Objective To construct a nursing follow-up checklist for patients undergoing autologous hematopoietic stem cell transplantation,providing a basis for postoperative follow-up care.Methods Using evidence-based methods,the literature from major guide websites and databases using Chinese and English search terms was retrieved,and their quality was evaluated.The relevant items were extracted,and a first draft was formed.15 experts were selected in relevant fields from 14 tertiary hospitals in 13 provinces,cities,and autonomous regions across the country for Delphi inquiry.The nursing follow-up checklist was revised again based on expert opinions and clinical practice.The nursing follow-up checklist was initially applied and then revised again to form the final draft.Results 15 experts include 12 undergraduate and 3 master's degree holders.The positivity coefficients of the 2 rounds of inquiry were 100％;the authority coefficients of the experts were 0.815;the Kendall coefficients were 0.119 and 0.144,respectively;the differences were statistically significant(P＜0.001).The final nursing follow-up checklist was formed,which includes 6 primary indicators,including physiological status,psychological status,social and family support,living conditions,disease knowledge,and laboratory tests.19 patients(95％)found the follow-up content to be comprehensive.The follow-up nurses's satisfaction rate exceeded 85％.There were 27 secondary indicators and 61 tertiary indicators,with coefficients of variation of all indicators less than 0.25.Conclusion The nursing follow-up checklist is scientific,reliable,and practical,which can provide a basis for clinical nursing staff to follow up and comprehensively manage patients after autologous hematopoietic stem cell transplantation.

Objective To construct a nursing follow-up checklist for patients undergoing autologous hematopoietic stem cell transplantation,providing a basis for postoperative follow-up care.Methods Using evidence-based methods,the literature from major guide websites and databases using Chinese and English search terms was retrieved,and their quality was evaluated.The relevant items were extracted,and a first draft was formed.15 experts were selected in relevant fields from 14 tertiary hospitals in 13 provinces,cities,and autonomous regions across the country for Delphi inquiry.The nursing follow-up checklist was revised again based on expert opinions and clinical practice.The nursing follow-up checklist was initially applied and then revised again to form the final draft.Results 15 experts include 12 undergraduate and 3 master's degree holders.The positivity coefficients of the 2 rounds of inquiry were 100％;the authority coefficients of the experts were 0.815;the Kendall coefficients were 0.119 and 0.144,respectively;the differences were statistically significant(P＜0.001).The final nursing follow-up checklist was formed,which includes 6 primary indicators,including physiological status,psychological status,social and family support,living conditions,disease knowledge,and laboratory tests.19 patients(95％)found the follow-up content to be comprehensive.The follow-up nurses's satisfaction rate exceeded 85％.There were 27 secondary indicators and 61 tertiary indicators,with coefficients of variation of all indicators less than 0.25.Conclusion The nursing follow-up checklist is scientific,reliable,and practical,which can provide a basis for clinical nursing staff to follow up and comprehensively manage patients after autologous hematopoietic stem cell transplantation.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective To construct a model for predicting the risk of essential hypertension accompanied by left ventricular hypertrophy using machine learning algorithms based on pulse diagram parameters;To explore its clinical application value.Methods A total of 295 patients with essential hypertension who were hospitalized in Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai Hospital of Traditional Chinese Medicine and Shanghai Hospital of Integrated Traditional Chinese and Western Medicine were selected from July 2020 to May 2021 and July 2023 to July 2024.According to the echocardiographic results,the selected research subjects were divided into the essential hypertension with left ventricular hypertrophy group(referred to as the"LVH group")and the essential hypertension without left ventricular hypertrophy group(referred to as the"non-LVH group").The general data and clinical biochemical indicators were collected,and the pulse diagram parameters of the patients were detected using the SMART-I type TCM digital pulse analyzer.A clinical prediction model was constructed based on decision tree,support vector machine and extreme gradient boosting model algorithms.The predictive performance of the model was evaluated in terms of discrimination,calibration and clinical prediction ability by using the receiver operating characteristic(ROC)curve,calibration curve and decision curve analysis respectively.The influence of each predictive factor on the risk of LVH in essential hypertension was explained based on the SHAP algorithm.Results Compared with the non-LVH group,the BMI,the proportion of males,drinkers and smokers was lower in the LVH group,with statistical significance(P<0.05);the thickened ventricular wall,left ventricular internal dimension enlargement,left common carotid artery intima-media thickness and high density lipoprotein cholesterol were higher in the LVH group than in the non-LVH group(P<0.05);the left common carotid peak systolic velocity,left common carotid resistance index,serum uric acid and serum creatinine were lower in the LVH group than in the non-LVH group(P<0.05).The pulse diagram parameters T4,T,W1,W2,H3/H1 and H4/H1 were higher in the LVH group than in the non-LVH group(P<0.05).The areas of the ROC curves of the models constructed by the three types of machine learning algorithms were 0.887,0.962 and 0.873 respectively,indicating that the model had good discrimination and certain diagnostic efficacy.The calibration curve suggested that the prediction accuracy of the model was average;the clinical decision curve showed that XGBoost model has a higher net benefit.Conclusion The interpretable model constructed based on pulse diagram parameters and machine learning algorithms can be used as a reliable tool for predicting the risk of essential hypertension with LVH.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0％ were gram-positive and 71.0％ were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6％,81.9％ and 78.5％,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9％ of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4％ of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1％ in the isolates from children and and 95.9％ in the isolates from adults.The resistance rate to carbapenems was lower than 15.0％ for most Enterobacterales species except for Klebsiella,22.5％ and 23.6％ of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6％ to 10.0％.The resistance rate to imipenem and meropenem was 21.9％ and 17.4％ for Pseudomonas aeruginosa,respectively,and 67.5％ and 68.1％ for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in healthcare facilities in major regions of China in 2023.Methods Clinical isolates collected from 73 hospitals across China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2023 Clinical & Laboratory Standards Institute (CLSI) breakpoints.Results A total of 445199 clinical isolates were collected in 2023,of which 29.0％ were gram-positive and 71.0％ were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species (excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi) (MRSA,MRSE and MRCNS) was 29.6％,81.9％ and 78.5％,respectively.Methicillin-resistant strains showed significantly higher resistance rates to most antimicrobial agents than methicillin-susceptible strains (MSSA,MSSE and MSCNS).Overall,92.9％ of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 91.4％ of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis had significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 93.1％ in the isolates from children and and 95.9％ in the isolates from adults.The resistance rate to carbapenems was lower than 15.0％ for most Enterobacterales species except for Klebsiella,22.5％ and 23.6％ of which were resistant to imipenem and meropenem,respectively .Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.6％ to 10.0％.The resistance rate to imipenem and meropenem was 21.9％ and 17.4％ for Pseudomonas aeruginosa,respectively,and 67.5％ and 68.1％ for Acinetobacter baumannii,respectively.Conclusions Increasing resistance to the commonly used antimicrobial agents is still observed in clinical bacterial isolates.However,the prevalence of important crabapenem-resistant organisms such as crabapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a slightly decreasing trend.This finding suggests that strengthening bacterial resistance surveillance and multidisciplinary linkage are important for preventing the occurrence and development of bacterial resistance.

By combing the development of tongue image,this paper analyzes the image features,advantages and disadvantages of different stages,and makes it clear that tongue image is an important carrier of clinical information of tongue diagnosis.It has been regarded as an important way to understand tongue image since the first monograph on tongue diagnosis.The article also analyzes the formation and development of modern digital and standardized tongue image,and explains the role and value of tongue image in the development of TCM tongue diagnosis terminology,providing reference for the formulation of international standards of TCM diagnosis terminology and the consensus reached by international experts.

Objective: To investigate the expression discordances of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor2 (HER-2) and Ki-67 in primary and metastatic breast cancer specimens and explore the clinical significances. Methods: Biopsies of metastatic lesions were performed in 203 patients with breast cancer recurrence and metastasis indicated by physical examination and/or imaging examination. We confirmed pathological properties and assessed the expressions of ER, PR, HER-2 and Ki-67 in primary and metastatic lesions, their relationships with prognosis were also analyzed. Results: Biopsy failed in 3 patients, the pathology and immunohistochemitry results of metastatic lesions were not obtained. One person was diagnosed as tuberculosis and another was primary lung cancer. Among the 198 cases of primary and metastatic lesions, the discordance rates of ER, PR, HER-2 and Ki-67 were 27.3%, 34.3%, 11.8% and 15.1%, respectively.The expressions of ER, HER-2 and Ki-67 were not significantly different between the primary and metastatic lesions, however, the expressions of PR were more likely to turn negative in the metastases (P<0.001). The disease-free survival (DFS) of patients with ER, PR positive, HER-2 negative and low expression of Ki-67 in metastatic lesion was much longer (P<0.05). Conclusions The expressions of ER, PR, HER-2 and Ki-67 in metastatic lesions are associated with the prognosis of breast cancer patients.Their expression discordances between primary and metastatic lesions can guide the treatment and evaluate the risks of recurrence and prognosis.

Objective To investigate the expression discordances of estrogen receptor ( ER), progesterone receptor (PR), human epidermal growth factor receptor2 ( HER?2) and Ki?67 in primary and metastatic breast cancer specimens and explore the clinical significances. Methods Biopsies of metastatic lesions were performed in 203 patients with breast cancer recurrence and metastasis indicated by physical examination and／or imaging examination. We confirmed pathological properties and assessed the expressions of ER, PR, HER?2 and Ki?67 in primary and metastatic lesions, their relationships with prognosis were also analyzed. Results Biopsy failed in 3 patients, the pathology and immunohistochemitry results of metastatic lesions were not obtained. One person was diagnosed as tuberculosis and another was primary lung cancer. Among the 198 cases of primary and metastatic lesions, the discordance rates of ER, PR, HER?2 and Ki?67 were 27.3%, 34.3%, 11.8% and 15.1%, respectively.The expressions of ER, HER?2 and Ki?67 were not significantly different between the primary and metastatic lesions, however, the expressions of PR were more likely to turn negative in the metastases (P＜0.001). The disease?free survival (DFS) of patients with ER, PR positive, HER?2 negative and low expression of Ki?67 in metastatic lesion was much longer ( P＜0.05). Conclusions The expressions of ER, PR, HER?2 and Ki?67 in metastatic lesions are associated with the prognosis of breast cancer patients.Their expression discordances between primary and metastatic lesions can guide the treatment and evaluate the risks of recurrence and prognosis.

Objective To investigate the expression discordances of estrogen receptor ( ER), progesterone receptor (PR), human epidermal growth factor receptor2 ( HER?2) and Ki?67 in primary and metastatic breast cancer specimens and explore the clinical significances. Methods Biopsies of metastatic lesions were performed in 203 patients with breast cancer recurrence and metastasis indicated by physical examination and／or imaging examination. We confirmed pathological properties and assessed the expressions of ER, PR, HER?2 and Ki?67 in primary and metastatic lesions, their relationships with prognosis were also analyzed. Results Biopsy failed in 3 patients, the pathology and immunohistochemitry results of metastatic lesions were not obtained. One person was diagnosed as tuberculosis and another was primary lung cancer. Among the 198 cases of primary and metastatic lesions, the discordance rates of ER, PR, HER?2 and Ki?67 were 27.3%, 34.3%, 11.8% and 15.1%, respectively.The expressions of ER, HER?2 and Ki?67 were not significantly different between the primary and metastatic lesions, however, the expressions of PR were more likely to turn negative in the metastases (P＜0.001). The disease?free survival (DFS) of patients with ER, PR positive, HER?2 negative and low expression of Ki?67 in metastatic lesion was much longer ( P＜0.05). Conclusions The expressions of ER, PR, HER?2 and Ki?67 in metastatic lesions are associated with the prognosis of breast cancer patients.Their expression discordances between primary and metastatic lesions can guide the treatment and evaluate the risks of recurrence and prognosis.