Objective To explore the risk factors for obstetric septic shock.Methods The clinical data of 122 obstetric sepsis patients from Jan.2013 to Apr.2025 were retrospectively analyzed.The patients were assigned to shock group(n=26)or non-shock group(n=96)based on whether they progressed to septic shock.Variables including age,body mass index,multiple pregnancy,sequential organ failure assessment(SOFA)score,organ dysfunction status,white blood cell count(WBC),neutrophil count(NEU),neutrophil ratio,platelet count,procalcitonin,C-reactive protein,lactate(Lac),and D-dimer were recorded.Multivariate logistic regression analysis was used to identify the independent risk factors for obstetric septic shock.The predictive efficacy of these factors was evaluated using receiver operating characteristic(ROC)curve analysis.Results The proportions of patients aged≥35 years,and those with respiratory,cardiac,or central nervous system dysfunction,were significantly higher in the shock group than in the non-shock group,and the SOFA score,WBC,NEU,neutrophil ratio and Lac level were significantly higher in the shock group(all P＜0.05).Multivariate logistic regression analysis showed that increased NEU(odds ratio[OR]=1.093,95%confidence interval[CI]1.022-1.169,P=0.010)and age≥35 years(OR=3.433,95%CI 1.112-10.602,P=0.032)were independent risk factors for obstetric septic shock.ROC curve analysis showed that NEU had predictive value for obstetric septic shock(area under curve=0.741,95%CI 0.634-0.848),with an optimal cut-offvalue of 17.17×109/L.Conclusion Increased NEU and age≥35 years are independent risk factors for obstetric septic shock.NEU has predictive value for the development of obstetric septic shock and may serve as an important indicator for clinical assessment and timely treatment.

Objective To observe the value of apparent diffusion coefficient(ADC)for quantitatively evaluating progressive muscle injury of rabbit limbs in early stage of high-voltage electrical burn.Methods Twenty healthy adult rabbits were selected to establish limb high-voltage electrical burn models,which were randomly divided into 0.5,24,48 and 72 h groups(each n=5).MR diffusion weighted imaging(DWI)was collected for each group at 0.5,24,48 and 72 h after modeling,and the injured core muscles of the right hind limb and the normal muscles of the contralateral limb were taken for HE staining.The muscle's ADC,muscle fiber density(MFD)and muscle fiber diameter(D)values at the injured core of current entry and exit were compared,and those of normal muscle were also analyzed.The correlations of ADC values in injured core muscle and MFD or D values were investigated.Results There were significant differences of ADC values of injured core muscle at both the entry and exit and normal muscle,also of ADC values of injured core muscle at the entry and exit within each group(all P＜0.05).ADC values of injured core muscle at the entry and exit decreased with time going(all P＜0.05),but ADC values of normal muscle were not significantly different among different time points(P＞0.05).MFD values of injured core muscle at the entry and exit decreased with time going(all P＜0.05),while MFD values of the normal muscle,D values of the injured core muscle at the entry and exit and normal muscle were not significantly different among time points(all P＞0.05).ADC value of the injured core muscle was positively correlated with MFD value and negatively correlated with D value(rs=0.846,r=-0.507,both P＜0.05).Conclusion ADC could quantitatively evaluate the progressive muscle injury of rabbit limbs in early stage of high-voltage electrical burn.

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 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 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.

Objective To explore the feasibility of low concentration contrast medium and low-voltage combined with adaptive statistical iterative reconstruction(ASRI)technique in enhanced CT imaging of solitary pulmonary nodules. Methods A total of 40 patients with solitary pulmonary nodules who underwent routine exam-inations and were pathologically confirmed from February 2015 to February 2017 were collected and divided into conventional group(conventional dose,high osmolar contrast,using filtered back projection reconstruction)and low dose group(low voltage,low concentration isotonic contrast,iterative reconstruction). Results Subjective scoring of conventional group(3.97 ± 0.57)and low dose group(4.01 ± 0.54)indicated no statistical significance (P > 0.05). No significant difference was found regarding to reconstructed image quality,SNR and CNR in both two groups.The dose length product(DLP)and effective dose(ED)in low dose group were lower than those in the conventional group[(283.52 ± 11.50)mGy/cm vs(370.74 ± 29.56)mGy/cm;(3.65 ± 0.32)mSV vs(5.11±0.25) mSV],and the difference was statistically significant(P < 0.05). Conclusions Low concentration isotonic con-trast agent(iodixanol 270 mgI/L)and low voltage(100 kV)combined with ASIR technology could satisfy the clini-cal need in enhanced CT imaging of solitary pulmonary nodule.

Coronary artery disease (CAD) is a complex human disease, involving multiple genes and their nonlinear interactions, which often act in a modular fashion. Genome-wide single nucleotide polymorphism (SNP) profiling provides an effective technique to unravel these underlying genetic interplays or their functional involvements for CAD. This study aimed to identify the susceptible pathways and modules for CAD based on SNP omics. First, the Wellcome Trust Case Control Consortium (WTCCC) SNP datasets of CAD and control samples were used to assess the joint effect of multiple genetic variants at the pathway level, using logistic kernel machine regression model. Then, an expanded genetic network was constructed by integrating statistical gene–gene interactions involved in these susceptible pathways with their protein–protein interaction (PPI) knowledge. Finally, risk functional modules were identified by decomposition of the network. Of 276 KEGG pathways analyzed, 6 pathways were found to have a significant effect on CAD. Other than glycerolipid metabolism, glycosaminoglycan biosynthesis, and cardiac muscle contraction pathways, three pathways related to other diseases were also revealed, including Alzheimer’s disease, non-alcoholic fatty liver disease, and Huntington’s disease. A genetic epistatic network of 95 genes was further constructed using the abovementioned integrative approach. Of 10 functional modules derived from the network, 6 have been annotated to phospholipase C activity and cell adhesion molecule binding, which also have known functional involvement in Alzheimer’s disease. These findings indicate an overlap of the underlying molecular mechanisms between CAD and Alzheimer’s disease, thus providing new insights into the molecular basis for CAD and its molecular relationships with other diseases.

Objective:To establish the quality standard for Aitongxiao granules. Methods:TLC was used to identify Herba Hedy-otis Diffusa, Herba Scutell Barbatae, Radix Astragali and Radix Paeoniae Rubra in Aitongxiao granules, and the content of scutellarin was determined by HPLC. The stationary phase was a Kromasial C18 column (250 mm × 4. 6 mm,5μm), the mobile phase was metha-nol-3% acetic acid (33∶67), the flow rate was 1. 0 ml·min-1, the detection wavelength was at 335 nm, and the temperature was 25℃. Results:The characteristic TLC spots of the granule samples were the same as those of the standard samples without any inter-ference from the negative control. Scutellarin had a good linear relationship within the range of 2.18-10.90μg·ml-1(r=0.999 9), and the average recovery was 96. 65% with RSD of 1. 45﹪(n=6). Conclusion:The method is simple, accurate, reliable and repro-ducible, which could be used in the quality control of Aitongxiao granules.