Background Long-term exposure to ambient fine particulate matter (PM_2.5) may increase the risk of diabetes, and a healthy diet can effectively control fasting blood glucose levels. However, it is unclear whether dietary factors have a moderating effect on the risk of diabetes associated with atmospheric PM_2.5 exposure. Objective To investigate the association between long-term exposure to PM_2.5 and diabetes in rural areas of Ningxia, and potential interaction of long-term exposure to atmospheric PM_2.5 and diet on diabetes. Methods The study subjects were selected from the baseline survey data of the China Northwest Cohort-Ningxia (CNC-NX) , a natural population cohort. A total of 13917 subjects were included, excluding participants with missing covariate information. We utilized the annual average ambient PM_2.5 concentration from 2014 to 2018 as the long-term exposure level. Logistic regression and multiple linear regression were employed to analyze the associations of long-term atmospheric PM_2.5 exposure with diabetes and fasting blood glucose levels. Stratification by frequency of vegetable consumption, frequency of fruit consumption, and salty taste was used to examine moderating effects on the diabetes risk associated with atmospheric PM_2.5 exposure. Results The mean age of the 13917 subjects was (56.8±10.0) years, and the prevalence of diabetes was 9.8%. Between 2014 and 2018, the average annual concentration of PM_2.5 was (38.10±4.67) μg·m⁻³. The risk (OR) of diabetes was 1.018 (95%CI: 1.005, 1.032) and the fasting blood glucose was increased by 0.011 (95%CI: 0.004, 0.017) mmol·L⁻¹ for each 1 μg·m⁻³ increase in PM_2.5 concentration. Compared to those who consumed vegetables < 1 time per week, individuals who consume vegetables 1-3 times per week and ≥4 times per week had a reduced risk of developing diabetes by 27.1% (OR=0.729, 95%CI: 0.594, 0.893) and 16.8% (OR=0.832, 95%CI: 0.715, 0.971) respectively. Similarly, when compared to those who consumed fruits <1 time per week, individuals who consumed fruits 1-3 times per week and ≥4 times per week exhibited a reduced risk of diabetes by 16.4% (OR=0.836, 95%CI: 0.702, 0.998) and 18.2% (OR=0.818, 95%CI: 0.700, 0.959) respectively. Fasting blood glucose decreased by 0.202 (95%CI: -0.304, -0.101) mmol·L⁻¹ in participants who ate vegetables 1-3 times per week. The effect of salty taste on diabetes and fasting blood glucose was not significant. The results of stratified analysis by dietary factors and PM_2.5 concentration showed that the risks of diabetes were increased in the low PM_2.5 pollution-low vegetable intake frequency group and the high PM_2.5 pollution-low vegetable intake frequency group compared with the low PM_2.5 pollution-high vegetable intake frequency group, with OR values of 3.987 (95%CI: 2.943, 5.371) and 1.433 (95%CI: 1.143, 1.796) respectively. The risk of diabetes was 50.1% higher in participants with high PM_2.5 pollution and low fruit intake frequency than in participants with low PM_2.5 pollution and high fruit intake frequency (OR=1.501, 95%CI: 1.171, 1.926). No interaction was found between salty taste and PM_2.5 on diabetes. Conclusion Long-term exposure to ambient PM_2.5 is associated with an increased fasting blood glucose and an elevated risk of diabetes in rural Ningxia population. Increasing the frequency of weekly consumption of vegetables or fruits may have a certain protective effect against diabetes occurrence, as well as a moderating effect on diabetes and fasting blood glucose levels associated with long-term exposure to atmospheric PM_2.5.

ObjectiveTo investigate the acute effects of compound air pollution on children’s respiratory function. MethodsUsing panel group study design， 223 students in five classes of grade 4 from two primary schools （a， b） in Xuhui and Hongkou districts of Shanghai were randomly selected to measure pulmonary function and exhaled nitric oxide （FeNO）. The first three tests were carried out from May to June in 2020， and the fourth test was carried out from September to December in 2021. At the same time， the daily and hourly mean values of PM_2.5， PM₁₀， SO₂， NO₂， O₃ and CO was collected from the nearby air quality monitoring points of the two schools during the same period ， as well as meteorological monitoring data （temperature， humidity， wind speed and atmospheric pressure）. The linear mixed effect model was used to analyze the effects of air pollution on pulmonary function and respiratory inflammation in the summer. ResultsThe results of single pollutant model showed that PM_2.5， PM_10， SO₂ and NO₂ were positively correlated with FeNO， and the effect was reflected in lag0， lag1 and lag3 （P<0.05）. PM_2.5， PM₁₀ and NO₂ were negatively correlated with the changes of lung function FEF_25%， FEF_50%， FEF_75%， FeF_25%-75%， PEF， FVC， FEV1 and FEV1/FVC， and the effect was reflected in lag0 to lag3 days （P<0.05）. The results of the dual pollutant model showed that the concentration changes of SO₂ and NO₂ were significantly correlated with the decrease of FEV1 when combined with O₃ or PM_2.5 （P<0.01）， and the concentration changes of PM_2.5 was significantly correlated with the increase of FeNO when O₃， SO₂ and NO₂ were combined respectively （P<0.01）. The effects of the dual pollutant model were greater than the effect of PM_2.5 single pollutant model. ConclusionThe health effects of different air pollutants on children’s respiratory tract function indexes in summer are different. The combined effects of two pollutants on the lung function of children increased to different degrees. Although air pollution is light in summer， it still has an impact on children’s respiratory tract function index and inflammation index， and the combined effect of dual pollutants is more significant than that of single pollutant.

ObjectiveTo investigate the mechanism of Baihuan Xiaoyao Decoction （Xiaoyaosan added with Lilii Bulbus and Albiziae Cortex） in alleviating depression-like behaviors of juvenile rats by regulating the polarization of microglia. MethodSixty juvenile SD rats were randomized into normal control， model， fluoxetine， and low-， medium-， and high-dose （5.36， 10.71， 21.42 g·kg^-1， respectively） Baihuan Xiaoyao decoction groups. The rat model of juvenile depression was established by chronic unpredictable mild stress （CUMS）. The sucrose preference test （SPT） was carried out to examine the sucrose preference of rats. Forced swimming test （FST） was carried out to measure the immobility time of rats. The open field test （OFT） was conducted to measure the total distance， the central distance， the number of horizontal crossings， and the frequency of rearing. Morris water maze （MWM） was used to measure the escape latency and the number of crossing the platform. The immunofluorescence assay was employed to detect the expression of inducible nitric oxide synthase （iNOS， the polarization marker of M1 microglia） and CD206 （the polarization marker of M2 microglia）. Real-time polymerase chain reaction was employed to determine the mRNA levels of iNOS， CD206， pro-inflammatory cytokines ［tumor necrosis factor （TNF）-α， interleukin （IL）-1β， and IL-6］ and anti-inflammatory cytokines （IL-4 and IL-10） in the hippocampus. Western blotting was employed to determine the protein levels of iNOS and CD206 in the hippocampus. The levels of IL-4 and IL-6 in the hippocampus were detected by enzyme-linked immunosorbent assay. ResultCompared with the normal control group， the model rats showed a reduction in sucrose preference （P<0.05）， an increase in immobility time （P<0.05）， decreased motor and exploratory behaviors （P<0.05）， and weakened learning and spatial memory （P<0.05）. In addition， the model rats showed up-regulated mRNA and protein levels of iNOS and mRNA levels of IL-1β， IL-6， and TNF-α （P<0.05）. Compared with the model group， Baihuan Xiaoyao decoction increased the sucrose preference value （P<0.05）， shortened the immobility time （P<0.01）， increased the motor and exploratory behaviors （P<0.05）， and improved the learning and spatial memory （P<0.01）. Furthermore， the decoction down-regulated the positive expression and protein level of iNOS， lowered the levels of TNF-α， IL-1β， and IL-6 （P<0.01）， promoted the positive expression of CD206， and elevated the levels of IL-4 and IL-10 （P<0.01） in the hippocampus of the high dose group. Moreover， the high-dose Baihuan Xiaoyao decoction group had higher sucrose preference value （P<0.01）， shorter immobility time （P<0.01）， longer central distance （P<0.01）， stronger learning and spatial memory （P<0.01）， higher positive expression and protein level of iNOS （P<0.01）， lower levels of TNF-α， IL-1β， and IL-6 （P<0.05， P<0.01）， lower positive expression and mRNA level of iNOS （P<0.05）， and higher levels of IL-4 and IL-10 （P<0.05， P<0.01） than the fluoxetine group. ConclusionBaihuan Xiaoyao decoction can improve the depression-like behavior of juvenile rats by inhibiting the M1 polarization and promoting the M2 polarization of microglia in the hippocampus.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.

Objective:To explore the establishment of a Cox proportional hazard prediction model for the re-cent(within a week)delivery of pregnant women with threatened early preterm labor(28-33+6 weeks).Meth-ods:The clinical data of 293 patients with threatened early preterm labor at 28-33+6 weeks admitted to the De-partment of Obstetrics,Affiliated Hospital of North Sichuan Medical College from January 2021 to December 2022 were retrospectively collected.According to whether the patient gave birth recently(within a week)during hospi-talization,they were divided into delivery group(n=88)and non-delivery group(n=205).Demographic data,specialty conditions and clinical biochemical indicators were collected,and the differences of each observation in-dex between the two groups were compared.Cox multivariate analysis was used to screen variables,and then the Cox proportional hazard prediction model was constructed to calculate the hazard ratio(HR).The C-index was used to test the predictive ability of the model,and the nomogram was drawn to visualize the Cox proportional hazard prediction model.The calibration curve was used to test the consistency between the model prediction re-sults and the actual situation.Results:The average age of the delivery group was 30.2±5.0 years old,and the average prolonged pregnancy time was 61.3±47.5 hours.Compared to the group that gave birth and did not give birth,the proportion of patients with body mass index(BMI)at admission,parity＞1,gestational diabetes mellitus or diabetic pregnancy combined(GDM/PGDM),abnormal fetal orientation,regular contractions at admis-sion,vaginal cleanliness≥ Ⅲ,white blood cell count ≥10 ×109/L at admission and cervical length＜20 mm,the difference was statistically significant(P＜0.05).Multivariate Cox regression analysis:BMI＞30 kg/m2(HR 2.178,95％CI 1.208-3.928,P=0.010),parity＞1(HR 3.095,95％CI 1.759-5.447,P＜0.001),regular uterine contraction(HR3.447,95％CI 2.216-5.362,P＜0.001),cervical length＜20 mm(HR3.594,95％CI 2.289-5.646,P＜0.001)and white blood cell count≥10 ×109/L(HR2.124,95％CI 1.352-3.335,P=0.001)on admission were independent risk factors for recent(within a week)delivery of pregnant women with threatened early preterm birth.When the above 5 indicators were included in the prediction model,the C-index was 0.797(95％CI 0.750-0.844),indicating that the model had good prediction ability.The calibration chart shows that the prediction results of the model are in good agreement with the actual results.Conclusions:Preg-nant women with BMI＞30 kg/m2 at admission,parity＞1,regular uterine contraction at admission,cervical length＜20 mm at admission and white blood cell count≥10 ×109/L at admission are prone to premature delivery in the near future.Cox proportional risk prediction model based on the above risk factors has certain accuracy,which can be used to guide clinical workers to take corresponding intervention measures in advance to avoid or reduce the possibility of premature delivery in the near future and improve maternal and infant outcomes.