Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective To study the risk factors and strain resistance of Escherichia coli with extended-spectrum β-lactamases(ESBL)-producing bloodstream infection,so as to provide clinical basis for rational use of antibiotics and effective prevention and control of bloodstream infection.Methods The clinical data of patients with bloodstream infections caused by Escherichia coli in a tertiary hospital in Chongqing from January 2018 to December 2022 were retrospectively collected.The clinical characteristics and drug resistance of bloodstream infections caused by Escherichia coli were statistically analysed.According to the ESBL confirmation test of Escherichia coli strains,the patients were divided into the ESBL-producing group and the non-ESBL-producing group.The chi-square test was used to compare the differences in influencing factors between the two groups,and then the independent influencing factors of ESBL production were analyzed through multivariate Logistic regression.Results A total of 408 patients were included.The detection rate of ESBL-producing strains was 60.3％(246/408),and the detection rates in the nephrology department and the intensive care unit were relatively high(both＞76.0％).Diabetes[OR=1.98,95％CI(1.24,3.17)]and urinary tract intubation[OR=1.60,95％CI(1.02,2.51)]were independent influencing factors for bloodstream infection with ESBL-producing Escherichia coli.The resistance rate of ESBL-producing Escherichia coli to levofloxacin and ceftriaxone was＞90.0％.Moreover,the resistance rates of the second-generation cephalosporins(except ceftazidime),compound sulfamethoxazole,ciprofloxacin and amtronam were significantly higher than those in the non-ESBL-producing group(P＜0.05).Both groups of strains showed high sensitivity to amikacin and carbapenem drugs.Conclusion The severe current situation of bloodstream infections caused by ESBL-producing Escherichia coli in this region showing a high prevalence of drug resistance characteristics.Diabetes and urinary tract intubation,as independent risk factors,suggest that key monitoring should be implemented for such high-risk populations in clinical practice.Given that ESBL-producing strains remain sensitive to carbapenems and amikacin,it can be recommended as the first empirical medication.It is of great public health significance to achieve the effect of curbing the spread of such multi-drug resistant bacteria by establishing an early warning system based on risk factor assessment and standardized management of invasive operations.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To evaluate the efficacy and safety of transcatheter aortic valve implantation(TAVI)for the treatment of primary aortic valve regurgitation(NAVR)and to compare the difference in the choice of prosthetic valve size and the difference in complications with aortic stenosis(AS).Methods According to the definition of Valve Academic Research Consortium(VARC-3),143 patients with NAVR/AS treated with TAVI and patients with NAVR treated with surgical aortic valve replacement(SAVR)at Tongji Hospital,Tongji Medical College,Huazhong University of Science and Technology,China,from March 2019 to September 2024 were selected,and clinical data on baseline,perioperative,and primary endpoint events were were retrospectively collected and compared.Results Forty-three patients with NAVR were treated with TAVI,with a device success rate of 86.0％and a surgical success rate of 95.3％.Subgroup comparisons:(1)NAVR-TAVI group than NAVR-SAVR group:patients in the TAVI group had a significantly shorter operative time than those in the SAVR group(P＜0.001);complete left bundle branch block was more likely to occur after TAVI(P=0.042),and complete right bundle branch block was more likely to occur after SAVR(P=0.044).SAVR postoperatively The incidence of congestive heart failure was higher(P=0.013),and the mortality rate was significantly higher in the SAVR group than in the TAVI group(P=0.019).(2)NAVR-TAVI group than AS-TAVI group:the differences in access selection,THV size[28(22,34)mm vs.24(22,32)mm,P=0.044]and proportion of THV overdiameter[14％(7％,20％)vs.7％(3％,11％),P＜0.001]were statistically significant.patients in AS and NAVR groups had 1 case of permanent pacing after TAVI treatment.In the AS and NAVR groups,there was 1 case of permanent pacemaker implantation after TAVI.2 patients in the AS group were converted to surgical treatment,and 6 patients died.Conclusions The use of"off-label"(transfemoral)and"on-label"(transapical)TAVI devices(both from domestic sources)is safer than SAVR for the treatment of NAVR,especially in elderly and high-risk patients.Compared with patients with AS treated with TAVI,larger diameter annulas are usually selected for NAVR,with higher rates of valve migration,but overall safety and efficacy are comparable to AS.

Objective:To understand the changes in the experience of dietary behavior compliance management in middle-aged and young adults with newly diagnosed type 2 diabetes (T2DM) and provide strategies for healthcare professionals to manage patients' long-term dietary compliance.Methods:A longitudinal qualitative study design was used. Purposeful sampling was conducted to select 16 middle-aged and young adult patients diagnosed with T2DM at the Department of Endocrinology, the Affiliated Huaian No. 1 Hospital of Nanjing Medical University, from January to May 2024. Semi-structured interviews were conducted, and data was analyzed cross-sectionally and longitudinally.Results:A total of 3 main themes and nine sub-themes were identified: emotional changes in dietary compliance (negative emotional experiences, positive emotional coping, and emotional fluctuations transformation) ; management experience of dietary compliance (gradual adaptation to dietary management, disruption of daily eating routine, and lack of family decision-making support) ; diverse support needs for dietary compliance (needs for knowledge and information support, peer and decision-making support, and continuity of care management system) .Conclusions:The experience of dietary behavior compliance management in middle-aged and young adults with T2DM is a continuous, dynamic, and fluctuating process. Healthcare professionals can develop targeted interventions based on patients' real situations and management experiences to improve their compliance levels.

Objective:To understand the changes in the experience of dietary behavior compliance management in middle-aged and young adults with newly diagnosed type 2 diabetes (T2DM) and provide strategies for healthcare professionals to manage patients' long-term dietary compliance.Methods:A longitudinal qualitative study design was used. Purposeful sampling was conducted to select 16 middle-aged and young adult patients diagnosed with T2DM at the Department of Endocrinology, the Affiliated Huaian No. 1 Hospital of Nanjing Medical University, from January to May 2024. Semi-structured interviews were conducted, and data was analyzed cross-sectionally and longitudinally.Results:A total of 3 main themes and nine sub-themes were identified: emotional changes in dietary compliance (negative emotional experiences, positive emotional coping, and emotional fluctuations transformation) ; management experience of dietary compliance (gradual adaptation to dietary management, disruption of daily eating routine, and lack of family decision-making support) ; diverse support needs for dietary compliance (needs for knowledge and information support, peer and decision-making support, and continuity of care management system) .Conclusions:The experience of dietary behavior compliance management in middle-aged and young adults with T2DM is a continuous, dynamic, and fluctuating process. Healthcare professionals can develop targeted interventions based on patients' real situations and management experiences to improve their compliance levels.

Objective To investigate the anatomical and microscopic structures of interstitial fluid flow channels in the skin tissue of hand dorsum in human cadavers.Methods Totally 7 fresh cadavers within 12 hours post-mortem were included.MRI was used to observe the distribution of interstitial fluid flow from the first phalanx of the fingers to the wrist,precisely locating the flow channels.Based on imaging results,histological analyses were conducted to determine the histological characteristics of the flow channels.Furthermore,multi-immunofluorescence and microcomputed tomography(Micro-CT)techniques were employed to analyze the channels,and image post-processing was used to elucidate their anatomical structures at the microscopic level.Results After injecting a contrast agent into the first phalanx of ten finger specimens and applying repeated pressure,MRI image revealed centripetal long-range interstitial fluid flow along channels distinct from blood vessels and lymphatic vessels.Histological analysis and Micro-CT further confirmed that the flow primarily occurred within the fibrous connective tissue and adventitia of the skin.Conclusion The orderly fibrous connective tissue and adventitia in the skin form the interstitial fluid flow channels in the human hand dorsum skin,named as"stromal membrane channels"in the skin.

Objective:To study the impact of early blood concentrations of tacrolimus on the survival of patients after liver transplantation.Methods:Clinical data of 159 patients with liver diseases undergoing classic orthotopic liver transplantation at the Department of Hepatobiliary Surgery, the 900th Hospital of the Joint Logistics Support Force between January 2010 and December 2019 were retrospectively analyzed, including 123 males and 36 females, aged (48.0±12.2) years. According to survival status, patients were divided into the surviving group ( n=108) and death group ( n=51). Inverse probability of treatment weighting (IPTW) was applied to adjust for confounding factors by weighting covariates between the two groups. Univariate and multivariate Cox regression analysis were used to examine the relationship between early tacrolimus concentrations and mortality, and restrict cubic spline (RCS) curves were employed to assess the nonlinear relationship further. Results:After IPTW weighting, multivariate Cox regression analysis indicated that early tacrolimus concentration ( HR=2.479, 95% CI: 1.354-4.537, P<0.001) and preoperative international normalized ratio ( HR=0.358, 95% CI: 0.162-0.792, P=0.011) levels were risk factors for post-transplant survival. The RCS curve revealed that the optimal thresholds for early tacrolimus concentration were 6.30 ng/ml and 8.28 ng/ml ( P<0.001). Patients were therefore divided into the optimal concentration group ( n=60) and the non-optimal concentration group ( n=99). After IPTW weighting, the optimal concentration group comprised 102 cases, and the non-optimal concentration group included 212 cases. The 1-year, 3-year and 5-year survival rates in the optimal concentration group and the non-optimal concentration group were 97.06%, 81.37% and 75.49%, and 86.32%, 64.62% and 50.94%, respecitvely ( χ2=8.37, P<0.001). Conclusion:Early tacrolimus concentration is an independent risk factor for post-transplant survival. A tacrolimus concentration >8.28 ng/ml or <6.30 ng/ml is associated with a relatively higher mortality rate.