Evidence map›Paper›PMID 34059493›Full record

ArticleBMJ global health2021

Neonatal mortality in Kenyan hospitals: a multisite, retrospective, cohort study.

Grace Irimu, Jalemba Aluvaala, Lucas Malla, Sylvia Omoke, Morris Ogero, George Mbevi, Mary Waiyego, Caroline Mwangi, Fred Were, David Gathara and 4 more

Abstract read
In one paragraph

Article in BMJ global health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–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

37 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

14 authors.

Grace IrimuDepartment of Paediatrics and Child Health, University of Nairobi, Nairobi, Kenya GIrimu@kemri-wellcome.org.
Jalemba AluvaalaDepartment of Paediatrics and Child Health, University of Nairobi, Nairobi, Kenya.ORCID 0000-0002-0851-3711
Lucas MallaHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.
Sylvia OmokeHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.ORCID 0000-0003-1269-5519
Morris OgeroHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.
George MbeviHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.
Mary WaiyegoHealth Services, Nairobi Metropolitan Services, Nairobi, Kenya.
Caroline MwangiDivision of Neonatal and Child Health, Kenya Ministry of Health, Nairobi, Kenya.
Fred WereKenya Paediatric Research Consortium (KEPRECON), Nairobi, Kenya.
David GatharaHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.
Ambrose AgweyuHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.ORCID 0000-0001-8760-1279
Samuel AkechHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.
Mike EnglishHealth Services Unit, KEMRI - Wellcome Trust Research Institute, Nairobi, Kenya.ORCID 0000-0002-7427-0826
Clinical Information Network authors

Funding

Wellcome Trust 092654Wellcome Trust 207522Wellcome Trust 207522/Z/17/Z
6 · The paper itself

Abstract

backgroundMost of the deaths among neonates in low-income and middle-income countries (LMICs) can be prevented through universal access to basic high-quality health services including essential facility-based inpatient care. However, poor routine data undermines data-informed efforts to monitor and promote improvements in the quality of newborn care across hospitals.

methodsContinuously collected routine patients' data from structured paper record forms for all admissions to newborn units (NBUs) from 16 purposively selected Kenyan public hospitals that are part of a clinical information network were analysed together with data from all paediatric admissions ages 0-13 years from 14 of these hospitals. Data are used to show the proportion of all admissions and deaths in the neonatal age group and examine morbidity and mortality patterns, stratified by birth weight, and their variation across hospitals.

findingsDuring the 354 hospital months study period, 90 222 patients were admitted to the 14 hospitals contributing NBU and general paediatric ward data. 46% of all the admissions were neonates (aged 0-28 days), but they accounted for 66% of the deaths in the age group 0-13 years. 41 657 inborn neonates were admitted in the NBUs across the 16 hospitals during the study period. 4266/41 657 died giving a crude mortality rate of 10.2% (95% CI 9.97% to 10.55%), with 60% of these deaths occurring on the first-day of admission. Intrapartum-related complications was the single most common diagnosis among the neonates with birth weight of 2000 g or more who died. A threefold variation in mortality across hospitals was observed for birth weight categories 1000-1499 g and 1500-1999 g.

interpretationThe high proportion of neonatal deaths in hospitals may reflect changing patterns of childhood mortality. Majority of newborns died of preventable causes (>95%). Despite availability of high-impact low-cost interventions, hospitals have high and very variable mortality proportions after stratification by birth weight.

Indexed as

HospitalsInfant MortalityAdolescentChildChild, PreschoolCohort StudiesHumansInfantInfant, NewbornKenyaRetrospective Studiescohort studyepidemiologyhealth services researchpaediatrics

Identifiers

PMID34059493
PMCPMC8169483

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.