Evidence map›Paper›PMID 32866167›Full record

ArticlePloS one2020

Working with what you have: How the East Africa Preterm Birth Initiative used gestational age data from facility maternity registers.

Lara Miller, Phillip Wanduru, Nicole Santos, Elizabeth Butrick, Peter Waiswa, Phelgona Otieno, Dilys Walker

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
3.9field-weighted citation impact, top 7% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

  1. Article
  2. Observational
  3. Article
  4. Article
  5. Article
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

7 authors at 3 institutions in 3 countries.

Lara MillerInstitute for Global Health Sciences, University of California, San Francisco, San Francisco, California, United States of America.ORCID 0000-0001-8406-5159
Phillip WanduruSchool of Public Health, Makerere University, Kampala, Uganda.
Nicole SantosInstitute for Global Health Sciences, University of California, San Francisco, San Francisco, California, United States of America.
Elizabeth ButrickInstitute for Global Health Sciences, University of California, San Francisco, San Francisco, California, United States of America.
Peter WaiswaSchool of Public Health, Makerere University, Kampala, Uganda.
Phelgona OtienoKenya Medical Research Institute, Nairobi, Kenya.
Dilys WalkerInstitute for Global Health Sciences, University of California, San Francisco, San Francisco, California, United States of America.
University of California, San Francisco · USMakerere University · UGKenya Medical Research Institute · KE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivePreterm birth is the primary driver of neonatal mortality worldwide, but it is defined by gestational age (GA) which is challenging to accurately assess in low-resource settings. In a commitment to reducing preterm birth while reinforcing and strengthening facility data sources, the East Africa Preterm Birth Initiative (PTBi-EA) chose eligibility criteria that combined GA and birth weight. This analysis evaluated the quality of the GA data as recorded in maternity registers in PTBi-EA study facilities and the strength of the PTBi-EA eligibility criteria.

methodsWe conducted a retrospective analysis of maternity register data from March-September 2016. GA data from 23 study facilities in Migori, Kenya and the Busoga Region of Uganda were evaluated for completeness (variable present), consistency (recorded versus calculated GA), and plausibility (falling within the 3rd and 97th birth weight percentiles for GA of the INTERGROWTH-21st Newborn Birth Weight Standards). Preterm birth rates were calculated using: 1) recorded GA <37 weeks, 2) recorded GA <37 weeks, excluding implausible GAs, 3) birth weight <2500g, and 4) PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks.

resultsIn both countries, GA was the least recorded variable in the maternity register (77.6%). Recorded and calculated GA (Kenya only) were consistent in 29.5% of births. Implausible GAs accounted for 11.7% of births. The four preterm birth rates were 1) 14.5%, 2) 10.6%, 3) 9.6%, 4) 13.4%.

conclusionsMaternity register GA data presented quality concerns in PTBi-EA study sites. The PTBi-EA eligibility criteria of <2500g and between 2500g and 3000g if the recorded GA is <37 weeks accommodated these concerns by using both birth weight and GA, balancing issues of accuracy and completeness with practical applicability.

Indexed as

Gestational AgeBirth WeightData CollectionFemaleHumansInfantInfant, Extremely Low Birth WeightInfant, Extremely PrematureInfant MortalityInfant, NewbornKenyaMaternal Health ServicesPregnancyPremature BirthQuality ImprovementRegistries

Identifiers

PMID32866167
PMCPMC7458293
OpenAlexW3082831808

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.