Background and Aims:Postoperative pancreatic fistula(POPF)is one of the most severe and common complications following pancreaticoduodenectomy(PD)and is a major cause of mortality after PD.Given the multiple risk factors associated with PD-POPF,developing an effective predictive model is of significant clinical importance.This study was conducted to explore the predictive performance of the triglyceride-glucose(TyG)index combined with serological indicators for POPF following PD.Methods:The preoperative general data,laboratory indicators within one week before surgery,and postoperative complication data of 291 patients who underwent PD at the Department of General Surgery,Second Hospital of Lanzhou University,from January 2019 to June 2024,were retrospectively collected.Patients were randomly divided into a modeling group(203 cases)and a validation group(88 cases)using a computer-generated random number method at a 7∶3 ratio.Univariate Logistic regression and multivariate binary Logistic regression(Back-Wald method)were performed on the modeling group data.Based on regression analysis results,a predictive model was constructed and visualized using a nomogram.The discriminative ability of the nomogram model was evaluated by the area under the receiver operating characteristic(ROC)curve(AUC).A calibration curve was used to assess the agreement between predicted and actual probabilities,and a decision curve analysis was conducted to evaluate the clinical application value of the model.Subgroup analysis was performed on potential factors influencing the outcome variables.Results:Among the 291 patients,70 developed POPF,with 49 cases in the modeling group and 21 in the validation group.There was no statistically significant difference between the two groups(all P>0.05).Univariate analysis in the modeling group identified body mass index(BMI),triglycerides,TyG index,albumin(ALB),platelet count(PLT),absolute lymphocyte count(LYM),and absolute neutrophil count(NEUT)as significant factors associated with POPF(all P<0.05).Multivariate analysis revealed that BMI,TyG index,ALB,PLT,LYM,and NEUT were independent influencing factors for POPF(all P<0.05).A PD-POPF risk prediction model and nomogram were constructed based on these results.The model achieved an AUC of 0.80(0.73-0.86),and when applied to the validation group,the ROC analysis yielded an AUC of 0.80(0.70-0.90).The calibration curves of both the modeling and validation groups closely aligned with the standard curve.Subgroup analysis indicated that tumor nature and tumor stage had minimal impact on PD-POPF risk factors,demonstrating good model stability.Conclusion:The TyG index,along with BMI,PLT,NEUT,ALB,and LYM,is closely associated with PD-POPF occurrence.The risk prediction model based on the TyG index and these influencing factors exhibits good predictive performance and holds significant clinical value for guiding early intervention.

Background and Aims:Postoperative pancreatic fistula(POPF)is one of the most severe and common complications following pancreaticoduodenectomy(PD)and is a major cause of mortality after PD.Given the multiple risk factors associated with PD-POPF,developing an effective predictive model is of significant clinical importance.This study was conducted to explore the predictive performance of the triglyceride-glucose(TyG)index combined with serological indicators for POPF following PD.Methods:The preoperative general data,laboratory indicators within one week before surgery,and postoperative complication data of 291 patients who underwent PD at the Department of General Surgery,Second Hospital of Lanzhou University,from January 2019 to June 2024,were retrospectively collected.Patients were randomly divided into a modeling group(203 cases)and a validation group(88 cases)using a computer-generated random number method at a 7∶3 ratio.Univariate Logistic regression and multivariate binary Logistic regression(Back-Wald method)were performed on the modeling group data.Based on regression analysis results,a predictive model was constructed and visualized using a nomogram.The discriminative ability of the nomogram model was evaluated by the area under the receiver operating characteristic(ROC)curve(AUC).A calibration curve was used to assess the agreement between predicted and actual probabilities,and a decision curve analysis was conducted to evaluate the clinical application value of the model.Subgroup analysis was performed on potential factors influencing the outcome variables.Results:Among the 291 patients,70 developed POPF,with 49 cases in the modeling group and 21 in the validation group.There was no statistically significant difference between the two groups(all P>0.05).Univariate analysis in the modeling group identified body mass index(BMI),triglycerides,TyG index,albumin(ALB),platelet count(PLT),absolute lymphocyte count(LYM),and absolute neutrophil count(NEUT)as significant factors associated with POPF(all P<0.05).Multivariate analysis revealed that BMI,TyG index,ALB,PLT,LYM,and NEUT were independent influencing factors for POPF(all P<0.05).A PD-POPF risk prediction model and nomogram were constructed based on these results.The model achieved an AUC of 0.80(0.73-0.86),and when applied to the validation group,the ROC analysis yielded an AUC of 0.80(0.70-0.90).The calibration curves of both the modeling and validation groups closely aligned with the standard curve.Subgroup analysis indicated that tumor nature and tumor stage had minimal impact on PD-POPF risk factors,demonstrating good model stability.Conclusion:The TyG index,along with BMI,PLT,NEUT,ALB,and LYM,is closely associated with PD-POPF occurrence.The risk prediction model based on the TyG index and these influencing factors exhibits good predictive performance and holds significant clinical value for guiding early intervention.

Objective To compare the differences between two statistical methods for evaluating non-sensitivity of pathogenic bacteria to antimicrobial agents,and explore effect of non-consideration of clinical background on evalua-ting extent of bacterial resistance.Methods Data of Staphylococcus aureus and Acinetobacter spp .in a hospital in the first half year of 2008,2010 and 2013 were collected and conducted statistical analysis with two methods (me-thod 1 :based on all clinically isolated bacteria;method 2 :based on infection-related non-repetitive bacteria),two methods for evaluating bacterial non-sensitive rates to antimicrobial agents were compared.Results The non-sensi-tive rates of Acinetobacter spp .to various antimicrobial agents :statistical results by using method 1 were generally higher than those using method 2,absolute difference between two statistical methods was 10.46%-33.77%;the non-sensitive rates of Staphylococcus aureus to various antimicrobial agents :except compound sulfamethoxazole in 2010 and 2013(difference were 6.17% and 10.21 % respectively),penicillin G (difference was 3.86%),erythromy-cin (difference was 2.71 %),and azithromycin in 2013 (difference was 2.43%),statistical results by using method 1 were generally higher than those using method 2,absolute difference between two statistical methods was 0-18.04%.Conclusion There are deviation in the non-sensitive rates of bacterial strains to antimicrobial agents by using two different statistical methods,deviation is larger in Acinetobacter spp ..The resistance level might be incorrectly higher when evaluating the resistance status without considering clinical background of bacteria.

Objective To compare the efficacy and side effects between systemic chemotherapy and hepatic arterial infusion by combination of oxaliplatin and 5-fluorouracil (FOLFOX-6) with 5-fluorouracil in the patients who have developed hepatic metastasis after colorectal cancer operation. The factors that would affect the prognosis without operational treatment were also analyzed. Methods 46patients who had signed the informed consents were allocated into two groups: the group with general chemotherapy (Trial Group includes 26 cases) and the one with hepatic arterial infusion chemotherapy (Control Group includes 20 cases). The total effective rate, the prognosis, the cytoxicitic side effects,quality of life, the total survival rate and the responses were the main parameters determined. Kaplan-Meier was used to analyze Mono-factor to the prognostic responses and the Cox mode was used to analyze poly-factor to the prognostic responses. Results The overall survival rate was significantly higher by using systemic treatment versus HAI(median, 15. 0 v 11.2 months;P＜0.05). The difference in overall responsive rate (CR+PR) between the two groups was statistically significant (50% v 10%;P=0. 011). No significant difference was found in PS scale during the treatment. (P=0. 126). Except for myelosuppression and abdominal pain, no significant difference was found in the other side effects. Univariate analysis revealed that the invasive lesions to serosa, the distribution of liver metastases, the size and number of liver metastases, primary carcinoma involving lymph nodes and the treatment were correlated with prognoses. Cox regression analysis showed that the larger diameter of liver metastases, the number of liver lesions, primary carcinomas involved in serosal layer and the treatment modules were independent prognostic factors. Conclusions The oxaliplatin-based FOLFOX-6 chemotherapy regiment has a better responsive rate and survival rate than the traditional infusion with 5-fluorouracil to the main hepatic artery for interventional therapy. The diameter of the hepatic metastasis larger than 5em, multiple hepatic metastasis and the primary lesions penetrating serosal layer suggest the poor prognosis. The oxaliplatin-based systematic chemotherapy has a better prognosis. Therefore,it is worth carrying on further study on modification of traditional hepatic arterial infusion and on evaluation of therapy by combination of the hepatic arterial infusion with the systematic chemotherapy.

AIM: To observe the efficacy of hemoperfusion (HP) to treat one case suffering from overdose digoxin poisoning. METHODS: HA 330 ml and YT 160 hemoperfusion cartridges were used and blood vessel was femoral vein, single needle and two chamber catheter. Four HP were done. RESULTS: The blood digoxin level were 16 ?g?L -1 before and after the 1st HP, 9.22 ?g?L -1 at the 2nd, 12.4 ?g?L -1 before the 3th, 10.45 ?g?L -1 after the 3th, 3.22 ?g?L -1 before the 4th, and 2.84 ?g?L -1 after the 4th HP. CONCLUSION: This case demonstrats that multiple HP at different period may decrease the blood digoxin level step by step.