Objective To compare the differences between swept-source optical coherence tomography angiography(SS-OCTA)and ultra-wide-field fluorescein angiography(UWFA)in detecting non-perfusion areas(NPs)in patients with diabetic retinopathy(DR),to evaluate the accuracy of SS-OCTA in predicting NPs outside its visible range,and to explore the distribution patterns of NPs.Methods A retrospective analysis was made on 69 DR patients(88 eyes)who under-went both UWFA and SS-OCTA examinations at the Ophthalmology Department of Sichuan Provincial People's Hospital from December 2022 to September 2024.Manual NP labeling was conducted to compare the detection rate of NPs between the two imaging techniques.The distribution patterns of NPs and the accuracy of SS-OCTA for predicting NPs outside its visible range were also analyzed.Results In a scanning area of 20 mm x 24 mm,the overall NP detection rate by SS-OCTA was 47.40％,with UWFA taken as the standard.The NP detection rate by SS-OCTA was 51.56％in the superotemporal quad-rant,58.35％in the inferotemporal quadrant,45.50％in the superonasal quadrant,and 43.17％in the inferonasal quad-rant.Most NPs occurred in the inferonasal quadrant,accounting for 41.71％of the total NP.The accuracy of SS-OCTA in predicting NPs was 75.00％in the superonasal quadrant and 78.41％in the inferonasal quadrant.The ischemic indices(ISI)of the two imaging techniques were highly positively correlated(r2=0.74).Conclusion Although SS-OCTA can-not yet fully replace UWFA for NP detection in DR patients due to a small visible range,it is still an effective tool to assess retinal ischemia.SS-OCTA has the ability to predict NPs outside its visible range in its scanning range.The inferonasal quadrant is the region where NPs occur most frequently in DR patients,so it is suggested that special attention should be paid to this region in early diagnosis and follow-up periods.

Objective Deep learning provides strong technical support for early diagnosis,lesion segmentation,and treatment prediction of retinal diseases,significantly improving the efficiency and accuracy of diagnosis.But it also faces challenges in terms of different applicability and performance differences of the model,mainly due to the differences in fea-ture extraction ability,computational complexity,and clinical adaptability among different network structures,which make them have different advantages and limitations in different application scenarios.By systematically searching relevant litera-ture in PubMed and Web of Science databases over the past 5 years,this article summarizes the most commonly used deep learning network architectures in common vitreoretinal diseases,summarizes their different advantages and limitations,and analyzes the best application directions of each architecture in the field of ophthalmology,providing reference and inspira-tion for future research.

Objective To construct a prediction model for atrial fibrillation(AF)after pacemaker implantation based on clinical features and plasma atrial natriuretic peptide(ANP)and brain na-triuretic peptide(BNP).Methods A retrospective analysis was conducted on 242 patients under-going pacemaker implantation in our department from January 2020 to October 2023.According to the occurrence of postoperative AF or not,they were divided into an AF group(61 cases)and a non-AF group(181 cases).The risk factors of AF after pacemaker implantation were analyzed,and a risk prediction model of AF after pacemaker implantation was constructed based on clinical features and plasma ANP and BNP levels.Results The AF group had significantly advanced age,larger proportions of hypertension and coronary heart disease,larger left ventricular diameter,and higher ANP,BNP,IL-6 and IL-8 levels,but lower proportion of using calcium antagonists when compared with the non-AF group(P＜0.01).Binary logistic regression analysis showed that hy-pertension,coronary heart disease,ANP,BNP and IL-6 were risk factors(P＜0.05,P＜0.01),and taking calcium antagonists was protective factor for AF after pacemaker implantation(P＜0.05).Hosmer Lemeshow fitting test indicated the model had a good fitness(x2=7.264,P=0.508).ROC curve analysis showed that the area under curve(AUC)value of the risk model for AF after pacemaker implantation in the training set was 0.826(95％CI:0.768-0.884),with an accuracy of 79.3％(192/242),and the AUC value of the model in the validation set was 0.835(95％CI:0.733-0.938).Conclusion Our AF prediction model based on clinical features and plasma ANP and BNP had good performance,and can provide auxiliary reference in predicting AF in patients undergoing pacemaker implantation.

Objective To compare the differences between swept-source optical coherence tomography angiography(SS-OCTA)and ultra-wide-field fluorescein angiography(UWFA)in detecting non-perfusion areas(NPs)in patients with diabetic retinopathy(DR),to evaluate the accuracy of SS-OCTA in predicting NPs outside its visible range,and to explore the distribution patterns of NPs.Methods A retrospective analysis was made on 69 DR patients(88 eyes)who under-went both UWFA and SS-OCTA examinations at the Ophthalmology Department of Sichuan Provincial People's Hospital from December 2022 to September 2024.Manual NP labeling was conducted to compare the detection rate of NPs between the two imaging techniques.The distribution patterns of NPs and the accuracy of SS-OCTA for predicting NPs outside its visible range were also analyzed.Results In a scanning area of 20 mm x 24 mm,the overall NP detection rate by SS-OCTA was 47.40％,with UWFA taken as the standard.The NP detection rate by SS-OCTA was 51.56％in the superotemporal quad-rant,58.35％in the inferotemporal quadrant,45.50％in the superonasal quadrant,and 43.17％in the inferonasal quad-rant.Most NPs occurred in the inferonasal quadrant,accounting for 41.71％of the total NP.The accuracy of SS-OCTA in predicting NPs was 75.00％in the superonasal quadrant and 78.41％in the inferonasal quadrant.The ischemic indices(ISI)of the two imaging techniques were highly positively correlated(r2=0.74).Conclusion Although SS-OCTA can-not yet fully replace UWFA for NP detection in DR patients due to a small visible range,it is still an effective tool to assess retinal ischemia.SS-OCTA has the ability to predict NPs outside its visible range in its scanning range.The inferonasal quadrant is the region where NPs occur most frequently in DR patients,so it is suggested that special attention should be paid to this region in early diagnosis and follow-up periods.

Objective Deep learning provides strong technical support for early diagnosis,lesion segmentation,and treatment prediction of retinal diseases,significantly improving the efficiency and accuracy of diagnosis.But it also faces challenges in terms of different applicability and performance differences of the model,mainly due to the differences in fea-ture extraction ability,computational complexity,and clinical adaptability among different network structures,which make them have different advantages and limitations in different application scenarios.By systematically searching relevant litera-ture in PubMed and Web of Science databases over the past 5 years,this article summarizes the most commonly used deep learning network architectures in common vitreoretinal diseases,summarizes their different advantages and limitations,and analyzes the best application directions of each architecture in the field of ophthalmology,providing reference and inspira-tion for future research.

Objective To construct a prediction model for atrial fibrillation(AF)after pacemaker implantation based on clinical features and plasma atrial natriuretic peptide(ANP)and brain na-triuretic peptide(BNP).Methods A retrospective analysis was conducted on 242 patients under-going pacemaker implantation in our department from January 2020 to October 2023.According to the occurrence of postoperative AF or not,they were divided into an AF group(61 cases)and a non-AF group(181 cases).The risk factors of AF after pacemaker implantation were analyzed,and a risk prediction model of AF after pacemaker implantation was constructed based on clinical features and plasma ANP and BNP levels.Results The AF group had significantly advanced age,larger proportions of hypertension and coronary heart disease,larger left ventricular diameter,and higher ANP,BNP,IL-6 and IL-8 levels,but lower proportion of using calcium antagonists when compared with the non-AF group(P＜0.01).Binary logistic regression analysis showed that hy-pertension,coronary heart disease,ANP,BNP and IL-6 were risk factors(P＜0.05,P＜0.01),and taking calcium antagonists was protective factor for AF after pacemaker implantation(P＜0.05).Hosmer Lemeshow fitting test indicated the model had a good fitness(x2=7.264,P=0.508).ROC curve analysis showed that the area under curve(AUC)value of the risk model for AF after pacemaker implantation in the training set was 0.826(95％CI:0.768-0.884),with an accuracy of 79.3％(192/242),and the AUC value of the model in the validation set was 0.835(95％CI:0.733-0.938).Conclusion Our AF prediction model based on clinical features and plasma ANP and BNP had good performance,and can provide auxiliary reference in predicting AF in patients undergoing pacemaker implantation.

The corneal epithelium, an essential refractive interface, plays an integral role in the corneal healing after corneal refractive surgery. All existing corneal refractive surgeries entail a degree of corneal epithelial remodeling; however, excessive epithelial remodeling precipitates adverse outcomes on the refractive correction efficacy of such surgeries. This review summarizes the application of corneal epithelial remodeling in the corneal refractive surgery, and more comprehensively investigates the influencing factors of perioperative epithelial remodeling after corneal refractive surgery, with a view to augmenting the safety, efficacy, predictability, and stability of corneal refractive surgical outcomes.

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.

Abstract: Objective To investigate the expression of T cell immunoglobulin and mucin domain-containing protein 3 (Tim-3) on the surface of T cells in patients with brucellosis (Bm), as well as the expression of interleukin-10 (IL-10) and transforming growth factor beta (TGF-β) in serum, and to analyze the differential expression of these indicators in patients with acute and chronic brucellosis, in order to provide new approaches for the differential diagnosis of acute and chronic brucellosis. Methods A total of 56 patients diagnosed with brucellosis at the First Affiliated Hospital of Xinjiang Medical University from April 2023 to September 2023 were selected, including 31 patients in the acute phase and 25 patients in the chronic phase. Additionally, 35 healthy individuals underwent routine physical examinations within the same period served as healthy controls. Flow cytometry was used to detect and compare Tim-3 levels on the CD4+ T cells' surface among the groups. Levels of serum IL-10 and TGF-β were measured and compared using CBA and ELISA, respectively, and the relationship of these factors with the staging of brucellosis patients was analyzed. Results The proportions of Tim-3+CD3+CD4+T cells in the control group, acute group, and chronic group were (2.56±1.25)%, (5.14±1.98)%, and (13.66±2.66)%, respectively. The Tim-3 levels in the patients with brucellosis were higher than those in the healthy control group, with the chronic group showing even higher levels, and these differences were statistically significant (P<0.05). The levels of IL-10 and TGF in the patient group were higher than those in the healthy control group, with the chronic group exhibiting significantly higher levels of IL-10 and TGF-β than the acute group, also presenting statistically significant differences (P<0.05). The areas under the ROC curve for predicting chronic brucellosis with Tim-3, IL-10, and TGF-β scores were 0.876, 0.865, and 0.663, respectively. Conclusions There are certain differences in the expression of Tim-3, serum IL-10, and TGF-β among patients with brucellosis, with high expression indicating a potential transition to the chronic phase of the disease. Tim-3 has shown the best diagnostic performance. Therefore, as a diagnostic indicator, Tim-3 may provide new ideas and strategies for the treatment and differential diagnosis of brucellosis.

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.