Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.

Objective:To investigate the feasibility and clinical effects of the application of augmented reality (AR) navigation on assisted design of the chimeric twin-paddled anterolateral thigh perforator flap (ALTPF) in reconstruction of soft tissue defects in extremities.Methods:From June 2017 to June 2023, 8 patients with soft tissue defects in extremities received reconstruction of chimeric twin-paddled ALTPF designed with the assistance of AR navigation in Department of Hand & Foot Microsurgery Orthopaedics, Guigang City People’s Hospital. All of them were traffic accidents or machine injuries, with 3 cases of calf, 2 cases of ankle, 1 case of foot, and 2 cases of hand defects. All the wounds were wide or irregular (defect sized 14 cm×14 cm-25 cm×13 cm). The images of bilateral thighs were acquired by CT angiography preoperatively. The dominant side and dominant perforators were selected. Three dimensional reconstruction was performed by Mimics software. AR technology was applied to guide the design and harvest of the chimeric twin-paddled ALTPF. Flap area was 15 cm × 16 cm to 26 cm × 14 cm. The donor site was sutured directly. Follow-up with outpatient visits or WeChat images and videos at 1, 3, 6 and 12 months postoperatively to record the appearance, colour, texture, recurrence of infection, and knee extension function of the flap donor site.Results:According to the preoperative design, the perforator flaps were harvested and transferred in all the 8 patients. All flaps survived and the recipient and donor sites healed in one stage. All patients entered postoperative follow-up for 3 to 12 (mean, 8.6)months. The colour and texture of the flaps were excellent, and the appearance of donor and recipient sites was satisfactory. Two patients with hand injuries were evaluated using the brief Michigan Hand Outcomes Questionnaire (MHQ), with scores of 43.74 and 81.25, respectively. Six patients with lower limb injuries were evaluated using the Maryland foot score, with scores of 2 excellent, 3 good and 1 fair.Conclusion:The application of AR navigation can effectively assist the design of a chimeric twin-paddled ALTPF. It also provides an effective basis for clinical personalised flap design.

This article provides an interpretive review of the "2023 ACC/AHA/ACCP/HRS guideline for the diagnosis and management of atrial fibrillation", which was updated and published by the American College of Cardiology (ACC), the American Heart Association (AHA), the American College of Chest Physicians (ACCP), and the Heart Rhythm Society (HRS) based on the latest clinical evidence. It delves into the classification and management strategies for atrial fibrillation (AF), grounded in the most current evidence-based medical research. The guideline offers significant updates in various aspects such as the definition and staging of AF, clinical evaluation and treatment, modification of risk factors, prevention of thromboembolism, and management of specific populations. Notably, the introduction of a new staging model for AF and corresponding management strategies stands out, underscoring the importance of prevention and early intervention. This article focuses on the three pillars of integrated AF management—stroke risk assessment, modification of risk factors, and management of specific patient groups, in addition to rate and rhythm control, analyzes their substantial significance in clinical practice and guides clinicians in providing more precise treatment.

Background Alzheimer's disease(AD)is the most common type of dementia.There has been an increasing trend in incidence rate.The drug therapy has been proven ineffective in improving the cognitive function of AD patients or delaying the disease progression,leading to perceived low adherence with treatment and low efficacy.Previous basic research shows that blue light irradiation is helpful to improve the cognitive function of AD model rats,but there is no corresponding clinical study on the improvement effect of blue light irradiation on cognitive function of AD patients.Objective To explore the efficacy of blue light irradiation in improving the cognitive function of AD patients,so as to provide references for cognitive stabilization or improvement of AD patients.Methods A sample of 155 patients who were hospitalized in Geriatric Department of Shenzhen Kangning Hospital from June 2019 to December 2023 and met the International Classification of Diseases,tenth edition(ICD-10)diagnostic criteria for AD were retrospectively selected.Among them,80 cases who received blue light irradiation combined with memantine therapy and conventional psychotherapy were the study group,and 75 cases who only received memantine therapy and conventional psychotherapy were the control group.Blue light irradiation therapy lasted for 4 weeks,5 times per week,with each session lasting for 30 min.Then Mini-Mental State Examination(MMSE)and Activity of Daily Living Scale(ADL)were administered at the baseline and after treatment.Results After treatment,study group reported an increase in MMSE total score,orientation,immediate recall,attention/calculation,delayed recall and language dimension scores(Z=-6.931,-5.773,-4.123,-3.649,-3.508,-4.733,P<0.05),and a decrease in ADL total score(Z=-7.020,P<0.05)compared to baseline data.Analysis indicated that study group scored higher on MMSE total scale,orientation,immediate recall and language dimensions(Z=-2.784,-4.621,-2.483,-3.463,P<0.05),and lower on ADL total score(Z=-3.704,P<0.05)than those of control group after treatment.Conclusion Blue light irradiation for AD patients may improve their cognitive function and activities of daily living.

Objective Evaluate the performance of the encephalon state index(ESI)in depth of anesthesia monitoring during clinical surgery,compared with the bispectral index(BIS).Methods ESI and BIS data were collected from 60 patients in a single-center clinical trial to compare their efficacy in measuring the depth of anesthesia.Results Consistency analysis revealed mean differences and standard deviations of-0.18±5.42 and-0.11±6.51 between ESI and BIS for awake and anesthetized states,respectively.Correlation analysis showed a correlation coefficient of 0.92 throughout the operative period.Prediction probability analysis indicated that both ESI and BIS had prediction probabilities of 0.97,effectively predicting anesthesia status.Conclusion ESI and BIS show good equivalence in monitoring depth of anesthesia during clinical surgery,which meet the requirements of clinical anesthesia.

OBJECTIVE To analyze the influential factors on trough concentration （cmin） and area under the drug concentration time curve （AUC） of voriconazole （VRZ） in pediatric patients with thalassemia undergoing hematopoietic stem cell transplantation （HSCT）. METHODS A total of 60 pediatric patients with thalassemia undergoing HSCT who used VRZ for prevention or treatment of invasive fungal infection were collected in our hospital from January 2021 to January 2024. The plasma concentration of VRZ was measured by high-performance liquid chromatography and the AUC was calculated. The factors affecting cmin and AUC of VRZ were analyzed using multiple linear regression. RESULTS A total of 120 cases of VRZ cmin in 60 pediatric patients was obtained and 27 cases of VRZ AUC in 26 pediatric patients were obtained. The median concentration of VRZ cmin was 0.31 mg/L； 46 cases had a cmin in 0.5-5 mg/L（ 38.33%）， 2 cases had a cmin＞5 mg/L（ 1.67%）， and 72 cases had a cmin＜0.5 mg/L. The median AUC of VRZ was 11.68 mg·h/L. The patient’s body weight， HSCT postoperative days， lymphocyte count， and combined use of phenytoin sodium， tacrolimus or cyclosporine had significant effects on VRZ cmin （P＜0.05）. Lymphocyte count and combined use of phenytoin sodium had significant effects on VRZ AUC （P＜0.05）. CONCLUSIONS The body weight， HSCT postoperative days， lymphocyte count， and combined use of phenytoin sodium， tacrolimus or cyclosporine are independent factors affecting VRZ cmin. Lymphocyte count and combined use of phenytoin sodium are independent factors affecting VRZ AUC.

Objective:To construct a precision analysis–lean training–accurate evaluation (PLA) training model, for pre-selected health sergeants, composed of three cycle stages: precision analysis, lean training, and accurate evaluation, to promote the precise docking between the training supply side and the demand side of the army, and to improve the quality and effectiveness of pre-selected health sergeant training.Methods:Based on literature analysis and Delphi method, after expert consultation, SPSS 25.0 was used to analyze the Kendall harmony coefficient, determine the indicator system and weight, and carry out empirical research.Results:After two rounds of consultation, 15 valid questionnaires were collected, and the positive coefficient of experts was 100.00%; the mean authority coefficient was 0.85; the Kendall harmony coefficient was 0.303-0.516 ( P<0.05). Finally, an indicator system composed of three first-level indicators, eight second-level indicators, and 22 three-level indicators, including precision analysis, lean training, and accurate evaluation, was established. In the empirical study, the average overall satisfaction of the training subjects was 4.79. Conclusions:The consultation results are credible, and the PLA training model for pre-selected health sergeants can be used as a reference for organizing training reform.

Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.

Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.

Objective:To carry out a study on the cost analysis of the clinical use of Artificial Intelligence-assisted Diagnosis Technology for Coronary CT Angiography(CCTA-AI)to explore the cost differences and cost effects of Coronary CT Angiography(CCTA)examinations before and after the introduction of Artificial Intelligence(AI),and analyze the impact of the application of AI technology on the high-quality development of public hospitals.Methods:The operation cost method was used to measure the changes in the cost and efficiency of CCTA examinations before and after the application of AI technology in five sample hospitals in Beijing,and diagnostic accuracy was used as the effect value to calculate the cost effect of CCTA-AI diagnosis versus CCTA-manual diagnosis,and to analyze the main factors affecting the unit cost.Results:The average cost of examination in 5 sample hospitals after the application of AI-assisted diagnosis system was 1 074.90 yuan,and 1 266.61 yuan before the application,with a large difference between institutions.The cost-effectiveness analysis based on diagnostic accuracy showed that the AI group had an absolute advantage over the manual group,with a cost of 1 074 900 yuan for the AI group and an effectiveness of 855.05 persons,and a cost of 1 266 610 yuan for the physician group,with an effectiveness of 815.07 persons for the high-year-end physician group,and an effectiveness of 793.40 persons for the low-year-end physician group;0.46 man-hours could be saved for each patient examined;the unit cost of CCTA examination was affected by a number of factors,among which"the number of annual examinations"and"the number of CT units involved in CCTA examination"had the greatest influence on the unit cost of CCTA examination.Conclusion:The application of AI-assisted diagnostic technology can promote the improvement of quality and efficiency in public hospitals in a certain extent,and help optimize the overall distribution of medical resources at the system level.In the future,the cost analysis of AI technology should be further strengthened to comprehensively assess its actual contribution to the healthcare system.