Cornelia de Lange syndrome is a rare congenital malformation disease,and its typical features include growth restriction,mental retardation,craniofacial abnormality and hirsutism.This study reported 2 cases of CdLS patients,summarized their clinical manifestations and gene mutation characteristics,and the relevant literatures were reviewed.Patient 1,a 5-year-old girl,was admitted to the hospital due to growth retardation.Physical examination revealed hirsutism,monobrow,small and sparse teeth,hemangiomas(approximately 2 cm×2 cm)on the chest and back,delayed language development,and intellectual disability.The height was 98 cm[≤-2 standard deviation(SD)],the weight was 15 kg(-2SD--1SD),the head circumference was 46 cm(-3SD--2SD).Brain magnetic resonance imaging(MRI)plain scan showed slightly enlarged left lateral ventricle and bilateral lateral ventricle triangles,slightly thickened bilateral maxillary sinus and ethmoid sinus mucosa.Echocardiography revealed mild regurgitation of the mitral and tricuspid valves.Patient 2,a 1-month-old girl,was admitted to the hospital due to postpartum shortness of breath.The physical examination highlighted hirsutism,short nose,soft cleft palate,dysphagia,positive three-concave sign,audible throat sound,small hands,palm penetration in the left hand,short fifth finger of the right hand,limited right hip abduction,foot varus,and a white spot at the bottom of the right eye.Ultrasonography at 1 month showed mild regurgitation of the tricuspid valve and an open foramen ovale.Brain MRI at 2 d showed a few patchy low-signal shadows in the longitudinal fissure cistern and tentorium,a small amount of subarachnoid hemorrhage,and a small amount of fluid in the bilateral maxillary sinus,ethmoid sinus,and middle ear mastoid.No obvious structural or numerical abnormalities were observed in the chromosome karyotypes.Whole-exome sequencing detected a heterozygous variation of c.6653_6655del in the NIPBL gene in patient 1 and a heterozygous variation of c.337C＞T in the NIPBL gene in patient 2.These variations were not found in their parents.The study revealed that NIPBL gene variation could be the genetic cause of the two patients with CdLS.The identification of the variation c.337C＞T may expand the variation spectrum of the NIPBL gene,providing valuable insights into the pathogenic genetic basis of CdLS.

Transient perivascular inflammation of the carotid artery(TIPIC)syndrome is a relatively rare disease,and ultrasound is the first screening method for initial diagnosis of the disease.Contrast-enhanced ultrasound(CEUS)has unique advantages in the follow-up of patients with TIPIC syndrome.This paper reports a patient with TIPIC syndrome who was treated with acute left neck pain.The inflammation was significantly re-lieved and subsided after treatment with non-steroidal anti-inflammatory drugs.The ultrasound changes of carotid artery lesions in this patient during follow-up were analyzed,and the application value of CEUS in the follow-up diagnosis of this disease was summarized,in the hope of providing clinical reference.

ObjectiveTo investigate the current status of emergency management for severe mental disorders in Shanghai, and to provide countermeasures and suggestions for the establishment of a sound emergency management system for severe mental disorders and the enhancement of emergency management capability. MethodsA questionnaire survey and qualitative interviews were used to conduct an investigation into the emergency management in 17 district-level mental illness prevention and control institutions in Shanghai, which includes the basic situation of emergency management for severe mental disorders, the construction of emergency response teams and personnel, emergency preparedness drills and training, emergency management plans and rules and regulations, and problems encountered in emergency management. ResultsIn terms of emergency management mechanism and basic situation, resources such as personnel allocation, security funds and green channel were well equipped in each district-level mental illness prevention and control institution in Shanghai. However, the equipment of some hardware facilities was still insufficient to some extent. Therefore, further improvement on the emergency management mechanism for severe mental disorders was needed. With regard to the construction of emergency team and personnel allocation, the majority were those aged between 35‒<45 years old, with a bachelor’s degree, and more than 10 years of working experience. For example, 90.27% staff in district-level mental illness prevention and control institution had a bachelor’s degree or above, which was higher than that among the staff in community-level (73.60%); staff majored in clinical medicine in district-level institution accounted for the proportion at 52.71%, higher than that among the staff in community-level (28.86%); 57.24% staff in district-level institution had an intermediate professional title, higher than that among the staff in community-level (42.28%); and 69.90% staff in district-level institution had more than 10 years of working experience, higher than that among the staff in community-level (43.62%). In the aspect of emergency drills and training, all district-level mental illness prevention and control institutions in Shanghai had a high demand for emergency training, and the weak aspects mainly focused on lack of emergency service protocols, skills of addressing technical challenges, and construction of effectiveness evaluation system. Moreover, the teaching methods were primarily centered on case analysis, simulation drills, interactive discussions, and so forth. Concerning emergency management plans and rules and regulations, all districts in Shanghai had relatively established well-developed systems for emergency response plans, emergency response leadership groups, and emergency response operational task forces for severe mental disorders. About half of the institutions had established other rules and regulations related to emergency management of severe mental disorders in addition to emergency plans. ConclusionShanghai has initially established an emergency management system for severe mental disorders, but it is still fragile in specialized training for emergency management of severe mental disorders, construction of emergency management mechanisms, and the building-up of grassroots emergency teams. Further priorities should include strengthening emergency management training, enhancing the construction of emergency management personnel teams, and gradually establishing a more comprehensive and integrated emergency management mechanism for severe mental disorders.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Purpose To explore the predictive value of hepatosplenic hemodynamic indexes obtained by dual-energy CT combined with clinical features in non-invasive assessment of high-risk esophageal varices(EV)in cirrhosis.Materials and Methods We retrospectively collected 93 patients with cirrhosis from March 2022 to May 2023 in Zengcheng Branch of Nanfang Hospital.All patients underwent epigastric enhanced energy spectrum scan and gastroscopy.EV severity as assessed by gastroscopy(none,EV0;mild,EV1;medium,EV2;severe,EV3)were divided into low-risk EV group(EV0 and EV1)and high-risk EV group(EV2 and EV3).Age,gender,Child-Pugh grade,ascites and platelet of the two groups were collected,and dual-energy CT parameters including liver and spleen volume,mean iodine content in liver and spleen and liver and spleen iodine volume were measured.The difference of parameters between the low-risk EV and the high-risk EV group were analyzed,and the model was constructed by Logistic regression analysis.Receiver operating characteristic curve was used to evaluate the diagnostic performance of the model for high-risk EV.Results There were significant differences in age,Child-Pugh grade,ascites,platelet,liver and spleen volume,liver and spleen iodine volume between low-risk EV and high-risk EV groups(Z/χ2=-5.921-16.343,all P<0.05).Ascites,platelet,liver and spleen volume,liver and spleen iodine volume were included in multivariate regression analysis to construct regression models,and the results showed that spleen iodine volume(OR=1.002,P<0.001),ascites(OR=5.319,P=0.009),platelet(OR=0.99,P=0.062)were independent risk factors for predicting the high risk of EV.Hosmer-Lemeshow test showed that the regression model fit the observed values well(P=0.303),with accuracy of 83.9%,sensitivity of 78.6%,specificity of 88.2%,positive prediction rate of 84.6%and negative prediction rate of 83.3%.The area under the curve of this regression model was 0.894.Conclusion Spleen iodine content based on dual-energy CT,platelet and ascites can noninvasively predict high-risk EV.

Creutzfeldt-Jakob disease(CJD)is a rapidly progressive and fatal neurodegenerative disorder caused by prions,with certain infectivity and iatrogenic transmission risks.With the rapid progress and application of new dia-gnostic biomarkers and detection methods,as well as the construction and improvement of surveillance and reporting systems,the detection of CJD in patients domestically and internationally has shown an increasing trend year by year.Due to its long incubation period and heterogeneity of early symptoms,early identification and diagnosis of the disease is difficult,increasing the risk of transmission within medical institutions.Currently,there is a lack of con-sensus on the infection prevention and control of CJD.In order to timely identify and diagnose CJD as well as effec-tively block its transmission in medical institutions,this consensus summarizes 15 clinical concerns and formulates 24 specific recommendations based on the latest domestic and international research findings and clinical evidence,as well as combines with clinical practice,aiming to standardize healthcare-associated infection prevention and control measures for CJD and reduce its transmission risk in medical institutions.

Purpose To explore the predictive value of hepatosplenic hemodynamic indexes obtained by dual-energy CT combined with clinical features in non-invasive assessment of high-risk esophageal varices(EV)in cirrhosis.Materials and Methods We retrospectively collected 93 patients with cirrhosis from March 2022 to May 2023 in Zengcheng Branch of Nanfang Hospital.All patients underwent epigastric enhanced energy spectrum scan and gastroscopy.EV severity as assessed by gastroscopy(none,EV0;mild,EV1;medium,EV2;severe,EV3)were divided into low-risk EV group(EV0 and EV1)and high-risk EV group(EV2 and EV3).Age,gender,Child-Pugh grade,ascites and platelet of the two groups were collected,and dual-energy CT parameters including liver and spleen volume,mean iodine content in liver and spleen and liver and spleen iodine volume were measured.The difference of parameters between the low-risk EV and the high-risk EV group were analyzed,and the model was constructed by Logistic regression analysis.Receiver operating characteristic curve was used to evaluate the diagnostic performance of the model for high-risk EV.Results There were significant differences in age,Child-Pugh grade,ascites,platelet,liver and spleen volume,liver and spleen iodine volume between low-risk EV and high-risk EV groups(Z/χ2=-5.921-16.343,all P<0.05).Ascites,platelet,liver and spleen volume,liver and spleen iodine volume were included in multivariate regression analysis to construct regression models,and the results showed that spleen iodine volume(OR=1.002,P<0.001),ascites(OR=5.319,P=0.009),platelet(OR=0.99,P=0.062)were independent risk factors for predicting the high risk of EV.Hosmer-Lemeshow test showed that the regression model fit the observed values well(P=0.303),with accuracy of 83.9%,sensitivity of 78.6%,specificity of 88.2%,positive prediction rate of 84.6%and negative prediction rate of 83.3%.The area under the curve of this regression model was 0.894.Conclusion Spleen iodine content based on dual-energy CT,platelet and ascites can noninvasively predict high-risk EV.

Objective To develop a deep learning model based on fundus retinal images to improve the detection rate of mild cognitive impairment(MCI)in patients with coronary heart disease,achieve early intervention and improve prognosis.Methods The study was a single-center cross-sectional study that retrospectively included patients diagnosed with coronary heart disease(CHD)by coronary angiography(≥50％ stenosis of at least one coronary vessel)from Beijing Anzhen Hospital between November 2021 and December 2022.The whole data set was randomly divided into the training set and the testing set according to the ratio of 8∶2 for model development.After that,the patient data of the same center from January 2023 to April 2023 were included in the time verification method to verify the model.The diagnostic criteria for MCI were MMSE＜27 or MoCA＜26.Four kinds of convolutional neural network(CNN)architectures were used to train fundus images,and a comprehensive vision model of MCI detection was established through model integration.The area under the curve(AUC),sensitivity and specificity of the receiver operating curve(ROC)were used to evaluate the performance of the AI model.Results We collected 5 880 eligible fundus images from 3 368 CHD patients.Based on the results of the MMSE scale,the algorithm was labeled,including 2 898 males and 527 MCI patients.The AUC of the deep learning model in the test group is 0.733(95％CI 0.688-0.778),and the sensitivity of the algorithm in the test group is 0.577(95％CI 0.528-0.625)by using the operating point with the maximum sum of sensitivity and specificity.With a specificity of 0.758(95％CI 0.714-0.802),corresponding to a validated AUC of 0.710(95％CI 0.601-0.818).Based on the results of the MoCA scale,the algorithm labels 2 437 males and 1 626 MCI patients.The AUC of the deep learning model in the test group was 0.702(95％CI 0.671-0.733).The operating point with the maximum sum of sensitivity and specificity was selected,and the sensitivity of the algorithm was 0.749(95％CI 0.719-0.778)and the specificity was 0.561(95％CI 0.527-0.595),corresponding to the AUC value of the verification group was 0.674(95％CI 0.622-0.726).Conclusions The deep learning algorithm model based on fundus images has good diagnostic performance,and may be used as a new non-invasive,convenient and rapid screening method for MCI in CHD population.

【Objective】 To investigate the protective effects of aflexible sleeve penile protection device on reducing postoperative pain and wound edema in patients after circumcision. 【Methods】 A total of 54 patients who underwent circumcision at Yan’an Branch of Peking University Third Hospital during Feb.1 and May 31, 2023 were enrolled.The patients were randomly divided into the experimental group and control group, with 27 patients in either groups.Patients in the experimental group were treated with a flexible sleeve penis protection device after surgery, and patients in the control group were treated with traditional gauze bandage after surgery.Postoperative pain, wound edema and complications were compared between the two groups. 【Results】 In terms of pain, the visual analogue scale of the experimental group was significantly lower at 6 hours [(1.7±0.9) vs.(3.3±1.9), P<0.001] and 2 days [(2.0±1.3) vs.(3.3±1.3), P<0.001] after surgery than that of the control group, but there were no statistically significant differences between the two groups on the 4th and 7th postoperative days (P>0.05).In terms of edema, the edema score of the experimental group was significantly lower than that of the control group on the 2nd postoperative day [(2.0±1.0) vs.(4.0±0.8), P<0.001] , the 4th postoperative day [(1.5±1.2) vs.(2.6±0.9), P<0.001] , and the 7th postoperative day [(0.9±1.3) vs.(2.3±1.5), P<0.001] .There was no statistically significant difference in the incidence of complications between the two groups (P>0.05). 【Conclusion】 The flexible sleeve penile protection device has significant effects of reducing early postoperative pain and reducing edema in patients undergoing circumcision.