1.Comparison of two models in predicting the risk of thrombosis in elderly patients with CHF complicated with lower respiratory tract infection
Miaomiao JI ; Chuanbo LI ; Yuekun WANG ; Yong XU
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(7):890-894
Objective To compare the value of Logistic regression model and XGBoost model in predicting the risk of thrombosis in elderly patients with CHF complicated with LRTI.Methods A total of 138 elderly CHF patients with LRTI admitted to our department from April 2019 to April 2024 were prospectively enrolled,and divided into thrombus group(43 cases)and non-thrombus group(95 cases)according to whether thrombosis occurred.Clinical data of these pa-tients were collected,and two risk prediction models of thrombosis in these patients were con-structed based on logistic regression and XGBoost regression,respectively.The predictive value was compared between the two models.Results The thrombus group had higher neutrophil count,NLR,and CRP,D-D and vWF levels,and increased MA,estimated dissolution percentage,and percentage LY30,but K and R and lower coagulation index than the non-thrombus group(P<0.01).NLR,CRP,D-D,vWF,LY30,K and R were influencing factors for thrombosis in the elderly CHF patients with LRTI(P<0.05,P<0.01).The AUC value of the multivariate logistic regression model and XGBoost model in predicting thrombosis in the patients was 0.915(95%CI:0.861-0.986)and 0.894(95%CI:0.841-0.971),respectively,with a sensitivity of 85.40%and 88.90%and a specificity of 96.50%and 82.30%,respectively.There was no statistical difference in AUC value between the two models(Z=0.573,P=0.678).Hosmer Lemeshow test showed the differences were not significant in the calibration curves of the multivariate logistic regression model and XGBoost model(x2=0.485,P=0.452;x2=0.669,P=0.335).Conclusion Multivari-ate logistic regression model and XGBoost model show equivalent efficacy in predicting thrombo-sis in CHF patients with LRTI.Abnormal levels of NLR,CRP,D-D,vWF,LY30,K,and R are im-portant factors affecting thrombosis in these elderly patients.
2.Comparison on predictive efficacy of two models for MACE in elderly patients with coronary artery calcification
Chuanbo LI ; Xiding LI ; Miaomiao JI ; Yuekun WANG
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(1):48-52
Objective To compare the efficacy of multivariate logistic regression and XGBoost models in predicting major adverse cardiovascular events(MACE)after percutaneous coronary in-tervention(PCI)in elderly patients with coronary artery calcification(CAC).Methods A total of 120 elderly patients with CAC lesions undergoing PCI in our hospital from June 2020 to June 2023 were retrospectively enrolled in this study.The incidence of MACE was observed during 1 year of follow-up.Nine patients were lost during the period,and the left patients were divided into MACE group(28 patients)and non-MACE group(83 patients).Multivariate logistic regression analysis and XGBoost model were used to screen the influencing factors of MACE in elderly CAC patients after PCI.ROC curve and calibration curve were drawn to compare the predictive efficiency of the two models.Results The MACE group had significantly advanced age,larger proportions of smoking and diabetes,higher LDL-C and Gensini score,and increased ratios of diseased vessels ≥3,severe calcification,combined rotary grinding and number of stent implantation when compared with the non-MACE group(P<0.05,P<0.01).Multivariate logistic regression model showed that smoking,diabetes,LDL-C,Gensini score,and number of stents implanted were independent risk factors for MACE in CAC patients after PCI(P<0.05,P<0.01).XGBoost model indicated that the top five important feature scores were Gensini score of 35,number of stent implantation score of 25,combined diabetes score of 22,smoking score of 18,and LDL-C score of 15.ROC curve analysis revealed that the AUC value of multivariate logistic regression model in predicting MACE in elderly CAC patients after PCI was 0.925(95%CI:0.859-0.966),with a sensitivity of 82.14%and a specificity of 97.59%,and the value of the XGBoost model was 0.918(95%CI:0.850-0.961),with a sensitivity of 89.29%and a specificity of 78.31%.There was no significant difference in predictive efficacy between the two models(Z=0.148,P=0.8823).Conclusion Multiple logistic regression model and XGBoost model show equally efficacy in predicting MACE in elderly CAC patients after PCI.Smoking,diabetes,LDL-C,Gensini score and number of stents implanted are independent risk factors for MACE in the patients.
3.Comparison on predictive efficacy of two models for MACE in elderly patients with coronary artery calcification
Chuanbo LI ; Xiding LI ; Miaomiao JI ; Yuekun WANG
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(1):48-52
Objective To compare the efficacy of multivariate logistic regression and XGBoost models in predicting major adverse cardiovascular events(MACE)after percutaneous coronary in-tervention(PCI)in elderly patients with coronary artery calcification(CAC).Methods A total of 120 elderly patients with CAC lesions undergoing PCI in our hospital from June 2020 to June 2023 were retrospectively enrolled in this study.The incidence of MACE was observed during 1 year of follow-up.Nine patients were lost during the period,and the left patients were divided into MACE group(28 patients)and non-MACE group(83 patients).Multivariate logistic regression analysis and XGBoost model were used to screen the influencing factors of MACE in elderly CAC patients after PCI.ROC curve and calibration curve were drawn to compare the predictive efficiency of the two models.Results The MACE group had significantly advanced age,larger proportions of smoking and diabetes,higher LDL-C and Gensini score,and increased ratios of diseased vessels ≥3,severe calcification,combined rotary grinding and number of stent implantation when compared with the non-MACE group(P<0.05,P<0.01).Multivariate logistic regression model showed that smoking,diabetes,LDL-C,Gensini score,and number of stents implanted were independent risk factors for MACE in CAC patients after PCI(P<0.05,P<0.01).XGBoost model indicated that the top five important feature scores were Gensini score of 35,number of stent implantation score of 25,combined diabetes score of 22,smoking score of 18,and LDL-C score of 15.ROC curve analysis revealed that the AUC value of multivariate logistic regression model in predicting MACE in elderly CAC patients after PCI was 0.925(95%CI:0.859-0.966),with a sensitivity of 82.14%and a specificity of 97.59%,and the value of the XGBoost model was 0.918(95%CI:0.850-0.961),with a sensitivity of 89.29%and a specificity of 78.31%.There was no significant difference in predictive efficacy between the two models(Z=0.148,P=0.8823).Conclusion Multiple logistic regression model and XGBoost model show equally efficacy in predicting MACE in elderly CAC patients after PCI.Smoking,diabetes,LDL-C,Gensini score and number of stents implanted are independent risk factors for MACE in the patients.
4.On-site calibration of measurement equipment in state-controlled atmosphere radiation environment automatic monitoring stations
Shaoting LI ; Lixiang XIAO ; Shuyu JIANG ; Chuanbo DAI ; Wenxiang ZHENG
Chinese Journal of Radiological Health 2025;34(3):402-407
Objective To perform on-site calibration of high-pressure ionization chambers and NaI(Tl) γ spectrometers in state-controlled atmospheric radiation environment automatic continuous monitoring stations and verify the reliability of the online radiation environment monitoring system. Methods 137Cs, 60Co, and 241Am were used as γ reference radiation sources to measure the metrological performance of high-pressure ionization chambers in nine state-controlled atmospheric radiation environment automatic monitoring stations in Hubei Province, China. The performance metrics included background radiation, response, and repeatability. Additionally, the correlation between dose rate and humidity was analyzed, and the energy resolution and activity response of NaI(Tl) γ spectrometers were measured. Results Among the nine state-controlled atmospheric radiation environment automatic monitoring stations, the background radiation of high-pressure ionization chambers ranged from 58.2 nGy/h to 82.6 nGy/h. The response of the high-pressure ionization chambers ranged from 0.94 to 1.08, fulfilling the requirement of 1.0 ± 0.2. The repeatability of high-pressure ionization chambers ranged from 0.43% to 3.80%, satisfying the requirement of not exceeding 10%. A significant correlation was observed between dose rate and humidity, with a correlation coefficient of 0.4476. For NaI(Tl) γ spectrometers, the energy resolution ranged from 6.8% to 7.9%, fulfilling the requirement of not exceeding 9% for the 661.7 keV energy peak of 137Cs. The NaI(Tl) γ spectrometers showed 1.4% to 1.8% s−1·Bq−1 activity response to 241Am and 6.6‰ to 8.4‰ s−1·Bq−1 activity response to 60Co. Conclusion The online monitoring systems in the nine state-controlled atmospheric radiation environment automatic monitoring stations are stable and reliable, providing accurate radiation environment monitoring data for public awareness.
5.Analysis of respiratory pathogenic microorganisms in plasma samples from healthy plasma donors in winter
Yue WANG ; Li CHENG ; Ying LIU ; Qin GONG ; Jianxiao TONG ; Chuanbo ZHAO ; Jiaru GUO ; Yan LUO ; Jin ZHANG
Chinese Journal of Microbiology and Immunology 2025;45(2):141-148
Objective:To perform routine plasma test, SARS-CoV-2 nucleic acid test, and respiratory pathogenic microorganism nucleic acid test on plasma samples collected from 1 040 healthy plasma donors in winter.Methods:Plasma samples were collected from 1 040 healthy plasma donors at Yunmeng Plasma Collection Station in the winter of 2020. Routine plasma test, HBV/HCV/HIV nucleic acid test, SARS-CoV-2 nucleic acid test, and 22 respiratory pathogenic microorganism nucleic acid test were performed to analyze the quality of blood plasmas.Results:All plasma samples were qualified in the routine tests, meeting the requirements of the Chinese Pharmacopoeia, and tested negative for SARS-CoV-2 nucleic acid. Respiratory pathogenic microorganism nucleic acids were detected in 29 samples with a positive rate of 2.79% (29/1 040). There were 21 cases of simple virus infections, including 17 cases of coronavirus subtype infection, three cases of parainfluenza virus type 2 infection, and one case of human bocavirus infection. Eight cases were mixed infections of viruses and bacteria, four of which were viral infection combined with Bordetella pertussis. The 29 positive samples were collected from people of different age groups, including two from 31-40 years old (1.96%, 2/102 ), three from 41-50 years old (1.59%, 3/189), five from 51-55 years old (1.94%, 5/257), and 19 from 56-60 years old (4.59%, 19/414). Samples from the people aged 56-60 years accounted for the most (39.81%, 414/1 040), as well as the infection rate in this age group. Conclusions:In autumn and winter, respiratory pathogenic microorganism nucleic acid test should be performed when collecting plasma samples from donors aged 56-60 years in addition to meeting the requirements of the Chinese Pharmacopoeia. It is also suggested to conduct respiratory pathogenic microorganism nucleic acid test on pooled plasma and blood products.
6.Analysis of SLCO1B1 and ApoE genetic polymorphisms in patients of Han ethnic group with cardiovascular and cerebrovascular diseases from Anhui Province
Jie Li ; Xiaowen Cheng ; Xiang Xu ; Chuanbo Ha ; Wenjun Hu ; Hui Tao
Acta Universitatis Medicinalis Anhui 2025;60(4):619-623
Objective :
To investigate the distribution of solute carrier organic anion transporter family member 1B1(SLCO1B1) and apolipoprotein E(ApoE) gene polymorphisms in the patients of Han ethnic group with cardiovascular and cerebrovascular diseases from Anhui Province, in order to provide the basis for the individualized therapy of statins in clinical practice.
Methods:
924 Han patients with cardiovascular and cerebrovascular diseases were selected. The SLCO1B1 and ApoE genotypes of the patients were detected by polymerase chain reaction-fluorescent probe method, and their distribution was compared among different genders and other regions in China.
Results:
Seven SLCO1B1 gene subtypes were detected in 924 patients, including *1a/*1b(33.01%),*1b/*1b(41.45%), *1b/*15(12.34%), *1a/*1a(7.03%), *1a/*15(5.52%), *15/*15(0.54%) and *5/*5(0.11%), without detection of the two gene subtypes of *1a/*5 and *5/*15; the normal metabolic genotype I of SLCO1B1(*1a/*1a, *1a/*1b, *1b/*1b) accounted for the highest proportion in this population(81.49%), the intermediate metabolic genotype II and the weak metabolic genotype III of SLCO1B1 accounted for 17.86% and 0.65% respectively; six ApoE gene subtypes were detected, including E3/E3(66.78%), E3/E4(19.37%), E2/E3(9.63%), E4/E4(1.84%), E2/E4(1.73%) and E2/E2(0.65%); the E3 mass genotype(E2/E4, E3/E3) accounted for the highest proportion in this population(68.51%); there was no significant difference in the distribution of SLCO1B1 and ApoE genes between different genders; there was no significant difference in the distribution of SLCO1B1 between the Han population from Anhui and the South China and Central China, but a significant difference was found between the Anhui Han population and the Southwest China(P<0.05); the distribution of ApoE in the Anhui Han population demonstrated no statistically significant variation from those in South China and Southwest China, whereas significant differences were observed in comparison with Central China(P<0.05).
Conclusion
In the Han population with cardiovascular and cerebrovascular diseases in Anhui, the distributions of SLCO1B1 and ApoE gene polymorphisms show no significant gender differences but exhibit regional variations. These populations are predominantly characterized by class I normal metabolic genotype(SLCO1B1) and E3 mass genotypes(ApoE), indicating a higher tolerance to statin dosages and normal therapeutic efficacy in this cohort.
7.Comparison of two models in predicting the risk of thrombosis in elderly patients with CHF complicated with lower respiratory tract infection
Miaomiao JI ; Chuanbo LI ; Yuekun WANG ; Yong XU
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(7):890-894
Objective To compare the value of Logistic regression model and XGBoost model in predicting the risk of thrombosis in elderly patients with CHF complicated with LRTI.Methods A total of 138 elderly CHF patients with LRTI admitted to our department from April 2019 to April 2024 were prospectively enrolled,and divided into thrombus group(43 cases)and non-thrombus group(95 cases)according to whether thrombosis occurred.Clinical data of these pa-tients were collected,and two risk prediction models of thrombosis in these patients were con-structed based on logistic regression and XGBoost regression,respectively.The predictive value was compared between the two models.Results The thrombus group had higher neutrophil count,NLR,and CRP,D-D and vWF levels,and increased MA,estimated dissolution percentage,and percentage LY30,but K and R and lower coagulation index than the non-thrombus group(P<0.01).NLR,CRP,D-D,vWF,LY30,K and R were influencing factors for thrombosis in the elderly CHF patients with LRTI(P<0.05,P<0.01).The AUC value of the multivariate logistic regression model and XGBoost model in predicting thrombosis in the patients was 0.915(95%CI:0.861-0.986)and 0.894(95%CI:0.841-0.971),respectively,with a sensitivity of 85.40%and 88.90%and a specificity of 96.50%and 82.30%,respectively.There was no statistical difference in AUC value between the two models(Z=0.573,P=0.678).Hosmer Lemeshow test showed the differences were not significant in the calibration curves of the multivariate logistic regression model and XGBoost model(x2=0.485,P=0.452;x2=0.669,P=0.335).Conclusion Multivari-ate logistic regression model and XGBoost model show equivalent efficacy in predicting thrombo-sis in CHF patients with LRTI.Abnormal levels of NLR,CRP,D-D,vWF,LY30,K,and R are im-portant factors affecting thrombosis in these elderly patients.
8.Analysis of respiratory pathogenic microorganisms in plasma samples from healthy plasma donors in winter
Yue WANG ; Li CHENG ; Ying LIU ; Qin GONG ; Jianxiao TONG ; Chuanbo ZHAO ; Jiaru GUO ; Yan LUO ; Jin ZHANG
Chinese Journal of Microbiology and Immunology 2025;45(2):141-148
Objective:To perform routine plasma test, SARS-CoV-2 nucleic acid test, and respiratory pathogenic microorganism nucleic acid test on plasma samples collected from 1 040 healthy plasma donors in winter.Methods:Plasma samples were collected from 1 040 healthy plasma donors at Yunmeng Plasma Collection Station in the winter of 2020. Routine plasma test, HBV/HCV/HIV nucleic acid test, SARS-CoV-2 nucleic acid test, and 22 respiratory pathogenic microorganism nucleic acid test were performed to analyze the quality of blood plasmas.Results:All plasma samples were qualified in the routine tests, meeting the requirements of the Chinese Pharmacopoeia, and tested negative for SARS-CoV-2 nucleic acid. Respiratory pathogenic microorganism nucleic acids were detected in 29 samples with a positive rate of 2.79% (29/1 040). There were 21 cases of simple virus infections, including 17 cases of coronavirus subtype infection, three cases of parainfluenza virus type 2 infection, and one case of human bocavirus infection. Eight cases were mixed infections of viruses and bacteria, four of which were viral infection combined with Bordetella pertussis. The 29 positive samples were collected from people of different age groups, including two from 31-40 years old (1.96%, 2/102 ), three from 41-50 years old (1.59%, 3/189), five from 51-55 years old (1.94%, 5/257), and 19 from 56-60 years old (4.59%, 19/414). Samples from the people aged 56-60 years accounted for the most (39.81%, 414/1 040), as well as the infection rate in this age group. Conclusions:In autumn and winter, respiratory pathogenic microorganism nucleic acid test should be performed when collecting plasma samples from donors aged 56-60 years in addition to meeting the requirements of the Chinese Pharmacopoeia. It is also suggested to conduct respiratory pathogenic microorganism nucleic acid test on pooled plasma and blood products.
9.Ultrasound image segmentation algorithm for hepatic cystic echinococcosis based on improved DeepLabV3+
Miwueryiti HAILATI ; Renaguli AIHEMAITINIYAZI ; Li LI ; Chuanbo YAN
Chinese Journal of Medical Physics 2024;41(6):702-709
Objective To apply the improved DeepLabV3+based image semantic segmentation algorithm to the ultrasound image processing for hepatic cystic echinococcosis,thereby achieving automatic segmentation and detection of hepatic echinococcosis lesions,and improving clinical diagnostic efficiency.Methods DeepLabV3+based image semantic segmentation network was employed as the basic method,and the following improvements were made.To address the issues of high computational complexity,high memory consumption,difficulty in deploying on embedded platforms with limited computing power,and difficulty in fully utilizing multi-scale information when extracting image feature information,the original backbone network Xception of the model was replaced with MobileNetV2 for obtaining a lightweight model framework.Additionally,efficient channel attention was applied to underlying features for reducing computational complexity and improving the clarity of target boundaries;and finally,Dice Loss was introduced into the model to alleviate the problem of the model focusing more on the background area and ignoring the foreground area containing the target.Results Validation was conducted on 5 lesion types in the self-built VOC2007 dataset of hepatic cystic echinococcosis.Experimental results showed that the improved model achieved a mean intersection over union of 73.8 and a mean pixel accuracy of 83.5,indicating that the model can predict more precise semantic segmentation results and effectively optimize model complexity and segmentation accuracy.
10.Surgical design and fabrication of ear framework for auricular reconstruction based on digital technique
Panpan CUI ; Shijie TANG ; Xiaoyan MAO ; Xiaojian LI ; Chuanbo FENG ; Zhenfu HU ; Zhiqi HU
Chinese Journal of Plastic Surgery 2022;38(2):203-207
Objective:To investigate the application of three-dimensional digital technique in customized ear framework fabrication for auricular reconstruction.Methods:From July 2018 to October 2019, the patients with microtia who underwent ear reconstruction in the Department of Plastic and Aesthetic Surgery, Nanfang Hospital, Southern Medical University were enrolled. Each patient with unilateral microtia underwent auricular CT scan and preoperative analysis and ear framework design were carried out with Mimics software 18.0. The two-dimension(2D) ear films and three-dimension(3D) silicon models were produced by 1∶1 2D printing and 3D printing, respectively. Microtia reconstruction was performed according to the guide of the models, patients were followed up over a six-month period to evaluate the size, outline, height and auriculocephalic angle of the reconstructed ear. The satisfactory outcomes of the patients were scored according to a 5-point Likert scale.Results:A total of 15 patients were included in this study, including 11 males and 4 females, aged 8-27 years, with an average of 15.5 years old. All the 15 patients completed the surgical planning and ear reconstruction successfully, without major complications, such as hematomas, inflammation, skin necrosis and framework exposure. The costal cartilage frameworks were very similar to the printed 3D models in size and contour. Comparison between the two sides was made at six months postoperatively. The reconstructed ear was much the same as that of contralateral side, and all patients were satisfied with their reconstructed ear outcomes with average score of 4.4.Conclusions:With the application of digital technique for pre-surgical planning in microtia reconstruction patients, ear templates were produced from 2D to 3D, and the correction of microtia was changed from standard auricular reconstruction to personalized auricular reconstruction, with a great improvement of the precision in ear framework fabrication.


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