A global reference for caesarean section rates (C-Model) : a multicountry cross-sectional study
Auteurs & affiliatie
JP Souza, AP Betran, A Dumont, B de Mucio, CM Gibbs Pickens, C Deneux-Tharaux, E Ortiz-Panozo, E Sullivan, E Ota, G Togoobaatar, G Carroli, H Knight, J Zhang, JG Cecatti, JP Vogel, K Jayaratne, MC Leal, M Gissler, N Morisaki, N Lack, OT Oladapo, O Tuncalp, P Lumbiganon, R Mori, S Quintana, AD Costa Passos, AC Marcolin, A Zongo, B Blondel, B Hernandez, CJ Hogue, C Prunet, C Landman, C Ochir, C Cuesta, C Pileggi-Castro, D Walker, D Alves, E Abalos, ECD Moises, EM Vieira, G Duarte, G Perdona, I Gurol-Urganci, K Takahiko, L Moscovici, L Campodonico, L Oliveira-Ciabati, M Laopaiboon, M Danansuriya, M Nakamura-Pereira, ML Costa, MR Torloni, MR Kramer, P Borges, PB Olkhanud, R Perez-Cuevas, SB Agampodi, S Mittal, S Serruya, V Bataglia, Z Li, Marleen Temmerman, AM Guelmezoglu
Abstract
Objective: To generate a global reference for caesarean section (CS) rates at health facilities. Design: Cross-sectional study. Setting: Health facilities from 43 countries. Population/Sample: Thirty eight thousand three hundred and twenty-four women giving birth from 22 countries for model building and 10045875 women giving birth from 43 countries for model testing. Methods: We hypothesised that mathematical models could determine the relationship between clinical-obstetric characteristics and CS. These models generated probabilities of CS that could be compared with the observed CS rates. We devised a three-step approach to generate the global benchmark of CS rates at health facilities: creation of a multi-country reference population, building mathematical models, and testing these models. Main outcome measures: Area under the ROC curves, diagnostic odds ratio, expected CS rate, observed CS rate. Results: According to the different versions of the model, areas under the ROC curves suggested a good discriminatory capacity of C-Model, with summary estimates ranging from 0.832 to 0.844. The C-Model was able to generate expected CS rates adjusted for the case-mix of the obstetric population. We have also prepared an e-calculator to facilitate use of C-Model (). Conclusions: This article describes the development of a global reference for CS rates. Based on maternal characteristics, this tool was able to generate an individualised expected CS rate for health facilities or groups of health facilities. With C-Model, obstetric teams, health system managers, health facilities, health insurance companies, and governments can produce a customised reference CS rate for assessing use (and overuse) of CS.
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