Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

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 investigate the brain iron status in the sensorimotor cortex of patients with chronic low back pain (CLBP) and its relationship with changes in resting-state functional connectivity (RS-FC).Methods:This was a cross-sectional study. Thirty-two patients with CLBP (CLBP group) who were treated at Wuxi People′s Hospital Affiliated to Nanjing Medical University from July 2023 to March 2024 and 30 age-and gender-matched healthy volunteers (control group) were prospectively included. All subjects underwent pain and neuropsychological assessments and head MRI examinations, including conventional sequences, quantitative susceptibility mapping (QSM), and blood oxygen level-dependent (BOLD) functional MRI. QSM values of the sensorimotor cortex and the left middle frontal gyrus, right inferior temporal gyrus, right olfactory cortex, and right posterior cingulate gyrus were extracted using the ANTs toolkit. The bilateral postcentral gyrus and posterior portion of the bilateral precentral gyrus in the sensorimotor cortex were selected as seed points using SPM software to extract the average time series of BOLD signals and evaluate the changes in RS-FC values with other brain regions. Two-sample t-tests were used to compare the differences in QSM values and RS-FC values between the two groups. Pearson correlation analysis was used to analyze the correlation between iron deposition in key brain regions and RS-FC values and clinical scale scores. Results:The QSM values in the posterior portion of the bilateral precentral gyrus and the left postcentral gyrus in the CLBP group were significantly higher than those in the control group ( t=2.17, P=0.009; t=4.44, P<0.001), and the QSM value in the left postcentral gyrus was positively correlated with pain-related scale scores ( P<0.05). Compared with the control group, the QSM values in the left orbital part of the middle frontal gyrus ( t=2.22, P=0.031) and the right inferior temporal gyrus ( t=2.98, P=0.004) were increased, while the QSM values in the right olfactory cortex ( t=2.54, P=0.014) and the right posterior cingulate gyrus ( t=2.70, P=0.009) were decreased in the CLBP group. Compared with the control group, the RS-FC values between the left postcentral gyrus, the posterior part of the bilateral precentral gyrus, and the left superior frontal gyrus were increased in the CLBP group ( P<0.001), the RS-FC value between the right postcentral gyrus and the right precuneus was increased ( P<0.001). The RS-FC of the bilateral motor cortex and the left dorsolateral superior frontal gyrus was positively correlated with the QSM values of the bilateral motor cortex ( r=0.444, P=0.015). Conclusion:Iron deposition in the sensorimotor cortex (posterior portion of the bilateral precentral gyrus and the left postcentral gyrus) is increased in CLBP patients and is correlated with abnormal functional connectivity within and between brain regions.

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 develop and implement a drug treatment pathway for the initial treatment of diffuse large B-cell lymphoma(DLBCL)and to provide a foundation for refined medication use and cost control management under the Diagnosis Related Groups(DRG)payment system.Methods Clinical pharmacists collaborated to develop a drug treatment pathway for the initial treatment of DLBCL,utilizing evidence-based medicine and evidence-based pharmacy principles.The PDCA(Plan-Do-Check-Act)cycle method was employed for administrative intervention.The hematology department served as a pilot unit to assess the impact on economic indicators,including inpatient costs,drug expenses,and DRG payment balance,as well as treatment efficacy and the incidence of adverse reactions.Results Compared to the control group,the RG13 intervention group exhibited a significant reduction in average total hospitalization costs and drug expenses,along with a decreased DRG payment balance deficits.All differences were statistically significant(P＜0.05).Conclusion The development and implementation of a drug treatment pathway for the initial treatment of DLBCL can effectively reduce treatment costs,prevent DRG overspending,and alleviate the economic burden on patients,while ensuring the safety and effectiveness of the treatment.

Objective To investigate the risk factors associated with perioperative hemodynamic disorders(HD)following carotid artery stenting(CAS)for carotid sinus stenosis.Methods The clinical data of 71 patients who underwent CAS for carotid sinus stenosis were retrospectively analyzed.The patients were divided into the HD group(20 cases)and the non-HD group(51 cases)based on the occurrence of HD,and inter-group comparisons along with binary logistic regression analysis were performed.All patients underwent carotid computed tomography angiography(CTA)prior to surgery.Results In the HD group,the duration of dopamine usage ranged from 9 to 71 hours,the mean age was(73.90±5.24)years old(P=0.038),and the average length of hospital stay was(9.60±3.63)days(P＜0.001).Univariate logistic regression analysis revealed that plaque calcification(P=0.035),annular calcification(P＜0.001),plaque length(P=0.012),and the degree of stenosis(P=0.014)were associated with perioperative HD after CAS.Multivariate logistic regression analysis identified annular calcification and plaque length as independent predictors of perioperative HD(P＜0.05).Conclusion Age,plaque calcification,annular calcification,plaque length,and the degree of stenosis are closely associated with the occurrence of perioperative HD after CAS in patients with carotid sinus stenosis.Annular calcification and plaque length are independent risk factors for the occurrence of HD.

Objective To develop and implement a drug treatment pathway for the initial treatment of diffuse large B-cell lymphoma(DLBCL)and to provide a foundation for refined medication use and cost control management under the Diagnosis Related Groups(DRG)payment system.Methods Clinical pharmacists collaborated to develop a drug treatment pathway for the initial treatment of DLBCL,utilizing evidence-based medicine and evidence-based pharmacy principles.The PDCA(Plan-Do-Check-Act)cycle method was employed for administrative intervention.The hematology department served as a pilot unit to assess the impact on economic indicators,including inpatient costs,drug expenses,and DRG payment balance,as well as treatment efficacy and the incidence of adverse reactions.Results Compared to the control group,the RG13 intervention group exhibited a significant reduction in average total hospitalization costs and drug expenses,along with a decreased DRG payment balance deficits.All differences were statistically significant(P＜0.05).Conclusion The development and implementation of a drug treatment pathway for the initial treatment of DLBCL can effectively reduce treatment costs,prevent DRG overspending,and alleviate the economic burden on patients,while ensuring the safety and effectiveness of the treatment.

Objective To investigate the risk factors associated with perioperative hemodynamic disorders(HD)following carotid artery stenting(CAS)for carotid sinus stenosis.Methods The clinical data of 71 patients who underwent CAS for carotid sinus stenosis were retrospectively analyzed.The patients were divided into the HD group(20 cases)and the non-HD group(51 cases)based on the occurrence of HD,and inter-group comparisons along with binary logistic regression analysis were performed.All patients underwent carotid computed tomography angiography(CTA)prior to surgery.Results In the HD group,the duration of dopamine usage ranged from 9 to 71 hours,the mean age was(73.90±5.24)years old(P=0.038),and the average length of hospital stay was(9.60±3.63)days(P＜0.001).Univariate logistic regression analysis revealed that plaque calcification(P=0.035),annular calcification(P＜0.001),plaque length(P=0.012),and the degree of stenosis(P=0.014)were associated with perioperative HD after CAS.Multivariate logistic regression analysis identified annular calcification and plaque length as independent predictors of perioperative HD(P＜0.05).Conclusion Age,plaque calcification,annular calcification,plaque length,and the degree of stenosis are closely associated with the occurrence of perioperative HD after CAS in patients with carotid sinus stenosis.Annular calcification and plaque length are independent risk factors for the occurrence of HD.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

Objective To observe the predictive factors of poor prognosis in patients with acute basilar artery occlusion(BAO)who got first-pass effect(FPE)after mechanical thrombectomy(MT).Methods Eighty-two acute BAO patients who got FPE following MT were retrospectively collected and divided into good prognosis group(modified Rankin scale[mRS]score≤3,n=48)and poor prognosis group(mRS score＞3,n=34)90 days after treatments.The data were compared between groups,and variables which showed P＜0.1 were included in multivariate logistic regression analysis to identify independent predictors of poor prognosis in acute BAO patients who got FPE after MT.Results Higher age of patients,pre-treatment National Institute Health stroke scale(NIHSS)and neutrophil-to-lymphocyte ratio(NLR),also higher proportions of patients with diabetes mellitus,atrial fibrillation(AF)and cardioembolic stroke in trial of org 10 172 in acute stroke treatment(TOAST)classification were found in poor prognosis group than those in good prognosis group(all P＜0.05).Conversely,patients in poor prognosis group had lower pre-treatment Glasgow coma scale(GCS)scores,lower posterior circulation-Alberta stroke program early CT score(pc-ASPECTS)and basilar artery on CT angiography(BATMAN)scores(all P＜0.05).Multivariate logistic regression analysis revealed patients complicated with AF(OR[95%CI]=29.769[1.470,602.943])and elevated pre-treatment NLR(OR[95%CI]=1.212[1.016,1.446])had relatively poor prognosis(both P＜0.05),whereas those with increased pre-treatment GCS score(OR[95%CI]=0.615[0.429,0.882]),elevated pc-ASPECTS(OR[95%CI]=0.263[0.092,0.748])and higher BATMAN score(OR[95%CI]=0.260[0.085,0.796])had relatively better prognosis(all P＜0.05).Conclusion Complicated with AF,low pre-treatment GCS score,high NLR,low pc-ASPECTS and low BATMAN score were all predictive factors for poor prognosis in acute BAO patients who got FPE after MT.