Objective:To analyze the literature of Ilizarov methods, visualizing and discussing the research status, research hotspots and research trends.Methods:A bibliometric study on Ilizarov methods was performed. Using keyword "Ilizarov" and the Chinese translations to retrieve Chinese publications from CNKI database, Wanfang DATA, VIP database and SinoMed database. Using keywords "Ilizarov method, Ilizarov technique, Ilizarov treatment" to retrieve English publications from Web of Science Core Collection database before January 2021, extracting the information including author, journal, country, institution, keywords and cited times. Using the tools of bibliometrics and VOSviewer to analyze the data and draw knowledge maps.Results:A total of 1 789 Chinese publications and 1 709 English publications were included. USA, UK and China were on the top 3 list of the number of publications. Orthopaedic Journal of China, Chinese Journal of Orthopaedic Trauma, Chinese Journal of Reparative and Reconstructive Surgery, Chinese Journal of Orthopaedics, and Chinese Journal of Bone and Joint Surgery published the most literature. 7 English journals were identified as core journals in the field of Ilizarov methods, among which Clinical Orthopaedics and Related Research, Journal of Bone and Joint Surgery (British Volume), International Orthopaedics were JCR Q1 journals. According to the visualized keywords co-occurrence clusteranalysis, the research topics in Chinese literature could be sorted into 6 clusters, the latest hotspots were bone nonunion caused by infection and the treatment for the diabetic foot. In the English literature, the research topics could be sorted into 4 clusters, while the latest topics were infected and posttraumatic bone defects. Conclusion:The number of research on Ilizarov methods is increasing around the world, researches from China are gradually becoming one of the main forces. The research trends at home and at abroad are the same in essentials while differing in minor points, and researches with Chinese characteristics are developing. The strengthening of international cooperation is essential to the development of Ilizarov methods.

Objective To compare the effect of various manipulation of Tuina on surface electromyogram (sEMG) in hemiplegics after stroke. Methods From January to May, 2016, 20 inpatients with hemiplegia after stroke accepted Tuina on bilateral rectus femoris by the same therapist, with the techniques of rolling, patting, rubbing, shaking, kneading and pressing, one minute a manipulation and interval one minute. Integrated electromyography (iEMG), root mean square (RMS) and median frequency (MF) of sEMG were compared, both in rest and during Tuina. Results There was no significant difference of iEMG, RMS and MF between affected and unaffected sides in rest (t<1.147, P>0.05). iEMG and RMS were the most under patting (F>21.376, P<0.001), and MF was the highest under pressing (F>11.772, P<0.001). iEMG, RMS and MF were not very different under other manipulation (P>0.05). iEMG and RMS were less in the affected side than in the unaffected side under patting (P<0.05). Conclusion Various manipulation of Tuina may be different in neuromuscular stimulation, that patting may stimulate more muscles and motor units.

Objective To investigate the association between intraoperative hypotension and post-operative acute kidney injury(AKI)in patients undergoing brain tumor resections.Methods A total of 428 patients undergoing elective craniotomy for tumor resection were selected,276 males and 152 females,aged≥18 years,BMI 15-36 kg/m2,ASA physical statusⅡ orⅢ.Based on postoperative occurrence of AKI,the patients were divided into two groups:the AKI group and the control group.This study defined three thresholds for hypotension,including MAP during surgery below 65 mmHg,60 mmHg,and 55 mmHg.Multivariate logistic regression was used to analyze the correlation between intraoperative hypotension and postoperative AKI under three thresholds.Results A total of 107 patients had postoperative AKI.The re-sults of multivariable regression analysis indicated that intraoperative MAP＜65 mmHg(OR = 1.11,95%CI 1.03-1.20,P = 0.010)and intraoperative MAP＜60 mmHg(OR = 1.12,95%CI 1.02-1.23,P = 0.017)were associated with postoperative AKI.Conclusion Intraoperative MAP＜65 mmHg or 60 mmHg is associated with postoperative AKI in patients undergoing brain tumor resection.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Objective: This study investigated the value of multiparametric MRI (mpMRI) in predicting Gleason score (GS) upgrading and downgrading in radical prostatectomy (RP) compared with presurgical biopsy. Materials and Methods: Clinical and mpMRI data were retrospectively collected from 219 patients with prostate disease between January 2015 and December 2021. All patients underwent systematic prostate biopsy followed by RP. MpMRI included conventional diffusion-weighted and dynamic contrast-enhanced imaging. Multivariable logistic regression analysis was performed to analyze the factors associated with GS upgrading and downgrading after RP. Receiver operating characteristic curve analysis was used to estimate the area under the curve (AUC) to indicate the performance of the multivariable logistic regression models in predicting GS upgrade and downgrade after RP. Results: The GS after RP was upgraded, downgraded, and unchanged in 92, 43, and 84 patients, respectively. The AUCs of the clinical (percentage of positive biopsy cores [PBCs], time from biopsy to RP) and mpMRI models (prostate cancer [PCa] location, Prostate Imaging Reporting and Data System [PI-RADS] v2.1 score) for predicting GS upgrading after RP were 0.714 and 0.749, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, tPSA, PCa location, and PIRADS v2.1 score) was 0.816, which was larger than that of the clinical factors alone (P < 0.001). The AUCs of the clinical (age, percentage of PBCs, ratio of free/total PSA [F/T]) and mpMRI models (PCa diameter, PCa location, and PI-RADS v2.1 score) for predicting GS downgrading after RP were 0.749 and 0.835, respectively. The AUC of the combined diagnostic model (age, percentage of PBCs, F/T, PCa diameter, PCa location, and PI-RADS v2.1 score) was 0.883, which was larger than that of the clinical factors alone (P < 0.001). Conclusion Combining clinical factors and mpMRI findings can predict GS upgrade and downgrade after RP more accurately than using clinical factors alone.

Antibodies, Antiphospholipid ; Antiphospholipid Syndrome ; Female ; Humans ; Killer Cells, Natural ; Pregnancy ; Pregnancy Complications