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 evaluate preoperative high-resolution thin-layer cervical enhanced CT used to predict the venous route of the submental flap reflux vein and its relationship with adjacent structures in order to guide the anatomical understanding and protection of submental flap in pharyngeal cancer surgery.Methods:Sixty consecutive patients with pharyngeal cancer who underwent submental flap repair surgery in our department from March 2022 to December 2024, as well as 60 patients who were accepted neck dissection suffering other cancers, were selected. Before surgery, high-resolution cervical enhanced CT scans were performed, and the position of the transverse section of the facial vein in the venous phase horizontal image gradually variation tendency was focused layer by layer. The direction and adjacent relationship of the submental flap reflux veins were determined and recorded. Combined with 60 patients with other head and neck tumors who underwent neck dissection in our department during the same period (a total of 120 cases, 240 sides), the classification and management of the draining veins of Fang′s mental flap were conducted. Type Ⅰ mainly drains into the internal jugular vein; Type Ⅱ mainly drains into the external jugular vein and Type Ⅲ mainly drains into the anterior jugular vein (often accompanied by an external jugular draining branch). The status and proportion of venous drainage were analyzed.Results:Vascular predictive coincidence rate was 98.3% (59/60) among the 60 patients with pharyngeal cancer. Only one patient was predicted to have a simple return to the external jugular vein. However, during the operation, in addition to the main return to the external jugular vein, a small portion also returned to the internal jugular vein. Submental flap reflux vessels were classified into three types based on intraoperative submental flap venous return in 60 cases of laryngopharyngeal cancer, in conjunction with the analysis of venous return patterns from 240 cervical CT scans. Type Ⅰ mainly refluxed to the internal jugular vein, accounting for 42.1%. Type Ⅱ mainly refluxed to the external jugular vein (47.9%). Type Ⅲ mainly refluxed to the anterior jugular vein (10.0%). The total detection rate of CT reading of 240 venous reflux was 98.7% (237/240). Vascular predictive coincidence rate was 97.9%(235/240).Conclusion:The detailed analysis of submental venous return vessels can accurately predict the direction of reflux veins and its surrounding areas by preoperative high-resolution enhanced CT scan. This provides reliable guidance for the anatomy and protection of the submental flap reflux veins during surgery.

AIM To evaluate the chemical constituent consistency in formula granules and traditional decoctions of Gouteng Jiangya Formula.METHODS HPLC characteristic chromatograms were established,the analysis was performed on a 30 ℃ thermostatic YMC-Triart C18 column(4.6 mm× 250 mm,5 μm),with the mobile phase comprising of acetonitrile-0.2％phosphoric acid flowing at 1.0 mL/min in a gradient elution manner,and the detection wavelength was set at 240 nm.Puerarin was used as an internal standard to calculate the relative correction factors of 3'-methoxy puerarin,puerarin apioside,magnolflorine,paeoniflora,daidzin,baicalin,palmatine,berberine,wogonoside and benzoylpaeoniflorin,after which the content detemination was made by quantitative analysis of multi-components by single-marker(QAMS).RESULTS The characteristic chromatograms of 9 batches of formula granules and 15 bacthes of traditional decoctions demonstrated the similarities of more than 0.90 at the detection wavelengths of 192,210,240,260,280,300,320,360 nm,along with similar total peak areas.Eleven constituents showed good linear relationships within their own ranges(r＞0.999 0),whose average recoveries were 97.27％-101.64％with the RSDs of 0.36％-1.11％,the result obtained by QAMS and external standard method demonstrated no significant differences(P＞0.05).The contents of various constituents in the formula granules approximated those in the traditional decoctions.CONCLUSION The consistent kinds and contents of various constituents are obversable in formula granules and traditional decoctions of Gouteng Jiangya Formula,which can provide a reference for the reasonable clinical application of this formula.

Severe open tibiofibular fractures account for approximately 28.1% of all open fractures. Among them, Gustilo-Anderson type IIIB/C fractures present significant clinical challenges due to associated bone and soft tissue defects, high infection rates, and risk of amputation. Inadequate preoperative assessment may lead to suboptimal emergency surgical planning or intraoperative complications. Historically, external fixation was often preferred, but this approach has been associated with limitations such as restricted joint mobility, delayed bone union, joint stiffness, and disuse osteoporosis, resulting in poor functional recovery. With advancements of debridement techniques, standardization of antibiotic use, and popularization of early soft tissue coverage, early internal fixation has gained broader acceptance. Nevertheless, controversies persist regarding the choice of fixation method, timing of definitive fixation, use of reamed versus unreamed intramedullary nailing, and necessity of fibular fixation. To standardize the diagnosis and early management of severe open tibiofibular fractures, reduce complication rates, and improve functional recovery, the Society of Microsurgery of the Chinese Medical Association organized a panel of domestic experts to develop the Evidence-based guideline for the diagnosis and early fixation of severe open tibiofibular fractures ( version 2025), using evidence-based methodology. The guidelines provided 12 recommendations covering diagnostic and early fixation strategies of severe open tibiofibular fractures, aiming to provide clinicians with scientifically grounded and standardized guidance.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

ObjectiveTo analyze the epidemiological and clinical characteristics of pertussis in Baoshan District, Shanghai from 2017 to 2024, so as to provide an evidence-based reference for optimizing prevention and control strategies. MethodsData on pertussis cases were collected from the China Disease Prevention and Control Information System, Shanghai Integrated Management and Immunization Service Information System, and follow-up epidemiological investigations. Descriptive epidemiological analyses were performed to analyze the epidemiological characteristics, clinical manifestations, and vaccine effectiveness. Joinpoint regression analyses were used to examine the temporal trends in incidence rates, and a Poisson model was constructed for spatiotemporal scan analyses. ResultsA total of 1 634 pertussis cases were reported in Baoshan District from 2017 to 2024, with a male-to-female ratio of 1.08∶1. More cases were observed in males than in females, with the age ranged from 20 days to 81 years. Among them, 59.92% were in the 6‒<11 years age group, and 63.34% were students. Low-level sporadic incidence persisted during 2017‒2023, followed by a sharp increase in 2024 (71.37/100 000). Starting in January 2024, the incidence rate showed an upward trend, peaking in May before declining. The majority of cases occurred between April and June. The trend in reported pertussis incidence rates in Baoshan District from 2017 to 2023 showed no statistically significant change (APC=10.039%, t=2.586, P=0.150). Incidence rate rose from January 2024, peaked in May (APC=133.641%, t=3.841, P=0.006), then declined significantly (APC=-47.816%, t=2.586, P<0.001). The 12 subdistricts of Baoshan District were divided into low, medium, and high population density areas, with an average annual reported incidence rate of 6.09/100 000, 8.19/100 000 and 11.96/100 000, respectively. The reported incidence rate increased with an increase in population density. Spatiotemporal scan analyses showed that cases clustered in the southwest and northeast of Baoshan District. Epidemiological follow-up investigations of 1 520 cases revealed that the main clinical symptoms were cough (97.63%) and sputum production (41.58%), and 98.13% of the cases were confirmed by positive nucleic-acid test results. Among the 1 475 cases with immunization records, 83.53% had completed the four-dose pertussis vaccine before onset. The complication incidence rates, from high to low, were in the 0-dose vaccination group, 1‒3-dose vaccination group and 4-dose vaccination group. The duration of cough, from long to short, was observed in the the 0-dose vaccination group, 1‒3-dose vaccination group and 4-dose vaccination group, correspondingly. ConclusionIt is recommended to improve the pertussis surveillance system in medical institutions and establish an active monitoring network, prioritizing deployment in school settings and areas with high population density. Enhancing diphtheria-tetanus-pertussis (DTP) vaccination coverage among 6-year-old children and further optimizing the pertussis immunization strategies are essential to prevent and reduce the risk of pertussis among school-aged children.

AIM:To observe the effect of opioid-free anesthesia with esketamine on delirium after hip replacement surgery in elderly patients.METH-ODS:One hundred and fourteen elderly patients who underwent hip replacement were randomly di-vided into two groups:opioid-free anesthesia(OFA)group and opioid anesthesia(OA)group(n=57).During anesthesia induction and maintenance,es-ketamine was administered in OFA group,and that fentanyl and remifentanil were administered in OA group.Delirium was mainly recorded within 3 days after the surgeries,and the patients'delirium sta-tus was evaluated using the Chinese Revised Deliri-um Diagnostic Scale(CAM-CR).RESULTS:The pa-tients in OFA group had lower CAM-CR scores and delirium incidence compared to those in the OA group at 2 days after surgery.CONCLUSION:Opioid-free anesthesia based on esketamine can effective-ly reduce delirium after hip replacement in elderly patients.

Objective:To investigate the clinical diagnosis,treatment and prognosis of traumatic ectopic testis with torsion.Methods:We retrospectively analyzed the clinical data on a case of traumatic ectopic testis with torsion and reviewed relevant litera-ture.Results:After diagnosed with traumatic ectopic testis with torsion,the patient underwent exploratory operation for confirmation of orchiocatabasis,followed by testicular reduction and fixation.Follow-up visit at 1 month after surgery showed good blood supply and no obvious testicular atrophy.Conclusion:Traumatic ectopic testis with torsion is an extremely rare emergency condition,for which color Doppler ultrasonography is an effective means of examination.Once suspected of or confirmed with the problem,the patient should receive exploratory surgery,testicular reduction and fixation within 6 hours,and close postoperative observation.

AIM To compare total sugar,total protein,total phenol,total flavonoid,calycosin-7-O-β-D-glucoside,liquiritin,lobetyolin,quercetin,isoferulic acid,hesperidin,glycyrrhizic acid contents and their antioxidant activities,hypoglycemic activities of big honey pill,small honey pill,water pill,concentrated pill,granule,mixture and decoction of Buzhong Yiqi Recipe.METHODS Anthraquinone-sulfuric acid method,Coomassie brilliant blue method,Folin-phenol colorimetry method,sodium nitrite-aluminum nitrate method and HPLC were adopted in the content determination of total sugar,total protein,total phenol,total flavonoid and seven constituents,respectively,after which the scavenging capacities,reducing powers on DPPH·free radical,ABTS+free radical,hydroxyl free radical,and inhibition capacity on α-glucosidase activity were detected.Subsequently,correlation analysis was performed.RESULTS Total sugar,total protein,total phenol and total flavonoid contents demonstrated significant differences among different dosage forms(P＜0.05,P＜0.01).Calycosin-7-O-β-D-glucoside,glycyrrhizin,codonoside and quercetin displayed the highest contents in the decoction,while those of isoferulic acid,hesperidin and glycyrrhizin were observable in the mixture.The water pill exhibited the strongest antioxidant activity,while those of the concentrated pill and mixture were weak;the big honey pill exhibited the strongest hypoglycemic activity,while that of the decoction was the weakest.Total protein,total phenol,total flavonoid and liquiritin contents displayed significant positive correlations between antioxidant activity(P＜0.05,P＜0.01),while hesperidin content displayed significant negative correlation between the latter(P＜0.05);total protein,calycosin-7-O-β-D-glucoside,codonoside and quercetin contents displayed significant negative correlations between hypoglycemic activity(P＜0.05,P＜0.01).CONCLUSION Active constituent contents and their biological activities of Buzhong Yiqi Recipe with different dosage forms exist differences,total sugar,total protein,total flavonoids,calycosin-7-O-β-D-glucoside,licorice glycoside,hesperidin,codonoside and quercetin can be taken as quality control indices for this prescription.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.