Objective To investigate the clinical features and risk factors for deep vein thrombosis(DVT)of the lower ex-tremities in burn patients.Methods The clinical data of 155 burn patients admitted to Wuhan Third Hospital from January 2021 to January 2023 were retrospectively analyzed.The patients were divided into DVT group and non-DVT group according to whether they had concurrent DVT during hospitalization.Two groups of baseline data were compared[sex,age,body mass in-dex(BMI),coexisting diseases,smoking,drinking,DVT history of the lower limbs,burn cause,burn site,burn degree,central venous catheter retention in the femoral vein,wound infection,low-molecular-weight heparin application,time in bed,and labora-tory indicators[D-dimer(D-d),fibrinogen(FIB),homocysteine(Hey)].The levels of tumor necrosis factor α(TNF-α)and C-reac-tive protein(CRP)differed,and the risk factors for DVT in burn patients were determined via multivariate logistic regression a-nalysis.Finally,this study analyzed the value of BMI,time in bed,D-dimer,fibrinogen,Hcy,TNF-α,and CRP in predicting DVT in burn patients via receiver operating characteristic(ROC)curves.Results There were no significant differences between the two groups in terms of sex,combined disease,smoking or drinking,or cause of burn(all P＞0.05).The following risk factors were found to be significantly greater in the group with deep vein thrombosis(DVT)than in the group without DVT:age 60 years or older,history of lower limb DVT,lower limb burn of degree Ⅱ or above covering 30％or more of the area,femoral vein indentation central venous catheter,wound infection,and lack of low-molecular-weight heparin treatment.Additionally,BMI,D-dimer levels,fibrinogen levels(FIB),homocysteine(Hcy)levels,TNF-α levels,and C-reactive protein(CRP)levels were signifi-cantly higher in the DVT group than in the non-DVT group.The time in bed was significantly longer in the DVT group than in the non-DVT group(P＜0.01).Multivariate logistic regression analysis confirmed that the risk factors for DVT in burn pa-tients included age ≥60 years,history of lower extremity DVT,lower extremity burn,burn degree Ⅱ or above,burn area≥30％,femoral vein indwelling central venous catheter,wound inf ection,lack of low-molecular-weight heparin application,increased BMI,elevated levels of D-dimer,FIB,Hcy,TNF-α,and CRP,and prolonged time in bed.ROC analysis confirmed that BMI,time in bed,D-d,FIB,Hcy,TNF-α and CRP could all be used to predict DVT in burn patients,and the areas under the curve were 0.844,0.853,0.890,0.817,0.892,0.962 and 0.776,respectively,(all P＜0.01).Conclusion Burn patients complicated with DVT are affected by many factors.Moreover,ROC analysis confirmed that BMI,time in bed,D-d,FIB,Hcy,TNF-α and CRP could be indicators for predic-ting DVT,which should be considered in the subsequent clinical treatment of such patients.

Objective To explore the factors influencing the pregnancy rate after fallopian tube recanalization(FTR),and to construct and validate a nomogram prediction model.Methods The clinical data of a total of 322 female patients with tubal obstructive infertility,who received FTR at the Wuhan Municipal Third Hospital of China between January 2018 and December 2022,were retrospectively analyzed.According to whether the female patient had natural pregnancy or not within 12 months after FTR treatment,the female patients were divided into the pregnant group and the non-pregnant group.Logistic regression analysis was used to determine the independent factors influencing pregnancy.The female patients were randomly divided into training group and validation group at 1∶1 ratio.A nomogram model was constructed in the training group,and the predictive efficacy of the model was verified in the validation group by using receiver operating characteristic(ROC)curves,calibration curves and decision curve analysis(DCA).Results The natural pregnancy rate at one year after FTR was 45.34％(146/322).Age＞35 years,primary infertility,duration of infertility＞3 years,distal fallopian tube obstruction,and moderate to severe tubal lesion were the independent risk factors affecting the pregnancy rate after FTR(all P＜0.05).The constructed nomogram model had a good differentiation and calibration ability and it carried a high degree of clinical utility.Conclusion The nomogram model constructed in this study can effectively predict the risk of infertility within one year after FTR treatment,which is helpful for formulating the individualized therapeutic scheme for infertility female patients.

Objective To explore the risk factors for the prognosis of interventional treatment of multiple pelvic fractures with bleeding.Methods A total of 82 patients with multiple pelvic fractures with bleeding were selected.All patients underwent interventional treatment and were divided into a death group(n=9)and a survival group(n=73)based on their treatment prognosis.The data of the two groups were reviewed and the complications,abbreviated injury scale(AIS),Glasgow prognostic score(GPS),and injury severity score(ISS)between the two groups were compared,and multivariate logistic regression was used to explore the influencing factors of patients prognosis.Results Eighty-two patients with multiple pelvic fractures with bleeding had 9 deaths after interventional treatment,with a mortality rate of 10.98％.The univariate results showed that there were statistical differences in the mortality rate of patients with multiple pelvic fractures with bleeding after interventional treatment,as well as the time to hospital after injury,combined trauma,blood transfusion,and surgical time(P＜0.05).The total incidence of respiratory failure,shock and infection in the death group(44.44％)were higher than those in the survival group(15.07％)(P＜0.05).The AIS,ISS,and acute physiology and chronic health evaluationⅡ(APACHE Ⅱ)in the death group were higher than those in the survival group(P＜0.05);The GPS was lower than that of the survival group(P＜0.05);The multivariate logistic results showed that the time to hospital after injury,combined trauma,blood transfusion,surgical time,complications,AIS,ISS,APACHE Ⅱ and GPS were the influencing factors for the mortality rate of patients with multiple pelvic fractures with bleeding treated with intervention(P＜0.05).Conclusion The proportion of deaths in patients with multiple pelvic fractures with bleeding is often influenced by factors such as complications,time to hospital after injury,combined trauma,AIS,GPS,and ISS.However,early interventional treatment is recommended to improve the patient's treatment prognosis with minimal trauma and good results.

Objective:To screen the risk factors for pulmonary embolism in severe burn patients, based on which, a risk prediction model was established and validated.Methods:This study was a retrospective case series study. The clinical data of 267 severe burn patients who met the inclusion criteria and were admitted to the Department of Burns of Wuhan Third Hospital from March 2020 to March 2023 were collected, including 159 males and 108 females, aged 18-82 years. The patients were divided into pulmonary embolism group (26 cases) and non-pulmonary embolism group (241 cases) according to whether they were complicated with pulmonary embolism. The following data of patients in the 2 groups were collected and compared, including gender, age, body mass index, bedtime during treatment, cause of burn, albumin level on admission, combination of chronic obstructive pulmonary disease (COPD), combination of diabetes mellitus, combination of hypertension, combination of inhalation injury, and the abbreviated burn severity index (ABSI) on admission. The indicators with statistically significant differences between the two groups were conducted with univariate and multivariate logistic regression analyses to identify the independent risk factors for pulmonary embolism in 267 severe burn patients. Based on these findings, a nomogram prediction model was established. The performance of the prediction model was evaluated by the receiver operating characteristic (ROC) curve, while its validation was conducted through calibration curve and clinical decision curve analysis.Results:The proportions of beyond 60 years old, bedtime over 7 days during treatment, combination of COPD, and combination of diabetes mellitus (with χ2 values of 7.75, 29.15, 29.86, and 5.94, respectively), and ABSI score on admission ( t=6.01) of patients in pulmonary embolism group were significantly higher than those in non-pulmonary embolism group ( P<0.05). There were no statistically significant differences in the other indicators between the two groups of patients ( P>0.05). The univariate logistic regression analysis showed that age, bedtime during treatment, combination of COPD, combination of diabetes mellitus, and ABSI score on admission were the risk factors for pulmonary embolism in severe burn patients (with odds ratios of 3.40, 14.87, 17.78, 2.80, and 1.88, respectively, 95% confidence intervals of 1.38-8.39, 4.34-50.98, 4.63-68.22, 1.19-6.58, and 1.47-2.41, respectively, P<0.05). The multivariate logistic regression analysis showed that bedtime over 7 days during treatment, combination of COPD, and high ABSI score on admission were the independent risk factors for pulmonary embolism in severe burn patients (with odds ratios of 11.02, 30.82, and 1.86, respectively, 95% confidence intervals of 2.76-43.98, 3.55-267.33, and 1.38-2.50, respectively, P<0.05). Based on the three aforementioned independent risk factors, a nomogram prediction model for the risk of pulmonary embolism in severe burn patients was established. The ROC curve of prediction model showed that the area under the ROC curve was 0.91 (with 95% confidence interval of 0.82-0.99). When the optimal cut-off value of 25% was taken, the sensitivity and specificity of prediction model was 84.6% and 93.4%, respectively. The calibration curve showed that the calibration curve of prediction model was around the ideal curve, with a consistency index of 0.80 in Cox regression (with 95% confidence interval of 0.74-0.87). The clinical decision curve showed that the threshold probability value of the prediction model was in the range of 1% to 98%, with net return rate over 0. Conclusions:The independent risk factors for pulmonary embolism in severe burn patients include bedtime over 7 days during treatment, combination of COPD, and high ABSI score on admission. The nomogram prediction model established based on this has good predictive value for complicated pulmonary embolism in severe burn patients.

Objective:To screen the risk factors for pulmonary embolism in severe burn patients, based on which, a risk prediction model was established and validated.Methods:This study was a retrospective case series study. The clinical data of 267 severe burn patients who met the inclusion criteria and were admitted to the Department of Burns of Wuhan Third Hospital from March 2020 to March 2023 were collected, including 159 males and 108 females, aged 18-82 years. The patients were divided into pulmonary embolism group (26 cases) and non-pulmonary embolism group (241 cases) according to whether they were complicated with pulmonary embolism. The following data of patients in the 2 groups were collected and compared, including gender, age, body mass index, bedtime during treatment, cause of burn, albumin level on admission, combination of chronic obstructive pulmonary disease (COPD), combination of diabetes mellitus, combination of hypertension, combination of inhalation injury, and the abbreviated burn severity index (ABSI) on admission. The indicators with statistically significant differences between the two groups were conducted with univariate and multivariate logistic regression analyses to identify the independent risk factors for pulmonary embolism in 267 severe burn patients. Based on these findings, a nomogram prediction model was established. The performance of the prediction model was evaluated by the receiver operating characteristic (ROC) curve, while its validation was conducted through calibration curve and clinical decision curve analysis.Results:The proportions of beyond 60 years old, bedtime over 7 days during treatment, combination of COPD, and combination of diabetes mellitus (with χ2 values of 7.75, 29.15, 29.86, and 5.94, respectively), and ABSI score on admission ( t=6.01) of patients in pulmonary embolism group were significantly higher than those in non-pulmonary embolism group ( P<0.05). There were no statistically significant differences in the other indicators between the two groups of patients ( P>0.05). The univariate logistic regression analysis showed that age, bedtime during treatment, combination of COPD, combination of diabetes mellitus, and ABSI score on admission were the risk factors for pulmonary embolism in severe burn patients (with odds ratios of 3.40, 14.87, 17.78, 2.80, and 1.88, respectively, 95% confidence intervals of 1.38-8.39, 4.34-50.98, 4.63-68.22, 1.19-6.58, and 1.47-2.41, respectively, P<0.05). The multivariate logistic regression analysis showed that bedtime over 7 days during treatment, combination of COPD, and high ABSI score on admission were the independent risk factors for pulmonary embolism in severe burn patients (with odds ratios of 11.02, 30.82, and 1.86, respectively, 95% confidence intervals of 2.76-43.98, 3.55-267.33, and 1.38-2.50, respectively, P<0.05). Based on the three aforementioned independent risk factors, a nomogram prediction model for the risk of pulmonary embolism in severe burn patients was established. The ROC curve of prediction model showed that the area under the ROC curve was 0.91 (with 95% confidence interval of 0.82-0.99). When the optimal cut-off value of 25% was taken, the sensitivity and specificity of prediction model was 84.6% and 93.4%, respectively. The calibration curve showed that the calibration curve of prediction model was around the ideal curve, with a consistency index of 0.80 in Cox regression (with 95% confidence interval of 0.74-0.87). The clinical decision curve showed that the threshold probability value of the prediction model was in the range of 1% to 98%, with net return rate over 0. Conclusions:The independent risk factors for pulmonary embolism in severe burn patients include bedtime over 7 days during treatment, combination of COPD, and high ABSI score on admission. The nomogram prediction model established based on this has good predictive value for complicated pulmonary embolism in severe burn patients.