Evidence map›Paper›PMID 32133171›Full record

ArticleBMJ global health2020

Predictors of neonatal mortality: development and validation of prognostic models using prospective data from rural Bangladesh.

Farhad A Khan, Luke C Mullany, Lee F-S Wu, Hasmot Ali, Saijuddin Shaikh, Kelsey Alland, Keith P West, Alain B Labrique

Abstract read
In one paragraph

Article in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. 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

8 authors.

Farhad A KhanDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0002-2027-8953
Luke C MullanyDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0003-4668-9803
Lee F-S WuDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.
Hasmot AliDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0003-0044-1992
Saijuddin ShaikhDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0001-5095-1478
Kelsey AllandDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0001-8464-6308
Keith P WestDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0001-9458-362X
Alain B LabriqueDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.ORCID 0000-0003-2502-7819

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To assess the extent to which maternal histories of newborn danger signs independently or combined with birth weight and/or gestational age (GA) can capture and/or predict postsecond day (age>48 hours) neonatal death. Methods: Data from a cluster-randomised trial conducted in rural Bangladesh were split into development and validation sets. The prompted recall of danger signs and birth weight measurements were collected within 48 hours postchildbirth. Maternally recalled danger signs included cyanosis (any part of the infant's body was blue at birth), non-cephalic presentation (part other than head came out first at birth), lethargy (weak or no arm/leg movement and/or cry at birth), trouble suckling (infant unable to suckle/feed normally in the 2 days after birth or before death, collected 1-month postpartum or from verbal autopsy). Last menstrual period was collected at maternal enrolment early in pregnancy. Singleton newborns surviving 2 days past childbirth were eligible for analysis. Prognostic multivariable models were developed and internally validated. Results: Recalling ≥1 sign of lethargy, cyanosis, non-cephalic presentation or trouble suckling identified postsecond day neonatal death with 65.3% sensitivity, 60.8% specificity, 2.1% positive predictive value (PPV) and 99.3% negative predictive value (NPV) in the development set. Requiring either lethargy or weight <2.5 kg identified 89.1% of deaths (at 39.7% specificity, 1.9% PPV and 99.6% NPV) while lethargy or preterm birth (<37 weeks) captured 81.0% of deaths (at 53.6% specificity, 2.3% PPV and 99.5% NPV). A simplified model (birth weight, GA, lethargy, cyanosis, non-cephalic presentation and trouble suckling) predicted death with good discrimination (validation area under the receiver-operator characteristic curve (AUC) 0.80, 95% CI 0.73 to 0.87). A further simplified model (GA, non-cephalic presentation, lethargy, trouble suckling) predicted death with moderate discrimination (validation AUC 0.74, 95% CI 0.66 to 0.81). Conclusion: Maternally recalled danger signs, coupled to either birth weight or GA, can predict and capture postsecond day neonatal death with high discrimination and sensitivity.

Indexed as

Neonatal ScreeningPerinatal MortalityAdultBangladeshBirth WeightFemaleGestational AgeHumansInfantInfant, NewbornMaleModels, StatisticalPredictive Value of TestsPregnancyPrognosisRandomized Controlled Trials as TopicBangladeshdanger signneonatal mortalitynewborn mortalityprognostic modelsymptom

Identifiers

PMID32133171
PMCPMC7042570

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.