Objective:This study aims to explore the risk factors of Multi-center Investigator-Initiated Clinical Trials (MIITs), and provide a basis for developing study management strategies.Methods:The original draft of MIIT risk evaluation factors was determined through literature analysis and internal discussions of the research group. Thirty five experts were consulted using the Delphi method, and then the MIIT risk evaluation elements were finally determined. Analytic Hierarchy Process (AHP) was used to calculate the weights of each index.Results:The recovery rates of both rounds of expert consultation were 100%, and the degree of expert authority was 0.856. The study ultimately formed an MIIT risk evaluation framework consisting of three first-class indexes, twelve second-class indexes, and thirty-eight third-class indexes. The weight values of the first-class indexes (start-up period, implementation period, and summary period) were 0.209 8, 0.710 6, and 0.079 6, respectively. Meanwhile, the weight values of the second-class indexes and third-class indexes were determined.Conclusions:Exploring the risk evaluation factors of MIIT provides valuable insights into identifying critical risk points, which, in turn, contributes to enhancing MIIT management efficiency, research progress, and quality.

Objective:This study aims to construct an evaluation index system suitable for the core competency of Clinical Research Coordinators (CRCs) in Investigator-Initiated Trials (IITs) in China.Methods:This study developed a system framework through the Onion Model, literature research, and expert interviews, utilized the Delphi method to build the index system. and analyzed the weight of each indicator through the Analytic Hierarchy Process (AHP).Results:Four first-level indicators were basic knowledge (0.143), job skills (0.300 8), professional quality (0.483 9), and personality traits (0.072 3). Besides, 18 second-level indicators and 49 third-level indicators were developed through the Delphi method. According to the third round expert′s consultation, the average scores of all indexes were >3.50, the authoritative coefficient was 0.86, the coefficient of variation of each index was <0.30, and Kendall coefficients of concordance were 0.183~0.366 ( P<0.001). The consistency ratios of single-sort were<0.1, and the overall sort of all indexes was 0.043 7, which showed good logical reliability. Conclusions:This evaluation index system for Clinical Research Coordinators is of great scientific sense. It provides IIT-conducting investigators in institutions with a proficient assessment tool to help them find qualified and reliable CRCs.

Objective To analyze the distribution and drug resistance patterns of pathogenic bacteria in bile and blood cultures obtained from patients with biliary stones accompanied by acute biliary tract infection,to evaluate the clinical appropriate-ness of antibiotic use based on drug sensitivity results,and to provide evidence for empirical antibiotic treatment in such patients.Methods The clinical data of 161 patients with biliary calculi complicated by acute biliary tract infection who were admitted to the First People's Hospital of Neijiang from 2017 to 2023 were retrospectively analyzed.The results of microbial culture,drug sensitivity analysis,and patient characteristics were assessed to evaluate the appropriateness of clinical antimicrobial therapy.Results Among the 161 patients with positive cultures,212 strains of pathogenic bacteria were detected.The predominant patho-gens were Escherichia coli,Klebsiella pneumoniae subspecies,and Enterococcus faecium.Age and underlying diseases significantly affected the distribution of Escherichia coli and Klebsiella pneumoniae subspecies.Within the gram-negative bacterial group,Esche-richia coli and Klebsiella pneumoniae subspecies exhibited higher drug resistance to commonly used broad-spectrum penicillin,third-generation cephalosporin and quinolones but lower resistance rates to piperacillin and tazobactam;furthermore,elderly indi-viduals aged ≥65 years showed higher resistance rates to ceftriaxone than those under age 65 while people with drug exposure history had higher ceftazidime resistance rates that were statistically significant.In contrast to Enterococcus faecalis which displayed low antimicrobial resistance rates for most drugs tested in this study,Enterococcus faecium demonstrated high levels of antibiotic resistance;however,both Enterococcus faecalis and Enterococcus faecium exhibited zero-resistance rates against vancomycin and tigecycline although this may be attributed to their small sample size in our study cohort.Finally,we found that empirical anti-in-fective drugs,as well as target anti-infective drugs,were not prescribed rationally among these patients due mainly to inappropriate combinations of antibiotics or incorrect dosages.Conclusions The predominant pathogens in patients with acute biliary tract infection are gram-negative bacteria,Gram-positive bacteria,and fungi;however,the potential involvement of anaerobic bacteria should not be overlooked.Vancomycin exhibits sensitivity against gram-positive bacteria,yet the overall rationality of antibiotic usage remains suboptimal.Enhanced clinical testing for pathogenic microorganisms is imperative in the management of biliary stones accompanied by acute biliary tract infection.In contrast,clinical pharmacists should provide comprehensive training on anti-infective drugs to clinicians to facilitate their judicious selection of antibiotics based on drug sensitivity results and prevent the e-mergence of multidrug-resistant bacteria.

Objective To analyze the distribution and drug resistance patterns of pathogenic bacteria in bile and blood cultures obtained from patients with biliary stones accompanied by acute biliary tract infection,to evaluate the clinical appropriate-ness of antibiotic use based on drug sensitivity results,and to provide evidence for empirical antibiotic treatment in such patients.Methods The clinical data of 161 patients with biliary calculi complicated by acute biliary tract infection who were admitted to the First People's Hospital of Neijiang from 2017 to 2023 were retrospectively analyzed.The results of microbial culture,drug sensitivity analysis,and patient characteristics were assessed to evaluate the appropriateness of clinical antimicrobial therapy.Results Among the 161 patients with positive cultures,212 strains of pathogenic bacteria were detected.The predominant patho-gens were Escherichia coli,Klebsiella pneumoniae subspecies,and Enterococcus faecium.Age and underlying diseases significantly affected the distribution of Escherichia coli and Klebsiella pneumoniae subspecies.Within the gram-negative bacterial group,Esche-richia coli and Klebsiella pneumoniae subspecies exhibited higher drug resistance to commonly used broad-spectrum penicillin,third-generation cephalosporin and quinolones but lower resistance rates to piperacillin and tazobactam;furthermore,elderly indi-viduals aged ≥65 years showed higher resistance rates to ceftriaxone than those under age 65 while people with drug exposure history had higher ceftazidime resistance rates that were statistically significant.In contrast to Enterococcus faecalis which displayed low antimicrobial resistance rates for most drugs tested in this study,Enterococcus faecium demonstrated high levels of antibiotic resistance;however,both Enterococcus faecalis and Enterococcus faecium exhibited zero-resistance rates against vancomycin and tigecycline although this may be attributed to their small sample size in our study cohort.Finally,we found that empirical anti-in-fective drugs,as well as target anti-infective drugs,were not prescribed rationally among these patients due mainly to inappropriate combinations of antibiotics or incorrect dosages.Conclusions The predominant pathogens in patients with acute biliary tract infection are gram-negative bacteria,Gram-positive bacteria,and fungi;however,the potential involvement of anaerobic bacteria should not be overlooked.Vancomycin exhibits sensitivity against gram-positive bacteria,yet the overall rationality of antibiotic usage remains suboptimal.Enhanced clinical testing for pathogenic microorganisms is imperative in the management of biliary stones accompanied by acute biliary tract infection.In contrast,clinical pharmacists should provide comprehensive training on anti-infective drugs to clinicians to facilitate their judicious selection of antibiotics based on drug sensitivity results and prevent the e-mergence of multidrug-resistant bacteria.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

Objective:To investigate the prognostic value of deep learning-based automated quantification of tumor-stroma ratio (TSR) in patients undergoing neoadjuvant therapy (NAT) for breast cancer.Methods:Specimens were collected from 209 breast cancer patients who received NAT at Renmin Hospital of Wuhan University from October 2019 to June 2023. TSR levels in pre-NAT biopsy specimens were automatically computed using a deep learning algorithm and categorized into low stroma (TSR≤30%), intermediate stroma (TSR 30% to ≤60%), and high stroma (TSR>60%) groups. Residual cancer burden (RCB) grading of post-NAT surgical specimens was determined to compare the relationship between TSR expression levels and RCB grades. The correlation of TSR with NAT efficacy was analyzed, and the association between TSR expression and patient prognosis was further investigated.Results:There were 85 cases with low stroma (TSR≤30%), 93 cases with intermediate stroma (TSR 30% to ≤60%), and 31 cases with high stroma (TSR>60%). Different TSR expression levels showed significant differences between various RCB grades ( P<0.05). Logistic univariate and multivariate analyses showed that TSR was a risk factor for obtaining a complete pathological remission from neoadjuvant therapy for breast cancer when it was used as a continuous variable ( P<0.05); COX regression and survival analyses showed that the lower the percentage of tumorigenic mesenchyme was, the better the prognosis of the patient was ( P<0.05). Conclusions:The deep learning-based model enables automatic and accurate quantification of TSR. A lower pre-treatment tumoral stroma is associated with a lower RCB score and a higher rate of pathologic complete response, indicating that TSR can predict the efficacy of neoadjuvant therapy in breast cancer and thus holds prognostic significance. Therefore, TSR may serve as a biomarker for predicting therapeutic outcomes in breast cancer neoadjuvant therapy.

Objective:This study aims to explore the risk factors of Multi-center Investigator-Initiated Clinical Trials (MIITs), and provide a basis for developing study management strategies.Methods:The original draft of MIIT risk evaluation factors was determined through literature analysis and internal discussions of the research group. Thirty five experts were consulted using the Delphi method, and then the MIIT risk evaluation elements were finally determined. Analytic Hierarchy Process (AHP) was used to calculate the weights of each index.Results:The recovery rates of both rounds of expert consultation were 100%, and the degree of expert authority was 0.856. The study ultimately formed an MIIT risk evaluation framework consisting of three first-class indexes, twelve second-class indexes, and thirty-eight third-class indexes. The weight values of the first-class indexes (start-up period, implementation period, and summary period) were 0.209 8, 0.710 6, and 0.079 6, respectively. Meanwhile, the weight values of the second-class indexes and third-class indexes were determined.Conclusions:Exploring the risk evaluation factors of MIIT provides valuable insights into identifying critical risk points, which, in turn, contributes to enhancing MIIT management efficiency, research progress, and quality.

Objective:This study aims to construct an evaluation index system suitable for the core competency of Clinical Research Coordinators (CRCs) in Investigator-Initiated Trials (IITs) in China.Methods:This study developed a system framework through the Onion Model, literature research, and expert interviews, utilized the Delphi method to build the index system. and analyzed the weight of each indicator through the Analytic Hierarchy Process (AHP).Results:Four first-level indicators were basic knowledge (0.143), job skills (0.300 8), professional quality (0.483 9), and personality traits (0.072 3). Besides, 18 second-level indicators and 49 third-level indicators were developed through the Delphi method. According to the third round expert′s consultation, the average scores of all indexes were >3.50, the authoritative coefficient was 0.86, the coefficient of variation of each index was <0.30, and Kendall coefficients of concordance were 0.183~0.366 ( P<0.001). The consistency ratios of single-sort were<0.1, and the overall sort of all indexes was 0.043 7, which showed good logical reliability. Conclusions:This evaluation index system for Clinical Research Coordinators is of great scientific sense. It provides IIT-conducting investigators in institutions with a proficient assessment tool to help them find qualified and reliable CRCs.

Objective To investigate the distribution and antibiotic resistance profiles of the bacterial strains isolated from urine samples in a tertiary Traditional Chinese Medicine hospital in Shanghai in the 12-year period from 2010 through 2021 for better empirical antibiotic use in clinical practice.Methods The clinical data of patients with urinary tract infection,including the species and antibiotic resistance of the bacterial strains isolated from urine samples from January 2010 to December 2021 were retrospectively analyzed.Results A total of 5 231 nondupliate bacterial strains were isolated,among which E.coli was the most common(52.8％),followed by Enterococcus spp(19.1％)and Klebsiella spp(11.1％).Most of the urinary isolates(76.0％)were isolated from the elderly aged 60-89,and only 3.1％of the strains were isolated from the young people aged under 44.Most of the bacterial strains were isolated from female patients(75.8％),however,more P.aeruginosa and A.baumannii were isolated from male patients compared to female patients(55.3％vs 44.7％and 67.7％vs 32.3％).About 13.7％of the strains were collected from the Department of Nephrology,more than the strains from any other clincial department.In intensive care unit(ICU),the proportion of E.coli was the lowest,while the proportion of Enterococcus spp was the highest.Enterobacterales showed lower resistance raets to carbapenems,cephamycin,amikacin,cefepime,and β-lactam/β-lactamase inhibitor combinations.P.aeruginosa showed higher susceptibility rates to carbapenems,aminoglycosides and β-lactam/β-lactamase inhibitor combinations compared to A.baumannii(≥54.6％vs≤39.8％).Gram-positive cocci were highly sensitive to glycopeptide antibiotics.No SS.aureus or E.faecalis isolates were found resistant to vancomycin.About 2.7％of the E.faecium isolates were resistant to vancomycin.The prevalence of drug-resistant bacteria was the highest in elderly patients,and in the strains isolated from ICU and emergency department.Conclusions Compared with general hospitals,a high proportion of elderly patients were treated in this hospital.It should be more cautious in the treatment of patients with urinary tract infection.The major bacterial species isolated from urine were E.coli,Enterococcus,and K.pneumoniae.Empirical treatment should be prescribed considering patient age and gender as well as the species and distribution of pathogenic bacteria.Urine culture and antibiotic susceptibility testing should be performed proactively.Appropriate antimicrobial agents should be selected according to the results of antimicrobial susceptibility testing.Antimicrobial ressitance surveillance should also be strengthened.

Objective:The incidence of infections in patients with malignant hematologic diseases is extremely high and significantly affects their prognosis.Identifying early and precise biomarkers for infection is crucial for guiding the treatment of infections in these patients.Previous studies have shown that procalcitonin(PCT)can serve as an early diagnostic marker for bloodstream infections in patients with malignant hematologic diseases.This study aims to compare serum PCT levels in these patients with different pathogens,disease types,infection sites,and severity levels. Methods:Clinical data and laboratory results of infected patients with malignant hematologic diseases treated at the Department of Hematology,the Third Xiangya Hospital of Central South University from January 2018 to August 2023 were collected.General patient information was retrospectively analyzed.Serum PCT levels were compared among patients with different pathogens,types of malignant hematologic diseases,infection sites,and infection severity;Receiver operator characteristic(ROC)curves were used to determine the cut-off values and diagnostic value of serum PCT levels in diagnosing bloodstream infections versus local infections and severe infections versus non-severe infections.Mortality rates after 4-7 days of anti-infective treatment were compared among groups with rising,falling,and unchanged PCT levels. Results:A total of 526 patients with malignant hematologic diseases were included.The main pathogens were Gram-negative bacteria(272 cases,51.7%),followed by Gram-positive bacteria(120 cases,22.8%),fungi(65 cases,12.4%),viruses(23 cases,4.4%),and mixed pathogens(46 cases,8.7%).The main types of malignant hematologic diseases were acute myeloid leukemia(216 cases,41.1%),acute lymphoblastic leukemia(107 cases,20.3%),and lymphoma(93 cases,17.7%).Granulocyte deficiency was present in 68.3%(359 cases)of the patients during infection,with severe infection in 24.1%(127 cases).Significant differences in serum PCT levels were found among patients with different types of pathogens(P<0.001),with the highest levels in Gram-negative bacterial infections.Significant differences in serum PCT levels were also found among patients with different types of malignant hematologic diseases(P<0.05),with the highest levels in lymphoma patients.Serum PCT levels were significantly higher in systemic infections and severe infections compared to local infections and non-severe infections(both P<0.001).ROC curve analysis showed that the cut-off values for diagnosing bloodstream infections and severe infections were 0.22 and 0.28 ng/mL,with areas under the curve of 0.670 and 0.673,respectively.After 4-7 days of anti-infective treatment,the mortality rates of the PCT declining,PCT unchanged,and PCT rising groups were 11.9%,21.2%,and 35.7%,respectively,and pairwise comparisons were statistically significant(all P<0.05). Conclusion:PCT can be used as an auxiliary indicator for early identification of different pathogens,infection sites,and severity levels in patients with malignant hematologic diseases combined with infections.Dynamic monitoring of PCT levels after empirical antibiotic treatment provides important guidance for assessing patient's prognosis.