Objective To explore the differences and similarities in the changes of pulp repair response after direct pulp capping with iRoot BP Plus and MTA.Methods A total of 36 male SD rats were randomly divided into 3 groups,namely iRoot BP Plus group,MTA group and blank control group.Dental pulp exposure and direct pulp capping was performed on both sides of maxillary first molars of each rat.Four rats were randomly selected and sacrificed from each group at 7,14,and 28 days postoperatively,and the specimens were taken for hematoxylin-eosin(HE)staining,and then each index was observed.Results ①From the perspective of dentin tubular formation quality,at 14 d and 28 d,there were statistical differences between iRoot BP Plus group and MTA group(P＜0.05),and iRoot BP Plus was significantly better than MTA in terms of quality of restorative dentin formation.②At 14 days after operation,iRoot BP Plus had a greater area of neodontinin than that in MTA group(P＜0.05).Conclusion Both iRoot BP Plus and MTA can promote the formation of restorative dentin bridges after direct pulp capping,and the formation quality is high.The long-term effects need to be further studied.

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 explore the developmental trajectories of depression and their influencing factors among women conceiving through assisted reproductive technology (ART) from the beginning of the treatment cycle to late pregnancy.Methods:A convenience sampling method was used to recruit 863 women who successfully conceived through ART at the International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University between January 2017 and November 2019. Depressive symptoms were assessed using the Center for Epidemiological Studies Depression Scale (CES-D) at the beginning of the ART cycle (T1), early pregnancy (12-14 weeks, T2), mid-pregnancy (22-24 weeks, T3), and late pregnancy (32-34 weeks, T4). Group-based trajectory model was applied to identify developmental trajectories of antenatal depression, and multivariate Logistic regression was used to analyze influencing factors.Results:The detection rates of depressive symptoms among the 863 women conceiving through ART at T1, T2, T3, and T4 were 29.9% (258/863), 33.3% (287/863), 17.1% (148/863), and 19.8% (171/863), respectively. Three distinct trajectory groups were identified: persistently normal group (51.1%, 441/863), high-then-decreasing group (42.3%, 365/863), and persistently high-depression group (6.6%, 57/863). Multivariate Logistic regression analysis revealed that anxiety symptoms, sleep quality, spouse's age, passive smoking, and pre-pregnancy body mass index were significant influencing factors of the developmental trajectories of antenatal depression ( P<0.05) . Conclusions:Healthcare providers should pay close attention to antenatal depression in women conceiving through ART. Targeted interventions addressing the identified influencing factors should be developed to safeguard maternal and infant health.

Objective:To develop and validate a 30-day readmission risk prediction model for patients with chronic obstructive pulmonary disease (COPD) using multiple machine learning algorithms.Methods:Convenience sampling was used to select 1 450 COPD patients hospitalized at Tianjin Medical University General Hospital from January 2017 to December 2023 as study subjects. Twenty-nine variables associated with readmission were included. LASSO was used to screen for primary characteristic variables associated with 30-day readmission. The 1 450 patients were divided into a training set ( n=870) and a test set ( n=580) in a 6∶4 ratio. Ten machine learning methods, including random forest, AdaBoost, extreme radient Boosting (XGB), decision tree and so on, were used for model training and testing to identify the optimal prediction model. The optimal model and SHAP were employed to analyze key features and rank characteristic importance. Results:Among 1 450 COPD patients, the 30-day readmission rate was 24.48% (355/1 450). There were no significant differences in the general information between patients in test set and training set ( P>0.05). LASSO regression analysis identified seven variables with the highest predictive value, namely regular weekly exercise, hospital stay, mean arterial pressure, forced expiratory volume in one second/forced vital capacity (FEV1/FVC), C-reactive protein, body mass index, and medication adherence. Machine learning showed that in the training set, XGB had the highest area under the receiver operating characteristic curve ( AUC), sensitivity, and F1 score of 0.943, 0.926, and 0.930, respectively. In the test set, the AUC and accuracy of XGB were 0.882 and 0.858, respectively, and XGB's various scores showed that it had good generalization and predictive performance. XGB analysis showed that medication adherence, FEV1/FVC, and regular weekly exercise were negatively correlated with the 30-day readmission risk, while body mass index, C-reactive protein, mean arterial pressure, and hospital stay were positively correlated. The characteristics ranked in order of importance were medication adherence, body mass index, C-reactive protein, mean arterial pressure, FEV1/FVC, hospital stay and regular weekly exercise. Conclusions:The XGB model has strong predictive performance and good generalization ability, which can effectively predict the 30-day readmission risk of COPD patients, assist in clinical identification of high-risk patients, implement nursing interventions, and reduce readmission rates.

Objective:To summarize the tools and applications of functionality appreciation assessment.Methods:A computerized search was conducted in PubMed, Web of Science, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang Data, VIP, and China Biology Medicine disc for literature related to functionality appreciation assessment tools and their applications, with the time frame from database inception to May 12, 2024.Results:A total of 26 articles were included. Functionality appreciation was found to be associated with demographic, physiological, psychological, and social health factors. Functionality appreciation assessment tools demonstrated good psychometric properties across different cultural backgrounds and populations.Conclusions:Functionality appreciation exerts multidimensional benefits on physical and psychological health. However, the available functionality appreciation assessment tools are limited in variety. Future research should further explore the applicability of these tools in different populations in China.

OBJECTIVE To explore the implementation and standardized management of infection control core ele-ments in grass-roots medical institutions within county-level medical communities.METHODS From Mar.2024 to Apr.2024,the current status of implementation of infection control core elements in the grass-roots medical institu-tions within county-level medical communities was investigated by means of questionnaire survey and qualita-tive interview,and the implementation strategies were further explored.RESULTS The infection management or-ganizational system and functions of the two county-level medical institutions within the county medical communi-ties were completed,there is no independent hospital infection management department in the primary medical in-stitutions.The infection management personnel in the 16 grass-roots medical institutions were part-time person-nel,the personnel with the educational background below junior college accounted for 84.21％,the personnel with the professional background of nursing accounted for 100.00％,the personnel with less than 5 years of working experience accounted for 78.95％,none of them had an on-the-job training certificate.The monitoring programs of the county-level medical institutions within the county medical communities were completed,there was no infec-tion management monitoring information platform in the grass-roots medical institutions.The infection cases,hand hygiene,environmental health and occupational exposures were monitored by people.The grass-roots medi-cal institutions had the highest requirements for various professional trainings and increase of training contents of prevention and control of public health infectious diseases(100.00％).The county-level medical institutions had inadequate capabilities of professional examination of medical equipment replacement and construction of medi-cal architecture.CONCLUSION It is necessary for the country and local levels of governments to attach great importance to the implementation of the infection control core elements in the grass-roots medical institutions within the county-lev-el medical communities,establish the county-level regional information platform,formulate the corresponding surveil-lance indexes and homogenized management systems,complete the cultivation of talents,and offer financial support.

BACKGROUND: Over 20 million colonoscopies are performed in China annually. An automatic clinical decision support system (CDSS) with accurate semantic recognition of colonoscopy reports and guideline-based is helpful to relieve the increasing medical burden and standardize the healthcare. In this study, the CDSS was built under a hierarchical-label interpretable classification framework, trained by a state-of-the-art transformer-based model, and validated in a multi-center style. METHODS: We conducted stratified sampling on a previously established dataset containing 302,965 electronic colonoscopy reports with pathology, identified 2041 patients' records representative of overall features, and randomly divided into the training and testing sets (7:3). A total of five main labels and 22 sublabels were applied to annotate each record on a network platform, and the data were trained respectively by three pre-training models on Chinese corpus website, including bidirectional encoder representations from transformers (BERT)-base-Chinese (BC), the BERT-wwm-ext-Chinese (BWEC), and ernie-3.0-base-zh (E3BZ). The performance of trained models was subsequently compared with a randomly initialized model, and the preferred model was selected. Model fine-tuning was applied to further enhance the capacity. The system was validated in five other hospitals with 3177 consecutive colonoscopy cases. RESULTS: The E3BZ pre-trained model exhibited the best performance, with a 90.18% accuracy and a 69.14% Macro-F1 score overall. The model achieved 100% accuracy in identifying cancer cases and 99.16% for normal cases. In external validation, the model exhibited favorable consistency and good performance among five hospitals. CONCLUSIONS The novel CDSS possesses high-level semantic recognition of colonoscopy reports, provides appropriate recommendations, and holds the potential to be a powerful tool for physicians and patients. The hierarchical multi-label strategy and pre-training method should be amendable to manage more medical text in the future.
Humans ; Colonoscopy/methods* ; Deep Learning ; Decision Support Systems, Clinical ; Female ; Male

OBJECTIVE To construct and evaluate nomogram prediction model for refractory chemotherapy-induced nausea and vomiting （CINV）. METHODS The data of malignant tumor patients who received chemotherapy at the Third People’s Hospital of Zhengzhou from January 2017 to December 2023 were collected. These patients were categorized into the occurrence group and the non-occurrence group according to the occurrence of refractory CINV. Multivariate Logistic regression analysis was employed to screen predictive factors for refractory CINV and constructing a nomogram prediction model. Model performance was assessed via receiver operating characteristic curve analysis. Model calibration was evaluated using Bootstrap resampling. Decision curve analysis （DCA） was used to determine the clinical net benefit of three strategies under different risk thresholds. Clinical impact curves were utilized to assess the clinical value of the model at different risk thresholds. Shapley additive explanations （SHAP） analysis was performed to evaluate individual factor contributions to the predictive model. RESULTS A total of 388 patients were included， with 219 experiencing refractory CINV. Multivariate Logistic regression identified 11 predictive factors for refractory CINV， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， etc. The model’s area under the curve was 0.80 [95% confidence interval （0.76， 0.84）]， with a mean error of 0.036. DCA demonstrated the prediction model had higher clinical net benefit when the risk threshold was between 0.05 and 0.85. SHAP analysis revealed the top three predictive factors as gastrointestinal disease history （0.924）， chemotherapy- induced emetic risk classification （0.866）， and electrolyte levels （0.581）. CONCLUSIONS Eleven factors， including gastrointestinal disease history， anticipated nausea and vomiting， chemotherapy-induced emetic risk classification， and electrolyte levels， are identified as predictors of refractory CINV. The model based on these factors has good predictive ability， which can be used to predict the risk of refractory CINV.

OBJECTIVE To explore the implementation and standardized management of infection control core ele-ments in grass-roots medical institutions within county-level medical communities.METHODS From Mar.2024 to Apr.2024,the current status of implementation of infection control core elements in the grass-roots medical institu-tions within county-level medical communities was investigated by means of questionnaire survey and qualita-tive interview,and the implementation strategies were further explored.RESULTS The infection management or-ganizational system and functions of the two county-level medical institutions within the county medical communi-ties were completed,there is no independent hospital infection management department in the primary medical in-stitutions.The infection management personnel in the 16 grass-roots medical institutions were part-time person-nel,the personnel with the educational background below junior college accounted for 84.21％,the personnel with the professional background of nursing accounted for 100.00％,the personnel with less than 5 years of working experience accounted for 78.95％,none of them had an on-the-job training certificate.The monitoring programs of the county-level medical institutions within the county medical communities were completed,there was no infec-tion management monitoring information platform in the grass-roots medical institutions.The infection cases,hand hygiene,environmental health and occupational exposures were monitored by people.The grass-roots medi-cal institutions had the highest requirements for various professional trainings and increase of training contents of prevention and control of public health infectious diseases(100.00％).The county-level medical institutions had inadequate capabilities of professional examination of medical equipment replacement and construction of medi-cal architecture.CONCLUSION It is necessary for the country and local levels of governments to attach great importance to the implementation of the infection control core elements in the grass-roots medical institutions within the county-lev-el medical communities,establish the county-level regional information platform,formulate the corresponding surveil-lance indexes and homogenized management systems,complete the cultivation of talents,and offer financial support.