Objective:To improve the quality standard of Xiaoer Shenzhu Jianpi Pills.Methods:The microscopic identification method was used to qualitatively identify Hordei Fructus Germinatus.TLC was used to qualitatively i-dentify of Atractylodis Macrocephalae Rhizoma,Glycyrrhizae Radix Et Rhizoma,Citri Reticulatae Pericapium.HPLC was adopted to determine the contents of hesperidin and ammonium glycyrrhizinate.Results:The microscop-ic identification of Hordei Fructus Germinatus had strong specificity and high viewing rate.The TLC identification spots of Atractylodis Macrocephalae Rhizoma,Glycyrrhizae Radix Et Rhizoma,Citri Reticulatae Pericapium were clear,with good separation and durability.The linear ranges of hesperidin and ammonium glycyrrhizinate were 0.060 0-1.501 0 μg and 0.020 1-0.502 2 μg,respectively(r≥0.999 8).The average recoveries(n=9)were 99％,96％and RSDs were 2.8％and 1.8％.The RSDs of precision,stability and repeatability of the two components were less than 3.0％.Conclusion:The newly established quality standard increases the quality control research of microscopic identification,thin layer chromatography and content determination.The experimental method is accurate and reliable,simple and fast,and has good applicability.It can be used for the quality control and evaluation of Xiaoer Shenzhu Jianpi Pills.

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.

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.

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.