Objective To prepare mouse monoclonal antibodies against the ectodomain of E2 (E2ecto) glycoprotein of Western equine encephalitis virus (WEEV). Methods A prokaryotic expression plasmid pET-28a-WEEV E2ecto was constructed and transformed into BL21 (DE3) competent cells. E2ecto protein was expressed by IPTG induction and presented mainly as inclusion bodies. Then the purified E2ecto protein was prepared by denaturation, renaturation and ultrafiltration. BALB/c mice were immunized with the formulated E2ecto protein using QuickAntibody-Mouse5W as an adjuvant via intramuscular route, boosted once at an interval of 21 days. At 35 days post-immunization, mice with antibody titer above 1×10⁴ were inoculated with E2ecto intraperitoneally, and spleen cells were fused with SP2/0 cells three days later. Hybridoma cells secreting specific monoclonal antibodies were screened by the limited dilution method, and ascites were prepared after intraperitoneal inoculation of hybridoma cells. The subtypes and titers of the antibodies in ascites were assayed by ELISA. The biological activity of the mAb was identified by immunofluorescence assay(IFA) on BHK-21 cells which were transfected with eukaryotic expression plasmid pCAGGS-WEEV-CE3E2E1. The specificity of the antibodies were evaluated with E2ecto proteins from EEEV and VEEV. Results Purified WEEV E2ecto protein was successfully expressed and obtained. Four monoclonal antibodies, 3G6G10, 3D7G2, 3B9E8 and 3D5B7, were prepared, and their subtypes were IgG2c(κ), IgM(κ), IgM(κ) and IgG1(κ), respectively. The titers of ascites antibodies 3G6G10, 3B9E8 and 3D7G2 were 10⁵, and 3D5B7 reached 10⁷. None of the four antibody strains cross-reacted with other encephalitis alphavirus such as VEEV and EEEV. Conclusion Four strains of mouse mAb specifically binding WEEV E2ecto are successfully prepared.
Horses ; Animals ; Mice ; Encephalitis Virus, Western Equine ; Ascites ; Immunosuppressive Agents ; Antibodies, Monoclonal ; Immunoglobulin M

Objective:To identify the risk factors for 1-year death after surgery in elderly patients with hip fractures and evaluate the accuracy of the prediction model based on LASSO-logistic regression analysis.Methods:A case-control study was conducted on elderly patients (age ≥65 yr) who underwent surgical treatment for hip fractures in the Second Affiliated Hospital of Wenzhou Medical University from January to December 2019. Patients were divided into death group and survival group according to their survival status at 1-year after surgery. General data and preoperative laboratory indicators were obtained. The variables were selected by utilizing LASSO regression and incorporated into multivariate logistic regression analysis to identify the risk factors for 1-year death after surgery in elderly patients with hip fractures. Then a prediction model was established based on the results and evaluated.Results:There were 63 patients in death group and 564 in survival group. The results of LASSO regression and multivariate logistic regression analysis showed that age, preoperative cognitive dysfunction, Chalson comorbidity index ≥3 points and preoperative serum prealbumin level were the independent risk factors for 1-year death after surgery in elderly patients with hip fractures ( P<0.05). The area under the receiver operating characteristic curve of the prediction model was 0.788 (95% confidence interval [0.731-0.846]), with the sensitivity and specificity of 76.2% and 68.6% respectively. The average absolute error of the calibration curve was 0.007. The results of Hosmer-Lemeshow goodness-of-fit test showed that there was no significant difference between the predicted value and actual observed value ( χ2=5.065, P=0.751). Decision curve analysis showed that patients had a high net benefit rate when the threshold probability range was 0-0.7. Conclusions:Age, preoperative cognitive dysfunction, Chalson comorbidity index ≥3 points and preoperative serum prealbumin level are the independent risk factors for 1-year death after surgery in elderly patients with hip fractures, and the prediction model developed based on LASSO-logistic regression has high accuracy.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.

Objective:To explore the role of Technique for Order Preference by Similarity to Ideal Solution(TOPSIS)combined with Rank Sum Ration(RSR)comprehensive evaluation method in establishing the China Healthcare Security Diagnosis Related Groups(CHS-DRG)operational performance system under the CHS-DRG payment system.Methods:SPSSPRO statistical analysis software was used,and TOPSIS method was used to regularly evaluate and rank the CHS-DRG disease groups in the hospital based on five indicators:Case Mix Index(CMI),total weight,average cost per weight,average length of stay per weight,and group profit and loss.RSR method was used to classify the TOPSIS disease group ranking results,establish performance reward standards for different grades of disease groups,and summarize and restore the reward results for each patient in the disease group to each clinical department,ultimately forming a department performance reward plan.The changes in key operational indicators related to medical insurance patients in hospitals were observed to verify the effectiveness of implementing performance reward programs.Results:After the application of TOPSIS combined with RSR comprehensive evaluation method in the construction of CHS-DRG operational performance system,the number of hospital medical insurance patients were increased,CMI value were stabilized,average cost per visit were decreased,average length of stay were shortened,and DRG disease group surplus were increased.Conclusion:The TOPSIS combined with RSR comprehensive evaluation method has played a good role in the construction of the CHS-DRG operational performance system.As a method of hospital economic operation evaluation,it is practical and innovative.