OBJECTIVE: To explore the changes of stress and displacement of intervertebral discs and vertebral bodies in adolescent idiopathic cervical kyphosis models caused by Wuqinxi () Huju() and extension movement after torque loading by finite element analysis. METHODS: One healthy male volunteer aged 24-year-old (heighted 178 cm and weighted 65 kg) was selected, software such as Mimics 21.0, Geomagic wrap 2017, SolidWorks 2017, and Ansys Workbench 17.0 were used to simulate adolescent idiopathic cervical spine model, an axial compressive load of 266 N was applied to the center of the end plate on C₂ for head physical gravity simulation, the lower part of C₇ vertebral body was set as the point of freedom constraint, a torque of 1.5 N·m was applied with C₂ as the reference point to simulate the stress on intervertebral discs and vertebral bodies after 45° movement of Wuqinxi () Huju (). RESULTS: The normal C₂-C₇ cervical spine model and adolescent idiopathic cervical kyphosis model were successfully constructed. The maximum stress value of intervertebral disc when the Huju()was raised and extended at 45° and loaded with torque occurred in C_3,4 intervertebral disc (3.588 1) MPa. The maximum stress values of each intervertebral disc were C_3,4(3.588 1 MPa)>C_2,3 (3.467 5 MPa) >C_4,5(2.597 7 MPa) >C_5,6 (2.378 8 MPa) >C_6,7 (1.404 9 MPa), respectively. The maximum stress of C6 vertebral body was 5.842 9 MPa, while the stresses of C₂, C₃, C₄, and C₅ vertebral bodies was 4.184 8, 4.437 8, 4.148 7, and 2.852 4 MPa respectively. The overall stress of vertebral body was mainly concentrated in the front of vertebral body. CONCLUSION After long-term practice of Huju()movement, the stress concentration in intervertebral discs and the front of vertebral body changes the stress load state of intervertebral discs and vertebral body. As time goes by, intervertebral discs may change, forming a shape that is higher in the front and lower in the back. The vertebral body may also undergo remodeling, resulting in a relative increase in the height of the anterior edge of vertebral body and promoting the recovery of cervical kyphosis to a physiological lordosis state.
Humans ; Finite Element Analysis ; Male ; Cervical Vertebrae/physiopathology* ; Kyphosis/therapy* ; Young Adult ; Adolescent ; Adult

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.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

To formulate an expert consensus on the principles of preoperative hair removal and provide scientific guidance for standardized removal of hair before surgical procedures so as to reduce the incidence of surgical site infections.METHODS Led by the Hospital Management Institute of National Health Commission of the People's Republic of China,this consensus was reached with the joint efforts from the expects of relevant fields such as surgeries,interventional therapies,nursing,and infection prevention and control.The consensus facilitates the classification and evaluation of literatures by following the evidence grade formulated by Oxford Evidence-based Medicine Center and focuses on the association of preoperative hair removal with surgical site infection,it reaches the evidence grade of expert consensus and recommendation intensity by integrating with discussions on meetings and clinical experience of the expects from relevant fields.RESULTS A total of 6 items of consensus were reached by summarizing the latest evidence on the aspects including the indications for preoperative hair removal,tools,range,timing and places.CONCLUSION The consensus,to some extent,make supplements to and complete the exiting regulations and standards.It provides guidance for the medical institutions to carry out the preoperative hair removal.

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 clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective To investigate the incidence rate,clinical characteristics,and prognosis of neonatal stroke in Shenzhen,China.Methods Led by Shenzhen Children's Hospital,the Shenzhen Neonatal Data Collaboration Network organized 21 institutions to collect 36 cases of neonatal stroke from January 2020 to December 2022.The incidence,clinical characteristics,treatment,and prognosis of neonatal stroke in Shenzhen were analyzed.Results The incidence rate of neonatal stroke in 21 hospitals from 2020 to 2022 was 1/15 137,1/6 060,and 1/7 704,respectively.Ischemic stroke accounted for 75％(27/36);boys accounted for 64％(23/36).Among the 36 neonates,31(86％)had disease onset within 3 days after birth,and 19(53％)had convulsion as the initial presentation.Cerebral MRI showed that 22 neonates(61％)had left cerebral infarction and 13(36％)had basal ganglia infarction.Magnetic resonance angiography was performed for 12 neonates,among whom 9(75％)had involvement of the middle cerebral artery.Electroencephalography was performed for 29 neonates,with sharp waves in 21 neonates(72％)and seizures in 10 neonates(34％).Symptomatic/supportive treatment varied across different hospitals.Neonatal Behavioral Neurological Assessment was performed for 12 neonates(33％,12/36),with a mean score of(32±4)points.The prognosis of 27 neonates was followed up to around 12 months of age,with 44％(12/27)of the neonates having a good prognosis.Conclusions Ischemic stroke is the main type of neonatal stroke,often with convulsions as the initial presentation,involvement of the middle cerebral artery,sharp waves on electroencephalography,and a relatively low neurodevelopment score.Symptomatic/supportive treatment is the main treatment method,and some neonates tend to have a poor prognosis.

Objective UPLC-Q-TOF-MS integrated molecular network strategy was used to rapidly analyze and identify the chemical components of Yuye detoxification Particle. Methods The secondary mass spectrometry data of compounds were obtained using mass spectrometry scanning in both positive and negative ion mode. The similarity of MS/MS fragmentation patterns was calculated to create the global natural product social molecular networking (GNPS) platform. The major components in Yuye detoxification Particle were quickly identified according to the molecular clusters with similar structures in GNPS. Manual analysis and identification of other compounds were performed according to the mass fragment ion information of the primary and secondary mass spectrum data and related references by using the molecular feature extraction (MFE) function of Agilent Masshunter Qualitative Analysis workstation and traditional Chinese Medicine composition database (TCM-DATA). Results A total of 89 compounds in Yuye detoxification Particle were identified by LC-MS,including 22 phenoliacids,21 flavonoids and their glycosides,6 iridoid glycosides,28 triterpenoid saponins and 12 other types of ingredients. Conclusion UPLC-Q-TOF-MS/MS integrated molecular network technology can be used for rapid and systematic identification of chemical components of Yuye detoxification Particle,which provides theoretical basis for its quality control and clinical application. The established molecular network can provide reference for rapid qualitative analysis of components of traditional Chinese medicine compound.

The long-acting cabotegravir and rilpivirine injection regimen（CAB+RPV regimen）is the first approved long-acting antiretroviral therapy（ART）for HIV in China，administered once every two months. This regimen provides an innovative alternative to daily oral ART，benefiting virologically suppressed patients. Several large clinical-studies have shown that the CAB+RPV regimen achieves comparable virologic suppression and safety to daily oral regimens，while significantly enhancing patient satisfaction. Based on international and domestic HIV/AIDs guidelines and clinical evidence，this consensus offers expert recommendations on patient selection，clinical management，and key communication strategies for healthcare providers to support the effective use of this regimen，aiming to improve quality of life for people living with HIV and accumulate domestic clinical experience with this advanced treatment approach.

The long-acting cabotegravir and rilpivirine injection regimen（CAB+RPV regimen）is the first approved long-acting antiretroviral therapy（ART）for HIV in China，administered once every two months. This regimen provides an innovative alternative to daily oral ART，benefiting virologically suppressed patients. Several large clinical-studies have shown that the CAB+RPV regimen achieves comparable virologic suppression and safety to daily oral regimens，while significantly enhancing patient satisfaction. Based on international and domestic HIV/AIDs guidelines and clinical evidence，this consensus offers expert recommendations on patient selection，clinical management，and key communication strategies for healthcare providers to support the effective use of this regimen，aiming to improve quality of life for people living with HIV and accumulate domestic clinical experience with this advanced treatment approach.