1|OVERVIEW.Machine learning(ML)has been increasingly used for tackling various diagnostic,therapeutic,and prognostic tasks owing to its capability to learn and reason without explicit programming[1].Most developed ML ...1|OVERVIEW.Machine learning(ML)has been increasingly used for tackling various diagnostic,therapeutic,and prognostic tasks owing to its capability to learn and reason without explicit programming[1].Most developed ML models have had their accuracy proven through internal validation using retrospective data.However,external validation using retrospective data,continual monitoring using prospective data,and randomized controlled trials(RCTs)using prospective data are important for the translation of ML models into real-world clinical practice[2].展开更多
Abiraterone acetate is approved for the treatment of castration-resistant prostate cancer （CRPC）; however, its effects vary. An accurate prediction model to identify patient groups that will benefit from abiraterone...Abiraterone acetate is approved for the treatment of castration-resistant prostate cancer （CRPC）; however, its effects vary. An accurate prediction model to identify patient groups that will benefit from abiraterone treatment is therefore urgently required. The Chi model exhibits a good profile for risk classification, although its utility for the chemotherapy-naive group is unclear. This study aimed to externally validate the Chi model and develop a new nomogram to predict overall survival （OS）. We retrospectively analyzed a cohort of 110 patients. Patients were distributed among good-, intermediate-, and poor-risk groups, according to the Chi model. The good-, intermediate-, and poor-risk groups had a sample size of 59 （53.6%）, 34 （30.9%）, and 17 （15.5%） in our dataset, and a median OS of 48.4, 29.1, and 10.5 months, respectively. The C-index of external validation of Chi model was 0.726. Univariate and multivariate analyses identified low hemoglobin concentrations （〈110 g l^-1）, liver metastasis, and a short time interval from androgen deprivation therapy to abiraterone initiation （〈36 months） as predictors of OS. Accordingly, a new nomogram was developed with a C-index equal to 0.757 （95% CI, 0.678-0.836）. In conclusion, the Chi model predicted the prognosis of abiraterone-treated, chemotherapy-naive patients with mCRPC, and we developed a new nomogram to predict the overall survival of this group of patients with less parameters.展开更多
In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance w...In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance with an area under the curve exceeding 0.90.However,limitations exist regarding its narrow temporal scope,potential overestimation due to feature collinearity and imputation opacity,and limited generalizability due to single-center derivation and validation.Moreover,no clear clinical implementation strategy was outlined.Prospective multicenter validation and integration of endoscopist variability,longitudinal outcome data,and deployment mechanisms are warranted to ensure broader applicability and clinical utility.展开更多
Objective:This study aimed to develop and validate a risk scoring system to identify high-risk individuals carrying malignant lesions in stomach for tailored gastric cancer screening.Methods:A gastric cancer risk scor...Objective:This study aimed to develop and validate a risk scoring system to identify high-risk individuals carrying malignant lesions in stomach for tailored gastric cancer screening.Methods:A gastric cancer risk scoring system(GC-RSS)was developed based on questionnaire-based predictors for gastric cancer derived from systematic literature review.To assess the capability of this system for discrimination,risk scores for 8,214 and 7,235 outpatient subjects accepting endoscopic examination in two endoscopy centers,and 32,630 participants in a community-based cohort in China were calculated to plot receiver operating characteristic curves and generate area under the curve(AUC).To evaluate the performance of GC-RSS,the screening proportion,sensitivity and detection rate ratio compared to universal screening were used under different risk score cutoff values.Results:GC-RSS comprised nine predictors including advanced age,male gender,low body mass index(<18.5 kg/m^(2)),family history of gastric cancer,cigarette smoking,consumption of alcohol,preference for salty food,irregularity of meals and consumption of preserved food.This tool performed well in determining the risk of malignant gastric lesions with AUCs of 0.763,0.706 and 0.696 in three validation sets.When subjects with risk scores≥5 were evaluated with endoscopy,nearly 50%of these endoscopies could be saved with a detection rate of over 1.5 times achieved.When the cutoff was set at 8,only about 10%of subjects with the highest risk would be offered endoscopy,and detection rates for gastric cancer could be increased 2-4 fold compared to universal screening.Conclusions:An effective questionnaire-based GC-RSS was developed and validated.This tool may play an important role in establishing a tailored screening strategy for gastric cancer in China.展开更多
Background Arrhythmogenic right ventricular dysplasia/cardiomyopathy is an inherited cardiomyopathy.European Society of Cardiology was devised a new prediction model to estimate ventricular arrhythmias and guide decis...Background Arrhythmogenic right ventricular dysplasia/cardiomyopathy is an inherited cardiomyopathy.European Society of Cardiology was devised a new prediction model to estimate ventricular arrhythmias and guide decisions regarding primary prevention ICDs.This paper aimed to conduct external validation of European prediction model in the South China.展开更多
Objective:To validate and compare the performance of four risk stratification tools-the DEVI(Adverse Cardiac Events in Valvular Rheumatic Heart Disease in Pregnancy)score,Zwangerschap bij Aangeboren Hartafwijking(ZAHA...Objective:To validate and compare the performance of four risk stratification tools-the DEVI(Adverse Cardiac Events in Valvular Rheumatic Heart Disease in Pregnancy)score,Zwangerschap bij Aangeboren Hartafwijking(ZAHARA)score,Cardiac Disease in Pregnancy II(CARPREG II),and modified WHO(mWHO)classification-in predicting adverse cardiac events during pregnancy in women with valvular heart disease(VHD).Methods:This retrospective cohort study was conducted at Fernandez Hospital,a tertiary care referral center in Hyderabad,India,utilizing clinical data from pregnancies managed between January 2011 and December 2023.The primary outcome was the development of composite adverse cardiac events.Discriminative ability was assessed using the area under the receiver operating characteristic curve(AUC),calibration was evaluated via calibration plots,and clinical utility was determined by decision curve analysis(DCA).Categorical variables were reported as frequencies and percentages and continuous variables were presented as means with standard deviations or medians with interquartile ranges.Individual risk assessment was conducted using both the CARPREG II and DEVI risk stratification models,while the ZAHARA score was calculated by aggregating weighted parameters according to established scoring criteria.Results:The study enrolled 176 women and analyzed 205 pregnancies with adverse cardiac events in 19 pregnancies(9.3%).The DEVI score demonstrated superior discrimination(AUC=0.846,95%CI:0.765-0.927,P<0.001),followed by mWHO(AUC=0.826,95%CI:0.736-0.917,P<0.001),CARPREG II(AUC=0.762,95%CI:0.652-0.872,P<0.001),and ZAHARA(AUC=0.716,95%CI:0.628-0.803,P<0.001).Calibration plots revealed an overestimation of risk at higher probabilities for DEVI and CARPREG II.DCA indicated net clinical benefit for both tools at 10-30%threshold probabilities.Conclusion:The DEVI score showed the highest discriminative performance,though its calibration and clinical utility were comparable to CARPREG II.These findings support its use for risk stratification in pregnant women with VHD,particularly in resource-limited settings where rheumatic VHD predominates.展开更多
The simulated patient methodology(SPM)is considered the“gold standard”as covert participatory observation.SPM is attracting increasing interest for the investigation of community pharmacy practice;however,there is c...The simulated patient methodology(SPM)is considered the“gold standard”as covert participatory observation.SPM is attracting increasing interest for the investigation of community pharmacy practice;however,there is criticism that SPM can only show a small picture of everyday pharmacy practice and therefore has limited external validity.On the one hand,a certain design and application of the SPM goes hand in hand with an increase in external validity.Even if,on the other hand,this occurs at the expense of internal validity due to the trade-off situation,the justified criticism of the SPM for investigating community pharmacy practice can be countered.展开更多
The relative toxicity of 48 anilines using the Tetrahymena pyriformis population growth characteristics IGC50 （concentration causing 50% growth inhibition）, available in the literature, was studied. At first, the en...The relative toxicity of 48 anilines using the Tetrahymena pyriformis population growth characteristics IGC50 （concentration causing 50% growth inhibition）, available in the literature, was studied. At first, the entire data set was randomly split into a training set （31 chemicals） used to establish the QSAR model, and a test set （17 chemicals） for statistical external validation. A biparametric model was developed using, as independent variables, 3D theoretical descriptors derived from DRAGON software. The GA-MLR （genetic algorithm variable subset selection） procedure was performed on the trainingset by the software mobydigs using the OLS （ordinary least squares） regression method, and GA（genetic algorithm）-VSS（variable subset selection） by maximising the cross-validated explained variance （Q^2Loo）＇ The obtained model was examined for robustness （Q^2LOOcross-validation, Y-scrambling） and predictive ability through both internal （Q^2LM0, bootstrap） and external validation （Q^2ext） methods. Descriptors included in the QSAR model indicated that log/GC^-150 value was related to molecular size and shape, and interaction of molecule with its surrounding medium or its target. Moreover, the applicability domain of the model was discussed.展开更多
Metabolic dysfunction-associated steatotic liver disease(MASLD)is now the leading cause of chronic liver disease in children,affecting up to 38%with obesity of children.With the global shift from non-alcoholic fatty l...Metabolic dysfunction-associated steatotic liver disease(MASLD)is now the leading cause of chronic liver disease in children,affecting up to 38%with obesity of children.With the global shift from non-alcoholic fatty liver disease(NAFLD)to MASLD using affirmative criteria(hepatic steatosis plus≥1 cardiometabolic risk factor)and approximately 99%concordance in pediatrics,the development of non-invasive fibrosis tools is accelerating.Yao et al report a machine-learning“chronic MASLD with fibrosis(CH-MASLD-Fib)”score for advanced fibrosis with area under the receiver operating characteristic curve(AUROC)of 0.92.While timely,we urge caution.First,high accuracy from a single-center cohort signals overfitting:Complex models can learn cohort-specific noise and fail to generalize.Consistent with this,established pediatric scores(NAFLD fibrosis score,fibrosis-4,pediatric NAFLD fibrosis score)perform modestly(AUROC:Approximately 0.6-0.7),and aspartate aminotransferase-to-platelet ratio index is variable,raising concern that CH-MASLD-Fib’s result reflects a statistical artifact.Second,MASLD epidemiology varies by ethnicity(highest in Hispanic,lower in Black children);a model derived in a mono-ethnic Chinese cohort may misclassify other populations.Third,clinical utility and cost-effectiveness are unproven;dependence on specialized assays(e.g.,bile acids,cholinesterase)would limit access and increase cost.We recommend external validation in multi-ethnic cohorts,head-to-head comparisons with simple serum indices and elastography,and formal economic analyses.Until then,clinical judgment anchored in readily available markers and judicious,targeted liver biopsy remains paramount.展开更多
Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic ris...Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic risk patients.Their prospective cohort design and dual-feature selection(LASSO+RFE)culminating in an interpretable XGBoost model(area under the curve:0.82)represent a significant methodological advance.The inclusion of TCM diagnostics addresses metabolic dysfunction-associated fatty liver disease(MAFLD’s)multisystem heterogeneity-a key strength that bridges holistic medicine with precision analytics and underscores potential cost savings over imaging-dependent screening.However,critical limitations impede clinical translation.First,the model’s singlecenter validation(n=711)lacks external/generalizability testing across diverse populations,risking bias from local demographics.Second,MAFLD subtyping(e.g.,lean MAFLD,diabetic MAFLD)was omitted despite acknowledged disease heterogeneity;this overlooks distinct pathophysiologies and may limit utility in stratified care.Third,while TCM features ranked among the top predictors in SHAP analysis,their clinical interpretability remains nebulous without mechanistic links to metabolic dysregulation.To resolve these gaps,we propose external validation in multiethnic cohorts using the published feature set(e.g.,aspartate aminotransferase/alanine aminotransferase,low-density lipoprotein cholesterol,TCM tongue markers)to assess robustness.Subtype-specific modeling to capture MAFLD heterogeneity,potentially enhancing accuracy in highrisk subgroups.Probing TCM microbiome/metabolomic correlations to ground tongue phenotypes in biological pathways,elevating model credibility.Despite shortcomings,this work pioneers a low-cost screening paradigm.Future iterations addressing these issues could revolutionize early MAFLD detection in resource-limited settings.展开更多
Background:The effect of bariatric surgery on type 2 diabetes mellitus(T2DM)control can be assessed based on predictive models of T2DM remission.Various models have been externally verified internationally.However,lon...Background:The effect of bariatric surgery on type 2 diabetes mellitus(T2DM)control can be assessed based on predictive models of T2DM remission.Various models have been externally verified internationally.However,long-term validated results after laparoscopic sleeve gastrectomy(LSG)surgery are lacking.The best model for the Chinese population is also unknown.Methods:We retrospectively analyzed Chinese population data 5 years after LSG at Beijing Shijitan Hospital in China between March 2009 and December 2016.The independent t-test,Mann–Whitney U test,and chi-squared test were used to compare characteristics between T2DM remission and non-remission groups.We evaluated the predictive efficacy of each model for longterm T2DM remission after LSG by calculating the area under the curve(AUC),sensitivity,specificity,Youden index,positive predictive value(PPV),negative predictive value(NPV),and predicted-to-observed ratio,and performed calibration using Hosmer–Lemeshow test for 11 prediction models.Results:We enrolled 108 patients,including 44(40.7%)men,with a mean age of 35.5 years.The mean body mass index was 40.3±9.1 kg/m^(2),the percentage of excess weight loss(%EWL)was(75.9±30.4)%,and the percentage of total weight loss(%TWL)was(29.1±10.6)%.The mean glycated hemoglobin A1c(HbA1c)level was(7.3±1.8)%preoperatively and decreased to(5.9±1.0)%5 years after LSG.The 5-year postoperative complete and partial remission rates of T2DM were 50.9%[55/108]and 27.8%[30/108],respectively.Six models,i.e.,"ABCD",individualized metabolic surgery(IMS),advanced-DiaRem,DiaBetter,Dixon et al’s regression model,and Panunzi et al’s regression model,showed a good discrimination ability(all AUC>0.8).The"ABCD"(sensitivity,74%;specificity,80%;AUC,0.82[95%confidence interval[CI]:0.74–0.89]),IMS(sensitivity,78%;specificity,84%;AUC,0.82[95%CI:0.73–0.89]),and Panunzi et al’s regression models(sensitivity,78%;specificity,91%;AUC,0.86[95%CI:0.78–0.92])showed good discernibility.In the Hosmer–Lemeshow goodness-of-fit test,except for DiaRem(P<0.01),DiaBetter(P<0.01),Hayes et al(P=0.03),Park et al(P=0.02),and Ramos-Levi et al’s(P<0.01)models,all models had a satifactory fit results(P>0.05).The P values of calibration results of the"ABCD"and IMS were 0.07 and 0.14,respectively.The predicted-to-observed ratios of the"ABCD"and IMS were 0.87 and 0.89,respectively.Conclusion:The prediction model IMS was recommended for clinical use because of excellent predictive performance,good statistical test results,and simple and practical design features.展开更多
The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo aff...The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo affect the stability of spectral acquisition and the biological variabilities affect the robustness of models.Given these issues,in this study,an efficient prototype in-line detection system in transmittance mode was designed and evaluated in comparison with an off-line detection system.Data from the years 2019 and 2020 were used for modeling and the external validation data were obtained by the inline detection system in 2021.The wavelength selection methods of changeable size moving window(CSMW),random frog(RF),and competitive adaptive reweighted sampling(CARS)were used to improve the prediction accuracy of partial least squares regression(PLSR)models.The best performance of internal prediction was obtained by CARS-PLSR and the determination coefficient of prediction(),root mean square error of prediction(RMSEP),and residual predictive deviation(RPD)were 0.958,0.204%,and 4.821,respectively.However,all models obtained large prediction biases in external validation.The latent variable updating(LVU)method was proposed to update models and improve the performance in external validation.Ten samples from the external validation set were randomly selected to update the models.Compared with the recalibration method,LVU could effectively modify the original models which matched the SSC range of the external validation set.The CSMW-PLSR models were more robust in external validations.The off-line model with LVU performed best with a root mean square error of validation(RMSEV)of 0.599%and the in-line model with recalibration obtained RMSEV of 0.864%.These results demonstrated the application potential of the transmittance Vis-NIRS for in-line rapid prediction of SSC in pomelos and the modeling and updating methods could be applied to samples with biological variabilities.展开更多
Clinical research methods have been rapidly developing, and the design of clinical trials including traditional Chinese medicine is advancing. To a certain extent, all of these ensure that the results of clinical rese...Clinical research methods have been rapidly developing, and the design of clinical trials including traditional Chinese medicine is advancing. To a certain extent, all of these ensure that the results of clinical research are objective and scientific, but whether these results and the resulting guidelines or consensus have much practical significance on clinical practice is still controversial. The authors engage in both clinical practice and clinical research; they strongly feel that it is necessary to discuss the relationship between clinical trials and clinical practice. This essay discusses this relationship in four parts.展开更多
Advances in spinal cord injury-based research in the last 50 years have resulted in significant improvements to therapy options.However,the efficacy of such research could be further enhanced if threats to internal an...Advances in spinal cord injury-based research in the last 50 years have resulted in significant improvements to therapy options.However,the efficacy of such research could be further enhanced if threats to internal and external validity were addressed.To provide perspective,a sample topic was identified:the effects of acute and chronic exercise on clinical and sub-clinical markers of cardiovascular health.The intention was not a systematic review,nor a critique of exercise-based research,but rather a means to generate further discussion.Thirty-one articles were identified,and four common issues were found relating to:(1)sampling;(2)study design;(3)control group;and(4)clinical inference.These concerns were largely attributed to insufficient resources,and challenges associated with recruiting individuals with spinal cord injury.Overcoming these challenges will be difficult,but some opportunities include:(1)implementing multi-center trials;(2)sampling from subject groups appropriate to the research question;(3)including an appropriate control group;and(4)clearly defining clini-cal inference.These opportunities are not always feasible,and some easier to implement than others.However,addressing these concerns may assist in progressing spinal cord injury-based research,thereby helping to ensure steady advancement of therapy options for persons with spinal cord injury.展开更多
文摘1|OVERVIEW.Machine learning(ML)has been increasingly used for tackling various diagnostic,therapeutic,and prognostic tasks owing to its capability to learn and reason without explicit programming[1].Most developed ML models have had their accuracy proven through internal validation using retrospective data.However,external validation using retrospective data,continual monitoring using prospective data,and randomized controlled trials(RCTs)using prospective data are important for the translation of ML models into real-world clinical practice[2].
文摘Abiraterone acetate is approved for the treatment of castration-resistant prostate cancer （CRPC）; however, its effects vary. An accurate prediction model to identify patient groups that will benefit from abiraterone treatment is therefore urgently required. The Chi model exhibits a good profile for risk classification, although its utility for the chemotherapy-naive group is unclear. This study aimed to externally validate the Chi model and develop a new nomogram to predict overall survival （OS）. We retrospectively analyzed a cohort of 110 patients. Patients were distributed among good-, intermediate-, and poor-risk groups, according to the Chi model. The good-, intermediate-, and poor-risk groups had a sample size of 59 （53.6%）, 34 （30.9%）, and 17 （15.5%） in our dataset, and a median OS of 48.4, 29.1, and 10.5 months, respectively. The C-index of external validation of Chi model was 0.726. Univariate and multivariate analyses identified low hemoglobin concentrations （〈110 g l^-1）, liver metastasis, and a short time interval from androgen deprivation therapy to abiraterone initiation （〈36 months） as predictors of OS. Accordingly, a new nomogram was developed with a C-index equal to 0.757 （95% CI, 0.678-0.836）. In conclusion, the Chi model predicted the prognosis of abiraterone-treated, chemotherapy-naive patients with mCRPC, and we developed a new nomogram to predict the overall survival of this group of patients with less parameters.
基金Supported by the Wuhu Municipal Science and Technology Bureau Project,No.2024kj072.
文摘In 2025,Shi et al constructed a model utilizing machine learning techniques to predict the one-year recurrence of colorectal polyps following endoscopic mucosal resection,showing excellent discriminatory performance with an area under the curve exceeding 0.90.However,limitations exist regarding its narrow temporal scope,potential overestimation due to feature collinearity and imputation opacity,and limited generalizability due to single-center derivation and validation.Moreover,no clear clinical implementation strategy was outlined.Prospective multicenter validation and integration of endoscopist variability,longitudinal outcome data,and deployment mechanisms are warranted to ensure broader applicability and clinical utility.
基金supported by the National Science&Technology Fundamental Resources Investigation Program of China(No.2019FY101102)the National Natural Science Foundation of China(No.82073626,81773501)+5 种基金the National Key R&D Program of China(No.2016YFC0901404)the Beijing-Tianjin-Hebei Basic Research Cooperation Project(No.J200016)the Digestive Medical Coordinated Development Center of Beijing Hospitals Authority(No.XXZ0204)the Beijing Hospitals Authority Youth Programme(No.QML20201101)Sanming Project of Shenzhen(No.SZSM201612061)the Beijing Nova Program(No.Z201100006820093)。
文摘Objective:This study aimed to develop and validate a risk scoring system to identify high-risk individuals carrying malignant lesions in stomach for tailored gastric cancer screening.Methods:A gastric cancer risk scoring system(GC-RSS)was developed based on questionnaire-based predictors for gastric cancer derived from systematic literature review.To assess the capability of this system for discrimination,risk scores for 8,214 and 7,235 outpatient subjects accepting endoscopic examination in two endoscopy centers,and 32,630 participants in a community-based cohort in China were calculated to plot receiver operating characteristic curves and generate area under the curve(AUC).To evaluate the performance of GC-RSS,the screening proportion,sensitivity and detection rate ratio compared to universal screening were used under different risk score cutoff values.Results:GC-RSS comprised nine predictors including advanced age,male gender,low body mass index(<18.5 kg/m^(2)),family history of gastric cancer,cigarette smoking,consumption of alcohol,preference for salty food,irregularity of meals and consumption of preserved food.This tool performed well in determining the risk of malignant gastric lesions with AUCs of 0.763,0.706 and 0.696 in three validation sets.When subjects with risk scores≥5 were evaluated with endoscopy,nearly 50%of these endoscopies could be saved with a detection rate of over 1.5 times achieved.When the cutoff was set at 8,only about 10%of subjects with the highest risk would be offered endoscopy,and detection rates for gastric cancer could be increased 2-4 fold compared to universal screening.Conclusions:An effective questionnaire-based GC-RSS was developed and validated.This tool may play an important role in establishing a tailored screening strategy for gastric cancer in China.
文摘Background Arrhythmogenic right ventricular dysplasia/cardiomyopathy is an inherited cardiomyopathy.European Society of Cardiology was devised a new prediction model to estimate ventricular arrhythmias and guide decisions regarding primary prevention ICDs.This paper aimed to conduct external validation of European prediction model in the South China.
文摘Objective:To validate and compare the performance of four risk stratification tools-the DEVI(Adverse Cardiac Events in Valvular Rheumatic Heart Disease in Pregnancy)score,Zwangerschap bij Aangeboren Hartafwijking(ZAHARA)score,Cardiac Disease in Pregnancy II(CARPREG II),and modified WHO(mWHO)classification-in predicting adverse cardiac events during pregnancy in women with valvular heart disease(VHD).Methods:This retrospective cohort study was conducted at Fernandez Hospital,a tertiary care referral center in Hyderabad,India,utilizing clinical data from pregnancies managed between January 2011 and December 2023.The primary outcome was the development of composite adverse cardiac events.Discriminative ability was assessed using the area under the receiver operating characteristic curve(AUC),calibration was evaluated via calibration plots,and clinical utility was determined by decision curve analysis(DCA).Categorical variables were reported as frequencies and percentages and continuous variables were presented as means with standard deviations or medians with interquartile ranges.Individual risk assessment was conducted using both the CARPREG II and DEVI risk stratification models,while the ZAHARA score was calculated by aggregating weighted parameters according to established scoring criteria.Results:The study enrolled 176 women and analyzed 205 pregnancies with adverse cardiac events in 19 pregnancies(9.3%).The DEVI score demonstrated superior discrimination(AUC=0.846,95%CI:0.765-0.927,P<0.001),followed by mWHO(AUC=0.826,95%CI:0.736-0.917,P<0.001),CARPREG II(AUC=0.762,95%CI:0.652-0.872,P<0.001),and ZAHARA(AUC=0.716,95%CI:0.628-0.803,P<0.001).Calibration plots revealed an overestimation of risk at higher probabilities for DEVI and CARPREG II.DCA indicated net clinical benefit for both tools at 10-30%threshold probabilities.Conclusion:The DEVI score showed the highest discriminative performance,though its calibration and clinical utility were comparable to CARPREG II.These findings support its use for risk stratification in pregnant women with VHD,particularly in resource-limited settings where rheumatic VHD predominates.
文摘The simulated patient methodology(SPM)is considered the“gold standard”as covert participatory observation.SPM is attracting increasing interest for the investigation of community pharmacy practice;however,there is criticism that SPM can only show a small picture of everyday pharmacy practice and therefore has limited external validity.On the one hand,a certain design and application of the SPM goes hand in hand with an increase in external validity.Even if,on the other hand,this occurs at the expense of internal validity due to the trade-off situation,the justified criticism of the SPM for investigating community pharmacy practice can be countered.
文摘The relative toxicity of 48 anilines using the Tetrahymena pyriformis population growth characteristics IGC50 （concentration causing 50% growth inhibition）, available in the literature, was studied. At first, the entire data set was randomly split into a training set （31 chemicals） used to establish the QSAR model, and a test set （17 chemicals） for statistical external validation. A biparametric model was developed using, as independent variables, 3D theoretical descriptors derived from DRAGON software. The GA-MLR （genetic algorithm variable subset selection） procedure was performed on the trainingset by the software mobydigs using the OLS （ordinary least squares） regression method, and GA（genetic algorithm）-VSS（variable subset selection） by maximising the cross-validated explained variance （Q^2Loo）＇ The obtained model was examined for robustness （Q^2LOOcross-validation, Y-scrambling） and predictive ability through both internal （Q^2LM0, bootstrap） and external validation （Q^2ext） methods. Descriptors included in the QSAR model indicated that log/GC^-150 value was related to molecular size and shape, and interaction of molecule with its surrounding medium or its target. Moreover, the applicability domain of the model was discussed.
文摘Metabolic dysfunction-associated steatotic liver disease(MASLD)is now the leading cause of chronic liver disease in children,affecting up to 38%with obesity of children.With the global shift from non-alcoholic fatty liver disease(NAFLD)to MASLD using affirmative criteria(hepatic steatosis plus≥1 cardiometabolic risk factor)and approximately 99%concordance in pediatrics,the development of non-invasive fibrosis tools is accelerating.Yao et al report a machine-learning“chronic MASLD with fibrosis(CH-MASLD-Fib)”score for advanced fibrosis with area under the receiver operating characteristic curve(AUROC)of 0.92.While timely,we urge caution.First,high accuracy from a single-center cohort signals overfitting:Complex models can learn cohort-specific noise and fail to generalize.Consistent with this,established pediatric scores(NAFLD fibrosis score,fibrosis-4,pediatric NAFLD fibrosis score)perform modestly(AUROC:Approximately 0.6-0.7),and aspartate aminotransferase-to-platelet ratio index is variable,raising concern that CH-MASLD-Fib’s result reflects a statistical artifact.Second,MASLD epidemiology varies by ethnicity(highest in Hispanic,lower in Black children);a model derived in a mono-ethnic Chinese cohort may misclassify other populations.Third,clinical utility and cost-effectiveness are unproven;dependence on specialized assays(e.g.,bile acids,cholinesterase)would limit access and increase cost.We recommend external validation in multi-ethnic cohorts,head-to-head comparisons with simple serum indices and elastography,and formal economic analyses.Until then,clinical judgment anchored in readily available markers and judicious,targeted liver biopsy remains paramount.
文摘Tian et al present a timely machine learning(ML)model integrating biochemical and novel traditional Chinese medicine(TCM)indicators(tongue edge redness,greasy coating)to predict hepatic steatosis in high metabolic risk patients.Their prospective cohort design and dual-feature selection(LASSO+RFE)culminating in an interpretable XGBoost model(area under the curve:0.82)represent a significant methodological advance.The inclusion of TCM diagnostics addresses metabolic dysfunction-associated fatty liver disease(MAFLD’s)multisystem heterogeneity-a key strength that bridges holistic medicine with precision analytics and underscores potential cost savings over imaging-dependent screening.However,critical limitations impede clinical translation.First,the model’s singlecenter validation(n=711)lacks external/generalizability testing across diverse populations,risking bias from local demographics.Second,MAFLD subtyping(e.g.,lean MAFLD,diabetic MAFLD)was omitted despite acknowledged disease heterogeneity;this overlooks distinct pathophysiologies and may limit utility in stratified care.Third,while TCM features ranked among the top predictors in SHAP analysis,their clinical interpretability remains nebulous without mechanistic links to metabolic dysregulation.To resolve these gaps,we propose external validation in multiethnic cohorts using the published feature set(e.g.,aspartate aminotransferase/alanine aminotransferase,low-density lipoprotein cholesterol,TCM tongue markers)to assess robustness.Subtype-specific modeling to capture MAFLD heterogeneity,potentially enhancing accuracy in highrisk subgroups.Probing TCM microbiome/metabolomic correlations to ground tongue phenotypes in biological pathways,elevating model credibility.Despite shortcomings,this work pioneers a low-cost screening paradigm.Future iterations addressing these issues could revolutionize early MAFLD detection in resource-limited settings.
基金supported by Clinical Cooperation Ability Construction Project of Chinese and Western Medicine for Major and Difficult Diseases(Department of Medical Administration,National Administration of Traditional Chinese Medicine[2018]No.3)
文摘Background:The effect of bariatric surgery on type 2 diabetes mellitus(T2DM)control can be assessed based on predictive models of T2DM remission.Various models have been externally verified internationally.However,long-term validated results after laparoscopic sleeve gastrectomy(LSG)surgery are lacking.The best model for the Chinese population is also unknown.Methods:We retrospectively analyzed Chinese population data 5 years after LSG at Beijing Shijitan Hospital in China between March 2009 and December 2016.The independent t-test,Mann–Whitney U test,and chi-squared test were used to compare characteristics between T2DM remission and non-remission groups.We evaluated the predictive efficacy of each model for longterm T2DM remission after LSG by calculating the area under the curve(AUC),sensitivity,specificity,Youden index,positive predictive value(PPV),negative predictive value(NPV),and predicted-to-observed ratio,and performed calibration using Hosmer–Lemeshow test for 11 prediction models.Results:We enrolled 108 patients,including 44(40.7%)men,with a mean age of 35.5 years.The mean body mass index was 40.3±9.1 kg/m^(2),the percentage of excess weight loss(%EWL)was(75.9±30.4)%,and the percentage of total weight loss(%TWL)was(29.1±10.6)%.The mean glycated hemoglobin A1c(HbA1c)level was(7.3±1.8)%preoperatively and decreased to(5.9±1.0)%5 years after LSG.The 5-year postoperative complete and partial remission rates of T2DM were 50.9%[55/108]and 27.8%[30/108],respectively.Six models,i.e.,"ABCD",individualized metabolic surgery(IMS),advanced-DiaRem,DiaBetter,Dixon et al’s regression model,and Panunzi et al’s regression model,showed a good discrimination ability(all AUC>0.8).The"ABCD"(sensitivity,74%;specificity,80%;AUC,0.82[95%confidence interval[CI]:0.74–0.89]),IMS(sensitivity,78%;specificity,84%;AUC,0.82[95%CI:0.73–0.89]),and Panunzi et al’s regression models(sensitivity,78%;specificity,91%;AUC,0.86[95%CI:0.78–0.92])showed good discernibility.In the Hosmer–Lemeshow goodness-of-fit test,except for DiaRem(P<0.01),DiaBetter(P<0.01),Hayes et al(P=0.03),Park et al(P=0.02),and Ramos-Levi et al’s(P<0.01)models,all models had a satifactory fit results(P>0.05).The P values of calibration results of the"ABCD"and IMS were 0.07 and 0.14,respectively.The predicted-to-observed ratios of the"ABCD"and IMS were 0.87 and 0.89,respectively.Conclusion:The prediction model IMS was recommended for clinical use because of excellent predictive performance,good statistical test results,and simple and practical design features.
基金the key research and development projects of Zhejiang province(Grant No.2022C02021).
文摘The aim of this study was in-line,rapid,and non-destructive detection for soluble solid content(SSC)in pomelos using visible and near-infrared spectroscopy(Vis-NIRS).However,the large size and thick rind of pomelo affect the stability of spectral acquisition and the biological variabilities affect the robustness of models.Given these issues,in this study,an efficient prototype in-line detection system in transmittance mode was designed and evaluated in comparison with an off-line detection system.Data from the years 2019 and 2020 were used for modeling and the external validation data were obtained by the inline detection system in 2021.The wavelength selection methods of changeable size moving window(CSMW),random frog(RF),and competitive adaptive reweighted sampling(CARS)were used to improve the prediction accuracy of partial least squares regression(PLSR)models.The best performance of internal prediction was obtained by CARS-PLSR and the determination coefficient of prediction(),root mean square error of prediction(RMSEP),and residual predictive deviation(RPD)were 0.958,0.204%,and 4.821,respectively.However,all models obtained large prediction biases in external validation.The latent variable updating(LVU)method was proposed to update models and improve the performance in external validation.Ten samples from the external validation set were randomly selected to update the models.Compared with the recalibration method,LVU could effectively modify the original models which matched the SSC range of the external validation set.The CSMW-PLSR models were more robust in external validations.The off-line model with LVU performed best with a root mean square error of validation(RMSEV)of 0.599%and the in-line model with recalibration obtained RMSEV of 0.864%.These results demonstrated the application potential of the transmittance Vis-NIRS for in-line rapid prediction of SSC in pomelos and the modeling and updating methods could be applied to samples with biological variabilities.
基金Supported by the National Key Technologies R&D Program(2004BA716B01)National Natural Science Foundation of China(30600834)and China Postdoctoral Science Foundation(20070411156)
文摘Clinical research methods have been rapidly developing, and the design of clinical trials including traditional Chinese medicine is advancing. To a certain extent, all of these ensure that the results of clinical research are objective and scientific, but whether these results and the resulting guidelines or consensus have much practical significance on clinical practice is still controversial. The authors engage in both clinical practice and clinical research; they strongly feel that it is necessary to discuss the relationship between clinical trials and clinical practice. This essay discusses this relationship in four parts.
文摘Advances in spinal cord injury-based research in the last 50 years have resulted in significant improvements to therapy options.However,the efficacy of such research could be further enhanced if threats to internal and external validity were addressed.To provide perspective,a sample topic was identified:the effects of acute and chronic exercise on clinical and sub-clinical markers of cardiovascular health.The intention was not a systematic review,nor a critique of exercise-based research,but rather a means to generate further discussion.Thirty-one articles were identified,and four common issues were found relating to:(1)sampling;(2)study design;(3)control group;and(4)clinical inference.These concerns were largely attributed to insufficient resources,and challenges associated with recruiting individuals with spinal cord injury.Overcoming these challenges will be difficult,but some opportunities include:(1)implementing multi-center trials;(2)sampling from subject groups appropriate to the research question;(3)including an appropriate control group;and(4)clearly defining clini-cal inference.These opportunities are not always feasible,and some easier to implement than others.However,addressing these concerns may assist in progressing spinal cord injury-based research,thereby helping to ensure steady advancement of therapy options for persons with spinal cord injury.
