Objective To construct a risk prediction model for venous thromboembolism(VTE)in patients with acute stroke and analyze its predictive value with decision curve.Methods Clinical data of 265 patients with acute stroke admitted to Department of Neurology of Pingxiang People's Hospital between May 2022 and May 2024 were collected,and 185 of them(69.8％)were assigned to a training set and 80 cases(30.2％)into a validation set.Based on the results of color Doppler ultrasound examination,the patients in the training set were divided into the VTE group(72 cases)and the non-VTE group(113 cases).Multivariate logistic regression analysis was used to identify the risk factors for VTE occurrence in the patients.A prediction model was constructed and a nomegram was developed to visually present the logistic regression prediction model.ROC curve and decision curve analyses were applied to evaluate the predictive performance of the logis-tic regression model.Results The VTE group had significantly larger intracranial hemorrhage volume,higher fibrinogen(FIB),D-dimer and C-reactive protein(CRP)levels,and lower Glasgow Coma Scale(GCS)score than the non-VTE group(P＜0.01).Multivariate logistic regression analysis indicated that intracranial hemorrhage volume(OR=1.243,95％CI:1.015-1.522),FIB(OR=3.161,95％CI:1.711-5.841),CRP(OR=1.595,95％CI:1.283-1.981),and D-dimer(OR=6.234,95％CI:2.693-14.434)were independent risk factors for the occurrence of VTE in the patients with acute stroke,while GCS score(OR=0.587,95％CI:0.413-0.834,P=0.003)was an independent protective factor against the occurrence.A VTE prediction model based on these influencing factors obtained a consistency index of 0.978.The calibration curve results showed that the observed values were in good agreement with the predicted values.ROC curve analysis indicated that the AUC value of the prediction model was 0.978(95％CI:0.945-0.994)in the training set and 0.959(95％CI:0.890-0.991)in the validation set.Decision curve analysis revealed that the model achieved higher net benefit when the threshold probability was between 20％and 80％.Conclusion Intracranial bleeding volume,GCS score,CRP,Didimer and FIB are related influencing factors of VTE in patients with acute stroke,and the prediction model of deci-sion curve based on the above factors is of high prediction efficiency.

Objective To construct a risk prediction model for venous thromboembolism(VTE)in patients with acute stroke and analyze its predictive value with decision curve.Methods Clinical data of 265 patients with acute stroke admitted to Department of Neurology of Pingxiang People's Hospital between May 2022 and May 2024 were collected,and 185 of them(69.8％)were assigned to a training set and 80 cases(30.2％)into a validation set.Based on the results of color Doppler ultrasound examination,the patients in the training set were divided into the VTE group(72 cases)and the non-VTE group(113 cases).Multivariate logistic regression analysis was used to identify the risk factors for VTE occurrence in the patients.A prediction model was constructed and a nomegram was developed to visually present the logistic regression prediction model.ROC curve and decision curve analyses were applied to evaluate the predictive performance of the logis-tic regression model.Results The VTE group had significantly larger intracranial hemorrhage volume,higher fibrinogen(FIB),D-dimer and C-reactive protein(CRP)levels,and lower Glasgow Coma Scale(GCS)score than the non-VTE group(P＜0.01).Multivariate logistic regression analysis indicated that intracranial hemorrhage volume(OR=1.243,95％CI:1.015-1.522),FIB(OR=3.161,95％CI:1.711-5.841),CRP(OR=1.595,95％CI:1.283-1.981),and D-dimer(OR=6.234,95％CI:2.693-14.434)were independent risk factors for the occurrence of VTE in the patients with acute stroke,while GCS score(OR=0.587,95％CI:0.413-0.834,P=0.003)was an independent protective factor against the occurrence.A VTE prediction model based on these influencing factors obtained a consistency index of 0.978.The calibration curve results showed that the observed values were in good agreement with the predicted values.ROC curve analysis indicated that the AUC value of the prediction model was 0.978(95％CI:0.945-0.994)in the training set and 0.959(95％CI:0.890-0.991)in the validation set.Decision curve analysis revealed that the model achieved higher net benefit when the threshold probability was between 20％and 80％.Conclusion Intracranial bleeding volume,GCS score,CRP,Didimer and FIB are related influencing factors of VTE in patients with acute stroke,and the prediction model of deci-sion curve based on the above factors is of high prediction efficiency.

The relationship between Ala/Ser polymorphism in 133 codon of exon 3 region of the RASSF1 gene and genetic susceptibility of lung cancer in Hubei province Han population was investigated by a case-control study. Polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) technique was adopted to analyze the polymorphism of codon 133 of exon 3 in the RASSF1 gene of 100 pathologically diagnosed lung cancer patients, and 100 healthy controls. The relationship between different genotypes and the susceptibility of lung cancer was analyzed. Among 200 blood samples from Han people in Hubei Province, including 100 from lung cancer patients and 100 from healthy controls, the frequencies of Ala/Ala, Ala/Ser, Ser/Ser genotype of the RASSF1 in lung cancer patients were 83%, 16%, 1%, and those in healthy controls was 93%, 7%, 0% respectively, with the difference being statistically significant between two groups (P<0.05). The individuals with Ala/Ser genotype had higher risk of suffering from lung cancer, with an OR of 2.341, and 95% CI of 1.009-6.393 respectively. It was concluded that RASSF1Ala133Ser was a susceptible genetic factor of lung cancer. Ala/Ser genotype increased the risk of lung cancer.

is and K-ras mutation. It was concluded that aberrant methylation of the RASSF2A gene with the subsequent loss of RASSF2A expression plays an important role in the pathogenesis of HCC.

The relationship between Ala/Ser polymorphism in 133 codon of exon 3 region of the RASSF 1 gene and genetic susceptibility of lung cancer in Hubei province Han population was inves-tigated by a case-control study. Polymerase chain reaction-restriction fragment length polymorphisrr (PCR-RFLP) technique was adopted to analyze the polymorphism of codon 133 of exon 3 in the RASSF1 gene of 100 pathologically diagnosed lung cancer patients, and 100 healthy controls. The relationship between different genotypes and the susceptibility of lung cancer was analyzed. Among 200 blood samples from Han people in Hubei Province, including 100 from lung cancer patients and 100 from healthy controls, the frequencies of Ala/Ala, Ala/Ser, Ser/Ser genotype of the RASSF1 in lung cancer patients were 83%, 16%, 1%, and those in healthy controls was 93%, 7%, 0% respec-tively, with the difference being statistically significant between two groups (P<0.05). The individu-als with Ala/Ser genotype had higher risk of suffering from lung cancer, with an OR of 2.341, and 95% CI of 1.009-6.393 respectively. It was concluded that RASSFIAla133Ser was a susceptible ge-netic factor of lung cancer. Ala/Ser genotype increased the risk of lung cancer.