Purpose: To confirm the clinical features of hemicentral retinal vein occlusion and identify predictors of visual outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with hemicentral retinal vein occlusion between January 2018 and December 2022 and followed for more than 6 months. Patients underwent intravitreal injections as necessary for intraretinal edema. Visual acuity, central macular thickness, ellipsoid zone damage, and the location of inner retinal layer edema were assessed. Patients were categorized into groups A and group B based on the visual acuity at 6 months. Results: In total, 20 eyes were followed, with 15 eyes observed for up to 12 months. Seven patients (35.0%) had diabetes and 11 (55.0%) had hypertension. There was a correlation between poor vision at 6 months and hypertension (p = 0.033). The visual acuity of all patients improved from a logMAR of 0.96 at the initial visit to a logMAR of 0.35 at 6 months (p = 0.005). In the group with good initial visual acuity, there were no significant changes in visual acuity during the follow-up period (p = 0.444). The group with good visual acuity at 6 months had a lower degree of photoreceptor ellipsoid zone disruption compared to the group with poor initial vision, indicating a normal structure (p = 0.015). Conclusions During follow-up of patients with hemicentral retinal vein occlusion, overall visual acuity improved over time. Patients with good initial acuity maintained it. Favorable visual outcomes can be expected if the ellipsoid zone has a normal structure at the time of the first examination.

Purpose: To confirm the clinical features of hemicentral retinal vein occlusion and identify predictors of visual outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with hemicentral retinal vein occlusion between January 2018 and December 2022 and followed for more than 6 months. Patients underwent intravitreal injections as necessary for intraretinal edema. Visual acuity, central macular thickness, ellipsoid zone damage, and the location of inner retinal layer edema were assessed. Patients were categorized into groups A and group B based on the visual acuity at 6 months. Results: In total, 20 eyes were followed, with 15 eyes observed for up to 12 months. Seven patients (35.0%) had diabetes and 11 (55.0%) had hypertension. There was a correlation between poor vision at 6 months and hypertension (p = 0.033). The visual acuity of all patients improved from a logMAR of 0.96 at the initial visit to a logMAR of 0.35 at 6 months (p = 0.005). In the group with good initial visual acuity, there were no significant changes in visual acuity during the follow-up period (p = 0.444). The group with good visual acuity at 6 months had a lower degree of photoreceptor ellipsoid zone disruption compared to the group with poor initial vision, indicating a normal structure (p = 0.015). Conclusions During follow-up of patients with hemicentral retinal vein occlusion, overall visual acuity improved over time. Patients with good initial acuity maintained it. Favorable visual outcomes can be expected if the ellipsoid zone has a normal structure at the time of the first examination.

Purpose: To confirm the clinical features of hemicentral retinal vein occlusion and identify predictors of visual outcomes. Methods: A retrospective analysis was conducted on patients diagnosed with hemicentral retinal vein occlusion between January 2018 and December 2022 and followed for more than 6 months. Patients underwent intravitreal injections as necessary for intraretinal edema. Visual acuity, central macular thickness, ellipsoid zone damage, and the location of inner retinal layer edema were assessed. Patients were categorized into groups A and group B based on the visual acuity at 6 months. Results: In total, 20 eyes were followed, with 15 eyes observed for up to 12 months. Seven patients (35.0%) had diabetes and 11 (55.0%) had hypertension. There was a correlation between poor vision at 6 months and hypertension (p = 0.033). The visual acuity of all patients improved from a logMAR of 0.96 at the initial visit to a logMAR of 0.35 at 6 months (p = 0.005). In the group with good initial visual acuity, there were no significant changes in visual acuity during the follow-up period (p = 0.444). The group with good visual acuity at 6 months had a lower degree of photoreceptor ellipsoid zone disruption compared to the group with poor initial vision, indicating a normal structure (p = 0.015). Conclusions During follow-up of patients with hemicentral retinal vein occlusion, overall visual acuity improved over time. Patients with good initial acuity maintained it. Favorable visual outcomes can be expected if the ellipsoid zone has a normal structure at the time of the first examination.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Objective To propose a lead attention network-based ST-T change recognition algorithm to detect ECG ST-T changes accurately.Methods Firstly,heartbeat signals were extracted through R-wave localization,and a 12-lead heartbeat matrix was generated by correlation-based screening and merging to realize data augmentation.Secondly,a lead attention module was constructed by combining depthwise convolution(DWConv)with the channel attention squeeze-and-excitation block(SE-block)structure to perceive the differences in ST-T status among electrocardiogram leads.Thirdly,the mapping output by two independent attention modules was fused and splicing with the original signal residual was carried out,so that attention information extraction and original information transfer were enhanced effectively.Finally,SE-ResNet was used as the backbone network to extract signal features to complete the classification and identification of ST-T changes.To validate the recognition performance of the proposed algorithm for ST-T changes in ECG,the 12-lead ECG data of 97 472 patients containing different ECG rhythms were collected for ablation and comparison experiments at the First Affiliated Hospital of Army Medical University.Results The proposed algorithm achieved an AUC of 0.965 with a sensitivity of 90.51%,specificity of 90.23%,positive predictive value of 89.24%and overall accuracy of 90.36%on an independent test set.Comparative analysis demonstrated superior performance to four benchmark architectures,including VGG16,ResNet18,MobileNetV3-Small and ShuffleNet,in terms of both classification accuracy and computational efficiency.Conclusion The algorithm designed can accurately detect ST-T changes and can be used for wearable ECG automatic analysis to assist in the early warning of cardiovascular diseases in both acute and chronic patients and highland residents.[Chinese Medical Equipment Journal,2025,46(7):1-11]

Postoperative infection of internal fixation of closed fractures the lower limbs in adults represents a devastating complication, characterized by diagnostic challenges, prolonged treatment duration and high disability rates. Current management of these infections faces multiple challenges, such as difficulties in early accurate diagnosis, and various controversies about the treatment plan, leading to poor overall diagnosis and treatment results. To address these issues, based on evidence-based medicine and principles with emphasis on scientific rigor, clinical applicability and innovation, the Trauma Branch of the Chinese Medical Association, Orthopedic Branch of the Chinese Medical Doctor Association, Orthopedics Branch of the Chinese Medical Association, and Trauma Orthopedics and Polytrauma Group of the Resuscitation and Emergency Committee of the Chinese Medical Doctor Association have collaboratively organized a panel of relevant experts to develop the Guideline for diagnosis and treatment of infection after internal fixation of closed lower limb fractures in adults ( version 2025). The guideline proposed 10 recommendations, aiming to provide a foundation for standardized diagnosis and treatment of postoperative infection in adults with closed lower limb fractures.

Purpose: Ejection fraction, measured as the fraction of blood ejected from the ventricle in each heartbeat using M-mode echocardiography, serves as a primary indicator of left ventricular systolic function. This study explores the correlation between blood pressure and left ventricular systolic function in neonates using M-mode echocardiography. Methods: Neonates who underwent echocardiography in the neonatal intensive care unit between January 2011 and December 2020 were retrospectively studied. Results: Our analyses showed a significant association between ejection fraction and systolic blood pressure, but not with diastolic or mean blood pressure—both of which are more sensitive to hypotension. Ejection fraction was also not significantly associated with heart rate, urine output, or inotropic support in this study, suggesting that factors influencing urine output may not directly relate to ejection fraction. Additionally, we found that higher systolic blood pressure was correlated with advanced gestational age, the absence of patent ductus arteriosus, and no need for fentanyl administration. Notably, lower gestational age and lack of mechanical ventilation were both associated with increased hourly urine output, suggesting that developmental maturity and respiratory stability may influence renal function. Conclusion Neonatal hypotension occurred secondary to decreased systolic cardiac function and peripheral vascular resistance. Neonatologists should carefully monitor the individual components of blood pressure and prescribe medications accordingly, considering that systolic blood pressure is correlated with ejection function.

This study aimed to assess the competency of artificial intelligence (AI) in pediatric dentistry and compare it with that of dentists. We used open-source data obtained from the Korea Health Personnel Licensing Examination Institute. A total of 32 item multiple-choice pediatric dentistry exam questions were included. Two AI-based chatbots (ChatGPT 3.5 and Gemini) were evaluated. Each chatbot received the same questions seven times in separate chat sessions initiated on April 25, 2024. The accuracy was assessed by measuring the percentage of correct answers, and consistency was evaluated using Cronbach’s alpha coefficient. Both ChatGPT 3.5 and Gemini demonstrated similar accuracy, with no significant differences observed between them. However, neither chatbot achieved the minimum passing score set by the Pediatric Dentistry National Examination. However, both chatbots exhibited acceptable consistency in their responses. Within the limits of this study, both AI-based chatbots did not sufficiently answer the pediatric dentistry exam questions. This finding suggests that pediatric dentists should be aware of the advantages and limitations of this new tool and effectively utilize it to promote patient health.

This study aimed to assess the competency of artificial intelligence (AI) in pediatric dentistry and compare it with that of dentists. We used open-source data obtained from the Korea Health Personnel Licensing Examination Institute. A total of 32 item multiple-choice pediatric dentistry exam questions were included. Two AI-based chatbots (ChatGPT 3.5 and Gemini) were evaluated. Each chatbot received the same questions seven times in separate chat sessions initiated on April 25, 2024. The accuracy was assessed by measuring the percentage of correct answers, and consistency was evaluated using Cronbach’s alpha coefficient. Both ChatGPT 3.5 and Gemini demonstrated similar accuracy, with no significant differences observed between them. However, neither chatbot achieved the minimum passing score set by the Pediatric Dentistry National Examination. However, both chatbots exhibited acceptable consistency in their responses. Within the limits of this study, both AI-based chatbots did not sufficiently answer the pediatric dentistry exam questions. This finding suggests that pediatric dentists should be aware of the advantages and limitations of this new tool and effectively utilize it to promote patient health.