Objective To evaluate whether a history of spontaneous early‐term birth (37+0–38+6 weeks of gestation) in the previous singleton pregnancy is a risk factor for preterm birth (PTB) in a subsequent twin pregnancy. Design Retrospective cohort study. Settings Two French university hospitals (2006–2016). Population All women who delivered twins from 24+0 weeks after a preceding singleton pregnancy birth at 37+0 to 41+6 weeks. Methods Multivariate logistic regression analysis of association between twin PTB and a previous spontaneous singleton early‐term birth. Main outcome measures Twin PTB rate before 37, 34 and 32 weeks of gestation. Results Among 618 twin pregnancies, 270 were born preterm, 92 of them with a preceding spontaneous singleton early‐term birth. The univariate analysis showed a significantly higher risk of twin PTB before 37, 34 and 32 weeks among those 92 women compared with those with a full‐ or late‐term birth in their previous singleton pregnancy. This association remained significant after logistic regression (odds ratio [OR] between 2.42 and 3.88). The secondary analysis, restricted to the twin pregnancies with spontaneous PTB found similar results, with a risk of PTB before 37, 34 and 32 weeks significantly higher among women with a previous spontaneous singleton early‐term birth, including after logistic regression analysis (OR between 3.51 and 3.56). Conclusion A preceding spontaneous singleton early‐term birth is a strong and easily identified risk factor for PTB in twin pregnancies. Tweetable abstract Spontaneous ‘early‐term’ birth of a singleton is a significant risk factor for future preterm births in twin pregnancies.

Seven years (2013–2019) of the French/Indian mission SARAL altimetry data have been successfully reprocessed within the SALP contract supported by CNES to produce a new data set of GDR (Geophysical Data Record) using an updated, modern set of algorithms and models. The main objective of this article is to assess the quality of the reprocessed dataset and estimate the system’s performance using GDR-F products. To achieve this goal, the new dataset has been validated against the previous one (identified as GDR-T) using mono-mission metrics and comparisons to reference altimetry missions such as Jason-2 and Jason-3. The new data set shows a clear improvement in data quality. The product validation shows a reduction of the standard deviation of crossovers’ Sea Surface Height differences from 5.5 cm (GDR-T) to 5.2 cm (GDR-F). This paper presents the main processing changes and shows some of the results from the validation and quality-assurance processes. The major improvement of the GDR-F data set with respect to the previous one is due to the use of state-of-the-art orbit standards (POE-F) and geophysical corrections, including new tidal models, a new wet troposphere retrieval algorithm, and a new algorithm for sea state estimation. The intent of this paper is to highlight the overall benefit of this new dataset.