Allergic rhinitis （AR） is one of the most common chronic non-infectious inflammatory diseases in children. Traditional Chinese medicine （TCM） employs a comprehensive therapeutic system integrating treatment by stages and syndrome differentiation and treatment， demonstrating significant advantages in the management of pediatric AR. This article systematically reviews the clinical treatment methods and underlying mechanisms of TCM for pediatric AR in recent years. It is found that internal therapies （such as herbal formulas or Chinese patent medicines like Xiaoqinglong decoction， Yiqi tuomin decoction）， external therapies （including intradermal needles， acupoint application， tuina， and herbal nasal therapy）， as well as combined internal and external approaches （oral herbs combined with acupoint application）， have demonstrated significant effects in alleviating clinical symptoms， improving immune indicators， and reducing recurrence rates in children with AR. The underlying mechanisms are primarily associated with the regulation of signaling pathways such as Toll-like receptor/nuclear factor-kappa B and mitogen-activated protein kinase， thereby modulating immune balance， suppressing inflammatory responses， inhibiting pyroptosis， reducing mucus secretion， and promoting nasal mucosal repair.

Refinement and standardisation of the management of clinical diagnostic and treatment operations is a key aspect of achieving high-quality development in hospitals.By analysing the management status quo of clinical diagnosis and treatment operations in hospitals,it combed the problems existing in this field.Based on the closed-loop management model,it proposed measures and recommendations to promote the continuous optimisation of the management of clinical diagnostic operations in hospitals.Hospitals should establish hospital-level operation catalog and conduct classified management,authorize operators and dynamically adjust them,carry out operation quality management,pay attention to information management of operation management,and combine operation management with physician performance management.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Objective:To develop and evaluate a deep learning-based automatic measurement model for panoramic ultrasound biomicroscopy (UBM) images.Methods:A diagnostic test study was conducted.Preoperative UBM examination results of 372 patients who underwent implantable collamer lens (ICL) implantation were collected at the Eye Center of Renmin Hospital of Wuhan University between February 2021 and March 2023.A total of 1 368 panoramic UBM images were obtained to establish an image database.The dataset was divided into a training set (760 images), a validation set (86 images) and an internal test set (522 images).An expert panel consisting of three ophthalmologists annotated the images.The UNet+ + network was used to automatically segment anterior segment tissues, such as the cornea, lens and iris.In addition, image processing techniques and geometric localization algorithms were developed to automatically identify the anatomical landmarks of pupil diameter (PD), anterior chamber depth (ACD), angle-to-angle distance (ATA) and sulcus-to-sulcus distance (STS) to complete the measurement of these parameters.Additionally, 480 panoramic UBM images of 135 patients (240 eyes) from Aier Eye Hospital of Wuhan University were used as an external test set to further evaluate the performance of the model in different centers.The consistency between the measurements from the model and expert panel, the Pentacam system was assessed.Finally, 150 images were randomly selected from the external test set for a human-machine comparison to further evaluate the model's performance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY-2022-K109) and Aier eye Hospital of Wuhan University (No.2023IRBKY120903).Written informed consent was obtained from each subject.Results:In the internal test dataset and external test dataset, with manual labeling as the reference standard, the model achieved a mean Dice coefficient of not less than 0.882.At least 95.65% of the anatomical landmark localization results had Euclidean distance differences within 250 μm.The intraclass correlation coefficients (ICCs) for the measurements of PD, ACD, angle-to-angle ATA, and STS were at least 0.958, with mean relative errors not exceeding 2.407%.With the Pentacam measurements as the reference standard, the ICCs for PD in the internal and external test sets were 0.540 and 0.466, respectively, while the ICCs for ACD were 0.946 and 0.908, respectively.In the human-machine comparison, the ICCs between the model's measurements and those of senior experts were all not lower than 0.969.Conclusions:The deep learning-based model can automatically measure anterior segment parameters from preoperative panoramic UBM images of patients undergoing ICL surgery.The model demonstrates a consistency comparable to that of senior experts, while providing higher efficiency.In terms of ACD measurement, the model shows good agreement between the measurements obtained from the model and Pentacam system.

Refinement and standardisation of the management of clinical diagnostic and treatment operations is a key aspect of achieving high-quality development in hospitals.By analysing the management status quo of clinical diagnosis and treatment operations in hospitals,it combed the problems existing in this field.Based on the closed-loop management model,it proposed measures and recommendations to promote the continuous optimisation of the management of clinical diagnostic operations in hospitals.Hospitals should establish hospital-level operation catalog and conduct classified management,authorize operators and dynamically adjust them,carry out operation quality management,pay attention to information management of operation management,and combine operation management with physician performance management.

Objective To explore the pneumoperitoneum signs of neonates on the bedside abdominal lying film.Methods The pneumoperitoneum signs of 52 neonates on the bedside abdominal lying films were analyzed retrospectively.Results Among 52 neonates with pneumoperitoneum,2 cases had no perforation,and there were 50 cases of digestive tract perforation,with 22 cases of gastric perforation,17 cases of small intestinal perforation and 11 cases of large intestinal perforation.Congenital muscular defect of gastric wall and necrotizing enterocolitis(NEC)were the most common causes of perforation.Forty-three cases with anteroposterior films all had pneumoperitoneum signs;and in 9 cases with anteroposterior and lateral films,6 cases with anteroposterior and lateral films all showed pneumoperitoneum signs,while 3 cases showed pneumoperitoneum signs only on lateral films.Pneumoperitoneum signs included 38 episodes of liver falciform ligament signs,37 episodes of football signs,22 episodes of Rigler signs,21 episodes of round liver ligament signs,10 episodes of liver area bright shadows,9 episodes of inverted"V"signs,6 episodes of scrotal gas,5 episodes of triangular signs,4 episodes of Cupola signs and 1 episodes of dolphin sign.Two or more signs were seen in 46 cases and three or more signs were seen in 31 cases.There was no statistically significant difference in the pneumoperitoneum signs except for scrotal gas among the three groups of gastric,small intestinal and large intestinal perforations(P>0.05).Conclusion Various signs such as liver falciform ligament signs,football signs,Rigler signs and round liver ligament signs can be seen on the bedside abdominal lying film for neonates pneumoperitoneum,and understanding the above signs is conducive to rapid and accurate diagnosis.

A novel technology is proposed for non-contact and real-time detection of atrial fibrillation using millimeter-wave radar.A 60 GHz PCR millimeter wave radar is used to continuously detect the chest echo signal of the subject.After signal acquisition,I-Q signal is generated through I-Q demodulation,and the signal phase information is extracted using effective points phase trend evaluation for obtaining the signals from oscillations in the chest wall,from which the respiratory signals and cardiac signals are extracted through digital filtering for the analysis of cardiac movement.Whether the atrial fibrillation occurs or not is determined by the characteristics of atrial fibrillation wave in the time domain.The effective points phase trend evaluation for extracting more accurate signal phase information and the time-domain method for real-time atrial fibrillation detection are the innovations of the study.The experimental results show that the proposed method achieves a detection accuracy of 99.2%in clinic.

Clinical pathway has great similarity with DRG,and plays an important role in standardizing diagnosis and treatment behavior and controlling medical expenses.Based on the analysis of the relationship between DRG payment method reform and clinical pathway,taking a public hospital in Wuhan City,Hubei Province as an example,the clinical pathway implementation strategy of large public hospitals under the DRG payment method reform was explored from five aspects:management system,suitable disease types,doctor's order setting,information system,training and assessment.

Objective:To investigate the influence of combining therapy of massage on sacro-2 to sacro-4 spinal cord reflexion area and anal dilatation therapy on constipation after cerebral apoplexy and promote the rehabilitation of defecation function in patients with constipation after stroke.Methods:Aandomized controlled study method was chosen, 80 patients with constipation after cerebral apoplexy treated in Guangzhou Traditional Chinese Medicine Hospital from August 2018 to July 2019 were selected as research subjects by convenience sampling. The enrolled patients were divided into 2 groups, 40 to the observation group and 40 to the control group by random number table method. On the basis of routine constipation related nursing measures, the control group was given anal dilatation therapy, while the observation group′s treatment was given massage on sacro-2 to sacro-4 spinal cord reflexion area combined with anal dilatation therapy. Before intervention and after intervention, the changes of therapeutic effect of constipation effect, constipation symptoms scores and the degree of neurological deficit were all compared between the two groups.Results:There were 22 males and 18 females in the observation group; age ranged from 40 to 75 (63.33 ± 8.49) years old; in the control group, there were 23 males and 17 females, aged 41-74 (63.03 ± 7.60) years old. Before intervention, there was no statistically significant difference in constipation symptom scores and neurological deficits between the two groups (both P>0.05). After intervention, the score of constipation symptoms was (3.80 ± 2.05) points and the score of the degree of neurological deficit was (7.58 ± 2.69) points in the observation group, both lower than (5.18 ± 3.52) points and (8.90 ± 2.73) points in the control group with statistically significant differences between the two groups ( t values were respectively -2.13 and -2.19, both P<0.05). The total efficacy of the observation group was 97.50% (39/40), which was significantly higher than 87.50% (35/40) of the control group with statistically significant differences between the two groups ( χ2 = - 2.11, P<0.05). Conclusions:Nursing intervention of massage on sacro-2 to sacro-4 spinal cord reflexion area combined with anus dilatation therapy on constipation after cerebral apoplexy can effectively reduce the symptoms of constipation and lowered the degree of neurological deficit, which is beneficial to the functional rehabilitation of patients with cerebral apoplexy.

White-matter tracts play a pivotal role in transmitting sensory and motor information, facilitating interhemispheric communication and integrating different brain regions. Meanwhile, sensorimotor disturbance is a common symptom in patients with major depressive disorder (MDD). However, the role of aberrant sensorimotor white-matter system in MDD remains largely unknown. Herein, we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls (HCs) from the DIRECT consortium. White-matter networks were derived from magnetic resonance imaging (MRI) data by combining voxel-based morphometry (VBM) and three-dimensional discrete wavelet transform (3D-DWT) approaches. Support vector machine (SVM) analysis was performed to discriminate MDD patients from HCs. The results indicated that the network topological changes in node degree, node efficiency, and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD. Using network nodal topological properties as classification features, the SVM model could effectively distinguish MDD patients from HCs. These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.
Humans ; Depressive Disorder, Major/pathology* ; White Matter/pathology* ; Male ; Female ; Support Vector Machine ; Adult ; Magnetic Resonance Imaging ; Middle Aged ; Case-Control Studies ; Sensorimotor Cortex ; Brain