Evidence map›Paper›PMID 31150513›Full record

SynthesisPloS one2019

Early warning systems in obstetrics: A systematic literature review.

Aminu Umar, Charles A Ameh, Francis Muriithi, Matthews Mathai

Open access · goldAbstract readSystematic Review
In one paragraph

Synthesis in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 3 pooled it
14.5field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

41 citing papers in PubMed, 3 syntheses or guidelines pooled it, 100 citations in OpenAlex.

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  13. [Early warning scores: a rapid umbrella review].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2025
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Aminu UmarCentre for Maternal and Newborn Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Charles A AmehCentre for Maternal and Newborn Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.ORCID 0000-0002-2341-7605
Francis MuriithiBlackpool Teaching Hospitals National Health Service Foundation Trust, Blackpool, United Kingdom.ORCID 0000-0002-2314-5611
Matthews MathaiCentre for Maternal and Newborn Health, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.
Liverpool School of Tropical Medicine · GBNational Health Service · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionSeveral versions of Early Warning Systems (EWS) are used in obstetrics to detect and treat early clinical deterioration to avert morbidity and mortality. EWS can potentially be useful to improve the quality of care and reduce the risk of maternal mortality in resource-limited settings. We conducted a systematic literature review of published obstetric early warning systems, define their predictive accuracy for morbidity and mortality, and their effectiveness in triggering corrective actions and improving health outcomes.

methodsWe systematically searched for primary research articles on obstetric EWS published in peer-reviewed journals between January 1997 and March 2018 in Medline, CINAHL, SCOPUS, Science Direct, and Science Citation Index. We also searched reference lists of relevant articles and websites of professional societies. We included studies that assessed the predictive accuracy of EWS to detect clinical deterioration, or/and their effectiveness in improving clinical outcomes in obstetric inpatients. We excluded studies with a paediatric or non-obstetric adult population. Cross-sectional and qualitative studies were also excluded. We performed a narrative synthesis since the outcomes reported were heterogeneous.

resultsA total of 381 papers were identified, 17 of which met the inclusion criteria. Eleven of the included studies evaluated the predictive accuracy of EWS for obstetric morbidity and mortality, 5 studies assessed the effectiveness of EWS in improving clinical outcomes, while one study addressed both. Sixteen published EWS versions were reviewed, 14 of which included five basic clinical observations (pulse rate, respiratory rate, temperature, blood pressure, and consciousness level). The obstetric EWS identified had very high median (inter-quartile range) sensitivity-89% (72% to 97%) and specificity-85% (67% to 98%) but low median (inter-quartile range) positive predictive values-41% (25% to 74%) for predicting morbidity or ICU admission. Obstetric EWS had a very high accuracy in predicting death (AUROC >0.80) among critically ill obstetric patients. Obstetric EWS improves the frequency of routine vital sign observation, reduces the interval between the recording of specifically defined abnormal clinical observations and corrective clinical actions, and can potentially reduce the severity of obstetric morbidity.

conclusionObstetric EWS are effective in predicting severe morbidity (in general obstetric population) and mortality (in critically ill obstetric patients). EWS can contribute to improved quality of care, prevent progressive obstetric morbidity and improve health outcomes. There is limited evidence of the effectiveness of EWS in reducing maternal death across all settings. Clinical parameters in most obstetric EWS versions are routinely collected in resource-limited settings, therefore implementing EWS may be feasible in such settings.

Indexed as

Databases, FactualDelivery, ObstetricAdultEarly Warning ScoreFemaleHospitalizationHumansIntensive Care UnitsMaternal DeathMorbidityObstetricsPregnancy

Identifiers

PMID31150513
PMCPMC6544303
OpenAlexW2947127311

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.