To analyze the ethnic differences in the genotype distribution of thalassemia between the Han and Li ethnic groups in the Qiongnan region (southern Hainan). A cross-sectional study employing a stratified multistage sampling method was conducted from January 2019 to December 2023. A total of 4 493 high-risk individuals (2 734 Han and 1 759 Li) from southern Hainan (including Sanya, Ledong, Baoting, Lingshui, and other counties) underwent thalassemia genetic testing. The genotype distribution was statistically analyzed. Inter-group comparisons were performed using χ2 test or Fisher′s exact test. The results showed an overall thalassemia positivity rate of 66.70% (2 997/4 493), with carrier, intermediate and major thalassemia rates of 62.01% (2 786/4 493), 3.98% (179/4 493) and 0.71% (32/4 493), respectively. The positivity rates for thalassemia were 87.83% (1 545/1 759) in the Li ethnic group and 53.11% (1 452/2 734) in the Han ethnic group. Among them, the Li ethnic group exhibited significantly higher positivity rates for α-thalassemia (71.12% vs. 40.64%, χ2=398.90, P<0.001) and α/β-compound thalassemia (13.36% vs. 3.33%, χ2=160.06, P<0.001) compared to the Han ethnic group, whereas the Han ethnic group had a higher β-thalassemia rate (9.14% vs. 3.35%, χ2=56.03, P<0.001). Both ethnic groups shared common α-thalassemia alleles (-α 3.7 and -α 4.2), but the -- SEA allele proportion was significantly higher in Han (21.33% vs. 4.34%, χ2=231.45, P<0.001). Six rare -α 21.9 mutations (0.26%) were exclusively identified in the Li ethnic group, whereas none were found in Han. For β-thalassemia, the β CD41-42 allele was predominant in Li (96.60% vs. 71.01%, χ2=77.24, P<0.001), whereas other alleles (β IVS-II-654, β CD71-72, β CD17, and β -28) were more prevalent in Han (11.01%, 6.96%, 4.64%, and 3.19% vs. 1.54%, 0.00%, 0.31%, and 0.62%, respectively),all P<0.05. In conclusion, distinct ethnic disparities in thalassemia genotype distribution are observed in southern Hainan. The Li ethnic group is predominantly characterized by α-thalassemia and α/β-compound genotypes with a predominant β CD41-42 mutation. In contrast, the Han ethnic group displays higher -- SEA proportion and heterogeneous β-thalassemia genotypes.

Objective:To observe the clinical efficacy of gentle moxibustion at different temperatures in treating people with diarrhea-predominant bowel syndrome(IBS-D)due to spleen deficiency.Methods:A total of 108 IBS-D patients were divided into two groups using the random number table method,with 54 participants in each group.Moxibustion group 1 received gentle moxibustion at(43±1)℃at bilateral Tianshu(ST25)and Zusanli(ST36),lasting 30 min each session;moxibustion group 2 received gentle moxibustion at(37±1)℃at the same points.Both groups received the intervention 3 times weekly for a total of 18 sessions.Abdominal pain intensity,stool form,pattern-based efficacy,quality of life,and mental health assessments were performed at weeks 0,3,6,and 8.Results:The total effective rate for abdominal pain intensity was 87.8%in moxibustion group 1 versus 51.1%in moxibustion group 2,and the difference was statistically significant(P<0.05).When the treatment finished,abdominal pain intensity,the Bristol score,IBS-symptom severity scale(IBS-SSS)score,self-rating anxiety scale(SAS)score,and self-rating depression scale(SDS)score dropped significantly in both groups(P<0.05),and the IBS-quality of life(IBS-QOL)score increased markedly(P<0.05).Between-group comparisons demonstrated that abdominal pain intensity,the Bristol general score,IBS-SSS score,traditional Chinese medicine(TCM)pattern score,and SDS score were significantly lower in moxibustion group 1 than in moxibustion group 2 at treatment week 6(P<0.05),and the IBS-QOL score was notably higher in moxibustion group 1(P<0.05).Conclusion:Whether at 43℃or 37℃,gentle moxibustion at Tianshu(ST25)and Zusanli(ST36)can improve abdominal pain,stool form,and quality of life,reduce disease severity,and mitigate TCM pattern in IBS-D patients;43℃gentle moxibustion performs better than 37℃gentle moxibustion in improving abdominal pain,stool form,disease severity,TCM pattern,quality of life,anxiety,and depression in IBS-D.

To analyze the ethnic differences in the genotype distribution of thalassemia between the Han and Li ethnic groups in the Qiongnan region (southern Hainan). A cross-sectional study employing a stratified multistage sampling method was conducted from January 2019 to December 2023. A total of 4 493 high-risk individuals (2 734 Han and 1 759 Li) from southern Hainan (including Sanya, Ledong, Baoting, Lingshui, and other counties) underwent thalassemia genetic testing. The genotype distribution was statistically analyzed. Inter-group comparisons were performed using χ2 test or Fisher′s exact test. The results showed an overall thalassemia positivity rate of 66.70% (2 997/4 493), with carrier, intermediate and major thalassemia rates of 62.01% (2 786/4 493), 3.98% (179/4 493) and 0.71% (32/4 493), respectively. The positivity rates for thalassemia were 87.83% (1 545/1 759) in the Li ethnic group and 53.11% (1 452/2 734) in the Han ethnic group. Among them, the Li ethnic group exhibited significantly higher positivity rates for α-thalassemia (71.12% vs. 40.64%, χ2=398.90, P<0.001) and α/β-compound thalassemia (13.36% vs. 3.33%, χ2=160.06, P<0.001) compared to the Han ethnic group, whereas the Han ethnic group had a higher β-thalassemia rate (9.14% vs. 3.35%, χ2=56.03, P<0.001). Both ethnic groups shared common α-thalassemia alleles (-α 3.7 and -α 4.2), but the -- SEA allele proportion was significantly higher in Han (21.33% vs. 4.34%, χ2=231.45, P<0.001). Six rare -α 21.9 mutations (0.26%) were exclusively identified in the Li ethnic group, whereas none were found in Han. For β-thalassemia, the β CD41-42 allele was predominant in Li (96.60% vs. 71.01%, χ2=77.24, P<0.001), whereas other alleles (β IVS-II-654, β CD71-72, β CD17, and β -28) were more prevalent in Han (11.01%, 6.96%, 4.64%, and 3.19% vs. 1.54%, 0.00%, 0.31%, and 0.62%, respectively),all P<0.05. In conclusion, distinct ethnic disparities in thalassemia genotype distribution are observed in southern Hainan. The Li ethnic group is predominantly characterized by α-thalassemia and α/β-compound genotypes with a predominant β CD41-42 mutation. In contrast, the Han ethnic group displays higher -- SEA proportion and heterogeneous β-thalassemia genotypes.

Objective:To observe the clinical efficacy of gentle moxibustion at different temperatures in treating people with diarrhea-predominant bowel syndrome(IBS-D)due to spleen deficiency.Methods:A total of 108 IBS-D patients were divided into two groups using the random number table method,with 54 participants in each group.Moxibustion group 1 received gentle moxibustion at(43±1)℃at bilateral Tianshu(ST25)and Zusanli(ST36),lasting 30 min each session;moxibustion group 2 received gentle moxibustion at(37±1)℃at the same points.Both groups received the intervention 3 times weekly for a total of 18 sessions.Abdominal pain intensity,stool form,pattern-based efficacy,quality of life,and mental health assessments were performed at weeks 0,3,6,and 8.Results:The total effective rate for abdominal pain intensity was 87.8%in moxibustion group 1 versus 51.1%in moxibustion group 2,and the difference was statistically significant(P<0.05).When the treatment finished,abdominal pain intensity,the Bristol score,IBS-symptom severity scale(IBS-SSS)score,self-rating anxiety scale(SAS)score,and self-rating depression scale(SDS)score dropped significantly in both groups(P<0.05),and the IBS-quality of life(IBS-QOL)score increased markedly(P<0.05).Between-group comparisons demonstrated that abdominal pain intensity,the Bristol general score,IBS-SSS score,traditional Chinese medicine(TCM)pattern score,and SDS score were significantly lower in moxibustion group 1 than in moxibustion group 2 at treatment week 6(P<0.05),and the IBS-QOL score was notably higher in moxibustion group 1(P<0.05).Conclusion:Whether at 43℃or 37℃,gentle moxibustion at Tianshu(ST25)and Zusanli(ST36)can improve abdominal pain,stool form,and quality of life,reduce disease severity,and mitigate TCM pattern in IBS-D patients;43℃gentle moxibustion performs better than 37℃gentle moxibustion in improving abdominal pain,stool form,disease severity,TCM pattern,quality of life,anxiety,and depression in IBS-D.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.

Objective:To establish a predictive model of the first cesarean delivery in multiparous women based on the situation of two consecutive pregnancies.Methods:The data of patients with two consecutive deliv-eries of single live birth and the previous delivery was vaginal delivery in the First Affiliated Hospital of Soochow U-niversity during the second delivery time range from January 1,2018 to December 31,2021 were retrospectively analyzed.According to whether the second pregnancy occurred cesarean section,the patients were divided into two groups(vaginal delivery group and cesarean section group).Univariate,stepwise,and multiple Logistic re-gression analyses were used to screen the influencing factors of multipara's first cesarean section delivery,and the prediction model was established.R language was used to build the model's nomogram and calibration curve.The bootstrap resampling method was used for internal verification.After establishing the model,clinical data of patients with two consecutive births of single live birth between January 1,2022 and April 1,2023 were retrospec-tively collected for external verification of the model.Results:①A total of 2709 patients were included in this study for modeling,of which 6.31％(171/2709)underwent cesarean section for the first time.603 cases were included for external verification.②According to univariate,stepwise and multivariate Logistic regression analysis,all the variables affecting the first delivery by cesarean section were screened out,including:abnormal labor in previous labor,age of current delivery,assisted reproductive technology,hypertension disorder complicating pregnancy,pregnancy with thrombocytopenia,oligohydramnios,excessive amniotic fluid,macrosomia,fetal growth restriction,abnormal fetal position,fetal distress,all of the above variables P＜0.05 and incorporated into the final prediction model.③The AUC of this model was 0.949(95％CI 0.928-0.969),and the calibration curve showed that the model intercept was 0 and the slope was 1.Hosmer-Lemeshow test had a P＞0.05,indicating that the model had a high accuracy.④The AUC of external validation was 0.958,the slope of the calibration curve was 0.972,and the Hosmer-Lemeshow test had a P of 0.49.Conclusions:The prediction model of the first delivery by cesarean section during the second pregnancy has been established.The prediction efficiency of the model is good,and it can provide a tool for the individualized evaluation of menstrual women in clinical work.