3 years ago

The QUiPP App: a safe alternative to a treat-all strategy for threatened preterm labor

P. T. Seed, R. M. Tribe, J. Carter, H. A. Watson, A. H. Shennan
Objective To evaluate the impact of triaging women at risk of spontaneous preterm birth (sPTB) using the QUiPP App, which incorporates a predictive model combining history of sPTB, gestational age and quantitative measurements of fetal fibronectin, compared with a treat-all policy (advocated by the UK National Institute for Health and Care Excellence) among women with threatened preterm labor before 30 weeks' gestation. Methods Prospectively collected data of pregnant women presenting with symptoms of preterm labor (abdominal pain or tightening) at 24–34 weeks' gestation were retrieved from the research databases of the EQUIPP and PETRA studies for subanalysis. Each episode of threatened preterm labor was retrospectively assigned a risk for sPTB within 7 days using the QUiPP App. A primary outcome of delivery within 7 days was used to model the performance accuracy of the QUiPP App compared with a treat-all policy. Results Using a 5% risk of delivery within 7 days according to the QUiPP App as the threshold for intervention, 9/9 women who presented with threatened preterm labor < 34 weeks would have been treated correctly, giving a sensitivity of 100% (one-sided 97.5% CI, 66.4%) and a negative predictive value of 100% (97.5% CI, 98.9–100%). The positive predictive value for delivery within 7 days was 30.0% (95% CI, 11.9–54.3%) for women presenting before 30 weeks and 20.0% (95% CI, 12.7–30.1%) for women presenting between 30 + 0 and 34 + 0 weeks. If this 5% threshold had been used to triage women presenting between 24 + 0 and 29 + 6 weeks, 89.4% (n = 168) of admissions could have been safely avoided, compared with 0% for a treat-all strategy. No true case of preterm labor would have been missed, as no woman who was assigned a risk of < 10% delivered within 7 days. Conclusion For women with threatened preterm labor, the QUiPP App can accurately guide management at risk thresholds for sPTB of 1%, 5% and 10%, allowing outpatient management in the vast majority of cases. A treat-all approach would not have avoided admission for any woman, and would have exposed 188 mothers and their babies to unnecessary hospitalization and steroid administration and increased the burden on network and transport services owing to unnecessary in-utero transfers. Prediction of sPTB should be performed before 30 weeks to determine management until there is evidence that such a high level of unnecessary intervention, as suggested by the treat-all strategy, does less harm than the occurrence of rare false negatives. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd. La aplicación QUiPP: una alternativa segura a la estrategia de “tratar a todas” en caso de riesgo de parto pretérmino Objetivo Evaluar el impacto del triaje de mujeres con riesgo de parto pretérmino espontáneo (PPTE) utilizando la Aplicación QUiPP, que incorpora un modelo predictivo que combina el historial de PPTE, la edad gestacional y medidas cuantitativas de la fibronectina fetal, y se compara con la política de “tratar a todas” (recomendada por el Instituto Nacional para la Excelencia en Salud y Cuidados del Reino Unido), entre mujeres con riesgo de parto prematuro antes de las 30 semanas de gestación. Métodos De las bases de datos de investigación de los estudios EQUIPP y PETRA, los datos de mujeres embarazadas que pudieran presentar síntomas de parto pretérmino (dolor abdominal o contracción) a las 24–34 semanas de gestación, se recuperaron para el subanálisis. A cada episodio de amenaza de parto pretérmino se le asignó retrospectivamente un riesgo de PPTE en un máximo de 7 días, mediante la aplicación QUiPP. Para la modelización de la precisión del desempeño de la aplicación QUiPP, en comparación con una política de “tratar a todas”, se utilizó como resultado primario el parto en un máximo de 7 días. Resultados Utilizando como umbral para la intervención un 5% de riesgo de parto en un máximo de 7 días según lo indicado por la aplicación QUiPP, 9/9 mujeres que presentaron riesgo de parto pretérmino a <34 semanas habrían sido tratadas correctamente, lo que supuso una sensibilidad del 100% (IC unilateral 97,5%, 66,4%) y un valor predictivo negativo del 100% (IC 97,5%, 98,9–100%). El valor predictivo positivo para el parto en un máximo de 7 días fue del 30,0% (IC 95%: 11,9–54,3%) para las mujeres que lo presentaron antes de las 30 semanas y del 20,0% (IC 95%: 12,7–30,1%) para las mujeres que lo presentaron entre 30+0 y 34+0 semanas. Si se hubiera utilizado este umbral del 5% para el triaje de las mujeres que presentaban entre 24+0 y 29+6 semanas, se podría haber evitado de manera segura el 89,4% (n=68) de las admisiones, en comparación con el 0% para la estrategia de “tratar a todas”. No se habría dejado sin tratar ningún caso verdadero de parto pretérmino, ya que ninguna mujer a la que se le asignó un riesgo <10% se puso de parto en un período máximo de 7 días. Conclusión Para las mujeres con r

-Abstract Truncated-

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/uog.17499

You might also like
Discover & Discuss Important Research

Keeping up-to-date with research can feel impossible, with papers being published faster than you'll ever be able to read them. That's where Researcher comes in: we're simplifying discovery and making important discussions happen. With over 19,000 sources, including peer-reviewed journals, preprints, blogs, universities, podcasts and Live events across 10 research areas, you'll never miss what's important to you. It's like social media, but better. Oh, and we should mention - it's free.

  • Download from Google Play
  • Download from App Store
  • Download from AppInChina

Researcher displays publicly available abstracts and doesn’t host any full article content. If the content is open access, we will direct clicks from the abstracts to the publisher website and display the PDF copy on our platform. Clicks to view the full text will be directed to the publisher website, where only users with subscriptions or access through their institution are able to view the full article.