| [Abstract] Objective: To explore the correlation between factors related to Robson Ten classification and cesarean section rate, and analyze the validity and validity of cesarean section prediction model based on Robson Ten classification. Methods: The clinical data of 2235 hospitalized parturients in Xuancheng People's Hospital and Langxi County Hospital from September 2022 to September 2023 were retrospectively analyzed. Descriptive epidemiological method was used to analyze the rate of cesarean section according to Robson's ten classification. Model 1 is "obstetric factors" and model 2 is "obstetric factors + demography and severity". Model 3 is "obstetric factors + demography and severity + comorbidities and complications". Multivariate Logistic regression model was used to analyze the correlation between Robson classification variables and cesarean section rate. ROC curve was drawn to analyze the effectiveness of the prediction model for cesarean section. Results: Among 2235 hospitalized parturiants, 1052 delivered by cesarean section (47.07%). There were statistical differences between parturiants with scarred uterus and those with non-scarred uterus in age, whether they participated in medical insurance, birth time, parity, fetal position and pregnancy week, caesarean section, scarred uterus and operation time (P<0.05). In this group, the top two cesarean section rates were as follows: Group 7 (breech presentation, , single pregnancy, primigravida, Induction of labor or Pre-labor cesarean section.) had the highest component ratio of 92.00%; Group 5 (head presentation, single pregnancy, primigravida, Induction of labor or Pre-labor cesarean section, gestational age ≥ 37 weeks), 86.11%; After correcting for maternal age, medical insurance and obstetric complications, the correlation was statistically different (P<0.05). ROC curve results showed that model 3 had a higher prediction efficiency than model 2 and model 1 (P<0.05). The prediction efficiency of model 2 was higher than that of model 1 (P<0.05). Conclusion: Robson classification system has a significant effect on the change of hospital cesarean section rate, and the relevant variables included are correlated with cesarean section and have high predictive ability. Attention should be paid to key multiparous population to reduce hospital cesarean section rate as much as possible. |
