Factors Affecting Cesarean Section Rate Using Robson Classification: a 24-year-old retrospective analysis in a multiethnic population [post]

Luigi Antonio De Vitis, Stefano Manodoro, Matteo Frigerio, Anna Maria Marconi
2020 unpublished
Objective To evaluate factors affecting cesarean section (CS) rates in groups 1, 2A, 3, 4A, 5 and 10 of the "Ten Group Classification System" (TGCS). Design Retrospective analysis of deliveries occurred from January 1996 to December 2019. Setting A single hospital in Milan. Population Pregnant women belonging to groups 1, 2A, 3, 4A, 5 and 10 of the TGCS. Methods A binary logistic regression analysis was conducted. Included independent variables were maternal age, neonatal birthweight, immigrant
more » ... thweight, immigrant status, use of obstetric analgesia, presence of diabetes, hypertension and obesity. Main outcome measures The effect of independent variables on CS rate was expressed as odds ratio. Results A total of 30591 deliveries were recorded. Advanced maternal age was an independent risk factor (RF) in groups 1, 2A, 3, and 4A; diabetes was a risk factor in groups 1 and 5; obesity was a RF in groups 1 and 2A and a protective one in group 5; hypertension was a RF in groups 2A, 5 and 10; macrosomia was a RF in groups 1, 2A and 3; use of obstetric analgesia was either a RF in group 1, and a protective factor in groups 2A, 5 and 10; immigrant status was either a protective factor in groups 1 and 10, and a RF in group 4A. Conclusion The TGCS is a well-established method to compare CS rates between institutions; however, inside each group, many factors can influence the CS rate and they have to be taken into consideration when comparing CS rates. Abstract Objective To evaluate factors affecting caesarean section (CS) rates in groups 1, 2A, 3, 4A, 5 and 10 of the "Ten Group Classification System" (TGCS). A single hospital in Milan. Population Pregnant women belonging to groups 1, 2A, 3, 4A, 5 and 10 of the TGCS. Methods A binary logistic regression analysis was conducted. Included independent variables were maternal age, neonatal birthweight, immigrant status, use of obstetric analgesia, presence of diabetes, hypertension and obesity. Main outcome measures The effect of independent variables on CS rate was expressed as odds ratio. Results A total of 30591 deliveries were recorded. Advanced maternal age was an independent risk factor (RF) in groups 1, 2A, 3, and 4A; diabetes was a RF in groups 1 and 5; obesity was a RF in groups 1 and 2A and a protective one in group 5; hypertension was a RF in groups 2A, 5 and 10; macrosomia was a RF in groups 1, 2A and 3; use of obstetric analgesia was either a RF in group 1, and a protective factor in groups 2A, 5 and 10; immigrant status was either a protective factor in groups 1 and 10, and a RF in group 4A. Conclusion The TGCS is a well-established method to compare CS rates between institutions; however, inside each group, many factors can influence the CS rate and they have to be taken into consideration when comparing CS rates. Tweetable abstract Obstetrics and maternal-fetal factors increase or reduce CS rate in a different way depending on Robson group.
doi:10.22541/au.160491832.24473224/v1 fatcat:pi6l4zydivhmhmbrnx4kx4haza