ArticleFrontiers in medicine2026
Development and internal validation of the LATE-PE model for predicting time-to-delivery in early-onset preeclampsia: a multicenter study.
Article in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: Managing early-onset preeclampsia requires balancing maternal risks against neonatal benefits. However, few simple and readily available tools are available to estimate pregnancy latency, particularly in resource-limited settings. Methods: This multicenter retrospective cohort study developed and internally validated the LATE-PE (Latency Assessment Tool for Early-onset Preeclampsia) model in 266 women with early-onset preeclampsia who had already been considered eligible for expectant management. The model estimates the probability of allcause delivery by day 2 after admission, used as an operational approximation of the clinically relevant 48-hour window, and by day 7. Six routinely available predictors were prespecified: gestational age, systolic blood pressure, proteinuria, AST, creatinine, and platelet count. Internal validation was performed using 1,000 bootstrap resamples. Results: The apparent AUC was 0.740 (95% CI 0.672-0.808) for delivery by day 2 and 0.767 (95% CI 0.708-0.826) for delivery by day 7, with corresponding optimism-corrected AUCs of 0.732 and 0.758. The optimismcorrected calibration slopes were 1.023 and 0.806 at day 2 and day 7, respectively, and the optimism-corrected C-index was 0.689. Exploratory decision-curve analysis suggested potential net benefit across selected threshold probabilities. An experimental web-based research prototype was developed to facilitate model exploration and future validation. Conclusion: LATE-PE provides a parsimonious approach to estimating short-term delivery probability using routinely available clinical and laboratory variables. Its accessibility may be particularly relevant where specialized biomarkers or imaging are not readily available. However, the model has undergone internal validation only. External validation in independent populations and prospective assessment of clinical impact are required before clinical use.
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