OBJECTIVE To analyze the impact of the diagnosis-related groups （DRG） payment reform on the length of stay and medical costs in patients with chronic obstructive pulmonary disease （COPD） in Kashgar region， aiming to provide localized empirical evidence for the optimization of regional medical insurance payment methods. METHODS Based on the inpatient settlement database of the Xinjiang Uygur Autonomous Region Healthcare Security Administration， settlement data of COPD inpatients from 17 medical institutions in Kashgar region between January 1， 2022， and December 31， 2024， were extracted. The overall changes in patients’ length of stay and costs were compared before and after the reform. Subsequently， interrupted time series analysis （ITSA） was employed to explore the impact of the DRG payment reform on these variables. RESULTS Following the reform， both the average length of stay and various cost decreased significantly compared to the pre-reform period （ P ＜0.001）. At the overall sample level， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission all demonstrated significant long-term downward trends after the reform （ P ＜0.05）. However， the decrease in average out-of-pocket costs and the increase in average consumable costs per admission were not statistically significant （ P ＞0.05）. In tertiary medical institutions， the average length of stay and all categories of costs （except average consumable costs per admission） exhibited significant long-term upward trends after the reform （ P ＜0.05）； conversely， in secondary and lower-level medical institutions， the average length of stay， average total cost， average drug cost， average medical service cost， and average examination cost per admission showed significant long-term downward trends （ P ＜0.05）. CONCLUSIONS The DRG payment reform has achieved an overall effect of reducing the length of stay and controlling costs in COPD patients from Kashgar region. However， the effects vary across different levels of medical institutions： secondary and lower-level institutions show a long-term downward trend in length of stay and costs， whereas tertiary institutions exhibit a long-term upward trend. Furthermore， patients’ out-of-pocket financial burden does not show significant improvement.

OBJECTIVE To investigate the prevalence and influencing factors of potentially inappropriate medication （PIM） among the elderly in nursing homes in Urumqi based on three PIM screening tools， and to compare the applicability of different tools. METHODS A cross-sectional study design was adopted. Elderly individuals from six nursing homes in Urumqi were selected as the research subjects from May 2021 to September 2023. Demographic characteristics， disease burden and medication records of the elderly were collected. PIM screening was performed using the Chinese PIM criteria （2024 edition）， the American Geriatrics Society （AGS） Beers criteria （2023 edition）， and the Screening Tool of Older Person’S Prescriptions（STOPP）/Screening Tool to Alert to Right Treatment（START） （2023 edition）. Fleiss’s Kappa test was used to assess the consistency among the three screening tools， and multivariate Logistic regression was used to analyze the influencing factors of PIM. RESULTS The prevalence of PIM screened by the Chinese PIM criteria was 47.4% （323/682）， by the AGS Beers criteria was 43.4% （296/682）， and by the STOPP criteria was 50.9% （347/682）. The consistency among the three screening tools was low （Fleiss’s Kappa＝0.12， P ＜0.001）. Multivariate Logistic regression analysis showed that all three screening tools indicated that polypharmacy， aspirin use and psychotropic drug use were independent risk factors for PIM among elderly in nursing houses （all OR＞1， P ＜0.05）. CONCLUSIONS The prevalence of PIM among the elderly in nursing homes in Urumqi is relatively high. Polypharmacy， aspirin use and psychotropic drug use are common independent risk factors for PIM. There are differences in screening results among the three tools with low consistency. The Chinese PIM criteria can serve as a first-line tool for PIM screening in nursing homes.

ObjectiveTo investigate the application value of a predictive model constructed based on quantitative imaging parameters and serum tumor markers in predicting the postoperative prognosis of patients with pancreatic ductal adenocarcinoma （PDAC）. MethodsA retrospective study was conducted among 146 patients with PDAC who underwent radical resection in Hebei Medical University Fourth Hospital from April 2020 to March 2023， and the patients were divided into a training set with 102 patients and a validation set of 44 patients at a ratio of 7∶3 using the completely randomized method. All patients underwent enhanced computed tomography （CT） and multi-parametric magnetic resonance imaging scans， and CT values in the arterial phase， the venous phase， and the delayed phase were recorded， as well as apparent diffusion coefficient （ADC） at b = 800 s/mm² and signal intensity （SI） of T₂ weighted imaging. The serum levels of carbohydrate antigen 19-9 （CA19-9） and carcinoembryonic antigen （CEA） were also measured. The independent-samples t test was used for comparison of continuous data between groups， and the chi-square test was used for comparison of categorical data between groups. Kaplan-Meier survival curves were plotted for survival analysis； the univariate and multivariate Logistic regression analysis was used to investigate the association of clinical and imaging indicators with prognosis； the least absolute shrinkage and selection operator （LASSO）-Cox regression model was used to identify the important influencing factors for prognosis， and a prognostic prediction model was constructed. The receiver operating characteristic （ROC） curve was used to analyze the predictive value of the model in predicting prognosis in both the training set and the validation set. ResultsThe Kaplan-Meier survival curve analysis showed a median survival time of 33.00 months in the training set and 32.00 months in the validation set， with no significant difference between the training set and the validation set （P>0.05）. The univariate analysis showed that patient age， degree of tumor differentiation， lymph node metastasis， tumor stage， vascular invasion， CA19-9， CEA， ADC value， and SI value were significantly associated with the survival prognosis of patients （χ²=5.906， 13.116， 12.807， 17.277， 14.611， 7.275， 14.339， 9.506， and 13.137， all P<0.05）. The LASSO-Cox multivariate regression analysis showed that six factors were incorporated into the regression model， i.e.， tumor stage （HR=8.934， 95%CI： 3.215 — 21.562， P<0.001）， lymph node metastasis （HR=2.971， 95%CI： 1.298 — 5.647， P=0.002）， CA19-9 （HR=3.948， 95%CI： 1.758 — 8.994， P<0.001）， CEA （HR=1.965， 95%CI： 1.083 — 3.664， P=0.039）， ADC value （HR=2.873， 95%CI： 1.307 — 6.037， P=0.003）， and SI value （HR=3.107， 95%CI： 1.264 — 7.339， P=0.001）. The nomogram model constructed based on these factors had an area under the ROC curve of 0.845 （95%CI： 0.774 — 0.915） in the training set and 0.919 （95%CI： 0.870 — 0.967） in the validation set. ConclusionThe combined model of quantitative imaging parameters and serum tumor markers constructed based on LASSO-Cox regression can effectively predict the postoperative prognosis of PDAC patients， thereby helping to identify high-risk patients and guide decision-making for adjuvant therapy.

AIM: To investigate the effect and potential mechanism of liraglutide(LIR)combined with neural stem cells(NSCs)in alleviating diabetic retinopathy(DR)in rats.METHODS:A DR rat model was established using a high-fat diet combined with a single intraperitoneal injection of streptozotocin(STZ). Rats in the control group were fed a normal diet and received an intraperitoneal injection of citric acid-sodium citrate buffer. After modeling, the rats were divided into the control group, DR group, DR+LIR group, DR+BMSCs group, DR+NSCs group, DR+BMSCs+LIR group, and DR+NSCs+LIR group. According to the grouping instructions, rats were given intraperitoneal injection of LIR at 200 μg/(kg·d)and intravitreal injection of bone marrow mesenchymal stem cells(BMSCs), or NSCs, or the combined therapy accordingly for 8 wk. Fasting blood glucose(FBG)and serum insulin levels, as well as retinal oxidative stress indexes and serum inflammatory indexes, were detected in each group. Retinopathy was evaluated by hematoxylin-eosin(HE)staining, retinal cell apoptosis was detected by TUNEL staining, SIRT1 expression in retinal tissues was detected by immunohistochemistry, and BDNF expression in retinal tissues was detected by immunofluorescence. The transcriptional levels of cZNF532, miR-29a-3p, SIRT1, TGF-β1, NRF2, Keap1, and BDNF in retinal tissues were detected by qRT-PCR, and the protein expression levels of SIRT1, TGF-β1, SMAD2/3, p-SMAD2/3, NRF2, Keap1, p65, and p-p65 in retinal tissues were detected by Western blot. RESULTS:Compared with the other groups of rats, the retinal morphology of rats in the DR+NSCs+LIR group was significantly improved, the levels of FBG, TNF-α, IL-1β, IL-6 and MDA were decreased(all P<0.05), the serum insulin level and the levels of SOD, CAT, and GSH-Px were increased(all P<0.05), the TUNEL-positive rate of retinal cells was reduced(all P<0.05). The expression levels of cZNF532, SIRT1, NRF2, and BDNF in retinal tissue were up-regulated(all P<0.05), whereas the expression levels of miR-29a-3p, TGF-β1, p-SMAD2/3, Keap1, and p-p65 were down-regulated(all P<0.05). CONCLUSION:LIR combined with NSCs alleviates DR by regulating the cZNF532-miR-29a-3p-SIRT1 network and its downstream TGF-β/SMAD, NF-κB, and Keap1/NRF2 signaling pathways.

Objective To explore the effect of follow-up management based on the digital information platform on the compliance of early screening and follow-up of liver cancer in patients with chronic liver diseases,and to provide a management method for clinical practice.Methods Convenience sampling was adopted to include 3,959 patients who had chronic liver diseases and visited the outpatient clinic of the Department of Infectious Liver Diseases in our hospital from January 2022 to December 2023.Before the application of the digital information platform for management,it was the medical staff of the Infectious Liver Disease Department who conducted telephone follow-ups and handwritten registrations for patients with chronic liver diseases within one week after their visits.After management,A liver cancer prediction model installed in the digital information platform of the hospital automatically collected data of the patients,including information about the diseases and results of examinations for intelligent risk stratification of liver cancer.The nurses who were in charge of the follow-up performed individualised follow-up reviews based on the levels of risk.Follow-up re-visit rate of the patients in very high-and high-risks were calculated.Scores of chronic disease self-efficacy and medication compliance were compared before and at 3 months after the follow-up management.Results A total of 3,860 patients completed the study.After the follow-up management,the total follow-up re-visit rate of the patients was 88.2%(1,818/2,062)and that of the high-risk patients was 95.3%(246/258)in 2022,while those in 2023 were 94.0%(1,691/1,798)and 98.3%(232/236),respectively.After 3 months of follow-up management,scores for medication compliance and chronic disease self-efficacy showed significant improvement in comparison with those before the implementation of follow-up management(P<0.001).Conclusion The follow-up management based on a digital information platform is suitable for screening of early liver cancer in the patients with chronic liver diseases,as it improves the re-visit rate of patients for follow-up,medication compliance and self-efficacy.

Objective:To analyze the correlation between blood glucose index and peripheral neuropathy in type 2 diabetes patients under continuous blood glucose monitoring.Methods:A total of 110 patients with type 2 diabetes admitted to the Lu′an Hospital Affiliated to Anhui Medical University from November 2022 to January 2024 were retrospectively observed, and the blood glucose indexes of patients were monitored by continuous glucose meter [glucose time in range (TIR), mean blood glucose (MBG), estimated hemoglobin A 1c (eHbA 1c), blood glucose standard deviation (SD), coefficient of variation (CV), largest amplitude of glycemic excursions (LAGE), mean amplitude of glycemic excursions (MAGE), means of daily differences (MODD), etc ]. All patients with type 2 diabetes were grouped according to whether they had peripheral neuropathy or not, and were divided into the developing group and the non-developing group. General data and blood glucose indexes of the two groups were collected and sorted out. Receiver operating characteristic (ROC) curve was used to analyze the value of various blood glucose indicators in predicting peripheral neuropathy in patients with type 2 diabetes. Spearman correlation analysis was also used to evaluate the correlation between blood glucose index and peripheral neuropathy. Results:The disease course, TIR, MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD of the occurrence group were significantly different from those of the non-occurrence group (all P<0.05). By plotting the ROC curve, It was found that the area under the curve (AUC) of TIR, MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD predicting peripheral neuropathy in patients with type 2 diabetes were 0.942, 0.840, 0.705, 0.759, 0.819, 0.813, 0.857 and 0.677, respectively. The AUC of the combined prediction was 0.971(95% CI: 0.946-0.997), which was higher than that of the single indicator (all P<0.05). Spearman correlation assessment showed a negative correlation between TIR and peripheral neuropathy ( r=-0.738, P<0.05). MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD were positively correlated with peripheral neuropathy ( r=0.554, 0.376, 0.452, 0.490, 0.527, 0.625, 0.272, all P<0.05). Conclusions:Based on continuous blood glucose monitoring, the blood glucose index of type 2 diabetes patients is closely related to peripheral neuropathy, and the above blood glucose index can accurately predict peripheral neuropathy, providing a reference for reducing or preventing the occurrence of peripheral neuropathy.

Objective To explore the diagnostic performance of prostate imaging reporting and data system(PI-RADS)V2.1 score combined with prostate specific antigen(PSA)-related parameters in transition zone prostate cancer(PCa)in patients with PSA levels of 4-20 ng/mL.Methods The clinical data of 129 patients who underwent prostate biopsy were retrospectively analyzed,including age,total prostate specific antigen(tPSA),free prostate specific antigen(fPSA),f/t PSA,prostate volume(PV),and prostate specific antigen density(PSAD).Among 129 patients,52 were diagnosed with transition zone PCa and 77 with benign prostate hyperplasia.The MRI images of all patients were scored according to the PI-RADS V2.1 criteria.The clinical and imaging parameters between transition zone PCa and benign prostate hyperplasia were compared using univariate logistic regression analysis.Independent predic-tors were identified via multivariate logistic regression,and a combined predictive model was constructed.Diagnostic performance of the model was evaluated using the receiver operating characteristic(ROC)curves.Results Univariate logistic regression analysis showed that the transition zone PCa exhibited significantly higher PI-RADS V2.1 score,tPSA,and PSAD than the benign prostate hyperplasia(P＜0.05).Multivariate logistic regression analysis identified PI-RADS V2.1 score and PSAD were independent predictors for predicting transition zone PCa(P＜0.05).Optimal diagnostic thresholds were PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mL2.The combined prediction model achieved an area under the curve(AUC)of 0.863,outperforming PI-RADS V2.1 score(AUC=0.821)and PSAD(AUC=0.779)alone(P＜0.05).Conclusion The combination of PI-RADS V2.1 score and PSAD has a high predictive value for transition zone PCa in patients with PSA levels of 4-20 ng/mL.Thresholds of PI-RADS V2.1 score＞3 points and PSAD＞0.23 ng/mLL2 significantly improve diagnostic accuracy.

Objective To explore the effectiveness of the peripheral arterial calcification scoring system(PACSS)based on computed tomography angiography(CTA)in assessing renal function in patients with peripheral arterial disease(PAD).Methods The clinical data,CTA imaging data,and laboratory results from PAD patients who underwent lower limb artery CTA examination were retrospectively collected.The PACSS was utilized to score the calcification in both lower limb arteries.Participants were categorized into three groups based on their estimated glomerular filtration rate(eGFR)(normal group:eGFR≥90 mL/min;mild renal dysfunction group:eGFR 60-89 mL/min,and moderate to severe renal dysfunction group:eGFR＜60 mL/min).The demographic data,clinical symptoms,and comorbidities among the three groups were compared by analysis of variance(ANOVA).The Spearman correlation coefficient was employed to evaluate the relationship between eGFR,cystatin C,and PACSS score.Results The age(P＜0.001)and PACSS score(P＜0.05)of patients with renal dysfunction were significantly higher than those of patients with normal renal function.However,there were no significant differences in gender,prevalence of diabetes,hypertension,or severe limb ischemia.Spearman correlation analysis showed that eGFR was negatively correlated with PACSS score(r=-0.18 in the right lower limb,P=0.037,r=-0.24 in the left lower limb,P=0.006).In contrast,cystatin C was positively correlated with PACSS score(r=0.26 in the right lower limb,P＜0.001,r=0.22 in the left lower limb,P=0.002).Conclusion The PACSS score of lower limb artery in PAD patients is corre-lated with the severity of renal dysfunction.This finding may facilitate early warning and clinical intervention for PAD patients with renal dysfunction.

Objective To explore the effect of follow-up management based on the digital information platform on the compliance of early screening and follow-up of liver cancer in patients with chronic liver diseases,and to provide a management method for clinical practice.Methods Convenience sampling was adopted to include 3,959 patients who had chronic liver diseases and visited the outpatient clinic of the Department of Infectious Liver Diseases in our hospital from January 2022 to December 2023.Before the application of the digital information platform for management,it was the medical staff of the Infectious Liver Disease Department who conducted telephone follow-ups and handwritten registrations for patients with chronic liver diseases within one week after their visits.After management,A liver cancer prediction model installed in the digital information platform of the hospital automatically collected data of the patients,including information about the diseases and results of examinations for intelligent risk stratification of liver cancer.The nurses who were in charge of the follow-up performed individualised follow-up reviews based on the levels of risk.Follow-up re-visit rate of the patients in very high-and high-risks were calculated.Scores of chronic disease self-efficacy and medication compliance were compared before and at 3 months after the follow-up management.Results A total of 3,860 patients completed the study.After the follow-up management,the total follow-up re-visit rate of the patients was 88.2%(1,818/2,062)and that of the high-risk patients was 95.3%(246/258)in 2022,while those in 2023 were 94.0%(1,691/1,798)and 98.3%(232/236),respectively.After 3 months of follow-up management,scores for medication compliance and chronic disease self-efficacy showed significant improvement in comparison with those before the implementation of follow-up management(P<0.001).Conclusion The follow-up management based on a digital information platform is suitable for screening of early liver cancer in the patients with chronic liver diseases,as it improves the re-visit rate of patients for follow-up,medication compliance and self-efficacy.

Objective:To analyze the correlation between blood glucose index and peripheral neuropathy in type 2 diabetes patients under continuous blood glucose monitoring.Methods:A total of 110 patients with type 2 diabetes admitted to the Lu′an Hospital Affiliated to Anhui Medical University from November 2022 to January 2024 were retrospectively observed, and the blood glucose indexes of patients were monitored by continuous glucose meter [glucose time in range (TIR), mean blood glucose (MBG), estimated hemoglobin A 1c (eHbA 1c), blood glucose standard deviation (SD), coefficient of variation (CV), largest amplitude of glycemic excursions (LAGE), mean amplitude of glycemic excursions (MAGE), means of daily differences (MODD), etc ]. All patients with type 2 diabetes were grouped according to whether they had peripheral neuropathy or not, and were divided into the developing group and the non-developing group. General data and blood glucose indexes of the two groups were collected and sorted out. Receiver operating characteristic (ROC) curve was used to analyze the value of various blood glucose indicators in predicting peripheral neuropathy in patients with type 2 diabetes. Spearman correlation analysis was also used to evaluate the correlation between blood glucose index and peripheral neuropathy. Results:The disease course, TIR, MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD of the occurrence group were significantly different from those of the non-occurrence group (all P<0.05). By plotting the ROC curve, It was found that the area under the curve (AUC) of TIR, MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD predicting peripheral neuropathy in patients with type 2 diabetes were 0.942, 0.840, 0.705, 0.759, 0.819, 0.813, 0.857 and 0.677, respectively. The AUC of the combined prediction was 0.971(95% CI: 0.946-0.997), which was higher than that of the single indicator (all P<0.05). Spearman correlation assessment showed a negative correlation between TIR and peripheral neuropathy ( r=-0.738, P<0.05). MBG, eHbA 1c, SD, CV, LAGE, MAGE and MODD were positively correlated with peripheral neuropathy ( r=0.554, 0.376, 0.452, 0.490, 0.527, 0.625, 0.272, all P<0.05). Conclusions:Based on continuous blood glucose monitoring, the blood glucose index of type 2 diabetes patients is closely related to peripheral neuropathy, and the above blood glucose index can accurately predict peripheral neuropathy, providing a reference for reducing or preventing the occurrence of peripheral neuropathy.