Objective To explore the efficacy of secondary targeted percutaneous vertebroplasty(PVP)for the treatment of refracture of injured vertebrae after vertebral augmentation for osteoporotic vertebral compression fracture(OVCF).Methods A retrospective case series study was performed on the clinical data of 25 patients with refracture of injured vertebrae after vertebral augmentation for OVCF admitted to Honghui Hospital,Xi'an Jiaotong University from January 2019 to January 2022,including 10 males and 15 females,aged 62-86 years[(73.8±5.2)years].The fractured segments involved T10 in 1 patient,T11 in 2,T12 in 10,L1 in 10 and L2 in 2.All the patients were treated with secondary targeted PVP.The operation time and the amount of bone cement injected were recorded.The visual analogue scale(VAS)of lower back,Oswestry disability index(ODI),vertebral body index(VBI)and kyphotic angle(KA)were compared before surgery,at 1 day,6 months after surgery and at the last follow-up.Odom criteria were used to evaluate the efficacy of the surgical procedure at the last follow-up.The intraoperative bone cement leakage and new vertebrae fracture during follow-up were observed.Results All the patients were followed up for 23-59 months[(36.8±7.6)months].The operation time was 35-60 minutes[(42.6±5.2)minutes],with the amount of bone cement injected for 3-5 ml[(3.6±0.8)ml].The VAS scores of lower back at 1 day,6 months after surgery and at the last follow-up were 3.1(2.0,4.0)points,1.7(1.0,2.0)points and 0.6(0.0,1.0)points respectively,significantly lower than 7.6(7.0,9.0)points before surgery(P＜0.01),and a statistically singnificant decrease was found over follow-up time(P＜0.01).The ODI values at 1 day,6 months after surgery and at the last follow-up were(49.5±5.9)％,(28.5±4.6)％and(19.2±4.8)％respectively,significantly lower than(78.8±6.8)％before surgery(P＜0.01),and a statistically singnificant decrease was found over follow-up time(P＜0.01).The VBI values at 1 day,6 months after surgery and at the last follow-up were(76.6±4.5)％,(76.3±4.0)％and(76.1±3.8)％respectively,significantly higher than(58.9±5.8)％before surgery(P＜0.01),while there were no significant differences among those at 1 day,6 months after surgery and at the last follow-up(P＞0.05).The KA values at 1 day,6 months after surgery and at the last follow-up were(12.4±2.7)°,(12.6±2.5)° and(12.8±2.9)° respectively,significantly lower than(20.8±3.6)° before surgery(P＜0.01),while there were no significant differences among those at 1 day,6 months after surgery and at the last follow-up(P＞0.05).According to the Odom criteria,20 patients were rated excellent and 5 good at the last follow-up,with an excellent and good rate of 100％.Intraoperative asymptomatic bone cement leakage occurred in 3 patients(12％),including 2 with intervertebral leakage and 1 with lateral vertebral leakage.No adjacent vertebral body or other vertebral fracture was observed during the follow-up.Conclusions For patients with refracture of injured vertebrae after vertebral augmentation for OVCF,the secondary targeted PVP has advantages of attenuation of the lower back pain,improvement of the quality of life,restoration of the height of refractured vertebrae,correction of the local kyphosis,and a low incidence of complications.
某些由政府机构和专业组织制定的指南以及作者以其他语言发表的科研成果等，需要让更多的读者了解。根据国际惯例（参考《向生物医学期刊投稿的统一要求》）和我国的实际情况，凡符合下列条件并提供相应材料，中华医学会系列杂志允许或接受论文用同一种语言或另一种语言的二次发表。
Bone defects, often accompanied by osteomyelitis, soft tissue contusions, etc, are facing lengthy treatment process and slow healing, seriously jeopardizing the structural integrity of the human bone tissue. Currently, the main treatment for bone defects involves autologous or allogeneic bone transplant. However, autologous bone transplant poses problems, including long surgical duration, increased pain and complications such as infections. Additionally, immune rejection reactions also limit the effectiveness of allogeneic bone transplant of the same species. Bone scaffolds have become a potential alternative for bone transplant, but problems such as sharp edges of the scaffolds and poor compatibility with human tissues exist. Triply periodic minimal surface (TPMS), with an average curvature of zero has lower levels of stress concentration and the ability to be precisely expressed with mathematical formulas, compared with other structures. Its application in bone scaffolds attracts much attention, but there is currently a lack of comprehensive understanding of the impacts of different types of TPMS on the performance of bone scaffolds. With this purpose, the authors reviewed the research progress in the impacts of different types of TPMS on the performance of bone scaffolds, providing a reference for the construction of bone scaffolds.
肢体大血管损伤常造成患者严重的肢体伤害，如救治不及时，将导致肢体坏死，最终造成肢体遗留严重的功能障碍。因此，肢体的存活及后期的功能恢复与肢体的缺血时间密切相关。目前，常规手术需先清创及骨折临时固定，最后吻合血管，存在缺血再灌注损伤、骨折不稳定导致的二次损伤等诸多缺陷。临时血管通血术（TIVS）可在最短的时间恢复肢体远端血流灌注，减少肢体远端缺血时间，可为清创、骨折固定等其他环节争取时间，减少并发症的发生。目前，此方法用于修复肢体大血管损伤的报道极少。为此，笔者采用回顾性病例系列研究分析2015年1月至2021年12月十堰市太和医院收治的15例肢体大血管损伤患者的临床资料，探讨TIVS在肢体大血管损伤修复中的应用效果。
Objective:To investigate the application value of joint friction sounds in diagnosing meniscus injury of the knee based on machine learning models.Methods:A case-control study was conducted to analyze the clinical data of 17 patients with meniscus injury of the knee (meniscus injury group) admitted to Sir Run Run Shaw Hospital Affiliated to Nanjing Medical University from August 2020 to October 2022, as well as 75 recruited healthy subjects without knee joint diseases (healthy group). The knee joint friction sounds of the subjects were collected in a relatively quiet environment (peak value below 40 dB). The sounds collected in a flexion-extension-flexion mode of exercise were split and divided randomly with a ratio of 4∶1 into the training set (125 segments from the meniscal injury group and 187 segments from the healthy group) and the test set (33 segments from the meniscal injury group and 47 segments from the healthy group). The sounds obtained in a sit-stand-sit mode of exercise were split and divided randomly with a ratio of 4∶1 into the training set (81 segments from the meniscal injury group and 164 segments from the healthy group) and the test set (20 segments from the meniscal injury group and 40 segments from the healthy group). Four machine learning models were built, including support vector machine with linear kernels, radial basis function support vector machine, random forest, and extremely randomized trees. The learning training of the model was performed on the training set, and its model performance was verified with the test set. The time required in a single collection of joint friction sound from the subjects and the interpretation of data analysis was recorded. Knee function of the subjects were scored according to the Lysholm Score before and at 1 day after the test. The accuracy rates of diagnosis of meniscus injury with friction sounds under the two modes of exercise were compared based on the test results to yield an optimal one. The effectiveness of the four models was compared to find the best machine learning model fitting the data frame of this study according to the test results such as accuracy, sensitivity, specificity, F1 score, and area under the receiver operating characteristic curve (AUC) obtained with the optimal mode of exercise. The diagnostic accuracy, misdiagnosis rate and missed diagnosis rate of joint friction sound for meniscal injury under the optimal machine learning model with the optimal mode of exercise were observed.Results:The time required in a single collection of joint friction sound ranged from 5 to 10 minutes [(7.1±1.3)minutes], when the time required for interpretation of data analysis was approximately 1 minute. The Lysholm Score before and after the test was (75.6±4.0)points and (77.7±3.7)points respectively in the meniscal injury group ( P>0.05), and (99.6±0.9)points and (99.5±1.0)points respectively in the healthy group ( P>0.05). The diagnosing accuracy rates for flexion-extension-flexion of exercise and sit-stand-sit modes of exercise were 0.775 and 0.817 under the support vector machine model with linear kernels; 0.813 and 0.900 under the radial basis function support vector machine model; 0.800 and 0.867 under the random forest model; 0.800 and 0.900 under the extremely randomized tree model. The accuracy rates for sit-stand-sit mode of exercise were all higher than those for flexion-extension-flexion mode of exercise. In the sit-stand-sit mode of exercise, the extremely randomized tree model had an accuracy rate of 0.900, sensitivity of 0.900, specificity of 0.950, F1 score of 0.900, and AUC of 0.942, which were higher than those under the remaining 3 models, showing better machine learning efficacy. Under the extremely randomized tree model in the sit-stand-sit mode of exercise, 22 (18 true positive and 4 false positive) were diagnosed as meniscal injury and 38 (36 true negative and 2 false negative) as healthy out of 60 segments in the test set (20 from the meniscal injury group and 40 from the healthy group). The diagnostic accuracy of joint friction sounds in diagnosing meniscus injury of the knee was 0.900, with the misdiagnosis rate of 0.100 and the missed diagnosis rate of 0.100. Conclusion:Diagnosis of meniscus injury of the knee with joint friction sounds can shorten time and enhance safety during the examination process. The diagnostic model using machine learning-based artificial intelligence is faster and more stable, which can be used as a diagnostic marker for such injury.
