Objective To observe the value of machine learning(ML)models constructed based on pre-treatment clinical and CT features for predicting acute liver function deterioration(ALFD)in hepatocellular carcinoma(HCC)patients after the first time TACE.Methods Totally 320 HCC patients who underwent the first TACE were retrospectively enrolled and divided into training set(n=256)and test set(n=64)at the ratio of 4∶1.ALFD was evaluated according to clinical,laboratory and image findings within 2 weeks after TACE.Univariate analysis was performed to compare clinical baseline data and diameter of HCC on pre-TACE CT in training set,and parameters being statistical different between patients with and without ALFD were used to construct ML models using 9 different ML algorithms.The efficacy of each model for predicting ALFD in test set was evaluated,and the optimal model was selected.The calibration degree and clinical value of the optimal model were assessed in test set,and the contribution of each parameter was analyzed using SHAP method.Results In training set,76 cases were ALFD and 180 cases were non-ALFD,while in test set,18 cases were ALFD and 46 cases were non-ALFD.Among 9 ML models,the sensitivity,specificity,accuracy,area under the curve,F1 value and Kappa value of extreme gradient boosting(XGBoost)model in test set was 85.12%,89.34%,88.08%,0.927,0.811 and 0.725,respectively.XGBoost model was considered as the optimal one,with predicted probability in test set in good agreement with actual probability and high clinical net benefit.The contribution of patients'age,lesion diameter on pre-TACE CT,glutamic-pyruvic transaminase,glutamic-oxaloacetic transaminase and TACE time were all great for XGBoost model.Conclusion XGBoost model based on pre-treatment clinical and CT features could be used to effectively predict ALFD in HCC patients after the first time TACE.

Objective:To evaluate the safety and feasibility of continuous lamellar pancreaticojejunostomy in laparoscopic pancreaticoduodenectomy (LPD).Methods:Clinical data of 313 patients with periampullary tumors undergoing LPD at the People's Hospital of Zhengzhou University from January 2017 to December 2021 were retrospectively analyzed, including 163 males and 150 females, aged (62.5±6.7) years. Patients were divided into two groups according to the type of pancreaticojejunostomy. Patients undergoing continuous lamellar pancreaticojejunostomy were included in the study group ( n=162) and those undergoing traditional pancreaticojejunostomy were included in the control group ( n=151). Clinical data such as gender, age, level of carbohydrate antigen 199 (CA199), operation time, postoperative hospital stay, and complications were collected. In order to reduce the baseline differences between groups, propensity score matching (PSM) was used. Results:There were significant differences in age and preoperative CA199 between the study group and the control group before PSM (all P<0.05). After PSM for age and CA199, 156 cases were successfully matched, with 78 cases in both the study and control group. Preoperative data were conparable between the two groups after PSM (all P>0.05). The drainage time [16.0 (14.0, 21.0)d vs. 18.0(15.8, 22.0)d] and postoperative hospital stay [20.0(15.0, 24.0)d vs. 21.5(20.0, 25.0)d] were shorter in the study group (all P<0.05). The incidence of grade B/C postoperative pancreatic fistula (POPF) in the study group was lower than that in the control group [7.7%(6/78) vs. 20.5%(16/78), P<0.05]. Conclusion:Compared with traditional pancreaticojejunostomy, continuous lamellar pancreaticojejunostomy could be safe and feasible, which might reduce the incidence of grade B/C POPF and enhance postoperative recovery.

Objective:To analyze the application value of three-dimensional visualization combined with indocyanine green fluorescence staining in laparoscopic resection of patients with complex liver cancer.Methods:The data of patients with complex liver cancer (liver cancer located in liver segments Ⅶ, Ⅷ, Ⅳa, Ⅴ and caudate lobe) who underwent laparoscopic anatomical liver resection in Zhengzhou University People's Hospital from August 2018 to August 2023 were retrospectively analyzed. A total of 334 patients were enrolled, including 249 males and 85 females, with the age of (57.0±10.6) years. Among the 334 patients, patients who underwent laparoscopic liver resection using three-dimensional visualization combined with indocyanine green fluorescence staining were included in the combined group ( n=128), and the other patients who underwent traditional laparoscopic liver resection were included in the traditional group ( n=206). Propensity score was used to match the preoperative indicators and postoperative pathology between the two groups. The two groups were compared in terms of gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, American Society of Anesthesiologists (ASA) grade, operation time, portal occlusion time, intraoperative blood loss, surgical margin and postoperative aspartate transaminase (ALT), alanine transaminase (AST), albumin, total bilirubin, and severe postoperative complications (Clavien-Dindo grade≥grade Ⅲ). The Kaplan-Meier method was used to analyze the prognosis, and the log-rank test was used to compare the survival rate. Results:After propensity score matching, 120 cases were included in the combined group and the traditional group, respectively. There were no significant differences in gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, and ASA grade between the two groups (all P>0.05). The intraoperative blood loss in the combined group was 200.0 (150.0, 300.0) ml, and the positive surgical margin rate was 6.7% (8/120), which were lower than 300.0 (150.0, 500.0) ml and 15.8% (19/120) in the traditional group, with statistically significant differences ( Z=-2.43, P=0.015, χ2=5.05, P=0.025). There were no statistically significant differences in the operation time, portal occlusion time, and postoperative ALT, AST, albumin, and total bilirubin between the two groups (all P>0.05). Eight cases (6.7%) in the combined group and 11 cases (9.2%) in the traditional group had severe complications after surgery, and all were discharged after treatment. The 1-, 3-, and 5-year recurrence-free survival rates of the combined group were 83.3%, 61.7%, and 58.3% respectively, while that of the traditional group were 71.7%, 52.5%, and 49.2%, respectively, with significant difference ( χ2=4.57, P=0.031). There was no significant difference in the cumulative survival rate between the combined group and the traditional group ( χ2=0.66, P=0.417). Conclusion:Compared with laparoscopic liver resection, laparoscopic liver resection for patients with complex liver cancer using three-dimensional visualization technology combined with indocyanine green fluorescence staining technology can reduce intraoperative blood loss, positive margin rate, and postoperative recurrence.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective To observe the value of machine learning(ML)models constructed based on pre-treatment clinical and CT features for predicting acute liver function deterioration(ALFD)in hepatocellular carcinoma(HCC)patients after the first time TACE.Methods Totally 320 HCC patients who underwent the first TACE were retrospectively enrolled and divided into training set(n=256)and test set(n=64)at the ratio of 4∶1.ALFD was evaluated according to clinical,laboratory and image findings within 2 weeks after TACE.Univariate analysis was performed to compare clinical baseline data and diameter of HCC on pre-TACE CT in training set,and parameters being statistical different between patients with and without ALFD were used to construct ML models using 9 different ML algorithms.The efficacy of each model for predicting ALFD in test set was evaluated,and the optimal model was selected.The calibration degree and clinical value of the optimal model were assessed in test set,and the contribution of each parameter was analyzed using SHAP method.Results In training set,76 cases were ALFD and 180 cases were non-ALFD,while in test set,18 cases were ALFD and 46 cases were non-ALFD.Among 9 ML models,the sensitivity,specificity,accuracy,area under the curve,F1 value and Kappa value of extreme gradient boosting(XGBoost)model in test set was 85.12%,89.34%,88.08%,0.927,0.811 and 0.725,respectively.XGBoost model was considered as the optimal one,with predicted probability in test set in good agreement with actual probability and high clinical net benefit.The contribution of patients'age,lesion diameter on pre-TACE CT,glutamic-pyruvic transaminase,glutamic-oxaloacetic transaminase and TACE time were all great for XGBoost model.Conclusion XGBoost model based on pre-treatment clinical and CT features could be used to effectively predict ALFD in HCC patients after the first time TACE.

Objective:To evaluate the safety and feasibility of continuous lamellar pancreaticojejunostomy in laparoscopic pancreaticoduodenectomy (LPD).Methods:Clinical data of 313 patients with periampullary tumors undergoing LPD at the People's Hospital of Zhengzhou University from January 2017 to December 2021 were retrospectively analyzed, including 163 males and 150 females, aged (62.5±6.7) years. Patients were divided into two groups according to the type of pancreaticojejunostomy. Patients undergoing continuous lamellar pancreaticojejunostomy were included in the study group ( n=162) and those undergoing traditional pancreaticojejunostomy were included in the control group ( n=151). Clinical data such as gender, age, level of carbohydrate antigen 199 (CA199), operation time, postoperative hospital stay, and complications were collected. In order to reduce the baseline differences between groups, propensity score matching (PSM) was used. Results:There were significant differences in age and preoperative CA199 between the study group and the control group before PSM (all P<0.05). After PSM for age and CA199, 156 cases were successfully matched, with 78 cases in both the study and control group. Preoperative data were conparable between the two groups after PSM (all P>0.05). The drainage time [16.0 (14.0, 21.0)d vs. 18.0(15.8, 22.0)d] and postoperative hospital stay [20.0(15.0, 24.0)d vs. 21.5(20.0, 25.0)d] were shorter in the study group (all P<0.05). The incidence of grade B/C postoperative pancreatic fistula (POPF) in the study group was lower than that in the control group [7.7%(6/78) vs. 20.5%(16/78), P<0.05]. Conclusion:Compared with traditional pancreaticojejunostomy, continuous lamellar pancreaticojejunostomy could be safe and feasible, which might reduce the incidence of grade B/C POPF and enhance postoperative recovery.

Objective:To analyze the application value of three-dimensional visualization combined with indocyanine green fluorescence staining in laparoscopic resection of patients with complex liver cancer.Methods:The data of patients with complex liver cancer (liver cancer located in liver segments Ⅶ, Ⅷ, Ⅳa, Ⅴ and caudate lobe) who underwent laparoscopic anatomical liver resection in Zhengzhou University People's Hospital from August 2018 to August 2023 were retrospectively analyzed. A total of 334 patients were enrolled, including 249 males and 85 females, with the age of (57.0±10.6) years. Among the 334 patients, patients who underwent laparoscopic liver resection using three-dimensional visualization combined with indocyanine green fluorescence staining were included in the combined group ( n=128), and the other patients who underwent traditional laparoscopic liver resection were included in the traditional group ( n=206). Propensity score was used to match the preoperative indicators and postoperative pathology between the two groups. The two groups were compared in terms of gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, American Society of Anesthesiologists (ASA) grade, operation time, portal occlusion time, intraoperative blood loss, surgical margin and postoperative aspartate transaminase (ALT), alanine transaminase (AST), albumin, total bilirubin, and severe postoperative complications (Clavien-Dindo grade≥grade Ⅲ). The Kaplan-Meier method was used to analyze the prognosis, and the log-rank test was used to compare the survival rate. Results:After propensity score matching, 120 cases were included in the combined group and the traditional group, respectively. There were no significant differences in gender, age, maximum diameter of tumor, alpha-fetoprotein, number of tumors, tumor location, and ASA grade between the two groups (all P>0.05). The intraoperative blood loss in the combined group was 200.0 (150.0, 300.0) ml, and the positive surgical margin rate was 6.7% (8/120), which were lower than 300.0 (150.0, 500.0) ml and 15.8% (19/120) in the traditional group, with statistically significant differences ( Z=-2.43, P=0.015, χ2=5.05, P=0.025). There were no statistically significant differences in the operation time, portal occlusion time, and postoperative ALT, AST, albumin, and total bilirubin between the two groups (all P>0.05). Eight cases (6.7%) in the combined group and 11 cases (9.2%) in the traditional group had severe complications after surgery, and all were discharged after treatment. The 1-, 3-, and 5-year recurrence-free survival rates of the combined group were 83.3%, 61.7%, and 58.3% respectively, while that of the traditional group were 71.7%, 52.5%, and 49.2%, respectively, with significant difference ( χ2=4.57, P=0.031). There was no significant difference in the cumulative survival rate between the combined group and the traditional group ( χ2=0.66, P=0.417). Conclusion:Compared with laparoscopic liver resection, laparoscopic liver resection for patients with complex liver cancer using three-dimensional visualization technology combined with indocyanine green fluorescence staining technology can reduce intraoperative blood loss, positive margin rate, and postoperative recurrence.

The aim of this updated guideline is to provide comprehensive recommendations for the management of gout in patients with common comorbidities, such as chronic kidney disease(CKD), cardiovascular disease(CVD), diabetes, osteoarthritis(OA), and gastrointestinal disorders. This guideline was developed by a multidisciplinary expert panel consisting of specialists in endocrinology, rheumatology, nephrology, cardiology, gastroenterology, and methodology. The development process adhered to standard methodologies, including PICO(population, intervention, comparator, and outcomes) question deconstruction, systematic literature review, the Grading of Recommendations Assessment, Development and Evaluation(GRADE) for evidence and recommendation evaluation, Delphi voting, and expert consensus. The guideline presents 26 evidence-based recommendations addressing 7 clinical questions for patients with hyperuricemia and gout in the context of comorbidities. Key recommendations include the maintenance of strict serum urate targets, particularly for patients with CKD stage≥3, chronic gouty arthritis, and OA, in order to prevent disease progression. In patients with CVD or diabetes, intra-articular triamcinolone is preferred over systemic glucocorticoids. Prioritized anti-inflammatory treatments for patients with CKD, gastrointestinal diseases and OA are recommended. The guideline also introduces emerging therapies, such as interleukin-1 inhibitors and selective urate transport inhibitors, as potential treatment options for refractory cases. The update offers a comprehensive, patient-centered approach to managing gout, particularly in individuals with associated comorbidities. Multidisciplinary collaboration and emerging new treatments and evidence ensure the optimization of the recommendations.

Objective:To analyze the risk factors for clinically relevant delayed gastric emptying (CR-DGE) following laparoscopic pancreaticoduodenectomy (LPD) and to develop a model to predict the postoperative CR-DGE after LPD using the machine-learning approach with multi-model comparison.Methods:Clinical data of 278 patients with tumors located in the pancreatic head and periampullary region undergoing LPD at People’s Hospital of Zhengzhou University from January 2019 to December 2023 were retrospectively analyzed, including 167 males and 111 females, aged 59 (53, 66) years. According to the occurrence of DGE, patients were divided into the CR-DGE group ( n=94) and the non-CR-DGE group ( n=184). Main clinical characteristics were compared between the groups, including pancreatic duct diameter, intraoperative blood loss and operative time. The perioperative indicators were selected using the least absolute shrinkage and selection operator (LASSO) algorithm. Following variable selection, 278 patients were allocated into a training set ( n=222) and a validation set ( n=56) in an 8∶2 ratio. Eight machine learning models were selected to model the training set: random forest, adaptive boosting, light gradient boosting, multilayer perceptron, support vector machine, K-nearest neighbor algorithm, decision tree and complementary set plain bayes. The area under the curve (AUC) of receiver operating characteristic curve of the validation set was utilized to identify the optimal model. The predictive performance of the optimal model was evaluated using calibration plots and decision curve analysis (DCA). The contribution of each feature to the prediction is assessed using Shapley additive explanation (SHAP). Results:Univariate analysis showed statistically significant differences between the CR-DGE and non-CR-DGE groups in terms of age [66(62, 69) years vs. 56(51, 60), years], diabetes [42.6%(40/94) vs. 11.4%(21/184)], level of fibrinogen [3.43(2.74, 4.18) g/L vs. 3.84(3.19, 4.68) g/L], pancreatic duct diameter [2.00(1.50, 2.70) mm vs. 3.40(1.60, 5.00) mm], intraoperative blood loss [300(200, 600) ml vs. 200(150, 300) ml], operative time [472(430, 502) min vs. 430(365, 475) min], clinically relevant postoperative pancreatic fistula [34.0%(32/94) vs. 3.8%(7/184)], abdominal fluid accumulation [46.8%(44/94) vs. 12.5%(23/184)], postoperative hemorrhage [20.2%(19/94) vs. 3.3%(6/184)], abdominal infection [28.7%(27/94) vs. 11.4% (21/184)] and duration of postoperative gastrointestinal decompression [4.00 (2.00, 6.00) d vs. 3.00 (2.00, 5.00) d] (all P<0.05). The eleven variables selected via LASSO were incorporated into each of the eight machine learning models. Results demonstrated that the random forest model achieved the highest performance in the validation set, with an AUC of 0.894 (95% CI: 0.800-0.985), accuracy of 0.820 and sensitivity of 0.606. Calibration plots and DCA confirmed the robustness of the random forest model. SHAP analysis indicated that age, pancreatic duct diameter and preoperative aspartate aminotransferase were important predictors in the random forest model. Conclusion:The random forest model developed in this study demonstrated a good predictive performance for CR-DGE after LPD and may assist in the early identification of high-risk patients in clinical practice.