Objective Construct a risk model for postoperative recurrence of hepatolithiasis and validate it.Methods From January 2020 to December 2021,237 patients undergoing hepatobiliary duct stone surgery were selected.All patients underwent liver lobectomy by the same team and were divided into two groups according to whether there was recurrence during the 2-year postoperative follow-up period.Among them,there were 34 cases in the recurrence group and 203 cases in the non-recurrence group.Using binary logistic regression analysis to identify risk factors for postoperative recurrence of liver and bile duct stones,and constructing a predictive model based on the results of binary logistic regression.Using ROC curve analysis to evaluate the diagnostic efficacy of the predictive model,and verifying its validity.Results Univariate analysis showed that age,BMI,course of disease,gender,common bile duct exploration,cholecystectomy,hypertension,diabetes,hepatitis and cirrhosis,smoking,drinking history in the recurrence group were not statistically significant compared with those in the non recurrence group(P＞0.05),while the size of stones in the liver,diameter of common bile duct,number of stones,biliary inflammation,biliary stricture,diverticulum near the nipple,residual stones,hypercholesterolemia in the recurrence group were statistically significant compared with those in the non recurrence group(P＜0.05).Logistic multiple regression analysis showed that intrahepatic stone size≥10 mm,number of stones＞1,biliary inflammation,biliary stricture,and diverticulum adjacent to the nipple were risk factors for postoperative recurrence of hepatobiliary stones[OR values(95％ CI)were 5.032(1.812-13.977),2.585(1.007-6.632),2.512(1.013-6.230),4.571(1.775-11.72),2.925(1.023-8.363),P＜0.05].Based on the risk factors,a prediction model was constructed.The Hosmer-Lemeshow fitting test showed that x2=3.506,P=0.743.Receiver operating characteristic(ROC)curve analysis showed that the area under the ROC curve(AUC)of the prediction model for recurrence after hepatobiliary calculi surgery was 0.828,the Youden index was 0.489,and the sensitivity and specificity were 76.5％ and 72.4％,respectively.95％ CI was(0.756,0.906).The accuracy was 88.2％.Conclusion The risk prediction model for postoperative recurrence of liver and gallbladder stones constructed in this study has certain predictive value.

Objective Construct a risk model for postoperative recurrence of hepatolithiasis and validate it.Methods From January 2020 to December 2021,237 patients undergoing hepatobiliary duct stone surgery were selected.All patients underwent liver lobectomy by the same team and were divided into two groups according to whether there was recurrence during the 2-year postoperative follow-up period.Among them,there were 34 cases in the recurrence group and 203 cases in the non-recurrence group.Using binary logistic regression analysis to identify risk factors for postoperative recurrence of liver and bile duct stones,and constructing a predictive model based on the results of binary logistic regression.Using ROC curve analysis to evaluate the diagnostic efficacy of the predictive model,and verifying its validity.Results Univariate analysis showed that age,BMI,course of disease,gender,common bile duct exploration,cholecystectomy,hypertension,diabetes,hepatitis and cirrhosis,smoking,drinking history in the recurrence group were not statistically significant compared with those in the non recurrence group(P＞0.05),while the size of stones in the liver,diameter of common bile duct,number of stones,biliary inflammation,biliary stricture,diverticulum near the nipple,residual stones,hypercholesterolemia in the recurrence group were statistically significant compared with those in the non recurrence group(P＜0.05).Logistic multiple regression analysis showed that intrahepatic stone size≥10 mm,number of stones＞1,biliary inflammation,biliary stricture,and diverticulum adjacent to the nipple were risk factors for postoperative recurrence of hepatobiliary stones[OR values(95％ CI)were 5.032(1.812-13.977),2.585(1.007-6.632),2.512(1.013-6.230),4.571(1.775-11.72),2.925(1.023-8.363),P＜0.05].Based on the risk factors,a prediction model was constructed.The Hosmer-Lemeshow fitting test showed that x2=3.506,P=0.743.Receiver operating characteristic(ROC)curve analysis showed that the area under the ROC curve(AUC)of the prediction model for recurrence after hepatobiliary calculi surgery was 0.828,the Youden index was 0.489,and the sensitivity and specificity were 76.5％ and 72.4％,respectively.95％ CI was(0.756,0.906).The accuracy was 88.2％.Conclusion The risk prediction model for postoperative recurrence of liver and gallbladder stones constructed in this study has certain predictive value.

Purpose/Significance To deeply analyze the research progress on the application of medical knowledge graph in the field of stroke,to discuss the problems of the development of stroke knowledge graph in China,and to put forward suggestions for the construc-tion of stroke knowledge graph.Method/Process By reviewing and analyzing the relevant literature,the application of medical knowledge graph in the field of stroke is sorted out and summarized.Result/Conclusion There are still many deficiencies in the development of stroke knowledge graph in China,and in the future,in-depth research can be carried out from four aspects,namely,expanding the ap-plication scope of knowledge graph,promoting the fusion of knowledge graph,developing more efficient algorithms,and upgrading to cog-nitive graph by joint artificial intelligence(AI).

Objective:To assess the value of amide proton transfer weighted (APTw) imaging in the evaluation of pH changes in infarct core (IC) and ischemic penumbra (IP) in subacute cerebral infarction.Methods:The data of twenty-three subacute cerebral infarction patients with unilateral steno-occlusive disease of the middle cerebral artery (subacute infarction group) from April to November 2019 in the First Affiliated Hospital of Dalian Medical University were prospectively analyzed. Fifteen healthy volunteers were enrolled in this study as the control group. All subjects underwent conventional MRI, DWI, 3D-pseudo continuous arterial spin labeling (3D-pCASL) and APTw sequences. Based on DWI images, relative cerebral blood flow (rCBF) and APTw images to determine the region of IC, blood flow penumbra [cerebral blood flow(CBF)-DWI mismatch area, IP CBF] and metabolic penumbra (APTw-DWI mismatched area, IP APT). 3D ROIs were used to semi-automatically measure the APTw signals and the volume of IC and IP CBF of the patients in subacute infarction group. The comparison of APTw signals between the infarct side and the contralateral side in the subacute infarction group, the comparison of bilateral APTw signals in the control group, and the comparison of APTw signals in the IC and IP CBF regions were performed by paired-sample t test or Wilcoxon signed-rank test. The paired-sample t test or Mann-Whitney U test was used to compare the APTw signals between the two groups. The Friedman test was applied to compare the difference of volumes among IP CBF1.5, IP CBF2.5 and IP APT . Results:There was no significant difference of the APTw signals among the IC, the contralateral side in the subacute infarction group and the control group ( P>0.05). The APTw signals of IP CBF and IC of the infarction group were statistically different ( P<0.05). Compared with the contralateral side of IP CBF1.5 (3.7±1.7, -1.84±1.48, 5.57±2.75), the APTwmax (3.07±1.41, t=-3.012, P=0.006), APTw min [-1.30 (-1.74, -0.57), Z=-2.099, P=0.036], and APTwmax-min(4.51±2.58, t=-3.273, P=0.003) signals in the IP CBF1.5 were decreased ( P<0.05). Compared with the contralateral side of IP CBF2.5 [-1.53 (-2.80, -0.91), 5.31±2.61], the APTw min [-1.08 (-1.60, -0.49), Z=-2.616, P=0.009] and APTwmax-min (4.41±2.72, t=-3.228, P=0.004) signals in the IP CBF2.5 were decreased. The volumes of IP CBF1.5 [107.51(50.08, 138.61)mm 3], IP APT [99.00 (53.27, 121.335) mm 3] and IP CBF2.5 [89.91 (51.53, 139.87) mm 3] were successively reduced (χ2=7.913, P=0.019), and the volume of IP CBF2.5 was significantly smaller than that of IP CBF1.5 ( P=0.037). Conclusion:The acid-base metabolism in the IC of subacute cerebral infarction is not obvious, but the blood flow penumbra has local acid-base metabolism imbalance, and the range of metabolic penumbra coincides with the blood flow penumbra.