPR is inexpensive and widely available,based on parameters which are included in a complete blood count.RPR is computed on the grounds of two different items,one of which,RDW,mirrors the host’s response to a variety of disease stimuli and is non-specific.The second parameter involved in RPR,platelet count,is more specific and has been used in the hepatological clinic to discriminate cirrhotic from non-cirrhotic chronic liver disease for decades.Cardiovascular disease is the primary cause of mortality among MASLD subjects,followed by extra-hepatic cancers and liver-related mortality.Therefore,MASLD biomarkers should be validated not only in terms of liver-related events but also in the prediction of major adverse cardiovascular events and cardiovascular mortality and extra-hepatic cancers.Adequately sized multi-ethnic confirmatory investigation is required to define the role and significance of RPR in the stratification of MASLD-cACLD.展开更多
Detection and treatment of colorectal cancer(CRC)at an early stage is vital for long-term survival.Liquid biopsy has emerged as a promising new avenue for non-invasive screening of CRC as well as prognostication and s...Detection and treatment of colorectal cancer(CRC)at an early stage is vital for long-term survival.Liquid biopsy has emerged as a promising new avenue for non-invasive screening of CRC as well as prognostication and surveillance of minimal residual disease.Cell free DNA(cfDNA)is a promising liquid biopsy analyte and has been approved for use in clinical practice.Here,we explore the current challenges of utilizing cfDNA in the screening and prognostication of CRC but also for detecting driver mutations in healthy,presymptomatic patients with normal colonic crypts.CfDNA for the detection of cancerous or premalignant colonic lesions has already been extensively explored,however few have considered utilizing cfDNA in the detection of driver mutations in healthy patients.Theoretically,this would allow us to detect patients who are at a higher risk of tumorigenesis decades in advance of established malignancy and stratify them into higher risk groups for early-intervention screening programs.We also explore the solutions necessary to overcome the challenges that prevent liquid biopsy from entering mainstream clinical use.The potential for liquid biopsy is immense if these challenges are successfully circumvented,and can dramatically reduce CRC rates as well as improve survival in patients.展开更多
Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heter...Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heterogeneity among patients.Traditional clinical criteria often fail to identify those most likely to benefit from surgery.Methods:This nationwide retrospective study in China included 2,167 ICH patients from 31 hospitals.Using machine learning techniques,we integrated clinical and radiomic data to perform unsupervised clustering and identify distinct phenogroups.Dimensionality reduction and cross-validation were applied to minimize overfitting.External validation was conducted using data from the INTERACT3 trial,and a prospective cohort was used to assess real-world applicability.Results:Three phenogroups were identified.Among them,only Phenogroup 1-characterized by older age,moderate hematoma volume,and intermediate Glasgow Coma Scale scores-showed significant benefit from early surgical intervention,with a 42%reduction in 3-month mortality and improved functional outcomes.In contrast,surgery did not significantly affect outcomes in Phenogroups 0 and 2.These findings were consistent across multiple machine learning models and validated externally.Conclusion:Machine learning-driven phenotypic stratification can effectively identify ICH patients who are most likely to benefit from surgical treatment.This approach supports personalized treatment strategies and may improve clinical decision-making in ICH management.Further validation in diverse populations is warranted.展开更多
Perioperative morbidity of esophagectomy significantly affects the surgical outcome,like any major gastrointestinal procedure.Despite introduction of minimally invasive esophagectomy,the morbidity is still close to 30...Perioperative morbidity of esophagectomy significantly affects the surgical outcome,like any major gastrointestinal procedure.Despite introduction of minimally invasive esophagectomy,the morbidity is still close to 30%-40%.The common complications following esophagectomy are pulmonary infections,cardiac events,anastomotic leakage,bleeding,chylous leak,and recurrent laryngeal nerve palsy which in turn lead to longer hospital stay,increased treatment cost and poor quality of life.A nomographic model comprising preoperative(patient,disease and treatment related)and intraoperative factors in combination with Artificial Intelligence may accurately identify the patients at higher risk of morbidity.This will aid in optimizing the modifiable risk factors preoperatively,and closely monitor these patients post operatively for early identification of complications and to initiate early corrective measures to improve the surgical outcome.展开更多
文摘This paper presents a control strategy of demand pulled spare parts inventory. It establishes a spare part demand prognosticating model based on reliability analysis. Through parts reliability data the model gets the reliable life function of spare parts and determines parts demand time, depending on part life at given reliabilities. Moreover, a case study is taken to illuminate the demand prognostication and inventory control of on condition maintenance rotables.
文摘BACKGROUND Liver transplantation(LT)is a life-saving intervention for patients with end-stage liver disease.However,the equitable allocation of scarce donor organs remains a formidable challenge.Prognostic tools are pivotal in identifying the most suitable transplant candidates.Traditionally,scoring systems like the model for end-stage liver disease have been instrumental in this process.Nevertheless,the landscape of prognostication is undergoing a transformation with the integration of machine learning(ML)and artificial intelligence models.AIM To assess the utility of ML models in prognostication for LT,comparing their performance and reliability to established traditional scoring systems.METHODS Following the Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines,we conducted a thorough and standardized literature search using the PubMed/MEDLINE database.Our search imposed no restrictions on publication year,age,or gender.Exclusion criteria encompassed non-English studies,review articles,case reports,conference papers,studies with missing data,or those exhibiting evident methodological flaws.RESULTS Our search yielded a total of 64 articles,with 23 meeting the inclusion criteria.Among the selected studies,60.8%originated from the United States and China combined.Only one pediatric study met the criteria.Notably,91%of the studies were published within the past five years.ML models consistently demonstrated satisfactory to excellent area under the receiver operating characteristic curve values(ranging from 0.6 to 1)across all studies,surpassing the performance of traditional scoring systems.Random forest exhibited superior predictive capabilities for 90-d mortality following LT,sepsis,and acute kidney injury(AKI).In contrast,gradient boosting excelled in predicting the risk of graft-versus-host disease,pneumonia,and AKI.CONCLUSION This study underscores the potential of ML models in guiding decisions related to allograft allocation and LT,marking a significant evolution in the field of prognostication.
基金Research project of meteorological science and technology in China (96-908-05-03)
文摘Based on the El Nino event data sequence from 1854 to 1993, the nature of sequences was de-termined by using statistical normal and independent tests, etc. With the Markov random process and first order auto-regression predictive model, we set up the prognostication mode and give the time limit of the occurrence of next El Nino event, which probably occurs around 2002.The occurring probability for 2001 is 44 %, and it is 61 % for 2002.
文摘 The systemic response to tissue injury, regardless of cause is characterized by a cytokine-mediated alteration in the hepatic synthesis of a number of different plasma proteins,known collectively as 'acute phase reactants'. These proteins include C-reactive protein, serum amyloid A protein, alphal glycoprotein, ceruloplasmin, alpha macroglobulins, complement components (C1-C4, factor B, C9, C11), alpha1antitrypsin, alpha1 antichymotrypsin, fibrinogen, prothrombin,factor Ⅷ, plasminogen, haptoglobin, ferritin, immunoglobulins and lipoproteins. The initiation of the acute phase response is linked to the production of hormone-like polypeptide mediators now called cytokines, namedly, interleukin 1(IL-1),tumor necrosis factor, interferon gamma, interleukin 6 (IL-6),leukemia inhibitory factor, ciliary neurotropic factor, oncostatin M, and interleukin 11 (IL- 11).……
文摘Background:Liver resection and local ablation are the only curative treatment for non-cirrhotic hepatocellular carcinoma(HCC).Few data exist concerning the prognosis of patients resected for non-cirrhotic HCC.The objectives of this study were to determine the prognostic factors of recurrence-free survival(RFS)and overall survival(OS)and to develop a prognostication algorithm for non-cirrhotic HCC.Methods:French multicenter retrospective study including HCC patients with non-cirrhotic liver without underlying viral hepatitis:F0,F1 or F2 fibrosis.Results:A total of 467 patients were included in 11 centers from 2010 to 2018.Non-cirrhotic liver had a fibrosis score of F0(n=237,50.7%),F1(n=127,27.2%)or F2(n=103,22.1%).OS and RFS at 5 years were 59.2%and 34.5%,respectively.In multivariate analysis,microvascular invasion and HCC differentiation were prognostic factors of OS and RFS and the number and size were prognostic factors of RFS(P<0.005).Stratification based on RFS provided an algorithm based on size(P=0.013)and number(P<0.001):2 HCC with the largest nodule≤10 cm(n=271,Group 1);2 HCC with a nodule>10 cm(n=176,Group 2);>2 HCC regardless of size Conclusions:We developed a prognostication algorithm based on the number(≤or>2)and size(≤or>10 cm),which could be used as a treatment decision support concerning the need for perioperative therapy.In case of bifocal HCC,surgery should not be a contraindication.
文摘This commentary critically appraises the study by Li et al which pioneered the exploration of the triglyceride-glucose(TyG)index as a prognostic marker in hepatitis B virus-related advanced hepatocellular carcinoma patients undergoing combined camrelizumab and lenvatinib therapy.While we acknowledge the study’s clinical relevance in proposing an easily accessible metabolic biomarker,we delve into the mechanistic plausibility linking insulin resistance to immunotherapy response and angiogenic inhibition.We further critically examine the methodological limitations,including the retrospective design,the populationspecific TyG cut-off value,and unaddressed metabolic confounders.We highlight the imperative for future research to validate its utility across diverse etiologies and treatment settings,and to unravel the underlying immunometabolic pathways.
文摘AIM:To evaluate the clinical characteristics and risk factors associated with visual prognosis in patients with open globe injuries(OGIs)treated at Vietnam National Eye Hospital.METHODS:A prospective observational study included patients with OGIs treated between June 2023 and June 2024.Data on demographics,injury features,and clinical findings were extracted from medical records.Poor visual outcome was defined as final best-corrected visual acuity(BCVA)worse than 20/400 or no light perception.Multivariable logistic regression was performed to identify independent risk factors.RESULTS:Among 509 patients(636 eyes),the mean age was 35.13y(range 20–51y),and 67.6%were male.After treatment,the proportion of eyes achieving≥20/40 increased from 12.6%to 42.1%,while no light perception decreased from 29.1%to 9.4%.Independent predictors of poor visual outcomes included delayed admission[>4h,odds ratio(OR)=3.33,95%confidence intervals(CI):1.76–6.33,P<0.001],Zone III injury(OR=5.90,95%CI:2.85–12.24,P<0.001),wound length>10 mm(OR=2.59,95%CI:1.60–4.18,P<0.001),relative afferent pupillary defect(RAPD,OR=1.65,95%CI:1.03–2.64,P=0.039),endophthalmitis(OR=1.75,95%CI:1.01–3.03,P=0.047),retinal detachment(OR=3.32,95%CI:2.02–5.45,P<0.001),and eyelid lacerations(OR=1.94,95%CI:1.13–3.33,P=0.016)associated with OGIs.Vitreous hemorrhage(OR=0.44,95%CI:0.22–0.89,P=0.023)was associated with better outcomes,and female gender appeared protective.CONCLUSION:Poor visual outcomes remain common after OGIs,despite improve visual acuity in many cases.Several clinical and injury-related factors are strongly associated with prognosis.Early recognition of these predictors can support risk stratification and improve trauma care in similar settings.
文摘Ossiculoplasty remains a challenging surgical procedure,with outcomes heavily influenced by diverse anatomical and pathological factors.Over the decades,numerous scoring systems have been developed to predict the prognosis of ossiculoplasty,each emphasizing different variables such as ossicular status,middle ear environment,and surgical history.This paper provides a comprehensive review of the evolution of prognostic scoring systems,including Austin's original ossicular classification,Bellucci's otorrhea staging,the Middle Ear Risk Index(MERI),the Ossiculoplasty Outcome Parameter Staging(OOPS),and the recently introduced Ear Environment Risk(EER)scale.While these systems have significantly contributed to preoperative assessment,each presents notable limitations in encompassing all variables affecting surgical success.Therefore,the aim of this paper is to provide a review of the ossiculoplasty prognostic scores and show the benefits,innovations and gaps associated with each.To address these gaps,a novel,modified scoring system is proposed,incorporating previously overlooked but clinically significant factors such as tympanic membrane status,type of tympanoplasty,ossicular replacement material,CT scan findings,and the presence of complicated ear conditions.By synthesizing elements from historical scores with updated clinical insights,the proposed system aims to provide a more holistic and predictive framework for preoperative evaluation.Future multicenter studies are encouraged to validate the efficacy and prognostic power of this new scoring system,with the goal of improving surgical planning and patient counseling in ossiculoplasty.
基金supported by a grant from the Central Level Public Welfare Research Institutes Basic Research Expenses of Chinese Academy of Medical Sciences(No.2023-RW320-05)。
文摘According to the 2024 global cancer data from GLOBOCAN,liver cancer ranks the 6th most common malignancy and the 3rd leading cause of cancer-related mortality worldwide[1].Among these cases,hepatocellular carcinoma(HCC)accounts for approximately 85%−90%[2,3].Its incidence and mortality rates remain persistently high worldwide.However,China has the highest incidence and mortality rates of the disease in the world[4].And the majority of patients are diagnosed at intermediate or advanced stages.Thus,identifying novel tumor biomarkers for early detection and implementing precision therapy has long been a key focus of research.
文摘Male breast cancer(MBC)is rare,representing 0.5%–1%of all breast cancers,but its incidence is increasing due to improved diagnostics and awareness.MBC typically presents in older men,is human epidermal growth factor receptor 2(HER2)-negative and estrogen receptor(ER)-positive,and lacks routine screening,leading to delayed diagnosis and advanced disease.Major risk factors include hormonal imbalance,radiation exposure,obesity,alcohol use,and Breast Cancer Gene 1 and 2(BRCA1/2)mutations.Clinically,it may resemble gynecomastia but usually appears as a unilateral,painless mass or nipple discharge.Advances in imaging and liquid biopsy have enhanced early detection.Molecular mechanisms involve hormonal signaling,HER2/epidermal growth factor receptor(EGFR)pathways,tumor suppressor gene alterations,and epigenetic changes.While standard treatments mirror those for female breast cancer,emerging options such as cyclin-dependent kinase 4 and 6(CDK4/6),and poly(ADP-ribose)polymerase(PARP)inhibitors,immunotherapy,and precision medicine are reshaping management.Incorporating artificial intelligence,molecular profiling,and male-specific clinical trials is essential to improve outcomes and bridge current diagnostic and therapeutic gaps.
基金Supported by Capital’s Funds for Health Improvement and Research(CFH2024-1-4021)。
文摘Objective To develop a prognostic prediction model for early-stage triple-negative breast cancer(TNBC)using H&E-stained pathological images and to investigate its underlying biological interpretability.Methods A deep learning model was trained on 340 WSIs and externally validated using 81 TCGA cases.Image-derived features extracted through convolutional neural networks were integrated with clinicopathological variables.Model performance was assessed using ROC curve analysis,and interpretability was evaluated by correlating image features with mRNA-seq data and characteristics of the immune microenvironment.Results The model achieved AUCs of 0.86 and 0.75 in the training and validation cohorts,respectively.Analysis using HoVer-Net indicated that lymphocyte abundance was associated with recurrence risk.Texture-related features showed significant correlations with immune cell infiltration and prognostic gene expression profiles.Conclusion This study demonstrates that deep learning can enable accurate prognostic prediction in early-stage TNBC,with interpretable image features that reflect the tumor immune microenvironment and gene expression profiles.
基金sponsored by the Peking University People’s Hospital Research and Development Fund(No.RDZH2024-06)the National Key Research and Development Program of China(No.2022YFC2704204)。
文摘Objective:We investigated the clinical value of a novel circulating tumor cell(CTC)detection method—subtraction enrichment combined with immunostaining and fluorescence in situ hybridization(SEi FISH)—in ovarian cancer(OC).This study evaluated the diagnostic and prognostic significance of chromosome 8aneuploidy in CTCs and circulating tumor endothelial cells(CTECs)for preoperative diagnosis,treatment efficacy assessment,and recurrence monitoring.Methods:A total of 331 patients were enrolled,including 56 with newly diagnosed primary OC,265 with benign ovarian tumors,and 10 with borderline tumors.Peripheral blood CTCs and CTECs were detected using SEi FISH;their quantity and ploidy characteristics were analyzed in relation to clinical indicators.To assess dynamic CTC changes during disease progression and treatment response,72 patients were followed longitudinally,of whom 19 experienced recurrence.Results:The CTC detection rate in OC patients was 92.9%,with significantly higher counts than that in the benign tumor group(median 5 vs.2).Receiver operating characteristic analysis demonstrated good diagnostic performance for total CTCs[area under the curve(AUC)=0.699],with triploid CTCs achieving the highest efficacy(AUC=0.792),surpassing carbohydrate antigen 125(CA125)(AUC=0.702).Postoperative follow-up showed that70%of patients exhibited concurrent decreases in CTCs and CA125 levels,indicating disease improvement.In30%of patients,CTC levels did not correlate with changes in CA125 levels.Individual case evidence suggests that CTC alterations may serve as an early indicator of recurrence or metastasis.Among the 19 recurrent cases,73.7%showed elevated CTCs at recurrence that decreased following treatment.In four patients,CTCs reflected disease progression earlier than CA125,indicating higher sensitivity for recurrence monitoring.Conclusions:CTCs with chromosome 8 aneuploidy demonstrate significant clinical value in the preoperative diagnosis,treatment efficacy evaluation,and recurrence monitoring of OC.Dynamic CTC changes may serve as a more sensitive indicator than CA125 for disease surveillance,supporting the translational potential of CTC-based biomarkers in OC.
基金the Natural Science Foundation of Yongchuan District,No.2023yc-jckx20021.
文摘BACKGROUND Breast cancer is one of the most prevalent malignancies affecting women worldwide,with approximately 2.3 million new cases diagnosed annually.Breast cancer stem cells(BCSCs)play pivotal roles in tumor initiation,progression,metastasis,therapeutic resistance,and disease recurrence.Cancer stem cells possess selfrenewal capacity,multipotent differentiation potential,and enhanced tumorigenic activity,but their molecular characteristics and regulatory mechanisms require further investigation.AIM To comprehensively characterize the molecular features of BCSCs through multiomics approaches,construct a prognostic prediction model based on stem cellrelated genes,reveal cell-cell communication networks within the tumor microenvironment,and provide theoretical foundation for personalized treatment strategies.METHODS Flow cytometry was employed to detect the expression of BCSC surface markers(CD34,CD45,CD29,CD90,CD105).Transcriptomic analysis was performed to identify differentially expressed genes.Least absolute shrinkage and selection operator regression analysis was utilized to screen key prognostic genes and construct a risk scoring model.Single-cell RNA sequencing and spatial transcriptomics were applied to analyze tumor heterogeneity and spatial gene expression patterns.Cell-cell communication network analysis was conducted to reveal interactions between stem cells and the microenvironment.RESULTS Flow cytometric analysis revealed the highest expression of CD105(96.30%),followed by CD90(68.43%)and CD34(62.64%),while CD29 showed lower expression(7.16%)and CD45 exhibited the lowest expression(1.19%).Transcriptomic analysis identified 3837 significantly differentially expressed genes(1478 upregulated and 2359 downregulated).Least absolute shrinkage and selection operator regression analysis selected 10 key prognostic genes,and the constructed risk scoring model effectively distinguished between high-risk and low-risk patient groups(P<0.001).Single-cell analysis revealed tumor cellular heterogeneity,and spatial transcriptomics demonstrated distinct spatial expression gradients of stem cell-related genes.MED18 gene showed significantly higher expression in malignant tissues(P<0.001)and occupied a central position in cell-cell communication networks,exhibiting significant correlations with tumor cells,macrophages,fibroblasts,and endothelial cells.CONCLUSION This study comprehensively characterized the molecular features of BCSCs through multi-omics approaches,identified reliable surface markers and key regulatory genes,and constructed a prognostic prediction model with clinical application value.
基金Supported by Xuhui District Health Commission,No.SHXH202214.
文摘Gastrointestinal tumors require personalized treatment strategies due to their heterogeneity and complexity.Multimodal artificial intelligence(AI)addresses this challenge by integrating diverse data sources-including computed tomography(CT),magnetic resonance imaging(MRI),endoscopic imaging,and genomic profiles-to enable intelligent decision-making for individualized therapy.This approach leverages AI algorithms to fuse imaging,endoscopic,and omics data,facilitating comprehensive characterization of tumor biology,prediction of treatment response,and optimization of therapeutic strategies.By combining CT and MRI for structural assessment,endoscopic data for real-time visual inspection,and genomic information for molecular profiling,multimodal AI enhances the accuracy of patient stratification and treatment personalization.The clinical implementation of this technology demonstrates potential for improving patient outcomes,advancing precision oncology,and supporting individualized care in gastrointestinal cancers.Ultimately,multimodal AI serves as a transformative tool in oncology,bridging data integration with clinical application to effectively tailor therapies.
基金Supported by the Faculty of Medicine,Prince of Songkla University.Wainipitapong S has received grants from the Faculty of Medicine,Prince of Songkla University。
文摘AIM:To investigate the clinical characteristics and treatment outcomes,including visual function and overall survival(OS)of patients with ocular adnexal diffuse large B-cell lymphoma(OA-DLBCL).METHODS:This retrospective cohort study enrolled 29 patients diagnosed with OA-DLBCL based on histopathological biopsy between 2006 and 2023.Patients were stratified into two subgroups:primary OA-DLBCL(no prior history of lymphoma)and secondary OA-DLBCL(history of DLBCL at non-ocular adnexal sites).OS was defined as the time interval from OA-DLBCL diagnosis to death from any cause.Survival analysis was performed using the Kaplan–Meier method,and prognostic factors affecting OS were identified using multivariate Cox proportional hazards regression with a stepwise selection approach.RESULTS:The cohort included 24 patients with primary OA-DLBCL(13 males,11 females;mean age:61.36±18.29y)and 5 patients with secondary OA-DLBCL(2 males,3 females;mean age:50.94±18.17y).Among the primary OA-DLBCL subgroup,12 patients(50%)presented with advanced disease(Ann Arbor stage IIIE–IV),and 16 patients(66%)were classified as T4 disease according to the tumor-node-metastasis(TNM)staging system.The mean final visual acuity was 1.72±1.10 in the primary group and 0.90±1.18 in the secondary group.The 5-year OS rate for the entire cohort was 27.7%.Multivariate analysis identified five factors significantly associated with poor survival outcomes:epiphora[adjusted hazard ratio(aHR),36.95],atherosclerotic cardiovascular disease(aHR,10.08),human immunodeficiency virus(HIV)infection(aHR,12.47),M1 stage(aHR,6.99),and secondary OA-DLBCL(aHR,6.03;all P<0.05).The median OS was 1.68y for primary OA-DLBCL and 1.12y for secondary OA-DLBCL.CONCLUSION:A substantial proportion of patients with primary OA-DLBCL present with advanced-stage disease at diagnosis.Epiphora,atherosclerotic cardiovascular disease,HIV infection,M1 stage,and secondary OA-DLBCL are independent prognostic factors for poor survival outcomes.These findings emphasize the urgent need for optimized therapeutic strategies and early screening protocols to improve the management of OA-DLBCL,particularly in developing countries.
文摘Background:Currently,surgical resection is the mainstay for colorectal liver metastases(CRLM)management and the only potentially curative treatment modality.Prognostication tools can support patient selection for surgical resection to maximize therapeutic benefit.This study aimed to develop a survival prediction model using machine learning based on a multicenter patient sample in Hong Kong.Methods:Patients who underwent hepatectomy for CRLM between 1 January 2009 and 31 December 2018 in four hospitals in Hong Kong were included in the study.Survival analysis was performed using Cox proportional hazards(CPH).A stepwise selection on Cox multivariable models with Least Absolute Shrinkage and Selection Operator(LASSO)regression was applied to a multiply-imputed dataset to build a prediction model.The model was validated in the validation set,and its performance was compared with that of Fong Clinical Risk Score(CRS)using concordance index.Results:A total of 572 patients were included with a median follow-up of 3.6 years.The full models for overall survival(OS)and recurrence-free survival(RFS)consist of the same 8 established and novel variables,namely colorectal cancer nodal stage,CRLM neoadjuvant treatment,Charlson Comorbidity Score,pre-hepatectomy bilirubin and carcinoembryonic antigen(CEA)levels,CRLM largest tumor diameter,extrahepatic metastasis detected on positron emission-tomography(PET)-scan as well as KRAS status.Our CRLM Machine-learning Algorithm Prognostication model(CMAP)demonstrated better ability to predict OS(C-index=0.651),compared with the Fong CRS for 1-year(C-index=0.571)and 5-year OS(C-index=0.574).It also achieved a C-index of 0.651 for RFS.Conclusions:We present a promising machine learning algorithm to individualize prognostications for patients following resection of CRLM with good discriminative ability.
文摘Prognostication of compensated advanced chronic liver disease(cACLD)is of paramount importance for the physician-and-patient communication and for rational clinical decisions.The paper published by Dallio et al reports on red cell distribution width(RDW)/platelet ratio(RPR)as a non-invasive biomarker in predicting decompensation of metabolic dysfunction-associated steatotic liver disease(MASLD)-related cACLD.Differently from other biomarkers and algorithms,RPR is inexpensive and widely available,based on parameters which are included in a complete blood count.RPR is computed on the grounds of two different items,one of which,RDW,mirrors the host’s response to a variety of disease stimuli and is non-specific.The second parameter involved in RPR,platelet count,is more specific and has been used in the hepatological clinic to discriminate cirrhotic from non-cirrhotic chronic liver disease for decades.Cardiovascular disease is the primary cause of mortality among MASLD subjects,followed by extra-hepatic cancers and liver-related mortality.Therefore,MASLD biomarkers should be validated not only in terms of liver-related events but also in the prediction of major adverse cardiovascular events and cardiovascular mortality and extra-hepatic cancers.Adequately sized multi-ethnic confirmatory investigation is required to define the role and significance of RPR in the stratification of MASLD-cACLD.
文摘Detection and treatment of colorectal cancer(CRC)at an early stage is vital for long-term survival.Liquid biopsy has emerged as a promising new avenue for non-invasive screening of CRC as well as prognostication and surveillance of minimal residual disease.Cell free DNA(cfDNA)is a promising liquid biopsy analyte and has been approved for use in clinical practice.Here,we explore the current challenges of utilizing cfDNA in the screening and prognostication of CRC but also for detecting driver mutations in healthy,presymptomatic patients with normal colonic crypts.CfDNA for the detection of cancerous or premalignant colonic lesions has already been extensively explored,however few have considered utilizing cfDNA in the detection of driver mutations in healthy patients.Theoretically,this would allow us to detect patients who are at a higher risk of tumorigenesis decades in advance of established malignancy and stratify them into higher risk groups for early-intervention screening programs.We also explore the solutions necessary to overcome the challenges that prevent liquid biopsy from entering mainstream clinical use.The potential for liquid biopsy is immense if these challenges are successfully circumvented,and can dramatically reduce CRC rates as well as improve survival in patients.
基金supported by the Shanghai Municipal Health Commission(201840063,201801075)the Science and Technology Commission of Shanghai Municipality(18441903300).
文摘Background:Spontaneous intracerebral hemorrhage(ICH)is a severe neurological emergency with high morbidity and mortality.The effectiveness of surgical intervention remains controversial,partly due to significant heterogeneity among patients.Traditional clinical criteria often fail to identify those most likely to benefit from surgery.Methods:This nationwide retrospective study in China included 2,167 ICH patients from 31 hospitals.Using machine learning techniques,we integrated clinical and radiomic data to perform unsupervised clustering and identify distinct phenogroups.Dimensionality reduction and cross-validation were applied to minimize overfitting.External validation was conducted using data from the INTERACT3 trial,and a prospective cohort was used to assess real-world applicability.Results:Three phenogroups were identified.Among them,only Phenogroup 1-characterized by older age,moderate hematoma volume,and intermediate Glasgow Coma Scale scores-showed significant benefit from early surgical intervention,with a 42%reduction in 3-month mortality and improved functional outcomes.In contrast,surgery did not significantly affect outcomes in Phenogroups 0 and 2.These findings were consistent across multiple machine learning models and validated externally.Conclusion:Machine learning-driven phenotypic stratification can effectively identify ICH patients who are most likely to benefit from surgical treatment.This approach supports personalized treatment strategies and may improve clinical decision-making in ICH management.Further validation in diverse populations is warranted.
文摘Perioperative morbidity of esophagectomy significantly affects the surgical outcome,like any major gastrointestinal procedure.Despite introduction of minimally invasive esophagectomy,the morbidity is still close to 30%-40%.The common complications following esophagectomy are pulmonary infections,cardiac events,anastomotic leakage,bleeding,chylous leak,and recurrent laryngeal nerve palsy which in turn lead to longer hospital stay,increased treatment cost and poor quality of life.A nomographic model comprising preoperative(patient,disease and treatment related)and intraoperative factors in combination with Artificial Intelligence may accurately identify the patients at higher risk of morbidity.This will aid in optimizing the modifiable risk factors preoperatively,and closely monitor these patients post operatively for early identification of complications and to initiate early corrective measures to improve the surgical outcome.
