Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Objective To determine the knee joint cartilage thickness using different methods and explore the feasibility of mathematical statistical models of dataset for the prediction of cartilage thickness.Methods A total of 304 patients diagnosed as knee osteoarthritis(OA)combined with varus deformity and undergoing unilateral total knee arthroplasty at the Second Affiliated Hospital of Army Medical University from March 2023 to March 2024 were selected for the study.All patients had complete preoperative and postoperative clinical data.The healthy cartilage at four anatomical sites of patients,including the distal femur lateral condyle,lateral tibial plateau,posterior medial femoral condyle,and posterior lateral femoral condyle were selected,and the knee joint cartilage thickness was determined based on preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen and digital vernier caliper.The baseline indicators of demographics,disease and imaging ffor patients were collected to construct a dataset,and four models of linear regression analysis,principal component analysis,Least Absolute Shrinkage and Selection Operator(LASSO)regression analysis,and K-nearest neighbors(KNN)analysis were established for predicting the accuracy,determination coefficient(R2)and root mean square error(RMSE),and the regression equation for predicting cartilage thickness was established.Results The knee joint cartilage thicknesses determined by preoperative MRI analysis,robotic navigation system tracing,tissue section of surgical specimen had no statistically significant difference with that by digital vernier caliper(P>0.05).The predictive efficiencies of models of linear regression analysis,principal component analysis,and LASSO regression analysis for the knee joint cartilage thickness all failed to meet the expectations(R2<0.3,RMSE>0.03).The predictive effect of KNN model on the cartilage thickness of the distal femur lateral condyle and lateral tibial plateau was not ideal(R2=0.23,RMSE=0.29),while it had potential predictive value(accuracy=0.21,accuracy=0.15).Conclusion The prediction model of knee joint cartilage thickness based on individual parameters has certain scientificity,and the feasibility of KNN model is relatively high.However,due to insufficient sample size and unclear individual parameter weight,the efficiencies of the four established prediction models are not ideal,which fails to provide definite prediction equations.Therefore,the construction scheme of the prediction model still needs to be further optimized.

Aged ; Cognitive Dysfunction/epidemiology* ; Cross-Sectional Studies ; Geriatric Assessment ; Humans ; Independent Living ; Sarcopenia/epidemiology*

Objective To compare the efficacy of transplanting bone marrow mesenchymal stem cell (BMSC) or microenvironmental induced BMSC ( iBMSC) into the ischemic myocardium of rats with myocardial infarction. Methods iBMSC was defined as BMSC co-cultured with myocardial cells for 2 weeks. The stem cells or equal volume PBS were injected into ischemic border zone 1 wk after experimental infarction. Cardiac performance was evaluated at 1, 2, and 4 wk after cell transplantation by echocardiography and analyzed histologically at 4 wk after cell transplantations. Results Compared with PBS group, both BMSC and iBMSC transplantations reduced infarct size. iBMSC enhanced the beneficial effects of BMSC on improving cardiac function (FS: 28.5% ±4.3% in PBS, 29.0% ±2.0% in BMSC and 45. 1% ±3. 1% in iBMSC group at 4 weeks post transplantation, iBMSC group vs. PBS group P <0. 05, iBMSC group vs. BMSC group P <0. 05). Immunofluorescence microscopy results revealed co-localization of SPIO-labeled transplanted cells with cardiac markers for cardiomyocytes, indicating regeneration of damaged myocardium. Conclusion Our data suggest that iBMSC implantation is more effective on improving cardiac function than BMSC implantation in this model. iBMSC might serve as a new promising therapeutic cell source for regenerating ischemic myocardium in patients with post-infarction heart failure.

OBJECTIVETo compare the therapeutic effect of percutaneous cervical disc nucleoplasty (PCN group) and percutaneous cervical discectomy (PCD group) for the treatment of cervical disc herniation.

METHODSA retrospective study was carried out from July of 2002 to December of 2004, and there were 80 cervical disc herniation cases who were operated by PCN (42 cases) or PCD (38 cases). The time of operation, clinical result and the stability of cervical spine after operation were evaluated and compared between 2 groups.

RESULTSAll cases had been followed up from 6 months to 26 months, average (12 +/- 5) months on the PCN group and (12 +/- 4) months on the PCD group, and there was no significant difference on 2 groups (t = -0.06, P = 0.953). All cases had been successfully operated. There was significant difference in the operation time between 2 groups (t = -21.70, P = 0.000). There was significant difference in the pre- and post-operation scores of each group (PCN group: t = 14.05, P = 0.000; PCD group: t = -14.79, P = 0.000). There was no significant difference in 2 groups of the clinical outcomes (z = -0.377, P = 0.706, > 0.05). There was no instability of cervical spine cases in 2 groups after operation (P > 0.05), and the cervical spine stability was no significant difference in pre- and-operation in each group.

CONCLUSIONSPCN and PCD for the treatment of cervical disc herniation achieves good outcomes and no difference on the stability of cervical spine. PCN and PCD is a safe, minimally invasive, short time of operation, less traumatic operation and excellent clinical outcome.

Adult ; Catheter Ablation ; Cervical Vertebrae ; surgery ; Decompression, Surgical ; methods ; Diskectomy, Percutaneous ; Female ; Humans ; Intervertebral Disc Displacement ; surgery ; Male ; Middle Aged ; Retrospective Studies ; Treatment Outcome