Adrien Roussot

Since the 2000s, selective episiotomy has been systematically recommended worldwide. In France, the recommended episiotomy rate in vaginal deliveries is less than 30%. The aims of this study were to describe the evolution of episiotomy rates between 2007 and 2014, especially for vaginal deliveries without instrumental assistance and to assess individual characteristics and birth environment factors associated with episiotomy. This population-based study included all hospital discharge abstracts for all deliveries in France from 2007 to 2014. The use of episiotomy in vaginal deliveries was identified by one code in the French Common Classification of Medical Procedures. The episiotomy rate per department and its evolution is described from 2007 to 2014. A mixed model was used to assess associations with episiotomy for non-operative vaginal deliveries and the risk factors related to the women’s characteristics and the birth environment. There were approximately 540,000 non-operative vaginal deliveries per year, in the study period. The national episiotomy rate for vaginal deliveries overall significantly decreased from 26.7% in 2007 to 19.9% in 2014. For non-operative deliveries, this rate fell from 21.1% to 14.1%. For the latter, the use of episiotomy was significantly associated with breech vaginal delivery (aOR = 1.27 [1.23–1.30]), epidural analgesia (aOR = 1.45 [1.43–1.47]), non-reassuring fetal heart rate (aOR = 1.47 [1.47–1.49]), and giving birth for the first time (aOR = 3.85 [3.84–4.00]). The episiotomy rate decreased throughout France, for vaginal deliveries overall and for non-operative vaginal deliveries. This decrease is probably due to proactive changes in practices to restrict the number of episiotomies, which should be performed only if beneficial to the mother and the infant.

Describe the 1-year hospitalization and in-hospital mortality rates, in infants born after 31 weeks of gestational age (GA). This nation-wide population-based study used the French medico-administrative database to assess the following outcomes in singleton live-born infants (32–43 weeks) without congenital anomalies (year 2011): neonatal hospitalization (day of life 1 – 28), post-neonatal hospitalization (day of life 29 – 365), and 1-year in-hospital mortality rates. Marginal models and negative binomial regressions were used. The study included 696,698 live-born babies. The neonatal hospitalization rate was 9.8%. Up to 40 weeks, the lower the GA, the higher the hospitalization rate and the greater the likelihood of requiring the highest level of neonatal care (both p < 0.001). The relative risk adjusted for sex and pregnancy-related diseases (aRR) reached 21.1 (95% confidence interval [CI]: 19.2-23.3) at 32 weeks. The post-neonatal hospitalization rate was 12.1%. The raw rates for post-neonatal hospitalization fell significantly from 32 – 40 and increased at 43 weeks and this persisted after adjustment (aRR = 3.6 [95% CI: 3.3–3.9] at 32 and 1.5 [95% CI: 1.1–1.9] at 43 compared to 40 weeks). The main causes of post-neonatal hospitalization were bronchiolitis (17.2%), gastroenteritis (10.4%) ENT diseases (5.4%) and accidents (6.2%). The in-hospital mortality rate was 0.85‰, with a significant decrease (p < 0.001) according to GA at birth (aRR = 3.8 [95% CI: 2.4–5.8] at 32 and 6.6 [95% CI: 2.1–20.9] at 43, compared to 40 weeks. There’s a continuous change in outcome in hospitalized infants born above 31 weeks. Birth at 40 weeks gestation is associated with the lowest 1-year morbidity and mortality.

Le Système national d’information interrégimes de l’assurance maladie (SNIIRAM) est une source de données médico-administrative de santé quasi exhaustive de la population française, réunissant les données de remboursement de soins de ville et d’hospitalisation. Compte tenu du nombre croissant d’utilisateurs des données du SNIIRAM à des fins d’études, de recherche et de surveillance épidémiologique, le réseau REDSIAM a pour objectif de favoriser l’interaction entre utilisateurs, de valider et de promouvoir les méthodes d’analyses issues des données. Au sein de ce réseau, le groupe de travail Troubles mentaux et du comportement (GT-TMC) s’est intéressé aux algorithmes d’identification de la dépression de l’adulte à partir des données du SNIIRAM. Il apparaît en effet que les pathologies psychiatriques, et notamment la dépression, ont été peu étudiées à partir des bases de données médico-administratives. La méthodologie s’est appuyée sur l’interview de dix experts ayant déjà travaillé sur le SNIIRAM, à partir de questionnaires validés. La synthèse des entretiens montre que les algorithmes doivent s’adapter aux objectifs spécifiques poursuivis par les études et dépendent du type d’enquête réalisée, du type de dépression, du périmètre de données interrogées et de l’association ou non aux données de consommation médicamenteuse.

In the context of implementing the National Stroke Plan in France, a spatial approach was used to measure inequalities in this disease. Using the national PMSI-MCO databases, we analyzed the in-hospital prevalence of stroke and established a map of in-hospital mortality rates with regard to the socio-demographic structure of the country. The principal characteristics of patients identified according to ICD10 codes relative to stroke (in accordance with earlier validation work) were studied. A map of standardized mortality rates at the level of PMSI geographic codes was established. An exploratory analysis (principal component analysis followed by ascending hierarchical classification) using INSEE socio-economic data and mortality rates was also carried out to identify different area profiles. Between 2008 and 2011, the number of stroke patients increased by 3.85 %, notably for ischemic stroke in the 36–55 years age group (60 % of men). Over the same period, in-hospital mortality fell, and the map of standardized rates illustrated the diagonal of high mortality extending from the north-east to the south-west of the country. The most severely affected areas were also those with the least favorable socio-professional indicators. The PMSI-MCO database is a major source of data on the health status of the population. It can be used for the area-by-area observation of the performance of certain healthcare indicators, such as in-hospital mortality, or to follow the implementation of the National Stroke Plan. Our study showed the interplay between social and demographic factors and stroke-related in-hospital mortality. The map derived from the results of the exploratory analysis illustrated a variety of areas where social difficulties, aging and high mortality seemed to meet. The study raises questions about access to neuro-vascular care in isolated areas and in those in demographic decline. Telemedicine appears to be the solution favored by decision makers. The aging of the population managed for stroke must not mask the growing incidence in younger people, which raises questions about the development of classical (smoking, hypertension) or new (drug abuse) risk factors.