Pulpotomy, which belongs to vital pulp therapy, has become a strategy for managing pulpitis in recent decades. This minimally invasive treatment reflects the recognition of preserving healthy dental pulp and optimizing long-term patient-centered outcomes. Pulpotomy is categorized into partial pulpotomy (PP), the removal of a partial segment of the coronal pulp tissue, and full pulpotomy (FP), the removal of whole coronal pulp, which is followed by applying the biomaterials onto the remaining pulp tissue and ultimately restoring the tooth. Procedural decisions for the amount of pulp tissue removal or retention depend on the diagnostic of pulp vitality, the overall treatment plan, the patient's general health status, and pulp inflammation reassessment during operation. This statement represents the consensus of an expert committee convened by the Society of Cariology and Endodontics, Chinese Stomatological Association. It addresses the current evidence to support the application of pulpotomy as a potential alternative to root canal treatment (RCT) on mature permanent teeth with pulpitis from a biological basis, the development of capping biomaterial, and the diagnostic considerations to evidence-based medicine. This expert statement intends to provide a clinical protocol of pulpotomy, which facilitates practitioners in choosing the optimal procedure and increasing their confidence in this rapidly evolving field.
Humans ; Calcium Compounds/therapeutic use* ; Consensus ; Dental Pulp ; Dentition, Permanent ; Oxides/therapeutic use* ; Pulpitis/therapy* ; Pulpotomy/standards*

Objective:To establish a set of reasonable,reliable and easy-to-operate evaluation index system for the clinical application of ventilators,so as to carry out all-round clinical evaluation for application of ventilators.Methods:A research group on the evaluation index system for the clinical application of ventilators was formed by 5 clinical engineers,who came from the Department of Medical Engineering of the First Affiliated Hospital of Zhejiang University School of Medicine,to form a primary evaluation index system for the clinical application of ventilators through literature review and internal discussion,and invited 14 experts from different provinces and cities engaged in respiratory therapy or ventilator maintenance management,after two rounds of online discussion and optimization,the importance scores of each evaluation index were obtained by the Delphi method,and the relative importance of each evaluation index was calculated by analytic hierarchy process.An evaluation index system for the clinical application of ventilators was established from three dimensions:technical performance,clinical effect and after-sales service.The ventilators of brand A and brand B used in the hospital during the same period were selected,and the clinical application of the two different brands of ventilators was compared and evaluated by using the evaluation index system.Results:The constructed evaluation index system for clinical application of ventilator included 3 first-level indicators(technical performance,clinical effect and after-sale service),and 8 second-level indicators and 35 third-level indicators.The combined weight of indicators showed that the ratio of importance of"technical performance"of the first-level indicators accounted for more than half,and the relatively important indicators in the second-level indicators were successively design for safety,static performance,reliability,service quality and applicability.The comprehensive average score of ventilator A was 4.468 points,and that of ventilator B was 4.117 points.The overall performance of ventilator A was better than that of ventilator B in the evaluation of this round,which was consistent with the actually clinical application of the two ventilators.Conclusion:The evaluation index system for clinical application of ventilator can conduct comprehensive evaluation for the effect of clinical application of various kinds of ventilators,and clarify the advantages and disadvantages of various kinds of ventilators,and provide reference basis for medical institutions in selecting ventilator's brands,and for manufacturers in improving product's performance.

Starting from the intrinsic relationship between the glymphatic system and the core pathogenesis of vascular cognitive impairment （VCI）， including internal dampness， phlegm turbidity， and blood stasis， this paper explores clinical approaches to the diagnosis and treatment of VCI. Dysfunction of the kidney's role in governing water leads to the accumulation of dampness， phlegm turbidity， and blood stasis， which are key pathological mechanisms underlying the onset and progression of VCI. The glymphatic system participates in the circulation of cerebrospinal fluid within the central nervous system， and its impairment can result in reduced clearance of soluble metabolic waste products in the brain， a crucial factor contributing to VCI. It is proposed that the "kidney governing water" function is related to the glymphatic system， and that the cerebral collaterals correspond structurally to the glymphatic pathways. Clinically， therapies aimed at tonifying the kidney， resolving phlegm， activating blood circulation， and unblocking collaterals， such as modified Kaixin Powder （开心散）， which eliminates dampness and turbidity， transforms phlegm， restores consciousness， enhances cognition， and strengthens the brain， are commonly employed. These treatments may improve VCI prognosis by regulating glymphatic system function， providing a theoretical basis for the prevention and treatment of VCI with traditional Chinese medicine.

Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.

Objective To addresses the challenges arising from the rapid expansion of pharmaceutical clinical trials and the growing demands for quality management,this paper investigates the application of low-code technology in project management.Its goals are to enhance the operational efficiency and execution capabilities of clinical trial institutions,ensure trial quality and safety,and accelerate the translation of pharmaceutical scientific achievements.Methods A brainstorming session was conducted to analyze the technical and functional requirements for managing pharmaceutical clinical trial projects.Utilizing the ＂template design＂ and ＂decision analysis＂ functionalities of low-code technology,the study adopted a modular and visually driven data management approach to develop a system compliant with Good Clinical Practice(GCP)standards.This system integrates key functionalities,including project progress management,funding management,drug inventory management,and quality control.Its effectiveness was evaluated through real-world operation and performance validation.Results The system had demonstrated stable operation with substantial improvements in practical application.Compared with conventional management approaches,it significantly enhanced project management efficiency:the time required for project schedule management was reduced by 80%,the efficiency of financial processing increased by 95%,drug inventory management efficiency improved by 75%,and the time spent on quality control was shortened by 60%.Conclusion The pharmaceutical clinical trial project management system developed using low-code technology offers substantial advantages and promising application potential.It represents a critical practice in applying digital and intelligent tools to advance pharmaceutical productivity in the medical and healthcare sectors.

Objective To addresses the challenges arising from the rapid expansion of pharmaceutical clinical trials and the growing demands for quality management,this paper investigates the application of low-code technology in project management.Its goals are to enhance the operational efficiency and execution capabilities of clinical trial institutions,ensure trial quality and safety,and accelerate the translation of pharmaceutical scientific achievements.Methods A brainstorming session was conducted to analyze the technical and functional requirements for managing pharmaceutical clinical trial projects.Utilizing the ＂template design＂ and ＂decision analysis＂ functionalities of low-code technology,the study adopted a modular and visually driven data management approach to develop a system compliant with Good Clinical Practice(GCP)standards.This system integrates key functionalities,including project progress management,funding management,drug inventory management,and quality control.Its effectiveness was evaluated through real-world operation and performance validation.Results The system had demonstrated stable operation with substantial improvements in practical application.Compared with conventional management approaches,it significantly enhanced project management efficiency:the time required for project schedule management was reduced by 80%,the efficiency of financial processing increased by 95%,drug inventory management efficiency improved by 75%,and the time spent on quality control was shortened by 60%.Conclusion The pharmaceutical clinical trial project management system developed using low-code technology offers substantial advantages and promising application potential.It represents a critical practice in applying digital and intelligent tools to advance pharmaceutical productivity in the medical and healthcare sectors.

Objective:To establish a set of reasonable,reliable and easy-to-operate evaluation index system for the clinical application of ventilators,so as to carry out all-round clinical evaluation for application of ventilators.Methods:A research group on the evaluation index system for the clinical application of ventilators was formed by 5 clinical engineers,who came from the Department of Medical Engineering of the First Affiliated Hospital of Zhejiang University School of Medicine,to form a primary evaluation index system for the clinical application of ventilators through literature review and internal discussion,and invited 14 experts from different provinces and cities engaged in respiratory therapy or ventilator maintenance management,after two rounds of online discussion and optimization,the importance scores of each evaluation index were obtained by the Delphi method,and the relative importance of each evaluation index was calculated by analytic hierarchy process.An evaluation index system for the clinical application of ventilators was established from three dimensions:technical performance,clinical effect and after-sales service.The ventilators of brand A and brand B used in the hospital during the same period were selected,and the clinical application of the two different brands of ventilators was compared and evaluated by using the evaluation index system.Results:The constructed evaluation index system for clinical application of ventilator included 3 first-level indicators(technical performance,clinical effect and after-sale service),and 8 second-level indicators and 35 third-level indicators.The combined weight of indicators showed that the ratio of importance of"technical performance"of the first-level indicators accounted for more than half,and the relatively important indicators in the second-level indicators were successively design for safety,static performance,reliability,service quality and applicability.The comprehensive average score of ventilator A was 4.468 points,and that of ventilator B was 4.117 points.The overall performance of ventilator A was better than that of ventilator B in the evaluation of this round,which was consistent with the actually clinical application of the two ventilators.Conclusion:The evaluation index system for clinical application of ventilator can conduct comprehensive evaluation for the effect of clinical application of various kinds of ventilators,and clarify the advantages and disadvantages of various kinds of ventilators,and provide reference basis for medical institutions in selecting ventilator's brands,and for manufacturers in improving product's performance.

Objective To investigate the correlation between glycemic variability metrics and the risk of diabetic foot(DF)in patients with type 2 diabetes mellitus(T2DM)utilizing flash glucose monitoring(FGM)tech-nology.Methods A retrospective analysis was conducted on 233 hospitalized patients with T2DM,with or without DF,who were treated in the Department of Endocrinology at Lianyungang First People's Hospital from January 2021 to May 2022 and monitored using FGM.Patients were categorized into a non-DF group(n=147)and a DF group(n=86)based on the presence of DF.The study compared general clinical characteristics,biochemical parameters,and glycemic variability metrics between the two groups and performed subgroup analyses.Binary logistic regression was employed to identify factors associated with the risk of DF,while receiver operating characteristic(ROC)curves were utilized to assess the predictive value of glycemic variability metrics for DF.Results Compared with the non-DF group,patients in the DF group exhibited significantly longer disease duration,higher body mass index(BMI),glycated hemoglobin(HbA1c),urinary albumin-to-creatinine ratio(UACR),alanine aminotransferase(ALT),serum uric acid(SUA),mean amplitude of glycemic excursions(MAGE),coefficient of variation(CV),mean of daily differences(MODD),and mean blood glucose(MBG),but lower fasting C-peptide(FCP),fasting insulin(FINS),high-density lipoprotein cholesterol(HDL-C),and time in range(TIR),with statistically signifi-cant differences(P<0.05).Subgroup analysis revealed that TIR was associated with the incidence of DF and diabetic retinopathy(DR).Binary logistic regression analysis identified HbA1c,MAGE,MODD,and MBG as risk factors for DF,while TIR was a protective factor(P<0.05).ROC curve analysis demonstrated that the area under the curve(AUC)for predicting DF using HbA1c,TIR,MAGE,MODD,MBG,and their combination were 0.646,0.850,0.868,0.764,0.619,and 0.967,respectively,indicating superior performance of the combined prediction model.Conclusions HbA1c,TIR,MAGE,MODD,and MBG are critical factors associated with the development of DF in patients with T2DM.Targeted early interventions aimed at optimizing these glycemic variability indicators may effectively reduce the incidence of DF.

Objective Exploring the clinical application value of long chain non-coding RNA(lncRNA)H19 in peripheral blood mononuclear cells(PBMCs)in type 2 diabetes mellitus(T2DM)patients with osteoporosis(OP).Methods A total of 176 patients with T2DM admitted to the Department of Endocrinology of the First People's Hospital of Lianyungang City from December 2022 to June 2023 were selected.They were divided into OP group(n=100)and simple T2DM group(n=76)according to the results of bone mineral density(BMD)determination by dual-energy X-ray.General data and biochemical indicators were compared between the two groups.The correlation between lncRNA H19 and other clinical indicators was analyzed by Spearman correlation analysis and the influencing factors for T2DM with OP were analyzed by logistic regression.Receiver operating characteristic(ROC)curve was used to evaluate the diagnostic value of lncRNA H19 in T2DM with OP.Results Compared with T2DM group,the proportion of females,age,HbA1c,TC and TGF-β1 were higher(P<0.05),while BMI,SUA,BMD and lncRNA H19 were lower in OP group(P<0.05).Spearman correlation analysis showed that lncRNA H19 expression level was positively correlated with BMI,SUA and BMD(P<0.05),and negatively correlated with age,HbA1c and TGF-β1(P<0.05).Logistic regression analysis showed that age,BMI,TC,TGF-β1 and lncRNA H19 were the influencing factors for T2DM combined with OP(P<0.05).ROC curve analysis showed that the AUC of lncRNA H19 in the diagnosis of T2DM with OP was 0.839,the sensitivity was 76.3%,and the specificity was 86.0%.Multiple linear regression analysis showed that age,TGF-β1 and OP were the influencing factors for lncRNA H19(P<0.05).Conclusion LncRNA H19 expression decreased in PBMCs in patients with T2DM with OP,which may participate in the occurrence and development of T2DM with OP through glucose metabolism and lncRNA H19/TGF-β1 pathway.

To analyze the prevalence, genomic characteristics and clinical relevance of carbapenem-resistant bacteria in untreated hospital wastewater, and to provide a reference basis for in-hospital assessment of public health situation and prevention of cross-infection. In March 2023, untreated wastewater in the wastewater treatment station of the Second Affiliated Hospital of Soochow University and wastewater in the U-shaped wastewater pipes of the hand-washing sinks in 26 wards were collected, centrifuged and diluted, and the drug-resistant bacteria were isolated by using LB solid plates containing meropenem (2 μg/ml) for species identification, drug sensitivity analysis, carbapenenase gene PCR detection and whole genome sequencing. The genome sequence was identified for drug resistance genes. Retrospective research was used, combining multilocus sequence typing (MLST) and single nucleotide polymorphism (SNP) analysis, to compare their homology with clinical isolates of the same quarter. The results showed that 56 carbapenem-resistant gram-negative bacteria were isolated from hospital wastewater, originating from 13 genera, of which 17 were isolated from the total hospital wastewater, with Aeromonas spp. as the most dominant genus (35.3%, 6/17), and 39 were isolated from the wastewater of 17 wards, with Pseudomonas spp. as the most dominant genus (30.8%, 12/39). All common wastewater isolates from our hospital were multidrug-resistant bacteria, with up to 100% resistant to some second-and third-generation cephalosporins. A total of 8 carbapenemase genes originated from wastewater isolates, including blaKPC, blaNDM, blaIMP, blaVIM, blaIND, blaOXA-58-like, blaOXA-48-like, and blaOXA-427-like. 39 wastewater isolates carried the carbapenemase genes, and the total wastewater of the hospital carried the highest isolation rate of blaKPC-2 bacteria (35.3%, 6/17) and the highest isolation rate of blaIMP-8 bacteria (31.8%, 7/22) were found in the wastewater from 26 wards. 14 wastewater isolates were found to carry both carbapenemase genes, with a total of 6 combinations. A new blaIMP-101 isoform was also identified for the first time. 4 wastewater isolates and 11 clinical isolates were screened for inclusion in the SNP analysis, in which only 15 SNPs differed between the two strains of ST11 Klebsiella pneumoniae of clinical and wastewater origin, which was highly homologous. In conclusion, the presence of multiple multi-drug resistant conditionally pathogenic bacteria in untreated hospital wastewater has the potential risk of spreading drug-resistant genes in the environment. The highly homologous Klebsiella pneumoniae isolated from hospital wastewater and clinics indicates the close association between hospital wastewater and clinical infections. Hospitals need to strengthen the monitoring of drug-resistant bacteria and drug-resistant genes in the wastewater environment, to prevent the widespread dissemination of drug-resistant bacteria and drug-resistant genes in hospital wastewater and to prevent nosocomial infections caused by drug-resistant bacteria in wastewater.