1.Role and Mechanisms of Mechanical Stress-Induced Oxidative Stress in Vascular Remodeling
Ziqi SHANG ; Zhijie YAN ; Yingxin QI ; Kai HUANG
Journal of Medical Biomechanics 2025;40(3):760-767
The incidence of vascular diseases is extremely high and mechanical stress plays an important role in vascular remodeling.Reactive oxygen species(ROS)at physiological levels modulate cell signaling while excessive ROS trigger oxidative stress and induce injury.The types of mechanical stresses in the vascular system and the sources of ROS are summarized.Besides,the roles and mechanisms of mechanical stress-induced oxidative stress in vascular diseases are discussed.This review will facilitate a deeper understanding of vascular activity and disease development at the molecular level,provide potential targets for treating vascular diseases.In addition,there are still research gaps on the mechanism of oxidative stress induced by mechanical stress in vascular diseases.Therefore,the potential research direction of mechanical stress-induced oxidative stress in the vascular system is also predicted,with the aim to promote the development of mechanobiology to a certain extent.
2.Establishment and Evaluation of A Forecasting Model for Platelet Transfusion Efficacy in Patients with Hematological Disorders
Yihua XIE ; Jun LI ; Xiaolei ZHANG ; Yan CUI ; Lan WANG ; Peng ZHANG ; Bijia LU ; Yuqi SHANG ; Ziqi CHEN ; Haoran LI ; Kuanyun ZHENG
Journal of Modern Laboratory Medicine 2025;40(5):101-106
Objective To establish the therapeutic effect prediction model of platelet transfusion in hematological patients,and receiver operating characteristic(ROC)curve and clinical cases are used to evaluate the clinical application value of the predic-tion model.Methods A total of 485 patients with hematological diseases who received platelet transfusion therapy in Kailuan General Hospital from January 2020 to December 2023 were selected,corrected count increment(CCI)was used to divide the patients into platelet transfusion effective group(n=340)and transfusion ineffective group(n=145).Multivariate Logistic regres-sion analysis was used to establish the prediction model of platelet infusion efficacy,and ROC curve was used to evaluate the application effect of the forcasting model.109 clinical cases were used to verify the practical application effect of the model,and the sensitivity,specificity and accuracy were calculated.Results Among 485 patients with hematological diseases,the incidence of ineffective platelet transfusion was 29.90%(145/485).Compated with the effective group,the ineffective group had more previous platelet transfusions was higher,and the difference was statistically significant(t=-4.435,P<0.05).In the ineffective group,there were more cases of hyperplenism,aplastic anemia and lymphoma,higher infection rate and higher positive rate of platelet antibody,and the differences were statistically significant(χ2=6.301~37.522,all P<0.05).Multivariate Logistic regres-sion analysis found that previous platelet infusion times,infection,leukemia,aplastic anemia and platelet antibodies were risk factors for ineffective platelet transfusion in patients with hematological diseases(Wald χ2=5.224~21.548,all P<0.05).Based on these risk factors,platelet infusion effect prediction models 1 and 2 were constructed.ROC curve was used to evaluate the application effect of the prediction model.The area under the curve(AUC),cut-offpoint,sensitivity and specificity of model 1 were 0.884,0.042,82.35%,88.89%.The AUC,cut-offpoint,corresponding sensitivity and specificity of prediction model 2 were 0.910,59.784,81.18%,94.44%,respectively.The Z values of model 1 and model 2 were 12.159 and 13.151,respectively.The prediction effect of model 2 was better than that of model 1.The actual application results showed that the sensitivity,specificity and accuracy of prediction model 1,2 were 85.71%,92.05%,90.89%and 90.48%,93.18%,92.66%,respectively.Conclusion The ineffective rate of platelet transfusion in hematological patients is relatively high.The prediction models 1 and 2 for platelet transfusion effectiveness have good results in predicting ineffective platelet transfusion,and prediction model 2 is better than pre-diction model 1,which can provide reliable basis for hematological patients on accurate platelet transfusion.
3.Role and Mechanisms of Mechanical Stress-Induced Oxidative Stress in Vascular Remodeling
Ziqi SHANG ; Zhijie YAN ; Yingxin QI ; Kai HUANG
Journal of Medical Biomechanics 2025;40(3):760-767
The incidence of vascular diseases is extremely high and mechanical stress plays an important role in vascular remodeling.Reactive oxygen species(ROS)at physiological levels modulate cell signaling while excessive ROS trigger oxidative stress and induce injury.The types of mechanical stresses in the vascular system and the sources of ROS are summarized.Besides,the roles and mechanisms of mechanical stress-induced oxidative stress in vascular diseases are discussed.This review will facilitate a deeper understanding of vascular activity and disease development at the molecular level,provide potential targets for treating vascular diseases.In addition,there are still research gaps on the mechanism of oxidative stress induced by mechanical stress in vascular diseases.Therefore,the potential research direction of mechanical stress-induced oxidative stress in the vascular system is also predicted,with the aim to promote the development of mechanobiology to a certain extent.
4.Establishment and Evaluation of A Forecasting Model for Platelet Transfusion Efficacy in Patients with Hematological Disorders
Yihua XIE ; Jun LI ; Xiaolei ZHANG ; Yan CUI ; Lan WANG ; Peng ZHANG ; Bijia LU ; Yuqi SHANG ; Ziqi CHEN ; Haoran LI ; Kuanyun ZHENG
Journal of Modern Laboratory Medicine 2025;40(5):101-106
Objective To establish the therapeutic effect prediction model of platelet transfusion in hematological patients,and receiver operating characteristic(ROC)curve and clinical cases are used to evaluate the clinical application value of the predic-tion model.Methods A total of 485 patients with hematological diseases who received platelet transfusion therapy in Kailuan General Hospital from January 2020 to December 2023 were selected,corrected count increment(CCI)was used to divide the patients into platelet transfusion effective group(n=340)and transfusion ineffective group(n=145).Multivariate Logistic regres-sion analysis was used to establish the prediction model of platelet infusion efficacy,and ROC curve was used to evaluate the application effect of the forcasting model.109 clinical cases were used to verify the practical application effect of the model,and the sensitivity,specificity and accuracy were calculated.Results Among 485 patients with hematological diseases,the incidence of ineffective platelet transfusion was 29.90%(145/485).Compated with the effective group,the ineffective group had more previous platelet transfusions was higher,and the difference was statistically significant(t=-4.435,P<0.05).In the ineffective group,there were more cases of hyperplenism,aplastic anemia and lymphoma,higher infection rate and higher positive rate of platelet antibody,and the differences were statistically significant(χ2=6.301~37.522,all P<0.05).Multivariate Logistic regres-sion analysis found that previous platelet infusion times,infection,leukemia,aplastic anemia and platelet antibodies were risk factors for ineffective platelet transfusion in patients with hematological diseases(Wald χ2=5.224~21.548,all P<0.05).Based on these risk factors,platelet infusion effect prediction models 1 and 2 were constructed.ROC curve was used to evaluate the application effect of the prediction model.The area under the curve(AUC),cut-offpoint,sensitivity and specificity of model 1 were 0.884,0.042,82.35%,88.89%.The AUC,cut-offpoint,corresponding sensitivity and specificity of prediction model 2 were 0.910,59.784,81.18%,94.44%,respectively.The Z values of model 1 and model 2 were 12.159 and 13.151,respectively.The prediction effect of model 2 was better than that of model 1.The actual application results showed that the sensitivity,specificity and accuracy of prediction model 1,2 were 85.71%,92.05%,90.89%and 90.48%,93.18%,92.66%,respectively.Conclusion The ineffective rate of platelet transfusion in hematological patients is relatively high.The prediction models 1 and 2 for platelet transfusion effectiveness have good results in predicting ineffective platelet transfusion,and prediction model 2 is better than pre-diction model 1,which can provide reliable basis for hematological patients on accurate platelet transfusion.

Result Analysis
Print
Save
E-mail