BACKGROUND: The available evidence regarding the benefits of percutaneous coronary intervention (PCI) on patients receiving dialysis with coronary artery disease (CAD) is limited and inconsistent. This study aimed to evaluate the association between PCI and clinical outcomes as compared with medical therapy alone in patients undergoing dialysis with CAD in China. METHODS: This multicenter, retrospective study was conducted in 30 tertiary medical centers across 12 provinces in China from January 2015 to June 2021 to include patients on dialysis with CAD. The primary outcome was major adverse cardiovascular events (MACE), defined as a composite of cardiovascular death, non-fatal myocardial infarction, and non-fatal stroke. Secondary outcomes included all-cause death, the individual components of MACE, and Bleeding Academic Research Consortium criteria types 2, 3, or 5 bleeding. Multivariable Cox proportional hazard models were used to assess the association between PCI and outcomes. Inverse probability of treatment weighting (IPTW) and propensity score matching (PSM) were performed to account for potential between-group differences. RESULTS: Of the 1146 patients on dialysis with significant CAD, 821 (71.6%) underwent PCI. After a median follow-up of 23.0 months, PCI was associated with a 43.0% significantly lower risk for MACE (33.9% [ n  = 278] vs . 43.7% [ n  = 142]; adjusted hazards ratio 0.57, 95% confidence interval 0.45-0.71), along with a slightly increased risk for bleeding outcomes that did not reach statistical significance (11.1% vs . 8.3%; adjusted hazards ratio 1.31, 95% confidence interval, 0.82-2.11). Furthermore, PCI was associated with a significant reduction in all-cause and cardiovascular mortalities. Subgroup analysis did not modify the association of PCI with patient outcomes. These primary findings were consistent across IPTW, PSM, and competing risk analyses. CONCLUSION This study indicated that PCI in patients on dialysis with CAD was significantly associated with lower MACE and mortality when comparing with those with medical therapy alone, albeit with a slightly increased risk for bleeding events that did not reach statistical significance.
Humans ; Percutaneous Coronary Intervention/methods* ; Male ; Female ; Coronary Artery Disease/drug therapy* ; Retrospective Studies ; Renal Dialysis/methods* ; Middle Aged ; Aged ; China ; Proportional Hazards Models ; Treatment Outcome

OBJECTIVE: To investigate the influence of different scanning conditions on the image quality of medical electron accelerator cone-beam computed tomography (CBCT) and provide a reference for the selection of scanning conditions for different body parts. Methods Set different scanning conditions, the Catphan 503 phantom was scanned using CBCT parameters to analyze the influence of spatial resolution, noise, uniformity, spatial geometric accuracy, and low-contrast resolution on the image quality of CBCT. RESULTS: For the head, chest, and abdomen, with the increase in scanning parameter values, the noise value decreased by 47.4%, 26.1%, and 51.3% respectively, and the uniformity values decreased by 30.2%, 26.6%, and 47.9% respectively. The low-contrast resolution values decreased by 50.6%, 34.2%, and 12.0%. The influence of different scanning conditions on spatial geometric accuracy and spatial resolution is not significant. CONCLUSION Different scanning parameters have a certain influence on the image quality of medical electron accelerator CBCT. Lower scanning parameters can be selected based on individual patients to reduce the additional radiation dose, providing a reference for the safe application of CBCT image guidance in radiotherapy.
Cone-Beam Computed Tomography/instrumentation* ; Phantoms, Imaging ; Particle Accelerators

Objective:To compare and analyze the differences in positioning errors and placement outside the target area between two different image-guided systems(Halcyon and Synergy)in radiotherapy for cervical cancer.Methods:The data of 40 patients with cervical cancer who received treatment in Dezhou People's Hospital from March 2023 to June 2023 were retrospectively selected.Each patient was treated respectively with Halcyon linear accelerator and Synergy linear accelerator,with 20 cases for each treatment method.All patients underwent cone beam computed tomography(CBCT)at kV level to conduct image scanning before radiotherapy,and the obtained CBCT images were matched with the positioned CT images by online.The registration results of left and right(x),head and foot(y)and front and back(z)of three translation direction,and pitch(Rx),rotation(Ry)and deflection(Rz)directions of rotation direction were respectively obtained.The margin of planning target volume(MPTV)was calculated according to positioning expansion formula.The differences of positioning errors and target area expansion between Halcyon and Synergy image-guided systems were compared and analyzed.Results:Halcyon and Synergy image-guided systems obtained respectively 479 and 447 sets of CBCT images.The translational errors of Halcyon image-guided system on x,y,and z directions were respectively(-0.03±0.21),(0.12±0.63)and(0.02±0.15)cm,and the rotational errors of that on Rx,Ry and Rz directions were respectively(0.38±1.26)°,(-0.40±1.02)°,and(0.07±1.07)°.The translational errors of Synergy image-guided system were respectively(-0.07±0.18),(0.08±0.49)and(0.11±0.22)cm on the three directions,and the rotational errors of that were respectively(0.28±1.29)°,(-0.29±1.29)° and(-0.16±1.20)°.The translational error values on the y direction of both image-guided system were larger than that on x and z directions,and the absolute values of the range of translational errors of them were basically within 5 mm.There were no statistically significant difference in the positioning errors of rotation on Rx and Ry directions between Halcyon and Synergy image-guided systems(P＞0.05),while there was a statistically significant difference in the positioning error of rotation on Rz direction between them(t=-3.06,P＜0.05).The MPTV values of Halcyon image-guided system on x,y and z directions were respectively 0.4,1.4 and 0.3 cm,and those of Synergy image-guided system were respectively 0.4,0.9 and 0.5 cm.The expansion boundary of target area of Halcyon image-guided system on the y direction was larger than that of Synergy image-guided system,and that on other directions were all less or equal to 0.5 cm.Conclusion:The MPTV values of Halcyon and Synergy image-guided systems can meet clinical requirements in radiotherapy.The positioning errors and the tube current of the scan of Halcyon image-guided system were larger than those of Synergy image-guided system,but the scanning time and treatment time of that were significantly lower than those of Synergy image-guided system.Different treatment systems can be selected individually for patients according to their different conditions.

Paraplegia caused by spinal cord injury is a serious neurological complication, for which surgery is currently the main treatment method. Due to different surgical approaches, patients are usually expected to maintain a passive prone position for a long time or switch between the supine and prone positions. Affected by multiple factors such as neurogenic sensory disorders, pathological changes in muscle tone and operative duration, the risk of intraoperative acquired pressure injury (IAPI) is significantly increased. Current clinical prevention strategies for IAPI in these patients predominantly focus on localized pressure relief during positioning, lacking systematic, standardized comprehensive prevention protocols or evidence-based guidelines. To address it, Department of Nursing, Orthopedics Branch, China International Exchange and Promotive Association for Medical and Health Care, Spinal Trauma Professional Committee, Orthopedics Branch, Chinese Medical Doctor Association, Nursing Group of Spine and Spinal Cord Professional Committee of Chinese Association of Rehabilitation Medicine organized experts in relevant fields to formulate Guideline for the prevention of intraoperative acquired pressure injury in paraplegic patients with spinal cord injury ( version 2025), based on evidence-based medical evidence and latest research results and clinical practice at home and abroad. Eleven recommendations were put forward from the aspects of preoperative risk assessment, intraoperative prevention strategies, postoperative handover and monitoring, and supportive mechanisms for IAPI prevention, aiming to standardize the prevention measures and management strategies of IAPI in paraplegic patients with spinal cord injury and accelerate the recovery of patients and improve the therapeutic effect.

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 assess the association between temperature and risk of animal injury, and identifying vulnerable populations.Methods:Based on a time-stratified case-crossover design, the number of animal injuries monitored in hospitals of Guangdong Provincial Injury Surveillance System in 2011 and 2015-2016 was included, and the daily meteorological data were derived from the fifth generation of European ReAnalysis-Land, which was produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression combined with a distributed lagged nonlinear model was applied to analyze the association of temperature and animal-specific injuries. We also conducted stratified analysis by region, sex, age, occupation, and location of injury occurrence.Results:There was an almost linear relationship between temperature and the occurrence of animal injury. The excess risk ( ER) of animal injury was 2.65% (95% CI: 2.27%-3.04%) for a 1 ℃ rise in temperature with much higher risk of occurrence ( ER=9.34%, 95% CI: 7.57%-11.13%) for non-mammalian injury than that for mammalian injuries ( ER=2.30%, 95% CI: 1.90%-2.70%). Stratified analysis revealed that the occurrence of animal injury was more susceptible to temperature influences in urban ( ER=2.78%, 95% CI: 2.35%-3.21%), female ( ER=2.71%, 95% CI: 2.16%-3.27%), the elderly aged 60 years and above ( ER=3.05%, 95% CI: 1.65%- 4.47%), farmer ( ER=4.66%, 95% CI: 3.03%-6.32%) and agricultural area ( ER=10.63%, 95% CI: 7.57%-13.79%) than their correspondents. In terms of mammalian injury, dog bites showed the highest risk ( ER=2.71%, 95% CI: 2.12%-3.30%). In terms of non-mammalian,snake injuries were highly influenced by temperature ( ER=16.74%, 95% CI: 11.33%-22.40%). Conclusions:The ambient temperature rises could increase the risk of animal injury with much higher risk for non-mammalian than that for mammalian injuries. Our findings suggest that global warming may increase the risk and disease burden from animal injuries.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

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 assess the association between temperature and risk of animal injury, and identifying vulnerable populations.Methods:Based on a time-stratified case-crossover design, the number of animal injuries monitored in hospitals of Guangdong Provincial Injury Surveillance System in 2011 and 2015-2016 was included, and the daily meteorological data were derived from the fifth generation of European ReAnalysis-Land, which was produced by the European Centre for Medium-Range Weather Forecasts. Conditional logistic regression combined with a distributed lagged nonlinear model was applied to analyze the association of temperature and animal-specific injuries. We also conducted stratified analysis by region, sex, age, occupation, and location of injury occurrence.Results:There was an almost linear relationship between temperature and the occurrence of animal injury. The excess risk ( ER) of animal injury was 2.65% (95% CI: 2.27%-3.04%) for a 1 ℃ rise in temperature with much higher risk of occurrence ( ER=9.34%, 95% CI: 7.57%-11.13%) for non-mammalian injury than that for mammalian injuries ( ER=2.30%, 95% CI: 1.90%-2.70%). Stratified analysis revealed that the occurrence of animal injury was more susceptible to temperature influences in urban ( ER=2.78%, 95% CI: 2.35%-3.21%), female ( ER=2.71%, 95% CI: 2.16%-3.27%), the elderly aged 60 years and above ( ER=3.05%, 95% CI: 1.65%- 4.47%), farmer ( ER=4.66%, 95% CI: 3.03%-6.32%) and agricultural area ( ER=10.63%, 95% CI: 7.57%-13.79%) than their correspondents. In terms of mammalian injury, dog bites showed the highest risk ( ER=2.71%, 95% CI: 2.12%-3.30%). In terms of non-mammalian,snake injuries were highly influenced by temperature ( ER=16.74%, 95% CI: 11.33%-22.40%). Conclusions:The ambient temperature rises could increase the risk of animal injury with much higher risk for non-mammalian than that for mammalian injuries. Our findings suggest that global warming may increase the risk and disease burden from animal injuries.

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.