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Using a Caesarean Section Classification System based on characteristics of the population as a way of monitoring obstetric practice by Maria L Costa; Jose G Cecatti; João P Souza; Helaine M Milanez; Metin A Gülmezoglu is a Medicine article available to read on EtoBox.
What is Using a Caesarean Section Classification System based on characteristics of the population as a way of monitoring obstetric practice about?
## Abstract ## Objective to compare the distribution of caesarean rates in the Robson's 10 groups classification in order to see if any change occurred after the implementation of an audit and feedback intervention. __Design:__ cross sectional, before and after an audit and feedback study. __Setting__: a university hospital in Brazil. ## Methods clinical records of all births during two three months-periods were evaluated. Each case of CS was classified into one of ten mutually exclusive categories according to obstetric characteristics. The proportion of CS in each group was compared in both periods. ## Results total number of deliveries and the high rate of CS were similar in both periods. Group 3 (multiparous excluding previous CS, single, cephalic, ≥ 37 weeks, spontaneous labour) accounted for the largest proportion of deliveries, 28.5 and 26.8% in both periods. Group 1 (nulliparous, single, cephalic, ≥ 37 weeks, spontaneous labour) was the second largest one, while Group 5 (previous caesarean section, single, cephalic, and ≥ 37 weeks) was the third but the largest contributor to CS, accounting for 16.6 and 14.9% among all deliveries in both periods. Groups 2 (nulliparous, sing
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- Author
- Maria L Costa; Jose G Cecatti; João P Souza; Helaine M Milanez; Metin A Gülmezoglu
- Publisher
- BioMed Central; Springer (Biomed Central Ltd.); [London]: BioMed Central, 2004-; Springer Science and Business Media LLC (ISSN 1742-4755)
- Published
- 2010
- Language
- EN
- Field
- Medicine (Health Sciences)