Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical 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.

Nonunion of osteoporotic vertebral fractures (OVF), predominantly affecting the elderly, can lead to intractable pain, vertebral collapse, progressive kyphotic deformity, and neurological impairment, significantly compromising patients′ quality of life. There exists considerable debate on diagnosis and management of OVF, encompassing key issues such as clinical diagnosis and staging criteria for nonunion, surgical indications and procedure selection, and postoperative rehabilitation planning. Currently, there lacks standardized clinical guideline and expert consensus on the diagnosis and management of OVF nonunion in China. To address this gap, Minimally Invasive Surgery Group of Chinese Orthopedic Association, Osteoporosis Committee of Chinese Association of Orthopedic Surgeons, Prevention and Rehabilitation Committee for Osteoporosis of Chinese Association of Rehabilitation Medicine and Minimally Invasive Orthopedic Surgery Branch of China Association for Geriatric Care jointly organized domestic experts in spinal surgery, endocrinology, and rehabilitation to formulate the Clinical guideline for the diagnosis and treatment for nonunion of osteoporotic vertebral fractures ( version 2025), based on existing literature and clinical experience and adhering to principles of scientific rigor and practicality. The guideline provided 13 evidence-based recommendations encompassing diagnosis and treatment of OVF nonunion, aiming to standardize its clinical management.

Spinal surgical site infection (SSI), especially deep SSI after internal fixation is difficult in treatment, with long course of disease and poor prognosis. At present, there are many controversies in the diagnosis and treatment of spinal SSI, with unsatisfactory overall efficacy of its diagnosis and treatment. Besides, no diagnosis and treatment guideline based on evidence-based medicine has been in existence. To this end, the Spinal Infection Group of the Orthopedic Branch of the Chinese Medical Doctor Association and the Spinal Infection Group of the Spinal Surgery Branch of the Chinese Rehabilitation Medicine Association jointly organized relevant experts to formulate Evidence-based clinical guideline for the diagnosis and treatment of surgical site infection in spinal trauma ( version 2024) based on an evidence-based approach. A total of 10 recommendations were proposed on the diagnosis and treatment of spinal SSI, so as to provide a clinical reference for the diagnosis and treatment of spinal SSI.

The diagnosis and treatment resources for rare diseases in China are highly imbalanced. The basic diagnosis and treatment capabilities are weak, the diagnosis period for patients is long, and the rates of missed diagnosis and misdiagnosis are relatively high. The establishment of a hierarchical diagnosis and treatment system is the inevitable approach to enhancing the diagnosis and treatment standards of rare diseases. Currently, the implementation of the domestic hierarchical diagnosis and treatment system for rare diseases still confronts numerous challenges, such as ambiguous referral standards and processes of primary medical institutions, and ineffective information interaction among institutions at all levels. Thus, it is essential to facilitate high-level information construction for the hierarchical diagnosis and treatment of rare diseases. This paper explores the process of constructing a multidisciplinary joint remote diagnosis and treatment platform and a health management platform through informatization, with the hope of establishing two closed loops of digital diagnosis and treatment services and health follow-up management for patients with rare diseases, as well as achieving timely diagnosis and lifelong health management for patients. It integrates and optimizes auxiliary diagnostic tools, promotes the rapid dissemination of rare disease diagnosis and treatment experiences to the grassroots, enhances the information construction level of the hierarchical diagnosis and treatment system, and endeavors to address the practical predicament of weak diagnosis and treatment capabilities of rare diseases in grassroots medical institutions. Additionally, this paper proposes an essential approach for multi-dimensional independent innovation to guide the popularization of efficient and high-quality rare disease diagnosis and treatment services. By encompassing innovating the rare disease diagnosis and treatment collaboration network and multidisciplinary diagnosis and treatment model, facilitating the application of the latest biomedical and informatics technologies to the grassroots, and constructing a national intelligent data platform for rare disease innovation, a new model for rare disease services with Chinese characteristics will be established. This will significantly enhance the medical treatment level of rare diseases in China and strive for more benefits for patients.

Spinal surgical site infection (SSI), especially deep SSI after internal fixation is difficult in treatment, with long course of disease and poor prognosis. At present, there are many controversies in the diagnosis and treatment of spinal SSI, with unsatisfactory overall efficacy of its diagnosis and treatment. Besides, no diagnosis and treatment guideline based on evidence-based medicine has been in existence. To this end, the Spinal Infection Group of the Orthopedic Branch of the Chinese Medical Doctor Association and the Spinal Infection Group of the Spinal Surgery Branch of the Chinese Rehabilitation Medicine Association jointly organized relevant experts to formulate Evidence-based clinical guideline for the diagnosis and treatment of surgical site infection in spinal trauma ( version 2024) based on an evidence-based approach. A total of 10 recommendations were proposed on the diagnosis and treatment of spinal SSI, so as to provide a clinical reference for the diagnosis and treatment of spinal SSI.

"The Expert Group on Tumor Ablation Therapy of Chinese Medical Doctor Association, The Tumor Ablation Committee of Chinese College of Interventionalists, The Society of Tumor Ablation Therapy of Chinese Anti-Cancer Association and The Ablation Expert Committee of the Chinese Society of Clinical Oncology" have organized multidisciplinary experts to formulate the consensus for thermal ablation of pulmonary subsolid nodules or ground-glass nodule (GGN). The expert consensus reviews current literatures and provides clinical practices for thermal ablation of GGN. The main contents include: (1) clinical evaluation of GGN, (2) procedures, indications, contraindications, outcomes evaluation and related complications of thermal ablation for GGN and (3) future development directions.
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Objective:To analyze the learning effect of laparoscopic radical cystectomy(LRC)+ modified ileal conduit(MIC).Methods:From 2014 to 2019, 42 patients underwent MIC and their clinical data was retrospectively analyzed. 34 operations were performed by surgeon 1 and 8 operations by surgeon 2. We divided the 34 patients of surgeon 1 into three groups according to their surgical sequence (group A, 1st to 12th; group B, 13th to 23th; group C, 24 th to 34 th), the 8 cases of surgeon 2 was regarded as group D. The history of abdomen surgery in the 4 groups were 0, 1, 4, 3 cases, respectively ( P<0.05). There was no significant difference of the other baseline characteristics, such as age, BMI, American Society of Anesthesiologists. Then we compared several variables between the 4 groups like operation time, time of ileal conduit construction, blood loss, complication rate, lymph node yield, surgical margin, etc. The key steps of the MIC included isolating terminal ileum when the mesentery was transilluminated, performing end-to-end reflux ureterointestinal anastomosis after the efferent loop was fixed, closing the rent of the retroperitoneum. Results:All operations were performed intracorporeally with no transition to open surgery. The operative time for group A, B, C were 330.0(320.0, 360.0)min, 300.0(250.0, 308.0)min, 270.0(216.0, 324.0)min, respectively ( P =0.010). The time of ileal conduit construction of the 3 groups were 136.5(131.3, 147.5)min, 92.0(79.0, 119.0)min, 79.0(72.0, 115.0)min, respectively ( P <0.001). In addition, the difference of the two variables above between A and B, A and C groups separately reached statistical significance ( P<0.05), while the difference between B and C groups did not ( P>0.05). Other variables, such as blood loss, complication rate, lymph node yield, surgical margin, between the 3 groups reached no statistical significance ( P>0.05). The operative time of group D was 420.0(350.0, 450.0)min, and it reached statistical significance ( P<0.05) when compared with group A. There were no significant differences in other variables, such as blood loss, complication rate, lymph node yield, surgical margin, among the 2 groups ( P>0.05). Conclusions:The learning effect of LRC+ MIC was obvious. When surgeon volume increased, the operative time decreased significantly. Variables like estimated blood loss and complication rate of the 2 surgeons did not reached significant difference, which indicated reproductivity and safety of this procedure.

Objective:To investigate the effect of Demodex palpebralis infestation and meibomian gland dysfunction(MGD) on the incidence of recurrent corneal erosion syndrome (RCES).Methods:A case-control study was performed.Thirty eyes of 30 RCES patients were enrolled from January to June 2018 in Hanyang Hospital of Wuhan Aier Eye Hospital, and served as the RCES group.Thirty-one eyes of 31 simple ametropia patients with matched age and gender were enrolled at the same time and served as the control group.Eyelash microscopic examination was performed for Demodex counting, slit-lamp examination was performed to observe the condition of meibomian gland.Keratograph 5M examination was performed to detect the morphological changes in the meibomian glands.This study was approved by the Ethics Committee of Wuhan Aier Eye Hospital.All subjects were aware of the method and purpose of this study.Results:The average meibomian glands score was 4(3, 4) in the RCES group, which was significantly higher than 2(1, 3) in the control group (Z=-4.55, P=0.00). The average meibomian gland secretion score was 15.5(11.0, 16.8) in the RCES group, which was significantly higher than 8.0(5.5, 10.0) in the control group (Z=-3.97, P=0.00). The average Demodex numbers was 8(4, 9) and 0(0, 2) in the RCES and control groups, respectively, with a significant difference between them (Z=-4.13, P<0.00). The average Demodex infection rate was 83.3% (25/30) and 38.7% (12/31) in the RCES and the control groups, respectively (χ 2=7.60, P<0.01). The recurrence frequency showed a positive correlation with the meibomian glands scores (r s=0.70, P<0.01), meibomian gland secretion scores (r s=0.47, P=0.04) and Demodex numbers (r s=0.73, P<0.01). Conclusions:The infection rate of Demodex palpebralis and the degree of MGD are obviously elevated in RCES patients, and are associated with the relapse frequency of RCES.