ObjectiveFrom the perspective of cardiovascular-kidney-metabolic （CKM） syndrome， this study aims to construct and validate a diagnostic machine learning model integrating traditional Chinese and Western medicine for severe coronary artery stenosis in patients with CKM， thereby providing clinical decision-making support for patients with borderline lesions. MethodsBased on a retrospective study design， a total of 535 hospitalized patients from two independent campuses of Jiangsu Province Hospital of Traditional Chinese Medicine： the main campus （from January 2024 to August 2024） and Zidong branch （from September 2024 to December 2024） were screened. Data from the main campus were randomly divided into the training dataset （376 cases） and the internal validation dataset （95 cases） at a 4∶1 ratio， while data from Zidong branch served as the external validation dataset （64 cases）. Risk factors were analyzed and screened through literature review， expert interviews， and the least absolute shrinkage and selection operator （LASSO） algorithm. Nine machine learning algorithms were utilized to construct diagnostic models. Comparative analyses of common evaluation metrics， calibration curves， and decision curves were conducted to select the model through internal and external validation. The Shapley additive explanations （SHAP） method and two cases were utilized to help understand the operational logic of the best model. Finally， the best model was applied to patients with borderline lesions to calculate diagnostic efficacy. ResultsNine risk factors were screened by LASSO regression， such as phlegm， hematoma， stagnation， deficiency， hypertension duration， gender， arterial stiffness index （ASI）， uric acid to high-density lipoprotein cholesterol ratio （UHR）， and glycosylated hemoglobin （HbA1c）. After comparison from multiple dimensions， the light gradient boosting machine （LightGBM） was the best model， achieving area under the curve （AUC） of 0.918 （95% confidence interval （CI）： 0.890-0.945） in the training dataset， 0.885 （95%CI： 0.820-0.951） in the internal validation dataset， and 0.897 （95%CI： 0.818-0.975） in the external validation dataset. Calibration curves indicated good consistency in the predicted probabilities， while decision curve analysis showed clinical benefit when threshold probabilities were less than 90%. SHAP importance rankings were stagnation， deficiency， hematoma， HbA1c， gender， phlegm， hypertension duration， ASI， and UHR. When applied to the patients with borderline lesions， the diagnostic model achieved an AUC of 0.783 （95%CI： 0.637-0.930）， with 73% of patients with actual severe stenosis getting benefit. ConclusionGuided by clinical value， the diagnostic model integrating traditional Chinese and Western medicine established in this study demonstrates favorable performance， providing a basis for clinical diagnosis， treatment， and decision-making in patients with CKM.

ObjectiveFrom the perspective of cardiovascular-kidney-metabolic （CKM） syndrome， this study aims to construct and validate a diagnostic machine learning model integrating traditional Chinese and Western medicine for severe coronary artery stenosis in patients with CKM， thereby providing clinical decision-making support for patients with borderline lesions. MethodsBased on a retrospective study design， a total of 535 hospitalized patients from two independent campuses of Jiangsu Province Hospital of Traditional Chinese Medicine： the main campus （from January 2024 to August 2024） and Zidong branch （from September 2024 to December 2024） were screened. Data from the main campus were randomly divided into the training dataset （376 cases） and the internal validation dataset （95 cases） at a 4∶1 ratio， while data from Zidong branch served as the external validation dataset （64 cases）. Risk factors were analyzed and screened through literature review， expert interviews， and the least absolute shrinkage and selection operator （LASSO） algorithm. Nine machine learning algorithms were utilized to construct diagnostic models. Comparative analyses of common evaluation metrics， calibration curves， and decision curves were conducted to select the model through internal and external validation. The Shapley additive explanations （SHAP） method and two cases were utilized to help understand the operational logic of the best model. Finally， the best model was applied to patients with borderline lesions to calculate diagnostic efficacy. ResultsNine risk factors were screened by LASSO regression， such as phlegm， hematoma， stagnation， deficiency， hypertension duration， gender， arterial stiffness index （ASI）， uric acid to high-density lipoprotein cholesterol ratio （UHR）， and glycosylated hemoglobin （HbA1c）. After comparison from multiple dimensions， the light gradient boosting machine （LightGBM） was the best model， achieving area under the curve （AUC） of 0.918 （95% confidence interval （CI）： 0.890-0.945） in the training dataset， 0.885 （95%CI： 0.820-0.951） in the internal validation dataset， and 0.897 （95%CI： 0.818-0.975） in the external validation dataset. Calibration curves indicated good consistency in the predicted probabilities， while decision curve analysis showed clinical benefit when threshold probabilities were less than 90%. SHAP importance rankings were stagnation， deficiency， hematoma， HbA1c， gender， phlegm， hypertension duration， ASI， and UHR. When applied to the patients with borderline lesions， the diagnostic model achieved an AUC of 0.783 （95%CI： 0.637-0.930）， with 73% of patients with actual severe stenosis getting benefit. ConclusionGuided by clinical value， the diagnostic model integrating traditional Chinese and Western medicine established in this study demonstrates favorable performance， providing a basis for clinical diagnosis， treatment， and decision-making in patients with CKM.

This study retrospectively analyzed the clinical data of 43 patients with large-volume renal calculi treated with flexible ureteroscopic lithotripsy (FURL)at our hospital from August 2020 to August 2023. Among the patients, 26 were male and 17 were female; 22 had left-sided stones and 21 had right-sided stones. Thirty-three patients had preoperative placement of a double-J (D-J)stent, while 10 did not. The mean age was (42.7±11.1)years, the mean stone volume was (10.3±3.5)cm 3, and the mean operative time was (97.9±10.4)minutes. All procedures were completed using reusable flexible ureteroscopic lithotripsy. Twenty-two patients received traditional methods of stone expulsion after FURL (control group), while 21 patients received a combination of traditional methods and extracorporeal physical vibration lithotripsy (EPVL) after FURL (experimental group). The experimental group showed a significantly higher stone-free rate at one month (85.7% vs. 54.5%)and a lower reoperation rate (4.8% vs. 31.8%)compared to the control group. The difference in reoperation rates between the experimental and control groups was statistically significant ( P< 0.05). These results suggest that the combination of reusable ureteroscopic lithotripsy and EPVL is a feasible treatment option for large-volume renal calculi.

Fatigue driving is a major cause of traffic accidents,which poses a great threat to public safety and property.In order to reduce the losses caused by fatigue driving,many researchers have devoted themselves to the study about fatigue driving,such as driver behavior monitoring,brainwave monitoring,eye tracking and facial expression analysis.Each of these methods has its own advantages and disadvantages.Behavioral monitoring reflects the fatigue state by analyzing the driver's driving habits and facial expression,which is easy to operate but prone to be affected by the external environment.Brainwave monitoring is more accurate and can detect the fatigue state in real time,but the equipment is complicated and costly,which limits its large-scale application.The detection based on eye-tracking and facial expression analysis also has a certain potential for application,but errors may occur under different light conditions.Herein the review introduces the effects of fatigue on driving ability and compares the research results of various fatigue driving detection methods by searching,collating,analyzing and summarizing the relevant literatures at home and abroad.Various detection methods are analyzed and summarized,and it is pointed out that the fatigue driving detection method based on multi-feature information fusion will become a research hotspot.

Fatigue driving is a major cause of traffic accidents,which poses a great threat to public safety and property.In order to reduce the losses caused by fatigue driving,many researchers have devoted themselves to the study about fatigue driving,such as driver behavior monitoring,brainwave monitoring,eye tracking and facial expression analysis.Each of these methods has its own advantages and disadvantages.Behavioral monitoring reflects the fatigue state by analyzing the driver's driving habits and facial expression,which is easy to operate but prone to be affected by the external environment.Brainwave monitoring is more accurate and can detect the fatigue state in real time,but the equipment is complicated and costly,which limits its large-scale application.The detection based on eye-tracking and facial expression analysis also has a certain potential for application,but errors may occur under different light conditions.Herein the review introduces the effects of fatigue on driving ability and compares the research results of various fatigue driving detection methods by searching,collating,analyzing and summarizing the relevant literatures at home and abroad.Various detection methods are analyzed and summarized,and it is pointed out that the fatigue driving detection method based on multi-feature information fusion will become a research hotspot.

This study retrospectively analyzed the clinical data of 43 patients with large-volume renal calculi treated with flexible ureteroscopic lithotripsy (FURL)at our hospital from August 2020 to August 2023. Among the patients, 26 were male and 17 were female; 22 had left-sided stones and 21 had right-sided stones. Thirty-three patients had preoperative placement of a double-J (D-J)stent, while 10 did not. The mean age was (42.7±11.1)years, the mean stone volume was (10.3±3.5)cm 3, and the mean operative time was (97.9±10.4)minutes. All procedures were completed using reusable flexible ureteroscopic lithotripsy. Twenty-two patients received traditional methods of stone expulsion after FURL (control group), while 21 patients received a combination of traditional methods and extracorporeal physical vibration lithotripsy (EPVL) after FURL (experimental group). The experimental group showed a significantly higher stone-free rate at one month (85.7% vs. 54.5%)and a lower reoperation rate (4.8% vs. 31.8%)compared to the control group. The difference in reoperation rates between the experimental and control groups was statistically significant ( P< 0.05). These results suggest that the combination of reusable ureteroscopic lithotripsy and EPVL is a feasible treatment option for large-volume renal calculi.

Objective:To investigate the surgical situations and perioperative outcome of pancreaticoduodenectomy in Jiangsu Province and the influencing factors for postoperative 90-day mortality.Methods:The retrospective case-control study was conducted. The clinicopathological data of 2 886 patients who underwent pancreaticoduodenectomy in 21 large tertiary hospitals of Jiangsu Quality Control Center for Pancreatic Diseases, including The First Affiliated Hospital of Nanjing Medical University, from March 2021 to December 2022 were collected. There were 1 732 males and 1 154 females, aged 65(57,71)years. Under the framework of the Jiangsu Provincial Pancreatic Disease Quality Control Project, the Jiangsu Quality Control Center for Pancreatic Diseases adopted a multi-center registration research method to establish a provincial electronic database for pancrea-ticoduodenectomy. Observation indicators: (1) clinical characteristics; (2) intraoperative and post-operative conditions; (3) influencing factors for 90-day mortality after pancreaticoduodenectomy. Measurement data with skewed distribution were represented as M( Q1, Q3) or M(IQR), and comparison between groups was conducted using the Mann-Whitney U test. Count data were expressed as absolute numbers or constituent ratio, and comparison between groups was conducted using the chi-square test, continuity correction chi-square test and Fisher exact probability. Maximal Youden index method was used to determine the cutoff value of continuous variables. Univariate analysis was performed using the corresponding statistical methods based on data types. Multivariate analysis was performed using the Logistic multiple regression model. Results:(1) Clinical characteristics. Of the 2 886 patients who underwent pancreaticoduodenectomy, there were 1 175 and 1 711 cases in 2021 and 2022, respectively. Of the 21 hospitals, 8 hospitals had an average annual surgical volume of <36 cases for pancreaticoduodenectomy, 10 hospitals had an average annual surgical volume of 36-119 cases, and 3 hospitals had an average annual surgical volume of ≥120 cases. There were 2 584 cases performed pancreaticoduodenectomy in thirteen hospitals with an average annual surgical volume of ≥36 cases, accounting for 89.536%(2 584/2 886)of the total cases. There were 1 357 cases performed pancrea-ticoduodenectomy in three hospitals with an average annual surgical volume of ≥120 cases, accounting for 47.020%(1 357/2 886) of the total cases. (2) Intraoperative and postoperative conditions. Of the 2 886 patients, the surgical approach was open surgery in 2 397 cases, minimally invasive surgery in 488 cases, and it is unknown in 1 case. The pylorus was preserved in 871 cases, not preserved in 1 952 cases, and it is unknown in 63 cases. Combined organ resection was performed in 305 cases (including vascular resection in 209 cases), not combined organ resection in 2 579 cases, and it is unknown in 2 cases. The operation time of 2 885 patients was 290(115)minutes, the volume of intra-operative blood loss of 2 882 patients was 240(250)mL, and the intraoperative blood transfusion rate of 2 880 patients was 27.153%(782/2 880). Of the 2 886 patients, the invasive treatment rate was 11.342%(327/2 883), the unplanned Intensive Care Unit (ICU) treatment rate was 3.087%(89/2 883), the reoperation rate was 1.590%(45/2 830), the duration of postoperative hospital stay was 17(11)days, the hospitalization mortality rate was 0.798%(23/2 882), and the failure rate of rescue data in 2 083 cases with severe complications was 6.529%(19/291). There were 2 477 patients receiving postoperative 90-day follow-up, with the 90-day mortality of 2.705%(67/2477). The total incidence rate of complication in 2 886 patients was 58.997%(1 423/2 412). The incidence rate of severe complication was 13.970%(291/2 083). The comprehensive complication index was 8.7(22.6) in 2 078 patients. (3) Influencing factors for 90-day mortality after pancreaticoduodenectomy. Results of multivariate analysis showed that age ≥ 70 years, postoperative invasive treatment, and unplanned ICU treatment were independent risk factors for 90-day mortality after pancreaticoduodenectomy ( odds ratio=2.403, 2.609, 16.141, 95% confidence interval as 1.281-4.510, 1.298-5.244, 7.119-36.596, P<0.05). Average annual surgical volume ≥36 cases in the hospital was an independent protective factor for 90-day mortality after pancreaticoduodenectomy ( odds ratio=0.368, 95% confidence interval as 0.168-0.808, P<0.05). Conclusions:Pancreaticoduodenectomy in Jiangsu Province is highly con-centrated in some hospitals, with a high incidence of postoperative complications, and the risk of postoperative 90-day mortality is significant higher than that of hospitallization mortality. Age ≥ 70 years, postoperative invasive treatment, and unplanned ICU treatment are independent risk factors for 90-day motality after pancreaticoduodenectomy, and average annual surgical volume ≥36 cases in the hospital is an independent protective factor.

Objective: To investigate the characteristics and trends of malaria cases in Lishui City, Zhejiang Province from 2012 to 2023, so as to provide a basis for improving malaria prevention and control measures. Methods: Case data of malaria in Lishui City from 2012 to 2023 were collected from the Parasitic Disease Control Information Management System of the National Information System for Disease Control and Prevention in China. The parasite species, source of infection, temporal distribution, population distribution, geographical distribution, and clinical diagnosis and treatment of the cases were descriptively analyzed. Results: A total of 169 malaria cases were reported in Lishui City from 2012 to 2023, and P. falciparum malaria was the main type, accounting for 79.88% (135 cases). The positive rate of Plasmodium detection was 3.30‰(169/51 212), the highest was 5.41‰ (18/3 327) in 2017, and the lowest was 0.38‰ (1/2 632) in 2021. Malaria cases were reported in every month from 2012 to 2023, with 91 cases (53.85%) reported from May to October. There were 168 imported cases, of which 163 (96.45%) originated from Africa. There were 127 male cases (75.15%), and the majority of cases were aged 20 to 49 years, with 138 cases accounting for 81.65%. The majority of the occupation was overseas labor export workers, with 164 cases accounting for 97.04%. A total of 161 cases (95.27%) were registered residents of Lishui City, and cases were reported from all nine counties (cities, districts), with Qingtian County and Liandu District having the higher numbers of 98 and 41 cases, respectively. The median interval from onset to hospital visit for malaria cases was 2.00 (interquartile range, 4.00) days, and the median interval from hospital visit to diagnosis was 0 (interquartile range, 1.00) day. The diagnostic rate of first-diagnosed malaria cases in municipal and county medical institutions was 95.90% (117/122) and 91.49% (43/47), respectively, with no statistical significance (P>0.05). Conclusions The P. falciparum malaria was the predominant type in Lishui City from 2012 to 2023, with the majority of cases being imported. Male overseas labor export personnel aged 20 to <50 were the key demographic.

Abstract: Objective To analyze and compare the differences in serum lipid metabolomics between patients with moderate to severe acne and healthy controls to understand the characteristics of serum lipid metabolism in acne patients. Methods Serum samples were collected from 30 patients with moderate to severe acne and 30 healthy controls matched for age, gender and body mass index in the Department of Dermatology, the Affiliated Hospital of Southwest Medical University from May 2019 to Apr. 2020. Serum lipid metabolomics was analyzed by liquid chromatography-tandem mass spectrometry. Partial least squares discriminant analysis (PLS-DA) was used for multivariate statistical analysis of differentially expressed lipid metabolites. The metabolic pathways with significant differences between the two groups were screened by Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Using Mann-Whitney U test to calculate differential metabolites. Spearman correlation analysis was used to analyze the correlation between serum PC (18: 2e/20: 2) concentration and acne severity. Results The PLS-DA results showed that the composition of serum lipid metabolites in acne patients was significantly separated from that in healthy controls. Of the top 30 lipid metabolites with the most significant differences, four kinds of triglycerides (TG), two kinds of diglycerides (DG), six kinds of phosphatidylcholine (PC), one kind of MePC, two kinds of sphingomyelin (SM), two kinds of phosphatidylinositol (PI), two kinds of ceramide (monohexosyl ceramide, Hex1Cer;dihexosyl ceramide, Hex2Cer), two cardiolipin (CL) were found to be increased in the acne group (P<0.05). The levels of one kind of DG, two kinds of lysophosphatidyl ethanolamines (LPE), one kind of dimethylphosphatidyl ethanolamine (dMePE), one kind of bismethyl phosphatidic acid (BisMePA), three kinds of phosphatidyl ethanolamine (PE) and one kind of ceramide were found to be decreased in the acne group (P<0.05), and most of them belonged to phospholipid metabolites. Spearman correlation analysis showed that serum PC (18:2e/20:2) concentration was positively correlated with acne severity (r=0.456, P=0.004). KEGG enrichment function analysis revealed that the differential lipid metabolites were primarily enriched in metabolic pathways such as sphingolipid signaling pathway, cholesterol metabolism, insulin resistance, glycerophospholipid metabolism, among which the sphingolipid signaling pathway may play an important role. Conclusion There are significant differences in serum lipid metabolism between acne patients and healthy controls. Lipid metabolism disorders may be related to the pathogenesis of acne, but it’s molecular mechanism still needs further experimental exploration.

Objective:To evaluate the efficacy and safety of sodium hyaluronate gel in preventing adhesion after prophylactic enterostomy.Methods:One hundred and twenty four patients from 6 hospitals were enrolled in this prospective multi-center randomized controlled trial. Patients were randomized into the study group ( n=59) or the control group ( n=65).All patients underwent prophylactic enterostomy. Patients of study group received odium hyaluronate gel for adhesion-prevention,while those in control group did not receive any adhesion-prevention treatment. The incidence of moderate to severe adhesion around the incision in the stoma area were evalutated during stoma reduction surgery. Results:The incidence of moderate to severe adhesion around the incision in the stoma area was 6.3% in the study group, the difference was statistically significant ( P<0.05) compared to that of the control group (32.6%). Conclusion:Sodium hyaluronate gel can safely and effectively reduce the incidence of moderate and severe adhesions after abdominal surgery.