Objective To investigate the efficacy of ablative fractionated erbium: yttrium aluminum garnet (Er: YAG) laser in facial acne scars and enlarged pores. Methods Forty-one patients with mild to moderate pitted acne scars and 23 patients with enlarged pores were treated with 81 (9 × 9) bits of facula for 3 to 5 sessions at an interval of 1 month. For acne scars, the pulse duration was medium to long, energy at 800 to 1200 mJ, and number of stacking passes 4 to 8; for enlarged pores, the pulse duration was medium, energy at 800 to 1000 mJ and number of stacking passes 2 to 4. The clinical improvement was evaluated by 2 blinded dermatologists. Meanwhile, the satisfaction rate was self-assessed by patients. Three-dimensional (3D) micro-topography imaging system was used to evaluate the improvement in surface roughness. Results The efficacy reached 82.93% and 86.96% for ache scars and enlarged pores, respectively. The satisfaction rate was 88.80% and 91.30% in patients with ache scars and those with enlarged pores, respectively. After treatment, the Ra and Rz values, as the indicators of roughness, decreased by 18.74% and 21.01%, individually (P < 0.001) in 11 patients including 6 with acne scars and 5 with enlarged pores. Conclusion Ablative fractionated Er:YAG laser can efficiently resurface pitted ache scars and shrink enlarged pores.

Objective To evaluate the therapeutic effect and safety of ureteroscopy pneumatic lithotripsy(PL) and extracorporeal shock wave lithotripsy(ESWL) in the treatment of distal ureteral calculi.Methods 368 cases of distal ureteral calculi were divided into the PL treatment group(178 cases) and the ESWL treatment groups(190 cases).The clinical datas were compared between the two groups.Results PL treatment group 97.19% patients became stone free in 4 weeks,and in ESWL treatment group the stone free rate was 73.16%(P

OBJECTIVE: To observe the clinical effect of platelet rich plasma (PRP) combined with β tricalcium phosphate bioceramic bone in the treatment of non traumatic necrosis of the femoral head in ARCO stageⅡ. METHODS: From January 2017 to December 2018, 100 patients (160 hips) with ARCO stageⅡnon traumatic necrosis of the femoral head were divided into PRP group and control group. In PRP group, 50 patients (80 hips), 22 males and 28 females, aged from 18 to 65 (43.47± 7.23) years, with a course of 4 to 18 (15.8±2.9) months, underwent core decompression and bone grafting combined with PRP implantation. There were 50 cases (80 hips) in the control group, including 27 males and 23 females, aged 20 to 63 (45.72± 7.43) years, and the course of disease was 6 to 19 (14.9±3.8) months. Hip X-ay film was followed up after operation. Harris score and VAS score were used to evaluate the curative effect, and the survival rate of hip joint was recorded. RESULTS: All patients had good wound healing, no infection, thrombosis and other complications. All patients were followed up for 12 to 14 (12.0±0.4) months. Twelve months after operation, the image expression of PRP group was better than that of control group( CONCLUSION Platelet-rich plasma(PRP) combined with artificialbone for core decompression and bone grafting can change the situation of simple artificial bone implantation and uncertain curative effect, improve the success rate of this operation, effectively reduce the collapse rate of femoral head necrosis in the early and middle stage, delay or even avoid hip replacement.
Adolescent ; Adult ; Aged ; Artemisinins ; Bone Transplantation ; Decompression, Surgical ; Female ; Femur Head/surgery* ; Femur Head Necrosis/surgery* ; Humans ; Male ; Middle Aged ; Naphthoquinones ; Platelet-Rich Plasma ; Treatment Outcome ; Young Adult

Objective To investigate a diabetic retinopathy ( DR ) detection algorithm based on transfer learning in small sample dataset. Methods Total of 4465 fundus color photographs taken by Gaoyao People ' s Hospital was used as the full dataset. The model training strategies using fixed pre-trained parameters and fine-tuning pre-trained parameters were used as the transfer learning group to compare with the non-transfer learning strategy that randomly initializes parameters. These three training strategies were applied to the training of three deep learning networks:ResNet50,Inception V3 and NASNet. In addition,a small dataset randomly extracted from the full dataset was used to study the impact of the reduction of training data on different strategies. The accuracy and training time of the diagnostic model were used to analyze the performance of different training strategies. Results The best results in different network architectures were chosen. The accuracy of the model obtained by fine-tuning pre-training parameters strategy was 90. 9％,which was higher than the strategy of fixed pre-training parameters (88. 1％) and the strategy of randomly initializing parameters ( 88. 4％) . The training time for fixed pre-training parameters was 10 minutes,less than the strategy of fine-tuning pre-training parameters ( 16 hours ) and the strategy of randomly initializing parameters (24 hours). After the training data was reduced,the accuracy of the model obtained by the strategy of randomly initializing parameters decreased by 8. 6％ on average,while the accuracy of the transfer learning group decreased by 2. 5％ on average. Conclusions The proposed automated and novel DR detection algorithm based on fine-tune and NASNet structure maintains high accuracy in small sample dataset,is found to be robust,and effective for the preliminary diagnosis of DR.

Objective To study the efficiency and accuracy of artificial intelligence (AI) system based on fundus photograph in diabetic retinopathy(DR)screening,and evaluate the clinical application value of AI system. Methods A diagnostic trial was adopted. Total of 13683 color fundus photos were collected in Zhaoqing Gaoyao People's Hospital from March,2017 to November,2018. The AI system for DR (ZOC-DR-V1) was established,based on transfer learning + NASNet algorithm,by training 4465 precisely labeled fundus images (2510 normal,and 1955 with any stage of DR). One thousand confirmed fundus images (300 normal and 700 with any stage of DR),diagnosed by AI ( AI group ) and doctors ( 3 ophthalmologist doctors and 3 endocrinologist doctors ) ( doctor group ) , respectively. Ophthalmologist group and endocrinologist group were both composed of primary,intermediate and senior physicians. The mean reading time of each image and the total time of 1000 images were recorded. The accuracy and efficiency of AI system and doctor groups were compared. The reading process was divided into two stages. The diagnostic coincidence rate and the average reading time of each group between the two parts were calculated and compared. This study protocol was approved by Ethic Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University (No. 2017KYPJ104). Results After training,the diagnostic coincidence rate of AI system (ZOC-DR-V1) in test set was 94. 7％,AUC was 0. 994. In this "man-machine to war",the diagnostic coincidence rate of primary,intermediate and senior endocrinologist was 94. 0％,91. 4％ and 93. 4％;the diagnostic coincidence rate of primary,intermediate and senior ophthalmologist was 92. 7％,94. 4％ and 95. 6％;the diagnostic coincidence rate of AI system was 95. 2％. There was no difference in the diagnostic coincidence rate between AI system and senior ophthalmologist ( P = 0. 749 ) . The mean reading time of each image of primary, intermediate and senior endocrinologists was (4. 63±1. 87),(3. 74±3. 47) and (5. 71±3. 47) seconds,and the total time of 1000 images of primary,intermediate and senior endocrinologists was 1. 29,1. 04 and 1. 58 hours;the mean reading time of each image of primary,intermediate and senior ophthalmologists was ( 7. 25 ± 6. 58 ) , ( 5. 18 ± 5. 01 ) and ( 5. 18 ± 3. 47 ) seconds,and the total time of 1000 images of primary,intermediate and senior endocrinologists was 2. 02,1. 44 and 1. 44 hours;the mean and total time of AI system was (1. 62±0. 67) seconds and 0. 45 hours,and the reading time of AI system was significantly shorter than that of the doctor groups (all at P=0. 000). The diagnostic coincidence rates between previous and posterior part of primary endocrinologist, primary and intermediate ophthalmologist were significantly different (χ2=11. 986,6. 517,10. 896;all at P<0. 05),and the mean reading time in the posterior part was significantly shorter than that in the previous part of intermediate and senior endocrinologist and primary ophthalmologist (t=4. 175,8. 189,5. 160;all at P<0. 01). While the reading time of AI system remained stable throughout the process(χ2=3. 151,P=0. 103;t=0. 038,P=0. 970). Conclusions The ophthalmic AI system based on fundus images has a good diagnostic efficiency,and its diagnostic coincidence rate can compare with senior ophthalmologist,providing a new method and platform for large-scale DR screening.

Ankylosing spondylitis (AS) combined with spinal fractures with thoracic and lumbar fracture as the most common type shows characteristics of unstable fracture, high incidence of nerve injury, high mortality and high disability rate. The diagnosis may be missed because it is mostly caused by low-energy injury, when spinal rigidity and osteoporosis have a great impact on the accuracy of imaging examination. At the same time, the treatment choices are controversial, with no relevant specifications. Non-operative treatments can easily lead to bone nonunion, pseudoarthrosis and delayed nerve injury, while surgeries may be failed due to internal fixation failure. At present, there are no evidence-based guidelines for the diagnosis and treatment of AS combined with thoracic and lumbar fracture. In this context, the Spinal Trauma Academic Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate the Clinical guideline for the diagnosis and treatment of adult ankylosing spondylitis combined with thoracolumbar fracture ( version 2023) by following the principles of evidence-based medicine and systematically review related literatures. Ten recommendations on the diagnosis, imaging evaluation, classification and treatment of AS combined with thoracic and lumbar fracture were put forward, aiming to standardize the clinical diagnosis and treatment of such disorder.