Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective To establish a method for the determination of lorlatinib in human plasma by two-dimensional high performance liquid chromatography.Methods In the two-dimensional high performance liquid chromatography method,one-dimensional column SX1E-1A(50 mm × 3.5 mm,5 μm)and two-dimensional column SCB-C18(125 mm × 4.6 mm,5 μm)were used with flow rates of 0.8 mL·min-1 and 1.0 mL·min-1,respectively.The column temperature was 40 ℃,The UV detection wavelength was 317 nm,and the sample size was 500 μL.This study investigated the specificity,standard curve and minimum quantification limit,precision and recovery rate,as well as stability of the method.Results The concentration of lolatinib in human plasma showed a good linear relationship in the range of 11.72-1 018.98 ng·mL-1,and the regression equation was y=944.50x-588.90(R2=0.999 7).The minimum limit of quantification was 11.72 ng·mL-1.The extraction recovery rates of the three quality control samples were 97.61％-99.86％,and the intra-day and inter-day precisions were less than 5.29％,indicating that the detection performance of the method was good.Conclusion The method has the characteristics of good stability,high sensitivity and strong anti-interference ability,and is suitable for the determination of loratinib in human plasma.

Objective To investigate the clinical efficacy of Yiqi Huayu Decoction(mainly composed of Astragali Radix,Dioscoreae Rhizoma,Poria,fried Euryales Semen,Ecliptae Herba,Rosae Laevigatae Fructus,charred Crataegi Fructus,Ligustri Lucidi Fructus,Salviae Miltiorrhizae Radix et Rhizoma,and Leonuri Herba)combined with Calcium Dobesilate in the treatment of diabetic nephropathy(DN)with qi deficiency and blood stasis syndrome,and to observe the effect of the therapy on vascular endothelial growth factor(VEGF)and insulin-like growth factor 1(IGF-1).Methods Ninety patients with DN of qi deficiency and blood stasis type were randomly divided into an observation group and a control group,with 45 patients in each group.All patients received basic hypoglycemic therapy and treatment for controlling blood pressure and regulating lipid metabolism disorders.Moreover,the patients in the control group were given Calcium Dobesilate orally,and the patients in the observation group were given Yiqi Huayu Decoction combined with Calcium Dobesilate.The course of treatment lasted for 3 months.The changes of traditional Chinese medicine(TCM)syndrome scores,renal function parameters and serum VEGF and IGF-1 levels in the two groups of patients were observed before and after the treatment,and the clinical efficacy of the two groups was evaluated after treatment.Results(1)After 3 months of treatment,the total effective rate of the observation group was 91.11%(41/45),and that of the control group was 75.56%(34/45).The intergroup comparison(tested by chi-square test)showed that the therapeutic effect of the observation group was significantly superior to that of the control group(P＜0.05).(2)After one month and 3 months of treatment,the TCM syndrome scores of both groups were significantly lower than those before treatment(P＜0.05),and the scores after 3 months of treatment in the two groups were significantly lower than those after one month of treatment(P＜0.05).The intergroup comparison showed that the reduction of TCM syndrome scores of the observation group was significantly superior to that of the control group after one month and 3 months of treatment(P＜0.01).(3)After treatment,the levels of renal function parameters such as serum creatinine(Scr),blood urea nitrogen(BUN),and glomerular filtration rate(GFR)in the two groups of patients were significantly improved compared with those before treatment(P＜0.05),and the observation group's effect on the improvement of all renal function parameters was significantly superior to that of the control group(P＜0.01).(4)After treatment,the serum VEGF and IGF-1 levels in the two groups of patients were significantly lower than those before treatment(P＜0.05),and the observation group's effect on the decrease of serum VEGF and IGF-1 levels was significantly superior to that of the control group(P＜0.01).(5)In the course of treatment,no significant adverse reactions occurred in the two groups of patients,with a high degree of safety.Conclusion Yiqi Huayu Decoction combined with Calcium Dobesilate exerts certain therapeutic effect in treating DN patients with qi deficiency and blood stasis syndrome.The combined therapy can effectively down-regulate the serum levels of VEGF and IGF-1,significantly improve the renal function,and alleviate the clinical symptoms of the patients,with a high degree of safety.

Objective To explore the efficacy and safety of recombinant human anti-severe acute respiratory syn-drome coronavirus 2(anti-SARS-CoV-2)monoclonal antibody injection(F61 injection)in the treatment of patients with coronavirus disease 2019(COVID-19)combined with renal damage.Methods Patients with COVID-19 and renal damage who visited the PLA General Hospital from January to February 2023 were selected.Subjects were randomly divided into two groups.Control group was treated with conventional anti-COVID-19 therapy,while trial group was treated with conventional anti-COVID-19 therapy combined with F61 injection.A 15-day follow-up was conducted after drug administration.Clinical symptoms,laboratory tests,electrocardiogram,and chest CT of pa-tients were performed to analyze the efficacy and safety of F61 injection.Results Twelve subjects(7 in trial group and 5 in control group)were included in study.Neither group had any clinical progression or death cases.The ave-rage time for negative conversion of nucleic acid of SARS-CoV-2 in control group and trial group were 3.2 days and 1.57 days(P=0.046),respectively.The scores of COVID-19 related target symptom in the trial group on the 3rd and 5th day after medication were both lower than those of the control group(both P＜0.05).According to the clinical staging and World Health Organization 10-point graded disease progression scale,both groups of subjects improved but didn't show statistical differences(P＞0.05).For safety,trial group didn't present any infusion-re-lated adverse event.Subjects in both groups demonstrated varying degrees of elevated blood glucose,elevated urine glucose,elevated urobilinogen,positive urine casts,and cardiac arrhythmia,but the differences were not statistica-lly significant(all P＞0.05).Conclusion F61 injection has initially demonstrated safety and clinical benefit in trea-ting patients with COVID-19 combined with renal damage.As the domestically produced drug,it has good clinical accessibility and may provide more options for clinical practice.

Persistent left superior vena cava(PLSVC)is a common congenital anomaly of systemic venous drainage,often draining into the right atrium without the need for special treatment.Sometimes,PLSVC drains into the left atrium,creating a right-to-left shunt,leading to reduced blood oxygen saturation and paradoxical embolism,requiring intervention.Traditional surgical ligation of PLSVC is the conventional approach for managing abnormal shunting,but it is associated with significant trauma and carries the risk of damaging the phrenic nerve.Here,we present a case of a patient with right heart dysfunction due to an untreated PLSVC-left atrium communication after corrective surgery for complex congenital heart disease,resulting in left-to-right shunting postoperatively.The patient was successfully treated by using a Plug vascular occluder via a transseptal approach to occlude the PLSVC.To our knowledge,this is the first report of successful closure of the left-to-right shunting through the heart chambers via a transseptal approach,indicating that interventional occlusion is an ideal management approach.

Low-level patent foramen ovale nonocclusion(PFO)is a rare type of PFO in which the PFO opening is low during transcatheter closure of PFO and the distance between the PFO left atrial opening and the root of the septal side of the mitral valve is less than 9 mm,and the smallest model of the current double-disk PFO occluder(18/18)commonly used in clinical practice for low-level PFOs can touch the mitral valve,resulting in increased risk of mitral regurgitation or leaflet abrasion.The risk of mitral regurgitation or leaflet abrasion is increased,and transcatheter closure of PFO procedure can only be abandoned when encountered intraoperatively.In this article,we present a case of successful transcatheter closure of a low-level PFO using the Amplatzer ADOⅡ occluder,which provides new ideas and strategies to deel wtih this rare type of PFO.