Search

Background: Improving the understanding of non-clinical factors that lead to the increasing caesarean section (CS) rates in many low- and middle-income countries is currently necessary to meet the challenge of implementing effective interventions in hospitals to reverse the trend. The objective of this study was to study the influence of organizational factors on the CS use in Argentina, Vietnam, Thailand and Burkina Faso. Methods: A cross-sectional hospital-based postpartum survey was conducted in 32 hospitals (8 per country). We selected women with no potential medical need for CS among a random sample of women who delivered at each of the participating facilities during the data collection period. We used multilevel multivariable logistic regression to analyse the association between CS use and organizational factors, adjusted on women's characteristics. Results: A total of 2,092 low-risk women who had given birth in the participating hospitals were included. The overall CS rate was 24.1%, including 4.9% of pre-labour CS and 19.3% of intra-partum CS. Pre-labour CS was significantly associated with a 24-hour anaesthetist dedicated to the delivery ward (ORa = 3.70 [1.41; 9.72]) and with the possibility to have an individual room during labour and delivery (ORa = 0.28 [0.09; 0.87]). Intra-partum CS was significantly associated with a higher bed occupancy level (ORa = 1.45 [1.09; 1.93]): intrapartum CS rate would increase of 6.3% points if the average number of births per delivery bed per day increased by 10%. Conclusion: Our results suggest that organisational norms and convenience associated with inadequate use of favourable resources, as well as the lack of privacy favouring women's preference for CS, and the excessive workload of healthcare providers drive the CS overuse in these hospitals. It is also crucial to enhance human and physical resources in delivery rooms and the organisation of intrapartum care to improve the birth experience and the working environment for those providing care. Trial registration: The QUALI-DEC trial is registered on the Current Controlled Trials website (https://www.isrctn.com/) under the number ISRCTN67214403. [ABSTRACT FROM AUTHOR]

Objective: To predict birth weight at various potential gestational ages of delivery based on data routinely available at the first antenatal visit., Design: Individual participant data meta-analysis., Data Sources: Individual participant data of four cohorts (237 228 pregnancies) from the International Prediction of Pregnancy Complications (IPPIC) network dataset., Eligibility Criteria for Selecting Studies: Studies in the IPPIC network were identified by searching major databases for studies reporting risk factors for adverse pregnancy outcomes, such as pre-eclampsia, fetal growth restriction, and stillbirth, from database inception to August 2019. Data of four IPPIC cohorts (237 228 pregnancies) from the US (National Institute of Child Health and Human Development, 2018; 233 483 pregnancies), UK (Allen et al, 2017; 1045 pregnancies), Norway (STORK Groruddalen research programme, 2010; 823 pregnancies), and Australia (Rumbold et al, 2006; 1877 pregnancies) were included in the development of the model., Results: The IPPIC birth weight model was developed with random intercept regression models with backward elimination for variable selection. Internal-external cross validation was performed to assess the study specific and pooled performance of the model, reported as calibration slope, calibration-in-the-large, and observed versus expected average birth weight ratio. Meta-analysis showed that the apparent performance of the model had good calibration (calibration slope 0.99, 95% confidence interval (CI) 0.88 to 1.10; calibration-in-the-large 44.5 g, -18.4 to 107.3) with an observed versus expected average birth weight ratio of 1.02 (95% CI 0.97 to 1.07). The proportion of variation in birth weight explained by the model (R 2 ) was 46.9% (range 32.7-56.1% in each cohort). On internal-external cross validation, the model showed good calibration and predictive performance when validated in three cohorts with a calibration slope of 0.90 (Allen cohort), 1.04 (STORK Groruddalen cohort), and 1.07 (Rumbold cohort), calibration-in-the-large of -22.3 g (Allen cohort), -33.42 (Rumbold cohort), and 86.4 g (STORK Groruddalen cohort), and observed versus expected ratio of 0.99 (Rumbold cohort), 1.00 (Allen cohort), and 1.03 (STORK Groruddalen cohort); respective pooled estimates were 1.00 (95% CI 0.78 to 1.23; calibration slope), 9.7 g (-154.3 to 173.8; calibration-in-the-large), and 1.00 (0.94 to 1.07; observed v expected ratio). The model predictions were more accurate (smaller mean square error) in the lower end of predicted birth weight, which is important in informing clinical decision making., Conclusions: The IPPIC birth weight model allowed birth weight predictions for a range of possible gestational ages. The model explained about 50% of individual variation in birth weights, was well calibrated (especially in babies at high risk of fetal growth restriction and its complications), and showed promising performance in four different populations included in the individual participant data meta-analysis. Further research to examine the generalisability of performance in other countries, settings, and subgroups is required., Trial Registration: PROSPERO CRD42019135045., Competing Interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/disclosure-of-interest/ and declare: support from the National Institute for Health and Care Research Health Technology Assessment UK programme for the submitted work; no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work., (Copyright © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Women's fear and uncertainty about vaginal delivery and lack of empowerment in decision-making generate decision conflict and is one of the main determinants of high caesarean section rates in low- and middle-income countries (LMICs). This study aims to develop a decision analysis tool (DAT) to help pregnant women make an informed choice about the planned mode of delivery and to evaluate its acceptability in Vietnam, Thailand, Argentina, and Burkina Faso. The DAT targets low-risk pregnant women with a healthy, singleton foetus, without any medical or obstetric disorder, no previous caesarean scarring, and eligibility for labour trials. We conducted a systematic review to determine the short- and long-term maternal and offspring risks and benefits of planned caesarean section compared to planned vaginal delivery. We carried out individual interviews and focus group discussions with key informants to capture informational needs for decision-making, and to assess the acceptability of the DAT in participating hospitals. The DAT meets 20 of the 22 Patient Decision Aid Standards for decision support. It includes low- to moderate-certainty evidence-based information on the risks and benefits of both modes of birth, and helps pregnant women clarify their personal values. It has been well accepted by women and health care providers. Adaptations have been made in each country to fit the context and to facilitate its implementation in current practice, including the development of an App. DAT is a simple method to improve communication and facilitate shared decision-making for planned modes of birth. It is expected to build trust and foster more effective, satisfactory dialogue between pregnant women and providers. It can be easily adapted and updated as new evidence emerges. We encourage further studies in LMICs to assess the impact of DAT on quality decision-making for the appropriate use of caesarean section in these settings., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2022 Dumont et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)