Literature DB >> 28436125

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

H A Watson1, J Carter1, P T Seed1, R M Tribe1, A H Shennan1.   

Abstract

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. Copyright © 2017 ISUOG. Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  fetal fibronectin; predictive model; preterm labor; quantitative; symptomatic women; triage

Mesh:

Substances:

Year:  2017        PMID: 28436125     DOI: 10.1002/uog.17499

Source DB:  PubMed          Journal:  Ultrasound Obstet Gynecol        ISSN: 0960-7692            Impact factor:   7.299


  10 in total

Review 1.  Relevance of the antenatal corticosteroids-to-delivery interval in the prevention of neonatal respiratory distress syndrome through the eyes of causal inference: a review and target trial.

Authors:  Isabelle Dehaene; Kristien Roelens; Koenraad Smets; Johan Decruyenaere
Journal:  Arch Gynecol Obstet       Date:  2021-08-30       Impact factor: 2.344

2.  Development and rapid rollout of The QUiPP App Toolkit for women who arrive in threatened preterm labour.

Authors:  Naomi Carlisle; Helena A Watson; Andrew H Shennan
Journal:  BMJ Open Qual       Date:  2021-05

3.  Logistic regression has similar performance to optimised machine learning algorithms in a clinical setting: application to the discrimination between type 1 and type 2 diabetes in young adults.

Authors:  Anita L Lynam; John M Dennis; Katharine R Owen; Richard A Oram; Angus G Jones; Beverley M Shields; Lauric A Ferrat
Journal:  Diagn Progn Res       Date:  2020-06-04

4.  EQUIPTT: The Evaluation of the QUiPP app for Triage and Transfer protocol for a cluster randomised trial to evaluate the impact of the QUiPP app on inappropriate management for threatened preterm labour.

Authors:  Helena A Watson; Naomi Carlisle; Katy Kuhrt; Rachel M Tribe; Jenny Carter; Paul Seed; Andrew H Shennan
Journal:  BMC Pregnancy Childbirth       Date:  2019-02-13       Impact factor: 3.007

5.  Leveraging Technology to Improve Diabetes Care in Pregnancy.

Authors:  Sarah D Crimmins; Angela Ginn-Meadow; Rebecca H Jessel; Julie A Rosen
Journal:  Clin Diabetes       Date:  2020-12

6.  The Tommy's Clinical Decision Tool, a device for reducing the clinical impact of placental dysfunction and preterm birth: protocol for a mixed-methods early implementation evaluation study.

Authors:  Jenny Carter; Dilly Anumba; Lia Brigante; Christy Burden; Tim Draycott; Siobhán Gillespie; Birte Harlev-Lam; Andrew Judge; Erik Lenguerrand; Elaine Sheehan; Basky Thilaganathan; Hannah Wilson; Cathy Winter; Maria Viner; Jane Sandall
Journal:  BMC Pregnancy Childbirth       Date:  2022-08-15       Impact factor: 3.105

7.  Causes of perinatal deaths in Australia: Slow progress in the preterm period.

Authors:  Kirstin Tindal; Gayathri Bimal; Vicki Flenady; Adrienne Gordon; Tanya Farrell; Miranda Davies-Tuck
Journal:  Aust N Z J Obstet Gynaecol       Date:  2022-03-03       Impact factor: 1.884

8.  Prediction of recurrent preterm delivery in asymptomatic women- an anxiety reducing measure?

Authors:  Sarah Petch; Alison DeMaio; Sean Daly
Journal:  Eur J Obstet Gynecol Reprod Biol X       Date:  2019-06-07

Review 9.  Mobile phone apps for clinical decision support in pregnancy: a scoping review.

Authors:  Jenny Carter; Jane Sandall; Andrew H Shennan; Rachel M Tribe
Journal:  BMC Med Inform Decis Mak       Date:  2019-11-12       Impact factor: 2.796

Review 10.  All the right moves: why in utero transfer is both important for the baby and difficult to achieve and new strategies for change.

Authors:  Helena Watson; James McLaren; Naomi Carlisle; Nandiran Ratnavel; Tim Watts; Ahmed Zaima; Rachel M Tribe; Andrew H Shennan
Journal:  F1000Res       Date:  2020-08-13
  10 in total

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