Objective The objective of this research was to investigate the risk factors of cement leakage in patients with metastatic spine tumors following percutaneous vertebroplasty (PVP). Methods Sixty-four patients with 113 vertebrae were retrospectively reviewed. Various clinical indexes, including age, sex, body mass index (BMI), smoking history, drinking history, chemotherapy history, radiotherapy history, primary cancer, location, other metastases, collapse, posterior wall defects, the laterality of injection, and the injected cement volume were analyzed as potential risk factors. Multivariate analyses were conducted to identify the independent risk factors. Results The cement leakage was found 64 in 113 treated vertebrae (56.63%), in which the incidence of each type was shown as below: spinal canal leakage 18 (15.93%), intravascular leakage around the vertebrae 11 (9.73%), and intradiscal and paravertebral leakage 35 (30.97%). Tomita classification (P = 0.019) and posterior wall destruction (P = 0.001) were considered strong risk factors for predicting cement leakage in general. The multivariate logistic analysis showed that defects of the posterior wall (P = 0.001) and injected volume (P = 0.038) were independently related to the presence of spinal canal leakage. The postoperative visual analog scale (VAS) and activities of daily living (ADL) scores showed significant differences compared with the pre-operative parameters (P < 0.05). No significant differences were found in every follow-up time between the leakage group and the non-leakage group for pain management and improvement of activities in daily life. Conclusion In our study, Tomita classification and the destruction of the posterior wall were independent risk factors for leakage in general. The defects of the posterior wall and injected volume were independently related to the presence of spinal canal leakage. The PVP procedure can be an effective way to manage the pain.

Background. Ewing sarcoma (ES) is the second most common pediatric bone tumor with a high rate of metastasis, high recurrence, and low survival rate. Therefore, the identification of new biomarkers which can improve the prognosis of ES patients is urgently needed. Methods. Here, GSE17679 dataset was downloaded from GEO databases. WGCNA method was used to identify one module associating with OVS (overall vital survival) and event. cytoHubba was used to screen out 50 hub genes from the module genes. Then, GSE17679 dataset was randomly divided into train cohort and test cohort. Next, univariate Cox analysis, LASSO regression analysis, and multivariate Cox analysis were conducted on 50 hub genes combined with train cohort data to select pivotal genes. Finally, an optimal 7-gene-based risk assessment model was established, which was verified by test cohort, entire GSE17679, and two independent datasets (GSE63157 and TCGA-SARC). Results. The results of the functional enrichment analysis revealed that the OVS and event-associated module were mainly enriched in the protein transcription, cell proliferation, and cell-cycle control. And the train cohort was divided into high-risk and low-risk subgroups based on the median risk score; the results showed that the survival of the low-risk subgroup was significantly longer than high-risk. ROC analysis revealed that AUC values of 1, 3, and 5-year survival were 0.85, 0.94, and 0.88, and Kaplan-Meier analysis also revealed that P value < 0.0001, indicating that this model was accurate, which was also verified in the test, entire cohort, and two independent datasets (GSE63157 and TCGA-SARC). Then, we performed a comprehensive analysis (differential expression analysis, correlation analysis and survival analysis) of seven pivotal genes, and found that four genes (NCAPG, KIF4A, NUF2 and CDC20) plays a more crucial role in the prognosis of ES. Conclusion. Taken together, this study established an optimal 7-gene-based risk assessment model and identified 4 potential therapeutic targets, to improve the prognosis of ES patients.

Objective This study aimed to further compare the abilities to measure hallux valgus parameters in different smartphones using the intrinsic photograph-editing function. Methods We retrospectively reviewed 61 patients (100 feet) of hallux valgus without medical or surgical interventions at our department. The radiographic parameters were assessed and measured via the Picture archiving and communication systems (PACS), iPhone, and Android. The accuracy, reliability, and the time-taken were compared and analyzed between each two methods. Results The mean value of measured hallux valgus parameters were as follow: hallux valgus angle (HVA): 33.71 ± 7.25°; the first and second intermetatarsal angle (IMA): 12.84 ± 3.62° in PACS; HVA: 33.59 ± 7.18° and IMA: 12.80 ± 3.65° in Android; HVA: 33.63 ± 7.23° and IMA: 12.87 ± 3.60° in iPhone. No significant difference was found among the average results measured by PACS, Android and iPhone (F = 0.008, P = 0.992 in HVA; F = 0.009, P = 0.991 in IMA). For measurements by PACS, Android smartphone, and iPhone, the variability of HVA (F = 0.061, P = 1.000) and IMA (F = 0.133, P = 1.000) was similar. The intraclass correlation coefficients (ICCs) of the mean results of four times measurements of HVA and IMA as follows: PACS vs Android: 0.995 (0.993–0.997) and 0.982 (0.973–0.988); PACS vs iPhone:0.997 (0.995–0.998) and 0.974 (0.962–0.982); Android vs iPhone:0.997 (0.995–0.998) and 0.981 (0.971–0.987). The interobserver and intraobserver reliability was very good for Android smartphones and iPhone in measuring hallux valgus parameters. The mean time of measurement by PACS, Android smartphone, and iPhone were 25.34 ± 1.18 s, 20.10 ± 0.92 s, and 19.92 ± 0.99 s respectively. The measurement time of smartphones is significantly faster than that of PACS by about 5 seconds (P = 0.000). The measurement time of iPhone was slightly faster than that of Android smartphone, while no significant difference was found (P = 0.24). Conclusion It is more convenient and faster to use smartphones when compared with PACS, at the same level of accuracy. Furthermore, the abilities of different smartphone platforms are proven to be of no significant difference.